perm filename AI.TXT[BB,DOC]9 blob
sn#850531 filedate 1987-12-19 generic text, type C, neo UTF8
COMMENT ⊗ VALID 00279 PAGES
C REC PAGE DESCRIPTION
C00001 00001
C00038 00002 This file (AI.TXT[BB,DOC]) currently holds volume 5 of the AI-LIST digest.
C00040 00003 ∂02-Jan-87 0014 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #1
C00067 00004 ∂02-Jan-87 0139 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #2
C00092 00005 ∂08-Jan-87 0048 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #3
C00117 00006 ∂08-Jan-87 0232 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #4
C00136 00007 ∂08-Jan-87 0429 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #5
C00159 00008 ∂11-Jan-87 2339 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #6
C00182 00009 ∂19-Jan-87 0119 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #7
C00199 00010 ∂19-Jan-87 0255 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #8
C00223 00011 ∂20-Jan-87 0036 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #9
C00255 00012 ∂21-Jan-87 0048 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #10
C00271 00013 ∂21-Jan-87 0233 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #11
C00295 00014 ∂22-Jan-87 0027 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #12
C00317 00015 ∂23-Jan-87 0152 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #13
C00356 00016 ∂25-Jan-87 2351 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #14
C00375 00017 ∂26-Jan-87 0147 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #15
C00397 00018 ∂26-Jan-87 0341 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #16
C00422 00019 ∂27-Jan-87 0224 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #17
C00441 00020 ∂28-Jan-87 0247 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #18
C00474 00021 ∂28-Jan-87 0704 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #19
C00509 00022 ∂28-Jan-87 1156 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #20
C00540 00023 ∂29-Jan-87 0254 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #21
C00563 00024 ∂29-Jan-87 0737 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #22
C00596 00025 ∂30-Jan-87 0217 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #23
C00631 00026 ∂30-Jan-87 0507 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #24
C00663 00027 ∂30-Jan-87 1230 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #25
C00697 00028 ∂30-Jan-87 1703 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #26
C00727 00029 ∂30-Jan-87 2034 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #27
C00763 00030 ∂02-Feb-87 0129 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #28
C00794 00031 ∂02-Feb-87 0352 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #29
C00830 00032 ∂02-Feb-87 0703 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #30
C00864 00033 ∂02-Feb-87 1919 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #31
C00895 00034 ∂05-Feb-87 0240 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #32
C00912 00035 ∂09-Feb-87 0024 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #33
C00940 00036 ∂09-Feb-87 0222 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #34
C00973 00037 ∂09-Feb-87 0420 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #35
C01008 00038 ∂09-Feb-87 1648 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #36
C01032 00039 ∂09-Feb-87 2017 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #37
C01060 00040 ∂11-Feb-87 0204 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #38
C01078 00041 ∂11-Feb-87 0443 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #39
C01099 00042 ∂12-Feb-87 0325 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #40
C01125 00043 ∂14-Feb-87 0030 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #41
C01146 00044 ∂14-Feb-87 0313 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #42
C01178 00045 ∂14-Feb-87 0633 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #43
C01209 00046 ∂14-Feb-87 0853 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #44
C01238 00047 ∂18-Feb-87 0052 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #45
C01256 00048 ∂19-Feb-87 0222 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #46
C01282 00049 ∂19-Feb-87 1553 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #47
C01306 00050 ∂22-Feb-87 0214 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #48
C01349 00051 ∂22-Feb-87 0412 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #49
C01377 00052 ∂22-Feb-87 0620 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #50
C01411 00053 ∂22-Feb-87 2313 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #51
C01432 00054 ∂23-Feb-87 0044 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #52
C01456 00055 ∂23-Feb-87 0216 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #53
C01473 00056 ∂24-Feb-87 0013 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #54
C01487 00057 ∂24-Feb-87 0141 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #55
C01505 00058 ∂24-Feb-87 2322 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #56
C01523 00059 ∂26-Feb-87 1432 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #57
C01543 00060 ∂01-Mar-87 0032 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #58
C01564 00061 ∂01-Mar-87 0210 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #59
C01583 00062 ∂01-Mar-87 0412 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #60
C01619 00063 ∂01-Mar-87 2055 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #62
C01641 00064 ∂04-Mar-87 0131 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #63
C01663 00065 ∂04-Mar-87 0324 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #61
C01677 00066 ∂05-Mar-87 0027 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #64
C01707 00067 ∂05-Mar-87 0234 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #65
C01733 00068 ∂05-Mar-87 1031 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #66
C01773 00069 ∂06-Mar-87 1051 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #67
C01807 00070 ∂06-Mar-87 1419 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #68
C01841 00071 ∂06-Mar-87 1731 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #69
C01875 00072 ∂07-Mar-87 0017 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #70
C01893 00073 ∂07-Mar-87 0207 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #71
C01920 00074 ∂08-Mar-87 2348 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #72
C01943 00075 ∂09-Mar-87 0257 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #73
C01965 00076 ∂09-Mar-87 0501 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #74
C01992 00077 ∂12-Mar-87 0306 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #75
C02008 00078 ∂12-Mar-87 0608 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #76
C02029 00079 ∂13-Mar-87 1526 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #77
C02056 00080 ∂15-Mar-87 0021 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #78
C02082 00081 ∂15-Mar-87 0232 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #79
C02108 00082 ∂16-Mar-87 0017 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #80
C02130 00083 ∂16-Mar-87 0219 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #81
C02152 00084 ∂17-Mar-87 2335 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #82
C02178 00085 ∂18-Mar-87 2334 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #83
C02199 00086 ∂23-Mar-87 0231 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #84
C02222 00087 ∂23-Mar-87 0434 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #85
C02244 00088 ∂25-Mar-87 0144 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #86
C02266 00089 ∂25-Mar-87 0419 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #87
C02294 00090 ∂26-Mar-87 0027 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #88
C02304 00091 ∂28-Mar-87 0047 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #89
C02322 00092 ∂28-Mar-87 0242 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #90
C02344 00093 ∂30-Mar-87 0047 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #91
C02367 00094 ∂31-Mar-87 0057 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #92
C02391 00095 ∂07-Apr-87 1158 LAWS@STRIPE.SRI.COM AIList Digest V5 #93
C02416 00096 ∂07-Apr-87 1854 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #94
C02449 00097 ∂07-Apr-87 2239 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #95
C02477 00098 ∂10-Apr-87 2156 LAWS@STRIPE.SRI.COM AIList Digest V5 #96
C02488 00099 ∂13-Apr-87 2329 LAWS@STRIPE.SRI.COM AIList Digest V5 #97
C02510 00100 ∂14-Apr-87 0129 LAWS@STRIPE.SRI.COM AIList Digest V5 #98
C02529 00101 ∂14-Apr-87 0325 LAWS@STRIPE.SRI.COM AIList Digest V5 #99
C02554 00102 ∂23-Apr-87 1228 LAWS@Stripe.SRI.COM AIList Digest V5 #100
C02578 00103 ∂23-Apr-87 1544 LAWS@Stripe.SRI.COM AIList Digest V5 #101
C02593 00104 ∂23-Apr-87 1803 LAWS@Stripe.SRI.COM AIList Digest V5 #102
C02617 00105 ∂23-Apr-87 2044 LAWS@Stripe.SRI.COM AIList Digest V5 #103
C02644 00106 ∂23-Apr-87 2309 LAWS@Stripe.SRI.COM AIList Digest V5 #104
C02666 00107 ∂24-Apr-87 0809 LAWS@Stripe.SRI.COM AIList Digest V5 #105
C02700 00108 ∂03-May-87 1609 LAWS@Stripe.SRI.COM AIList Digest V5 #106
C02723 00109 ∂03-May-87 1809 LAWS@Stripe.SRI.COM AIList Digest V5 #107
C02752 00110 ∂03-May-87 1958 LAWS@Stripe.SRI.COM AIList Digest V5 #108
C02772 00111 ∂03-May-87 2202 LAWS@Stripe.SRI.COM AIList Digest V5 #109
C02807 00112 ∂06-May-87 0004 LAWS@Stripe.SRI.COM AIList Digest V5 #110
C02833 00113 ∂07-May-87 2207 LAWS@Stripe.SRI.COM AIList Digest V5 #111
C02859 00114 ∂10-May-87 1920 LAWS@Stripe.SRI.COM AIList Digest V5 #112
C02888 00115 ∂10-May-87 2138 LAWS@Stripe.SRI.COM AIList Digest V5 #113
C02924 00116 ∂10-May-87 2348 LAWS@Stripe.SRI.COM AIList Digest V5 #114
C02959 00117 ∂11-May-87 0144 LAWS@Stripe.SRI.COM AIList Digest V5 #115
C02979 00118 ∂11-May-87 0329 LAWS@Stripe.SRI.COM AIList Digest V5 #116
C02996 00119 ∂12-May-87 0242 LAWS@Stripe.SRI.COM AIList Digest V5 #117
C03026 00120 ∂12-May-87 0506 LAWS@Stripe.SRI.COM AIList Digest V5 #118
C03060 00121 ∂12-May-87 0808 LAWS@Stripe.SRI.COM AIList Digest V5 #119
C03083 00122 ∂13-May-87 0025 LAWS@Stripe.SRI.COM AIList Digest V5 #120
C03114 00123 ∂13-May-87 0255 LAWS@Stripe.SRI.COM AIList Digest V5 #121
C03142 00124 ∂13-May-87 0455 LAWS@Stripe.SRI.COM AIList Digest V5 #122
C03156 00125 ∂14-May-87 0031 LAWS@Stripe.SRI.COM AIList Digest V5 #123
C03183 00126 ∂18-May-87 0028 LAWS@Stripe.SRI.Com AIList Digest V5 #124
C03209 00127 ∂21-May-87 0035 LAWS@Stripe.SRI.Com AIList Digest V5 #125
C03229 00128 ∂22-May-87 1438 LAWS@Stripe.SRI.Com AIList Digest V5 #126
C03254 00129 ∂22-May-87 1715 LAWS@Stripe.SRI.Com AIList Digest V5 #127
C03272 00130 ∂28-May-87 0233 LAWS@Stripe.SRI.Com AIList Digest V5 #128
C03301 00131 ∂28-May-87 0520 LAWS@Stripe.SRI.Com AIList Digest V5 #129
C03325 00132 ∂28-May-87 0746 LAWS@Stripe.SRI.Com AIList Digest V5 #130
C03351 00133 ∂30-May-87 0000 LAWS@Stripe.SRI.Com AIList Digest V5 #131
C03387 00134 ∂30-May-87 0256 LAWS@Stripe.SRI.Com AIList Digest V5 #132
C03423 00135 ∂30-May-87 0515 LAWS@Stripe.SRI.Com AIList Digest V5 #133
C03456 00136 ∂01-Jun-87 1336 LAWS@Stripe.SRI.Com AIList Digest V5 #134
C03486 00137 ∂01-Jun-87 2010 LAWS@Stripe.SRI.Com AIList Digest V5 #135
C03512 00138 ∂01-Jun-87 2316 LAWS@Stripe.SRI.Com AIList Digest V5 #136
C03544 00139 ∂02-Jun-87 0205 LAWS@Stripe.SRI.Com AIList Digest V5 #137
C03576 00140 ∂03-Jun-87 2316 LAWS@Stripe.SRI.Com AIList Digest V5 #138
C03601 00141 ∂10-Jun-87 0244 LAWS@Stripe.SRI.Com AIList Digest V5 #139
C03626 00142 ∂10-Jun-87 0507 LAWS@Stripe.SRI.Com AIList Digest V5 #141
C03658 00143 ∂10-Jun-87 1219 LAWS@Stripe.SRI.Com AIList Digest V5 #140
C03688 00144 ∂15-Jun-87 0107 LAWS@Stripe.SRI.Com AIList Digest V5 #142
C03715 00145 ∂15-Jun-87 0259 LAWS@Stripe.SRI.Com AIList Digest V5 #143
C03748 00146 ∂15-Jun-87 0440 LAWS@Stripe.SRI.Com AIList Digest V5 #144
C03768 00147 ∂15-Jun-87 0712 LAWS@Stripe.SRI.Com AIList Digest V5 #145
C03798 00148 ∂16-Jun-87 0300 LAWS@Stripe.SRI.Com AIList Digest V5 #146
C03836 00149 ∂16-Jun-87 1202 LAWS@Stripe.SRI.Com AIList Digest V5 #147
C03868 00150 ∂16-Jun-87 1724 LAWS@Stripe.SRI.Com AIList Digest V5 #148
C03896 00151 ∂16-Jun-87 2047 LAWS@Stripe.SRI.Com AIList Digest V5 #149
C03922 00152 ∂16-Jun-87 2332 LAWS@Stripe.SRI.Com AIList Digest V5 #150
C03941 00153 ∂18-Jun-87 0256 LAWS@Stripe.SRI.Com AIList Digest V5 #152
C03963 00154 ∂18-Jun-87 1623 LAWS@Stripe.SRI.Com AIList Digest V5 #151
C03999 00155 ∂20-Jun-87 0032 LAWS@Stripe.SRI.Com AIList Digest V5 #153
C04030 00156 ∂20-Jun-87 1842 LAWS@Stripe.SRI.Com AIList Digest V5 #154
C04066 00157 ∂26-Jun-87 1959 LAWS@Stripe.SRI.Com AIList Digest V5 #155
C04095 00158 ∂29-Jun-87 0103 LAWS@Stripe.SRI.Com AIList Digest V5 #156
C04123 00159 ∂29-Jun-87 0257 LAWS@Stripe.SRI.Com AIList Digest V5 #157
C04158 00160 ∂29-Jun-87 0451 LAWS@Stripe.SRI.Com AIList Digest V5 #158
C04193 00161 ∂29-Jun-87 0725 LAWS@Stripe.SRI.Com AIList Digest V5 #159
C04224 00162 ∂30-Jun-87 0132 LAWS@Stripe.SRI.Com AIList Digest V5 #160
C04245 00163 ∂30-Jun-87 0345 LAWS@Stripe.SRI.Com AIList Digest V5 #161
C04265 00164 ∂30-Jun-87 0728 LAWS@Stripe.SRI.Com AIList Digest V5 #162
C04290 00165 ∂01-Jul-87 0429 LAWS@Stripe.SRI.Com AIList Digest V5 #164
C04319 00166 ∂01-Jul-87 1027 LAWS@Stripe.SRI.Com AIList Digest V5 #163
C04345 00167 ∂02-Jul-87 0508 LAWS@Stripe.SRI.Com AIList Digest V5 #165
C04361 00168 ∂02-Jul-87 1112 LAWS@Stripe.SRI.Com AIList Digest V5 #166
C04384 00169 ∂03-Jul-87 0010 LAWS@Stripe.SRI.Com AIList Digest V5 #166
C04407 00170 ∂06-Jul-87 0246 LAWS@Stripe.SRI.Com AIList Digest V5 #167
C04428 00171 ∂06-Jul-87 0459 LAWS@Stripe.SRI.Com AIList Digest V5 #168
C04459 00172 ∂06-Jul-87 0823 LAWS@Stripe.SRI.Com AIList Digest V5 #169
C04487 00173 ∂06-Jul-87 1229 LAWS@Stripe.SRI.Com AIList Digest V5 #170
C04511 00174 ∂06-Jul-87 1551 LAWS@Stripe.SRI.Com AIList Digest V5 #171
C04534 00175 ∂09-Jul-87 2331 LAWS@Stripe.SRI.Com AIList Digest V5 #172
C04563 00176 ∂10-Jul-87 0310 LAWS@Stripe.SRI.Com AIList Digest V5 #172
C04595 00177 ∂10-Jul-87 0632 LAWS@Stripe.SRI.Com AIList Digest V5 #173
C04621 00178 ∂12-Jul-87 0159 LAWS@Stripe.SRI.Com AIList Digest V5 #174
C04657 00179 ∂12-Jul-87 0524 LAWS@Stripe.SRI.Com AIList Digest V5 #175
C04688 00180 ∂12-Jul-87 0816 LAWS@Stripe.SRI.Com AIList Digest V5 #176
C04712 00181 ∂13-Jul-87 0022 LAWS@Stripe.SRI.Com AIList Digest V5 #177
C04739 00182 ∂13-Jul-87 0332 LAWS@Stripe.SRI.Com AIList Digest V5 #178
C04769 00183 ∂15-Jul-87 1048 LAWS@Stripe.SRI.Com AIList Digest V5 #182
C04799 00184 ∂15-Jul-87 1158 LAWS@Stripe.SRI.Com AIList Digest V5 #179
C04830 00185 ∂15-Jul-87 1236 LAWS@Stripe.SRI.Com AIList Digest V5 #180
C04868 00186 ∂15-Jul-87 1313 LAWS@Stripe.SRI.Com AIList Digest V5 #181
C04903 00187 ∂17-Jul-87 0110 LAWS@Stripe.SRI.Com AIList Digest V5 #183
C04935 00188 ∂20-Jul-87 0003 LAWS@Stripe.SRI.Com AIList Digest V5 #184
C04963 00189 ∂20-Jul-87 0235 LAWS@Stripe.SRI.Com AIList Digest V5 #185
C04995 00190 ∂22-Jul-87 0051 LAWS@Stripe.SRI.Com AIList Digest V5 #186
C05019 00191 ∂27-Jul-87 0208 LAWS@Stripe.SRI.Com AIList Digest V5 #187
C05049 00192 ∂27-Jul-87 0335 LAWS@Stripe.SRI.Com AIList Digest V5 #188
C05075 00193 ∂27-Jul-87 0605 LAWS@Stripe.SRI.Com AIList Digest V5 #189
C05113 00194 ∂29-Jul-87 0121 LAWS@Stripe.SRI.Com AIList Digest V5 #190 - Msc.
C05136 00195 ∂30-Jul-87 0010 LAWS@Stripe.SRI.Com AIList V5 #191 - LISP Techniques
C05155 00196 ∂30-Jul-87 0200 LAWS@Stripe.SRI.Com AIList Digest V5 #192
C05169 00197 ∂04-Aug-87 1606 LAWS@SRI.Com AIList V5 #193 - Natural Kinds (Philosophy)
C05191 00198 ∂05-Aug-87 0031 LAWS@SRI.Com AIList V5 #194 - Msc., Image Tracking, Seminars
C05218 00199 ∂10-Aug-87 0205 LAWS@KL.SRI.Com AIList V5 #195 - Macsyma, FBRL, Philosophy
C05248 00200 ∂10-Aug-87 0413 LAWS@KL.SRI.Com AIList V5 #196 - Tools: Neural Nets, Image Processing, Grapher
C05272 00201 ∂14-Aug-87 0038 LAWS@KL.SRI.Com AIList V5 #197 - Macsyma, XLISP, Neural Networks
C05291 00202 ∂14-Aug-87 0250 LAWS@KL.SRI.Com AIList V5 #198 - TRList, Seminars, Conferences
C05317 00203 ∂16-Aug-87 2328 LAWS@KL.SRI.Com AIList V5 #199 - Msc., Neural Nets, Functional Representations
C05338 00204 ∂20-Aug-87 0036 LAWS@KL.SRI.Com AIList V5 #200 - TerminalTalk, GLisp References
C05357 00205 ∂24-Aug-87 0038 LAWS@KL.SRI.Com AIList V5 #201 - Philosophy of Science, AI Paradigms
C05389 00206 ∂24-Aug-87 0235 LAWS@KL.SRI.Com AIList V5 #202 - Conferences
C05410 00207 ∂24-Aug-87 0416 LAWS@KL.SRI.Com AIList V5 #203 - Spang Robinson Review & TerminalTalk
C05428 00208 ∂28-Aug-87 0209 LAWS@KL.SRI.Com AIList V5 #204 - S and P Puzzle, AAI Reporter, Msc.
C05449 00209 ∂28-Aug-87 0338 LAWS@KL.SRI.Com AIList V5 #205 - Philosophy
C05470 00210 ∂28-Aug-87 0511 LAWS@KL.SRI.Com AIList V5 #206 - Terminal Icons, Meetings
C05491 00211 ∂30-Aug-87 2323 LAWS@KL.SRI.Com AIList V5 #207 - Neural Networks
C05514 00212 ∂01-Sep-87 2330 LAWS@KL.SRI.Com AIList V5 #208 - Philosophy of Science, Logic Puzzles
C05534 00213 ∂04-Sep-87 0145 LAWS@KL.SRI.Com AIList V5 #209 - Neural Networks, Planning/Scheduling Systems
C05552 00214 ∂07-Sep-87 2325 LAWS@KL.SRI.Com AIList Digest V5 #210
C05566 00215 ∂08-Sep-87 0114 LAWS@KL.SRI.Com AIList V5 #211 - Neural Networks & OPS5 & Philosophy
C05589 00216 ∂10-Sep-87 2333 LAWS@KL.SRI.Com AIList V5 #212 - Philosophy, Neural Networks
C05606 00217 ∂16-Sep-87 0058 LAWS@KL.SRI.Com AIList V5 #213 - Queries
C05626 00218 ∂16-Sep-87 0238 LAWS@KL.SRI.Com AIList V5 #214 - Neural Networks, P = NP?, Science, Security
C05648 00219 ∂16-Sep-87 0520 LAWS@KL.SRI.Com AIList V5 #215 - Bibliography
C05684 00220 ∂19-Sep-87 0236 LAWS@KL.SRI.Com AIList Digest V5 #216
C05720 00221 ∂19-Sep-87 0419 LAWS@KL.SRI.Com AIList V5 #217 - Literature Duplication, Philosophy
C05747 00222 ∂21-Sep-87 2359 LAWS@KL.SRI.Com AIList V5 #218 - Prolog, Lisp Syntax, OPS5 for the PC
C05772 00223 ∂22-Sep-87 0202 LAWS@KL.SRI.Com AIList Digest V5 #219
C05794 00224 ∂29-Sep-87 0143 LAWS@KL.SRI.Com AIList V5 #220 - Seminars, Conference on Uncertainty
C05817 00225 ∂29-Sep-87 0358 LAWS@KL.SRI.Com AIList V5 #221 - Queries, Directions of AI
C05837 00226 ∂29-Sep-87 0635 LAWS@KL.SRI.Com AIList V5 #222 - Bindings, Spang Robinson, Neural Networks
C05851 00227 ∂29-Sep-87 0913 LAWS@KL.SRI.Com AIList V5 #223 - Philosophy of Science
C05873 00228 ∂29-Sep-87 1543 LAWS@KL.SRI.Com AIList Digest V5 #224
C05906 00229 ∂02-Oct-87 0207 LAWS@KL.SRI.Com AIList V5 #225 - CPSR, Time, Boltzmann Machines, Slava Prazdny
C05931 00230 ∂02-Oct-87 0444 LAWS@KL.SRI.Com AIList V5 #226 - Philosophy of AI and Computer Science
C05967 00231 ∂07-Oct-87 2330 LAWS@KL.SRI.Com AIList V5 #227 - Goal of AI
C05998 00232 ∂08-Oct-87 0216 LAWS@KL.SRI.Com AIList V5 #228 - Philosophy, Native American Languages
C06024 00233 ∂08-Oct-87 0443 LAWS@KL.SRI.Com AIList V5 #229 - Seminar, Conferences
C06050 00234 ∂08-Oct-87 0728 LAWS@KL.SRI.Com AIList V5 #230 - Speech Databases, Temporal Representation
C06081 00235 ∂12-Oct-87 0020 LAWS@KL.SRI.Com AIList V5 #231 - Neural Networks, Common Lisp
C06111 00236 ∂12-Oct-87 0242 LAWS@KL.SRI.Com AIList V5 #232 - Time, Financing, Othello, Philosophy
C06142 00237 ∂12-Oct-87 0431 LAWS@KL.SRI.Com AIList V5 #233 - Philosophy
C06167 00238 ∂12-Oct-87 0610 LAWS@KL.SRI.Com AIList V5 #234 - Seminars, Statistics Conference
C06184 00239 ∂15-Oct-87 0150 LAWS@KL.SRI.Com AIList V5 #235 - Business and Marketing, Neuromorphic Terminology
C06210 00240 ∂16-Oct-87 0027 LAWS@KL.SRI.Com AIList V5 #236 - Semantics of Flawed Minds
C06236 00241 ∂16-Oct-87 0251 LAWS@KL.SRI.Com AIList V5 #237 - Seminars, Connectionist Course, Conference
C06266 00242 ∂19-Oct-87 0133 LAWS@KL.SRI.Com AIList V5 #238 - Fault Diagnosis, Financing, AI Successes
C06299 00243 ∂19-Oct-87 0343 LAWS@KL.SRI.Com AIList V5 #239 - Neuromorphic Terminology, AI Successes, Logican Joke
C06327 00244 ∂22-Oct-87 0106 LAWS@KL.SRI.Com AIList V5 #240 - Net Mail to UK, Lisp Books, Logician Jokes
C06353 00245 ∂22-Oct-87 0247 LAWS@KL.SRI.Com AIList V5 #241 - Seminars, Course in Information Processing
C06368 00246 ∂22-Oct-87 0602 LAWS@KL.SRI.Com AIList V5 #242 - Successes of AI, Automated Discovery
C06402 00247 ∂24-Oct-87 0131 LAWS@KL.SRI.Com AIList V5 #243 - Lisp Text, Prolog, Design, Cash Flow, Neural Nets
C06426 00248 ∂24-Oct-87 0359 LAWS@KL.SRI.Com AIList V5 #244 - Financing, Neuromorphic Terminology, Flawed Minds
C06464 00249 ∂24-Oct-87 0914 LAWS@KL.SRI.Com AIList V5 #245 - AM, Success of AI, Dreyfus's Philosophy
C06498 00250 ∂26-Oct-87 0042 LAWS@KL.SRI.Com AIList V5 #246 - Seminars, Conferences
C06524 00251 ∂26-Oct-87 0230 LAWS@KL.SRI.Com AIList V5 #247 - Knowledge, Neural Terminology, Design, Linguistics
C06547 00252 ∂26-Oct-87 0431 LAWS@KL.SRI.Com AIList V5 #248 - OCR, Introductory Prolog, Flawed Minds
C06582 00253 ∂26-Oct-87 0728 LAWS@KL.SRI.Com AIList V5 #249 - Success of AI
C06609 00254 ∂28-Oct-87 0031 LAWS@KL.SRI.Com AIList V5 #250 - Cybernetics, Education, Neuromorphic Simulators
C06631 00255 ∂28-Oct-87 0231 LAWS@KL.SRI.Com AIList V5 #251 - Kolmogorov, Supercomputing, Methodology
C06654 00256 ∂29-Oct-87 0424 LAWS@KL.SRI.Com AIList V5 #252 - Neural Network Review, UK Mail, Seminars
C06673 00257 ∂30-Oct-87 0100 LAWS@KL.SRI.Com AIList V5 #253 - LISP, NIL, Msc.
C06688 00258 ∂30-Oct-87 0359 LAWS@KL.SRI.Com AIList V5 #254 - AI Methodology
C06710 00259 ∂03-Nov-87 0151 LAWS@KL.SRI.Com AIList V5 #255 - Future of AI & Speech & PDP Book & AI Categories
C06737 00260 ∂03-Nov-87 0505 LAWS@KL.SRI.Com AIList V5 #256 - Analogy, Inference
C06764 00261 ∂03-Nov-87 0844 LAWS@KL.SRI.Com AIList V5 #257 - Methodology
C06791 00262 ∂03-Nov-87 1357 LAWS@KL.SRI.Com AIList V5 #258 - BBS Abstracts, Knowledge Acquisition Bibliography
C06832 00263 ∂05-Nov-87 0422 LAWS@KL.SRI.Com AIList V5 #259 - FORTRAN, Natural Language Interfaces
C06855 00264 ∂05-Nov-87 0856 LAWS@KL.SRI.Com AIList V5 #260 - Resource Center for Software, AI Goals and Models
C06886 00265 ∂06-Nov-87 0600 LAWS@KL.SRI.Com AIList V5 #261 - Seminars, CADE-9, HICSS-22
C06920 00266 ∂09-Nov-87 0258 LAWS@KL.SRI.Com AIList V5 #262 - Neuromorphics, Speech Recognition, Goals
C06955 00267 ∂09-Nov-87 0624 LAWS@KL.SRI.Com AIList V5 #263 - Methodology, FORTRAN
C06980 00268 ∂09-Nov-87 1128 LAWS@KL.SRI.Com AIList Digest V5 #264
C07014 00269 ∂13-Nov-87 0224 LAWS@KL.SRI.COM AIList V5 #265 - Seminar, Conferences
C07032 00270 ∂13-Nov-87 0438 LAWS@KL.SRI.COM AIList V5 #266 - Queries
C07049 00271 ∂13-Nov-87 0724 LAWS@KL.SRI.COM AIList Digest V5 #267
C07077 00272 ∂13-Nov-87 1034 LAWS@KL.SRI.COM AIList V5 #268 - Spang Robinson 3/10, Bibliography, Methodology
C07097 00273 ∂16-Nov-87 0101 LAWS@KL.SRI.COM AIList V5 #269 - Inference, Sphexishness, Object-Oriented Databases
C07119 00274 ∂18-Nov-87 0233 LAWS@KL.SRI.COM AIList V5 #270 - Games, Learning, Pattern Recognition, Law
C07144 00275 ∂25-Nov-87 0216 LAWS@KL.SRI.COM AIList V5 #271 - Genetic Learning, Statistics, Benchmarking, Msc.
C07177 00276 ∂25-Nov-87 0439 LAWS@KL.SRI.COM AIList V5 #272 - Expert System Survey
C07206 00277 ∂25-Nov-87 0710 LAWS@KL.SRI.COM AIList V5 #273 - Seminars, Conferences
C07236 00278 ∂25-Nov-87 1024 LAWS@KL.SRI.COM AIList Digest V5 #274
C07260 00279 ∂01-Dec-87 0054 LAWS@KL.SRI.COM AIList V5 #275 - Pattern Recognition, VLSI Design, Philosophy, Law
C07288 ENDMK
C⊗;
This file (AI.TXT[BB,DOC]) currently holds volume 5 of the AI-LIST digest.
The digests are edited by Ken Laws at SRI. To get added to the list send
mail to AIList-REQUEST@SRI-STRIPE; better yet use CKSUM to read this file.
Mail your submissions to AIList@SRI-STRIPE.
Pointers to previous volumes:
Volume 1 (#1 to #117) of AI-LIST has been archived in file AI.V1[BB,DOC].
Volume 2 (#1 to #184) of AI-LIST has been archived in file AI.V2[BB,DOC].
Volume 3 (#1 to #193) of AI-LIST has been archived in file AI.V3[BB,DOC].
Volume 4 (#1 to #289) of AI-LIST has been archived in file AI.V4[BB,DOC].
The old volumes will not be kept on the disk, although they'll be available
from backup tape if necessary. Archive files are probably available online
at SRI-STRIPE.
∂02-Jan-87 0014 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #1
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 2 Jan 87 00:14:38 PST
Date: Thu 1 Jan 1987 21:57-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #1
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 2 Jan 1987 Volume 5 : Issue 1
Today's Topics:
Queries - AAAI-87 Workshop Program & Efficient Property Implementation &
Uncertainty Talk & IBM Expert System & Large-Scale Test Suite Tools &
Expert System Shells on Unix and PCDOS & Symbolics/VAX Database &
Proof of Correctness, Hardware Grammar & Everyday Life Survey
----------------------------------------------------------------------
Date: Mon, 22 Dec 86 10:55:21 EST
From: katz@mitre-bedford.ARPA
Subject: AAAI-87 Workshop Program
The AAAI-87 Program Committee invites members to submit proposals for the
Workshop Program--expected to be an important feature of this year's
conference.
Gathering in an informal setting, workshop participants will have the
opportunity to meet and discuss issues with a selected focus. This format
will provide for active exchange among researchers and practioners on topics
of mutual interest. Members from all segments of the AI community are
encouraged to submit proposals for review by the committee.
To encourage interaction and a broad exchange of ideas, the workshops will be
kept small. Attendance will be limited to active participants only. Workshop
sessions will consist of individual presentations, and ample time will be
allotted for general discussion.
Please submit your workshop proposals to:
Joseph Katz
MITRE MS-D070
Burlington Road
Bedford, Massachusetts 01730
or to,
Katz@mitre-bedford.arpa
------------------------------
Date: Sun, 21 Dec 86 11:38:29 ist
From: Ephraim Silverberg <ephraim%techunix.bitnet@WISCVM.WISC.EDU>
Reply-to: ephraim%techunix.bitnet@WISCVM.WISC.EDU
Subject: Efficient Property Implementation
I am looking for papers/projects concerning the implementation (on non-lisp
machines, in particular) of dynamic properties (those properties that can be
added/deleted/altered in objects as the functions: defprop, putprop, remprop
and (get obj prop), do in Franz Lisp) in lisp and other languages.
Please reply by e-mail.
Ephraim Silverberg,
Faculty of Electrical Engineering,
Israel Institute of Technology,
Haifa, Israel.
BITNET : ephraim@techunix
ARPANET : ephraim%techunix.bitnet@wiscvm.arpa
CSNET : ephraim%techunix.bitnet@csnet-relay
UUCP : {almost anywhere}!ucbvax!ephraim@techunix.bitnet
------------------------------
Date: 22 Dec 86 17:38 EST
From: SHAFFER%SCOVCB.decnet@ge-crd.arpa
Subject: Uncertainty Talk
Greetings:
We at GE get the AILIST very late. Every announced seminar
or paper presentation has already taken place by the time we hear
of it. One such seminar was a talk on UNCERTAINTY by CMU professor
Peter Szolouits (sic). Does anyone know if I can get a transcript
of his presentation, or at least a copy of the abstract and paper?
I am working with rule-based systems and uncertainty comes up a
great deal in system design. Thank you for your help.
E. Shaffer, PO Box 8555, Phila, Pa 19101
------------------------------
Date: 22 Dec 86 15:33:24 GMT
From: j1o%psuvm.bitnet@ucbvax.Berkeley.EDU
Subject: IBM Expert System
Has anyone out there got the IBM Expert System offering? If so, I'd like
to know how the FCB's work, and how you can eliminate parts of the search tree.
IBM's docs aren't perfectly clear.
-------
+-----------------------------------------------------------------------+
| -- Jim Owens (814)-898-6250 |
| {akgua,allegra,ihnp4,cbosgd}!psuvax1!psuvm.bitnet!j1o |
| j1o@psuvm (bitnet) |
| j1o@psuerie(bitnet) |
|-----------------------------------------------------------------------|
| |
| This space is blank when you are not looking at it. |
| |
+-----------------------------------------------------------------------+
------------------------------
Date: 23 Dec 86 23:12:50 GMT
From: felix!jim@hplabs.hp.com (Jim Gilbert)
Subject: Large Scale Test Suite Tools Wanted
I would appreciate references to any public domain or commercial packages
designed to facilitate the construction, operation, and maintenance
of script-driven regression testing suites for large-scale software
subsystems.
We desire to systematically exercise complex collections of transaction
processing, data base management, and records management software. We
would like tools to enable us to construct suites of tests which
were capable of running in unattended batch mode, and which produced
reports of the differences observed between expected results and the
results noted. Reports may be produced on the fly or by journaling
responses and comparing them to expected responses later.
The languages used to define test actions and expected responses
should be appropriate and much more productive to use than typical
high-level procedural languages, such as Pascal, FORTRAN, or C.
In our particular application we will be exercising complexes of
hardware and software configured in a LAN configuration. Out first
specific application area is building regression tests for our ISO
level 7 Application Services protocols.
I would also appreciate any pointers to published research on this
general topic.
Thank you kindly.
Jim Gilbert
Senior Consulting Engineer
FileNet Corporation
3530 Hyland Ave.
Costa Mesa, CA 92626 (714) 966-2344
...hplabs!felix!jim
------------------------------
Date: 24 Dec 86 01:29:27 GMT
From: hplabs!felix!fritz!kumar@seismo.CSS.GOV (John Kumar)
Subject: Expert System Shells on Unix and PCDOS
I am looking for an expert system shell that will run both under Unix and
PC-DOS. I need to be able to run it on the VAX with BSD 4.2 or DEC 8700 with
Ultrix and IBM-AT with PC-DOS. I am currently working with INSIGHT2+ from
Level Five Research. This "shell" runs on the IBM-AT and a VAX version
running under VMS is forthcoming from them.
Thanks for your input. In reply to my last request, except perhaps in the
Defence Dept., no work has been done on expert systems for software diagnosis.
Please reply to:
John Kumar
hplabs!felix!kumar
Thanks.
------------------------------
Date: 29 Dec 86 17:17:48 GMT
From: sundc!hqda-ai!merlin@seismo.css.gov (David S. Hayes)
Subject: Symbolics <--> Database
The Army AI Center is working on distribution of new
equipment to the Army, Army Reserve, and National Guard. As
you can imagine, we have enormous amounts of data to play
with. (Know how many different places need rifles?)
We have 12 Symbolics lisp machines, and a VAX-11/780.
The Oracle database is running on the VAX. We would like to
be able to access the database automatically, from inside an
expert-system program, without user intervention. Does
anyone have any software to do this? Has anyone ever tried
it? What did you learn?
We will be doing this ourselves, unless someone out in
net.land has already got a solution they would be willing to
share. If you know someone not on the net who could point
us in the right direction, please pass on their name and
phone number.
Thanks,
--
David S. Hayes, The Merlin of Avalon
PhoneNet: (202) 694-6900
ARPA: merlin%hqda-ai@brl-smoke
UUCP: ...!seismo!sundc!hqda-ai!merlin
------------------------------
Date: 29 Dec 86 16:57:00 EDT
From: wallacerm@afwal-aaa
Reply-to: <wallacerm@afwal-aaa>
Subject: Information on Proof of Correctness, Hardware Grammar
I N T E R O F F I C E M E M O R A N D U M
Date: 29-Dec-1986 04:31pm EST
From: Richard M. Wallace
WALLACERM
Dept: AADE
Tel No: 513-255-8654 (58654)
TO: Remote Addressee ( _MAILER! )
Subject: Material and Information on Proof of Correctness Contacts
Hello,
[...]
I am currently trying to find any work that has been done or is going on in
the areas of Formal Verification, Proof of Correctness, and Functional
Correcness for descriptive grammars in a LALR(1) form. My interest is focused
on analysis of only the descriptive LALR(1) grammar -- which includes
assertions and bounds -- without any annotation to the descriptive grammar.
The particular LALR(1) descriptive grammar that I am using is the Very High
Speed Integrated Circuit Hardware Description Language (VHDL) version 7.2.
This grammar is descriptive, it must be translated to another language that
can be compiled to executable form. VHDL is a structural/behavioral
simulation language for digital circuits. This is an overly brief description
of the language.
I have run across a lot of material on uses of prologs and frame-based shells
for structural circuit analysis, but have not seen any on text analysis for
grammars like the VHDL.
Any help would be appreciated.
Richard Wallace
AFWAL/AADE
WPAFB, OH 45433
513-255-8654
------------------------------
Date: Sun, 28 Dec 86 16:12 EST
From: Philip E. Agre <Agre@OZ.AI.MIT.EDU>
Reply-to: Survey@AI.AI.MIT.EDU
Subject: Everyday life survey
I need volunteers for an experiment. I've spent the last few years
studying small details of everyday routine activity, hoping to use my
observations to constrain theories of cognitive architecture. In doing
so, I've found it useful to write down anecdotes of small episodes from
ordinary activities like making breakfast and driving to work. This
method has some amazing properties. Suppose you've been worrying over,
say, deciding to perform two steps of an activity in a different order
than you have in the past. Then over the next few days, on several
occasions when such a thing occurs you will notice it. No need to
deliberately look out for them (and presumably much better if you
don't). Whenever this happens to me I write it down. Habitually
writing these things down then makes you notice them a LOT more. This
has to be experienced to be believed.
I want to get a lot of people to do this and see what happens. To this
end, I am going to describe two topics I've been interested in and
present some example stories about them. Read these descriptions. Then
when you spontaneously notice an example of them in your own activity,
write a paragraph or two about it. Collect these stories and send them
to Survey@MIT-AI (that's AI.AI.MIT.EDU in fancy notation).
First topic: Small mistakes.
Several psychologists have collected lists of what are often called
"action slips", mistakes one makes in the course of ordinary activity.
In reading these lists, I am always concerned at how remarkable they
are: how interesting or funny or odd. So I'd like to collect examples
of absolutely trivial mistakes of all types, ones that you quickly
recovered from without swearing or pondering or breaking stride. (Doing
so tends to make you think about whether there's a clear difference
between a mistake and something you tried that simply didn't work out.)
Example: I'd tipped my chair backward to lean against a shoulder-high
shelf. I was drinking a cup of tea and reading a book. It was kind of
a pain keeping the cup steady, so I went to put it down. Glancing
about, I found noplace convenient to put it except the shelf. Since my
shoulder was against the shelf, I saw the only way to put the cup on it
was to extend my arm fully. So I did this. I didn't bother watching
where the cup was going, instead I looked back at the book. I extended,
raised, moved back, and lowered my arm, expecting to feel the cup
landing on the shelf. After lowering my arm quite a lot this didn't
happen, so I looked and saw the cup wasn't over the shelf. Watching
this time, I did it again right.
Example: I often take the subway to work. Normally, given a choice, I
get on the train around the middle because the nearest exit from my
station is near the middle of the platform. Except now they're
rebuilding the station and they've closed that exit, as I discovered
yesterday morning. Nonetheless, this morning I got on near the middle
as usual. In fact, I got on more toward the front because there were
free seats in the next car along. I left the station through the main
exit.
Second topic: Anticipatory actions in a cyclic activity.
This happens an awful lot but for some reason there's no word for it.
When you start an activity, you do it in the obvious straightforward
order, but then you start rearranging and parallelizing the steps,
seemingly automatically.
Example: I had a stack of records propped up against a box and I was
alphabetizing it according to the artist's name, forming another,
sorted, stack propped up next to it. I would take a record from the top
of the first stack with my left hand, find and hold open the right place
for it in the second stack with my right hand, place the record in its
space, let the stack close over it, and repeat the cycle. After a while
I found I was doing something different: whereas before my eyes stayed
on the new record until I had picked it up, now I would read the
artist's name as soon as I was done with the last record. Then as I
picked it up with my left hand, my eyes were already helping my right
hand find the right place in the second stack.
Example: I was trying to get a long C program to compile. I was working
on a Sun and had divided the screen between two Unix shell windows so I
wouldn't have to exit and reenter the editor to run the compiler. I'd
run the compiler and it'd get errors, e.g., "syntax error near { on line
173", so I'd go back to the editor window. The only way I knew to get
to line 173 was to go to the top of the buffer and go down 172 lines.
This got to be a cycle, fixing errors and recompiling. After a while, I
found that I would move the editor to the top line before the compiler
had even starting generating error messages. (Finally one time the
compiler completed without errors and half of me had to skid to a
confused halt, but this detail is too amusing to be legal.)
[Try vi command 173G to skip to line 173. And for examples of
trivial little errors, you can't beat switching between vi and
emacs. Don Norman and others have done extensive studies of such
little errors, including the little errors that kill pilots. -- KIL]
Rules.
1. The episodes you write about must happen to you, in the course of
some solitary activity. They must happen after you read this note.
You cannot be aware of having this note or any other AI-ish topic on
your mind when they happen. You must have no memory of having
remarked on that same thing before.
2. They must be utterly mundane. They cannot be markedly stereotypical,
funny, disastrous, or otherwise interesting. They cannot have
occasioned any confusion, amazement, or careful reasoning-through.
3. You must write them down on the same day they happen. Write them
down accurately, being careful not to make them more clear-cut or
to-the-point than they actually were, in plain unscientific English,
the way you'd retell them as a story.
4. Though your descriptions naturally have to include any information
necessary to understand what happened, they cannot include any
speculations about "what was going on in your head" that weren't
definitely part of your experience of the episode at the time. If
you're unsure about some detail, say so.
If this experiment works out well, we can keep doing it periodically.
I suppose I'll write a paper about the experiments someday. Send any
notes requesting a copy to Survey-Request@MIT-AI.
Phil Agre
------------------------------
End of AIList Digest
********************
∂02-Jan-87 0139 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #2
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 2 Jan 87 01:36:48 PST
Date: Thu 1 Jan 1987 22:04-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #2
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 2 Jan 1987 Volume 5 : Issue 2
Today's Topics:
Review - Spang Robinson Report, December 1986,
Philosophy - Connectionism & Consciousness,
Seminar - The Qualitative Process Engine (BBN)
----------------------------------------------------------------------
Date: WED, 10 oct 86 17:02:23 CDT
From: leff%smu@csnet-relay
Subject: Spang Robinson Report, December 1986
Volume 2 Number 12, December 1986
Summary of Spang Robinson Report
AI at Microelectronics and Computer Technology Corporaiton (MCC)
Summary of organization and some of the projects of MCC.
In Douglas Lenat's attempt to encode "common sense" he will develop
20 megabytes of data, searchable by conventional technology, in 200
man-years.
MCC is working on Proteus, a shell with specific truth-maintenance capabilities.
__________________________________________________________________________
Maxell, a manufacturer of microcomputer disk products, is providing two
software products free of charge in their boxes of disks. The first is
a rule-based expert system that handles 400 rules, but which lacks math
in the rules and confidence factors. The other is a free-form
text searcher from Thunderstone called Logic-Line 1 with an integrated
thesaurus. [Thunderstone advertised several products including this
one in the March 1986 Byte among others. Logic-line1 was advertised
as "a major breakthrough in sub-cognitive mathematics" which "distills
the DNA/RNA like analog to any writer's thought processes." q. v. LEFF]
__________________________________________________________________________
New products:
Fuji Xerox - CSRL, a Battelle Memory Lab program running on the Xerox 1100
Fuji Xerox - a sytem for Smalltalk 80
Japan IBM - a Stock Portfolio Selection system for PC's
Mitsubishi - intelligent Dialog System
Mitsubishi - Meltran J/E English-Japanese translation system
Toshiba - English-Japanese system
Okidata - PENSEE, an English-Japanese system
Toshiba - Image Processor System
Sharp - Prolog interpreter/compiler for IX-5 and IX-7
__________________________________________________________________________
Other short notes
Intelligent Technology Incorporated has been selling Carnegie's
Knowledge Craft and Language Craft in Japan and the far east as well
as training other companies people to be knowledge engineers.
Nisshou Iwai, Marubeni and Nomura computers are investing in this
company.
...
AIR has been selling GCLISP for the PC 9801 and will be selling
it for the 286 based computers. ECC sells it for FM16B. MuLISP is also
popular in Japan.
Japan Univac is selling CAI systems for nuclear power operators and
for teaching people LISP.
Nihon LAD is working on an application system called LPS (logic program
synthesis)
Computer Applications Corp is working on a software maintenance expert system
and oen for estimating system size.
There are one hundred fielded systems based on Teknowledge's products
alone. Teknowlege had at least 300 more in advanced statges of development.
MONY and Harvard Tax and Investment Planners are using Plan Power, a
financial planning expert sytem to save 50 per cent time.
Inference and American Cimflex will be developing AI based computer-integrated
manufacturing products.
Votan is developing voice recognition systems that can handle 100 decibel
backgorund noises as found in manufacturing environments.
CL publications has purchased AI Expert.
Boole and Babbage are selling an expert system to work with their DASD
RESPONSE Manager.
__________________________________________________________________________
Review of Machinery of the Mind: Inside the New Science of Artificial
Intelligence which is for the nonspecialist. It has historical information
and info on the people who pioneered the field.
------------------------------
Date: 22 Dec 86 23:55:48 GMT
From: ihnp4!alberta!ubc-vision!ubc-cs!andrews@ucbvax.Berkeley.EDU
(Jamie Andrews)
Subject: Re: Challenge to Connectionists
In article <425@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>... meeting one or the other of the
>following criteria will be necessary:
> (i) Prove formally that not only is C not subject to perceptron-like
> constraints, but that it does have the power to generate
> mental capacity.
> (ii) Demonstrate C's power to generate mental capacity empirically...
Minsky and Papert's analysis of perceptrons was based on a very
exact and restricted type of machine. It seems to me that the
emphasis in the discussion about connectionism should be on proving
that the connectionist approach cannot work (possibly *using*
_Perceptrons_-like arguments), rather than that _Perceptrons_-like
proofs *cannot* be applied to connectionism.
I think both connectionists and anti-connectionists should be
involved in this proof process, however. I wouldn't want the
discussion to turn into yet another classic AI political battle.
>To summarize, my challenge to connectionists is that they either
>provide (1) formal proof or (ii) empirical evidence for their claims
>about the present or future capacity of C to model human performance
>or its underlying function.
If you mean by this that we should not study connectionism
until connectionists have done one of these things, then (as you
point out) we might as well write off the rest of AI too. The
main thing should be to try to learn as much from the connectionist
model as possible, and to accept any proofs of uselessness if
someone should come up with them. We can't expect to turn all
connectionist researchers into Minskys in order to prove theorems
about it that must needs be very complex.
--Jamie.
...!seismo!ubc-vision!ubc-cs!andrews
"Good heavens, Miss Sakamoto, you're beautiful"
This probably does not represent the views of the UBC
Computer Science Department, or anyone else, for that matter.
------------------------------
Date: Sun, 21 Dec 86 02:06:56 EST
From: "Keith F. Lynch" <KFL@AI.AI.MIT.EDU>
Subject: Consciousness
From: mcvax!ukc!rjf@seismo.CSS.GOV
If someone had lived for several years with a supposed-person who turned
out to be a robot, they would be severely shocked, when they discovered
that fact, and would *not* say 'Well, you certainly had me fooled. I guess
you robots must be conscious after all.'
That is what *I* would say. What WOULD be sufficient evidence for
consciousness? If only self experience is sufficient, does that mean
you don't think the rest of us are conscious?
What if YOU turned out to be a robot, much to your own surprise?
Would you then doubt your own consciousness? Or would you then say
"well, maybe robots ARE conscious, and humans AREN'T"?
The problem is not just about what would deserve the attribution of
consciousness, but about what we feel about making that attribution.
Huh? Does reality depend on feelings?
And such feelings go much deeper than mere prejudice. I think they go as
deep as love and sex, and are equally valid and valuable. I often turn
machines on, but they don't do the same for me - they're not good enough,
because they're not folks. And never will be.
What about aliens from another planet? They might give ample
evidence that they are intelligent (books, starships, computers,
robots, network discussion groups, etc) but might appear quite
physically repulsive to a human being. Would you believe them
to be conscious? Why or why not?
...Keith
------------------------------
Date: Thu, 18 Dec 86 18:45:46 n
From: DAVIS%EMBL.BITNET@WISCVM.WISC.EDU
Subject: unlikely submission to the ai-list...
*********rambling around conciousness*******************************************
There appear to me to be utterly different, though related, meanings of
the phrase `conciousness', especially when used in the ai-domain. The
first refers to an individual's sense of its own `conciousness', whilst
the second refers to that which we ascribe to other apparently sentient
objects, mostly other humans. There tends to be an automatic assumption
that the two are necessarily related, and in some guises, of course, this
is connected with the problem of `other minds'. However, the distinction
runs to the core of ai, particularly in connection with the infamous
Turing test. I would like to illustrate that this is so, and point to at
least one possible consequence for ai as a `nuts-and-bolts' discipline.
Let us ignore (perhaps forever!) the origin of the internal sensation of
conciousness, and concentrate upon our ascription of this capacity to
other objects. This ascription is dependent upon our observation of
some object's behaviour, and it could be argued, arises from our need to
rationalize and order the world as percieved. The ascription rests conditonally
upon an object exhibiting behaviour which is seen to either demand, or at
least be commensurate with, our own feeling of `conciousness'. This in turn
requires a whole subset of properties such as intentionality and intelligence.
As we note from everyday life, most humans fulfill these demands - their
behaviour appears purposeful, intelligent, self-concious etc..
However, turn now to an example which few would defend as being a case
of a sentient being: the ubiquitous and often excellent chess machine. Despite
our intellectual position being one of knowing that "this thing ain't nuthin'
but a blob of silicon", the reactions to, and more importantly, strategies
of play against such machines rarely fits what one might (naievly) expect
in the case of a complicated circuit. Instead, the machine is (publicly,
or privately) acknowledged to be `trying to win'. It is `smart'. It doesn't
like to lose. It `fouls up' or comes up with a `brilliant move'.
Of course, all this chat from computer chess players is meaningless - nobody
*really* believes in the will of the machine. Yet, it is very instructive
in the following sense: in order to formulate sensible strategies with a
well designed machine, we ascribe it intentionality. (I owe this argument
to Daniel Dennet) That is to say, we use the fact that the machine behaves
*AS IF* it had intent, despite the fact that we know it has no such capacity.
A similar, though more risky argument may be put forward for the reactions
of owners to their pets. I say more risky since it is arguable as to the
true status of sentience in dogs, cats etc..
This ascription of intentionality is not, I believe, a mistake, simply on
the grounds that intentionality simply does not exist. It is an explanatory
construct which creates an arbitrary class (`intentional objects'), but
has no real existence in the world (either as an emergent or concrete
property). What the ascription does is to provide a powerful way of dealing
with the world - it lets us make successful predictions about well designed
objects (such as human beings). We ccannot pretend that we really know
anything about why the somewhat loosely defined object called John invited
a similarly fluid Mary over for a meal, but we can make a lot of correct
prior judgements if we ascribe John with an intent......
So, back to nuts-and-bolts ai. As technicians sit in their nuts-and-bolts
laboratories, seeking the Josephson concurrent 5th generation hypercube
that will stroll though the Turing test, and into your lounge, workplace and
maybe even elsewhere, perhaps they should reflect upon their design
strategy. The accolade of appearing as `almost human' is a function of
the describer (aka: beauty is in the ......). Humans get special points
because they are exceedingly well designed, and hence our ascriptions
of intelligence, intentionality and conciousness do a very good job of
helping us to understand and interact with other people (They also seem
to work quite well with dogs.....).But this is ONLY because we do what do
exceedingly well, and what we do covers a very wide range of activities.
No computer that just tells the weather, just builds other computers,
or even just chats through a Turing interface will ever be regarded as we
regard other humans.Instead, they will get little more than the low level
ascription of intentionality that chess machines demand in order to beat
them. The assignment of conciousness, intelligence, and intentionality
are all just higher points in this scale, however.
To sum up - you can't build a 'concious' or an intelligent computer because
`conciousness' and `intelligence' are conceptual categories of description,
and not genuine properties. Current computers are not said to be `concious'
because we are able to understand and predict their behaviour without
invoking such a category. Build us a computer as bewildering as a certain
leading US politician, and the maybe, just maybe, we may have to turn round
and say "hell, this thing really has a mind of its own...". But then again...
paul davis
bitnet/earn/netnorth: davis@embl
on the relay interchat: 'redcoat' (central european daytime)
by mail: european molecular biology laboratory
postfach 10.2209
meyerhofstrasse 1
6900 heidelberg
west germany/bundesrepublic deutschland
------------------------------
Date: Sun, 21 Dec 86 05:20:44 EST
From: "Steven A. Swernofsky" <SASW%MX.LCS.MIT.EDU@MC.LCS.MIT.EDU>
Subject: Seminar - The Qualitative Process Engine (BBN)
Date: 25 Nov 1986 09:59-EST
From: Brad Goodman <BGOODMAN at BBNG.ARPA>
BBN Laboratories
Science Development Program
AI/Education Seminar
Speaker: Professor Kenneth D. Forbus
Qualitative Reasoning Group
University of Illinois
(forbus@a.cs.uiuc.edu)
Title: The Qualitative Process Engine
Date: 10:30a.m., Monday, December 1st
Location: 2nd floor large conference room,
BBN Laboratories Inc., 10 Moulton St., Cambridge
This talk describes how to use an assumption-based truth maintenance
system (ATMS) to build efficient qualitative physics systems. In
particular, I will describe the Qualitative Process Engine (QPE), a new
implementation of Qualitative Process theory that is signficantly simpler
and faster (by a factor of roughly 95) than the previous implementation.
After a short review of Qualitative Process theory, several organizing
abstractions for using an ATMS in problem solving will be identified. How
these abstractions can be applied to algorithms for qualitative physics
will then be described in detail. The performance of QPE is then compared
with a previous implementation, and the advantages and drawbacks of
ATMS technology will be discussed.
------------------------------
End of AIList Digest
********************
∂08-Jan-87 0048 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #3
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 8 Jan 87 00:48:30 PST
Date: Wed 7 Jan 1987 22:19-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #3
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 8 Jan 1987 Volume 5 : Issue 3
Today's Topics:
Queries - Prediction of Actions & Reasoning Under Uncertainty &
AI in Space Applications & Educational Material on AI &
Reviewers for New Review Journal in AI &
Reviewers for Methodologies for Studying Human Knowledge
----------------------------------------------------------------------
Date: 6 Jan 87 16:17 PST
From: zilberg.pasa@Xerox.COM
Subject: Query: goals based prediction
I am looking for pointers to
a. publications on intelligent prediction of a human object's actions
basing on his goals
b. an introdution literature on reasoning under uncertainty
Anna Zilberg
Zilberg.pasa@Xerox
Xerox Artificial Intelligence Systems
250 North Halstead Street, MS 432,
Pasadena, CA 91109
------------------------------
Date: Mon, 5 Jan 87 10:24:29 GMT
From: Ann Macintosh <alm%aiva.edinburgh.ac.uk@Cs.Ucl.AC.UK>
Subject: AI in Space Applications
Request for Information
AI in Space Applications
The AI Applications Institute at University of Edinburgh has recently been
awarded a grant by the UK Science and Engineering Research Council to look
at AI systems for a Technology Proving Satellite Study (T-SAT).
The proposed work is to consider two areas of application of AI for a
spacecraft: mission operation systems (MOS) and an on-board AI
technology demonstrator (O-BAIT).
One part of the study is a survey of previous and on-going research and
development of AI techniques related to spacecraft (ground-based and
on-board). We are now looking to complete our survey and in this
context I would appreciate any information on current work in this area
or surveys carried out.
Those that contribute significantly to our study will receive a copy of
the final report.
Replies to:
Ann Macintosh
AIAI
University of Edinburgh
80 South Bridge
Edinburgh EH1 1HN
UK
uk mail:alm@uk.ac.edinburgh.aiva
arpanet mail: alm%uk.ac.edinburgh.aiva@ucl-cs.arpa
------------------------------
Date: Tue 6 Jan 87 13:26:35-EST
From: John C. Akbari <AKBARI@CS.COLUMBIA.EDU>
Subject: educational material on ai
ever try explaining ai concepts to people who are good programmers and
even know something about ai, but who are not real experienced in
implementing ai? they've read the intro ai books & are ready for
intermediate and advanced levels of ai wizardry.
(have encountered this several times recently, & must
confess that it's difficult, especially when you try to explain
something you've haven't hacked a lot yourself.)
so, the question is, how do you do it? in looking around, it seems that
there is not a lot of material out there between the intro ai books that
explain at high levels (& the intro lisp books that give tons of syntax)
and the papers in _artificial intelligence_. on behalf of others who
may have run into this also, i'm willing to collect suggestions.
the best sort of thing is tutorial stuff like the second half of winston
& horn's lisp book (incremental description of some of the ideas that go
into developing a simplified version of something [rule-based expert
system, atn, object-oriented system]) with enough code to play with that
actually *works*. _inside computer understanding_ is also excellent.
experimenting with the simple version seems to be very helpful in
*incrementally* understanding how to design & debug a system.
does anyone in net land have, or know of, other sources? has anyone
done this sort of thing for a course, perhaps? pointers to
tech reports, course notes, tutorials, books in progress, mini versions
of master's or dissertation work, or especially
well-documented sources for simple versions of systems that can be studied
independently (in apprenticeship mode) are all great. public domain stuff
is probably best, but licenses are ok, too. any dialect of lisp is ok, even
prolog.
topics of interest (all the usual ai stuff):
expert systems (rule-based, object-oriented, etc.)
atn's
frame systems
truth maintenance systems
machine learning
intelligent computer-assisted instruction
...
so far:
winston & horn. _lisp_ (2nd ed.). [part ii.]
charniak, riesbeck, mcdermott. _artificial intelligence programming_.
charniak & mcdermott. _intro to ai_. [sprinkled throughout]
cullingford. _natural language processing: a knowledge engineering
approach_. [lots of sources sprinkled throughout]
keravnou & johnson. _competent expert systems: a case study in fault
diagnosis_. [lots of sources at the end]
touretzky. _advanced common lisp programming_. ijcai 86 tutorial.
[higher stages of hacking karma]
schank & riesbeck. _inside computer understanding_. [mini versions of
several dissertations.]
dekleer & forbus. _truth maintenance systems_. ijcai 86 tutorial.
[tough going, no sources]
will summarize to bboard.
ad...THANKS...vance!
john c akbari
ARPANET & Internet akbari@CS.COLUMBIA.EDU
BITnet akbari%CS.COLUMBIA.EDU@WISCVM.WISC.EDU
uucp & usenet ...!seismo!columbia!cs!akbari
DECnet akbari@cs
PaperNet 380 riverside drive, no. 7d
new york, new york 10025
SoundNet 212.662.2476
[The new AI Expert magazine seems to be what you want. -- KIL]
------------------------------
Date: 6 JAN 87 16:21-CST
From: SZTIPAJ%VUENGVAX.BITNET@WISCVM.WISC.EDU
Subject: New Review Journal in AI
To: The AI Community
From: J. R. Bourne and J. Sztipanovits,
Editors, CRC Critical Reviews in Artificial Intelligence
Subject: Knowledge Acquisition for CRC-CRAI
The CRC Press has recently announced the creation of
a new journal entitled "CRC Critical Reviews in Artificial
Intelligence" to be edited by J. Bourne and J. Sztipanovits
of Vanderbilt University. The CRC-CRAI will seek to
provide in-depth reviews of tightly constrained areas
in the broad field of Artificial Intelligence. We plan
to cover the breadth of the field and publish in the
following format. Each volume will consist of 4 issues
of roughly 100 pages in each issue. Each issue will contain
either 2 or 3 articles. The number of volumes published
each year will depend on the interest of the AI community.
The topic areas in AI that we have initially selected for
review include:
Knowledge Acquisition
Knowledge Representation
Automated reasoning
Learning
Education/Cognitive Modelling
Natural Language
Intelligent Robotics
Machine Vision
AI Languages
Applications
The purpose of this memorandum is to solicit opinions
and recommendations from the AI community concerning
prospective authors who would be capable of writing and
potentially willing to contribute excellent review articles
in the above areas. We are seeking authors who can review,
in depth, tightly constrained areas of research. At this
time we are not accepting papers for review or inviting
reviews; we are collecting a knowledge base about
authors and topics. Once this phase of the work is
complete we will begin to structure the initial
volumes of the journal.
If any of the above is of interest to anyone, and you
have suggestions for us, please reply to:
AIREVIEW@VUENGVAX.bitnet
------------------------------
Date: Wed, 7 Jan 87 10:50:24 EST
From: princeton!mind!harnad@seismo.CSS.GOV
Subject: Methodologies for Studying Human Knowledge
Subject: Anderson on algorithm/implementation: BBS Call for Commentators
Keywords: cognitive science, instructional science, AI, connectionism
Organization: Cognitive Science, Princeton University
The following is the abstract of a forthcoming article on which BBS
[Behavioral and Brain Sciences -- An international, interdisciplinary
Journal of Open Peer Commentary, published by Cambridge University Press]
invites self-nominations by potential commentators.
(Please note that the editorial office must exercise selectivity among the
nominations received so as to ensure a strong and balanced cross-specialty
spectrum of eligible commentators. The procedure is explained after
the abstract.)
-----
METHODOLOGIES FOR STUDYING HUMAN KNOWLEDGE
John R. Anderson
Psychology Department
Carnegie-Mellon University
Pittsburgh PA 15213
ABSTRACT
The appropriate methodology for psychological research depends
on whether one is studying algorithms or their implementation.
Mental algorithms are abstract specifications of the steps taken
by procedures that run in the mind. Implementational issues concern
factors that determine the speed and reliability with which these
procedures run. Issues at the algorithmic level can only be explored by
studying across-task variation. This contrasts with psychology's
dominant methodology of looking for within-task generalities,
which is only appropriate for studying implementational issues.
The implementation/algorithm distinction is related to a number of
other "levels" proposed in cognitive science. Its realization in the
ACT (Anderson 1973) theory of cognition is discussed. Research at the
algorithmic level is more promising because it is hard to make further
fundamental scientific progress at the implementational level with
the methodologies available at this level. Protocol data, which are
only appropriate for algorithm-level theories, provide a richer data
source than data available at the implementational level. Research at
the algorithmic level will also yield more insight into fundamental
properties of human knowledge because the significant learning
transitions are defined at this level.
The best way to study the algorithmic level is by pedagogical
experiments that manipulate instructional experience and look for
differential learning outcomes. This is because they provide control
and prediction in realistically complex learning situations. The
intelligent tutoring paradigm provides a particularly fruitful way to
implement such experiments. In addition to these major points, the
implications of this analysis are developed for the issue of modularity
of mind, the status of language, research on human-computer interaction,
and connectionist models.
-----
This is an experiment in using the Net to find eligible commentators
for articles in the Behavioral and Brain Sciences (BBS), an
international, interdisciplinary journal of "open peer commentary,"
published by Cambridge University Press, with its editorial office in
Princeton NJ.
The journal publishes important and controversial interdisciplinary
articles in psychology, neuroscience, behavioral biology, cognitive science,
artificial intelligence, linguistics and philosophy. Articles are
rigorously refereed and, if accepted, are circulated to a large number
of potential commentators around the world in the various specialties
on which the article impinges. Their 1000-word commentaries are then
co-published with the target article as well as the author's response
to each. The commentaries consist of analyses, elaborations,
complementary and supplementary data and theory, criticisms and
cross-specialty syntheses.
Commentators are selected by the following means: (1) BBS maintains a
computerized file of over 3000 BBS Associates; the size of this group
is increased annually as authors, referees, commentators and nominees
of current Associates become eligible to become Associates. Many
commentators are selected from this list. (2) The BBS editorial office
does informal as well as formal computerized literature searches on
the topic of the target articles to find additional potential commentators
from across specialties and around the world who are not yet BBS Associates.
(3) The referees recommend potential commentators. (4) The author recommends
potential commentators.
We now propose to add the following source for selecting potential
commentators: The abstract of the target article will be posted in the
relevant newsgroups on the net. Eligible individuals who judge that they
would have a relevant commentary to contribute should contact the editor at
the e-mail address indicated at the bottom of this message, or should
write by normal mail to:
Stevan Harnad
Editor
Behavioral and Brain Sciences
20 Nassau Street, Room 240
Princeton NJ 08542
(phone: 609-921-7771)
"Eligibility" usually means being an academically trained professional
contributor to one of the disciplines mentioned earlier, or to related
academic disciplines. The letter should indicate the candidate's
general qualifications as well as their basis for wishing to serve as
commentator for the particular target article in question. It is
preferable also to enclose a Curriculum Vitae. (This self-nomination
format may also be used by those who wish to become BBS Associates,
but they must also specify a current Associate who knows their work
and is prepared to nominate them; where no current Associate is known
by the candidate, the editorial office will send the Vita to
approporiate Associates to ask whether they would be prepared to
nominate the candidate.)
BBS has rapidly become a widely read read and highly influential forum in the
biobehavioral and cognitive sciences. A recent recalculation of BBS's
"impact factor" (ratio of citations to number of articles) in the
American Psychologist [41(3) 1986] reports that already in its fifth year of
publication (1982) BBS's impact factor had risen to become the highest of
all psychology journals indexed as well as 3rd highest of all 1300 journals
indexed in the Social Sciences Citation Index and 50th of all 3900 journals
indexed in the Science Citation index, which indexes all the scientific
disciplines.
Potential commentators should send their names, addresses, a description of
their general qualifications and their basis for seeking to comment on
this target article in particular to the address indicated earlier or
to the following e-mail address:
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
End of AIList Digest
********************
∂08-Jan-87 0232 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #4
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 8 Jan 87 02:32:07 PST
Date: Wed 7 Jan 1987 22:25-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #4
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 8 Jan 1987 Volume 5 : Issue 4
Today's Topics:
Philosophy - Intentions & Mind Modeling & Response to Minsky on Mind(s)
----------------------------------------------------------------------
Date: Sun, 4 Jan 87 19:51:22 EST
From: "Keith F. Lynch" <KFL%MX.LCS.MIT.EDU@MC.LCS.MIT.EDU>
Subject: Intentions
From: DAVIS%EMBL.BITNET@WISCVM.WISC.EDU
Subject: unlikely submission to the ai-list...
Of course, all this chat from computer chess players is meaningless -
nobody *really* believes in the will of the machine.
True.
This ascription of intentionality [to people] is not, I believe, a
mistake, simply on the grounds that intentionality simply does not exist.
It is an explanatory construct which creates an arbitrary class
(`intentional objects'), but has no real existence in the world ...
One minor flaw. I know that *I* have intentions. So there is at
least one thing in the world with intentions.
Given that I intend things, I find it plausible that other humans do
so as well. And given that human beings have intentions, I don't find
it totally impossible that machines might ever have intentions.
...Keith
------------------------------
Date: 7 Jan 87 03:28:09 GMT
From: sdcc6!calmasd!dbm@sdcsvax.ucsd.edu (Brian Millar)
Subject: mind modeling
I believe Stevan Harnad when he says he has a mind. The
alternative theory is that a mindless automaton is telling me.
How well does that fit with the preponderance of data? Very
poorly, considering that no AI program can yet generate the kind
of complex & original testimony he exhibits (despite his being
restricted to text displays). Therefore the rational, scientific
model for me to hold is that he has a mind with subjective
awareness just as I do.
Point: Testimony about subjective experience is a valid type of
data upon which reasonable scientific models of mind can be based.
The highly regular data which has accumulated in the area of
perception is almost entirely this type.
------------------------------
Date: Wed, 7 Jan 87 11:53:03 EST
From: princeton!mind!harnad@seismo.CSS.GOV
Subject: Response to Minsky on Mind(s)
On mod.ai, MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU (Marvin Minsky) wrote:
> the phenomena we call consciousness are involved with our
> short term memories. This explains why... it makes little sense to
> attribute consciousness to rocks.
I agree that rocks probably don't have short-term memories. But I
don't see how having a short-term memory explains why we're conscious
and rocks aren't. In particular, why are any of our short-term
memories conscious, rather than all being unconscious?
The extracts from Marvin Minsky's new book look as if they will be
very insightful correlative accounts of the phenomenology of (i) subjective
experience and (ii) the objective processes going on in machines that can be
interpreted as analogous to (i) in various ways. What none of the
extracts he has presented even hints at is (a) why interpreting any of
these processes (and the performance they subserve) as conscious is
warranted, and (b) why even our own processes and performance should
be conscious, rather than completely unconscious. That (as I've
regrettably had to keep recalling whenever it seems to be overlooked
or side-stepped) is called the mind/body problem.
Two constraints are useful in this sort of enterprise (just to keep
the real problem in focus and to prevent one from going off into
metaphor and hermeneutics):
(1) Before tackling the 2nd-order (and in many respects much easier)
problem of self-consciousness, it would be well to test whether one's
proposal has made any inroads on the problem of consciousness simpliciter.
To put it another way: Before claiming that one's account captures the
phenomenology of being aware that you're experiencing (or have
just felt), say, pain, one should show that one's account has captured
experiencing pain in the first place. (That's the little detail that
keeps slipping in the back door for free, as it does in attempts to
build perpetual motion machines or trisect the angle...)
(2) Before claiming with conviction that one has shown "why" a certain
performance is accomplished by a process that is validly interpreted
as a conscious one, one should indicate why the very same performance could
not be accomplished by the very same process, perfectly UNconsciously
(thereby rendering the conscious interpretation supererogatory).
> although people usually assume that consciousness is knowing
> what is happening in the minds, right at the
> present time, consciousness never is really concerned with the
> present, but with how we think about the records of our recent
> thoughts... how thinking about our short term memories changes them!
What does this have to do with, say, having a toothache now? Is there
anything in the short-term memory scenario that says (1) how my
immediate experience of the pain is a memory-function? (Note, I'm not
saying that subjective experience doesn't always involve some pasting
together of instants that, amongst others, probably requires memory.
My question concerns how the memory hypothesis -- or any other --
accounts for the fact that what is going on there in real time is
conscious rather than unconscious; how does it account for my
EXPERIENCE of pain?) And once that's answered, the second question is
(2) why couldn't all that have been accomplished completely
unconsciously? (E.g., if the "function" of toothache is to warn me of
tissue damage, to help me avoid it in future by learning from the past,
etc., why can't all that be accomplished without bothering to have
anything EXPERIENCE anything in the process?)
[In my view, by the way, this old conundrum about
thinking-perturbing-thinking is just another of the red herrings one
inherits when one focuses first on the 2nd-order awareness problem,
instead of the primary and much more profound 1st-order awareness problem.
This may make for the entertaining reflections about self-reference and
recursion in Doug Hofstadter's books or about the paradoxes of free
will in Donald MacKay's perorations, but it just circles around the mind/body
problem instead of confronting it head-on.]
[Let me also add that there are good reasons why it is called the
"mind/body" problem and not the "mindS/body" problem, as Marvin Minsky's
tacit pluralizations would seem to imply. The phenomenological fact is that,
at any instant, I (singular) have a toothache experience (singular).
Having this (singular) conscious experience is what one calls having a
(singular) mind. Now it may well be that one can INFER multiple processes
underlying the capacity to have such singular experiences. But the processes
are unconscious ones, not directly EXPERIENCED ones, hence they are not plural
minds, properly speaking. The fact that these processes may be INTERPRETABLE as
having local consciousnesses and intentions of their own is in fact yet
another argument against thus overinterpreting them, rather than an
argument for claiming we have more than one mind. Claims about minds
must rest exclusively on the phenomenological facts, which are,
without exception, singular. (This includes the putative problem cases
of multiple personality and altered states. Our contents of our
experiences can be varied, plural and bizarre in many ways, but it seems
inescapable that at any instant a person can only be the conscious subject
of one experience, not the subjects of many.)]
> Our brains have various agencies that learn to
> recognize - and even name - various patterns of external sensations.
> Similarly, there must be other agencies that learn to recognize
> events *inside* the brain - for example, the activities of the
> agencies that manage memories. And those, I claim, are the bases
> of the awarenesses we recognize as consciousness... I claim that to
> understand what we call consciousness, we must understand the
> activities of the agents that are engaged in using and changing our
> most recent memories.
You need an argument for (1) why any process you propose is correctly
interpreted as the basis of 1st-order awareness of anything --
external or internal -- rather than just a mindless process, and (2)
why the functions you describe it as accomplishing in the way it does
need to be accomplished consciously at all, rather than mindlessly.
> What do we mean by words like "sentience," "consciousness," or
> "self-awareness? They all seem to refer to the sense of feeling one's
> mind at work. When you say something like "I am conscious of what I'm
> saying," your speaking agencies must use some records about the recent
> activity of other agencies. But, what about all the other agents and
> activities involved in causing everything you say and do? If you were
> truly self-aware, why wouldn't you know those other things as well?
What about just a tooth-ache now? I'm not feeling my mind at work, I'm
feeling a pain. (I agree, of course, that there are many processes
going on in my brain that are not conscious; the real burden is to show
why ANY of them are conscious.)
> When people ask, "Could a machine ever be conscious?" I'm often
> tempted to ask back, "Could a person ever be conscious?"
> ...we can design our new machines as we wish, and
> provide them with better ways to keep and examine records of their
> own activities - and this means that machines are potentially capable
> of far more consciousness than we are.
"More" conscious than we are? What does that mean? I understand what
conscious "of" more means (more inputs, more sense modalities, more
memory, more "internal-process" monitoring) -- but "more conscious"?
[In its variant form, called the "other-minds" problem, by the way,
the question about (other) machines' consciousnesses and (other) persons'
consciousnesses are seen to be the same question. But that's no answer.]
> To "notice" change requires the ability to resist it, in order
> to sense what persists through time, but one can do this only
> by being able to examine and compare descriptions from the recent past.
Why should a process that allows a device to notice (respond to,
encode, store) change, resist it, examine, compare, describe, remember,
etc. be interpreted as (1) a conscious process, and (2) why couldn't it
accomplish the exact same things unconsciously?
I am not, by the way, a spokesman for the point of view advocated by
Dreyfus or by Searle. In asking these pointed question I am trying to
show that the mind/body problem is a red herring for cognitive
science. I recommend methodological epiphenomenalism and performance
modeling as (what I believe is) the correct research strategy. Instead
of spending our time trying to build metaphorical perpetual motion
machines, I believe we should try to build real machines that capture our
total performance capacity (the Total Turing Test).
------------------------------
End of AIList Digest
********************
∂08-Jan-87 0429 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #5
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 8 Jan 87 04:29:36 PST
Date: Wed 7 Jan 1987 22:29-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #5
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 8 Jan 1987 Volume 5 : Issue 5
Today's Topics:
Humor - Proposed Workshops for AAAI-87,
Seminars - Building Expert Systems in Loops (Denver IEEE) &
Time Modeling with Intervals (SU),
Conferences - Genetic Algorithms &
Workshop on Blackboard Systems &
Machine Learning Workshop
----------------------------------------------------------------------
Date: 2 Jan 87 11:12 PST
From: Shrager.pa@Xerox.COM
Subject: Proposed workshops for AAAI-87
Pursuent (-suant? -suint?) to Joseph Katz' call for workshop proposals
for AAAI-87, here are some suggestions:
*A. Hype: Hype and fleecing technology is growing in importance, even
as the field stagnates. This workshop will focus on virtual expert
systems for trivial domains; simulated robotics; and machine learning.
Attendance is limited to those who have contriubuted heavily to the
popular press (e.g., AI Magazine), or previous AAAI meetings. Invited
speakers: >>censored<<.
*B. AI and Softwar Engineering: This workshop will explore applications
of AI to wiping all living things off the face of the earth, and
destroying most beautiful natural and man-made objects. Since there are
so many relevant projects currently in progress, attendance will be
strictly limited to those who are not and have never been members of the
democratic party (no voter reg. cards required, we know who you are). A
special talk will be given by John DOE of The Agency, entitled:
"Automated Paranoia in the Pentagon's ''NutShell'' Programming
Environment".
*C. The Philosopher's Stone: Philosophy faculty will gather at this
workshop to discuss investigations in the morals and methods of
utilizing AI toward tenure and potential relevance. A special section
will be given on introductory programming (probably Lisp or Basic) for
those interested in gaining more understanding of the field. (This
workshop will not overlap with the workshop on Softwar Engineering).
*D. Problem Finding: The problem-solving community is running short of
problems that are isomorphic to either the Tower of Hanoi, or the
N-Queens puzzle. In this workshop proposals will be considered for
problem domains that are probably intractible, but still irrelevant. The
participants will also explore methods of going beyond renaming one's
symbol set in moving to a new domain. (Proposed technical sessions
urgently called for!)
#E. Machine Vision: -- Cancelled due to difficulties in finding a room
--
#6. Quantitative Physics: The successes and failures of qualitative
physics in AI has led researchers to propose a "quantitative physics" as
a finer approximation to reality. This meeting will focus on several
special topics in this newly emerging field including discovery of some
fascinating *quantitative* representations of the behavior of an
object moving in a straight line in a perfect vacuum with no external
forces, and a way of *quantitatively* figuring out how fast a car will
come to a stop from a certain ideal (quantitative) velocity given
certain ideal braking forces. Some recent results in quantitaive limit
cases will also be given, as an extension to recently developed
quantitative algebras. Invited speaker: Ceteris Paribus of the U. of
Milan.
#n. Humor: It is widely recognized that AI takes itself too $%~#ing
seriously. The purpose of this workshop will be to formulate a policy
toward a more laid-back field with enough maturity to laugh at itself a
little. Attendees must submit a title and abstract in some pseudo-field.
Previous examples have included: "A Black Magic Advisor", "Why the
Editor has no Close", and a series of proposed AAAI-87 workshops.
Invited speaker: Drew McDermott.
------------------------------
Date: 6 Jan 87 23:20:05 GMT
From: ihnp4!drutx!druxv!sandy@ucbvax.Berkeley.EDU (BishSL)
Subject: Seminar - Building Expert Systems in Loops (Denver IEEE)
The Denver Chapter of the IEEE Computer Society proudly
presents:
"Building Expert Systems in LOOPS"
Andrew MacRae, of XEROX Corp., will speak on the Lisp
Object Oriented Programming System, a software tool built at
XEROX PARC for knowledge programming. This is a powerful tool
that extends the power of the Interlisp-D programming environment
& brings several programming methodologies to bear on any problem.
Procedure, object, data & rule-oriented methods will be explored
in this demonstration of LOOPS on the XEROX 1186 AI Workstation.
YOU DO NOT NEED TO BE AN IEEE MEMBER TO ATTEND! Come one, come all.
For more information, call 538-8157 or 934-3635.
When: Tuesday, Jan 13, 6:30pm
Where: AT&T Information Systems
I-25 & 120th, Denver
How to get there: North on I-25; exit west on 120th Avenue
Take second left (south) on Pecos Street
Take second drive (east) into large parking lot
Enter through revolving doors
Meet in the lobby before 6:30pm
------------------------------
Date: 07 Jan 87 1642 PST
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Time Modeling with Intervals (SU)
Commonsense and Nonmonotonic Reasoning Seminar
NEW RESULTS ON TIME MODELLING WITH INTERVALS
Peter Ladkin
Kestrel Institute
(ladkin@kestrel.arpa)
Thursday, January 15, 4pm
Bldg. 160, Room 161K (NEW PLACE!)
James Allen introduced a calculus for reasoning about time using
intervals, instead of points. In this talk, we shall indicate two
new results for time modelling using intervals, and indicate why
they help overcome some of the objections to using an interval system
for reasoning about time. Much of this work is joint with Roger
Maddux. Briefly, we have shown that there is only one countable
representation of the calculus, up to isomorphism, and that the
system of time units introduced in [Ladkin AAAI-86] is isomorphic
to this countable representation.
------------------------------
Date: Mon, 5 Jan 87 13:00:07 est
From: John Grefenstette <gref@nrl-aic>
Subject: Conference - Genetic Algorithms
Call for Papers
2nd International Conference on Genetic Algorithms
and Their Applications
The 2nd International Conference on Genetic Algorithms and
Their Applications, sponsored by AAAI and the U.S. Navy
Center for Applied Research in AI (NCARAI), will be held on
July 28-31, 1987 at MIT in Cambridge, Mass. Authors are
invited to submit papers on all aspects of Genetic Algo-
rithms, including: foundations of genetic algorithms,
machine learning using genetic algorithms, classifier sys-
tems, apportionment of credit algorithms, relationships to
other search and learning paradigms. Papers discussing
specific applications (e.g., OR, engineering, science, etc.)
are encouraged.
Authors are requested to send three copies (hard copy only)
of a full paper by April 1, 1987 to the program chair:
Dr. John J. Grefenstette
Navy Center for Applied Research in AI
Code 5510
Naval Research Laboratory
Washington, DC 20375-5000
gref@NRL-AIC.ARPA
(202) 767-2685
For registration forms and information concerning local
arrangements, contact:
Mrs. Gayle M. Fitzgerald
Conference Services Office
Room 7-111
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139
(617) 253-1703
Conference Committee:
John H. Holland University of Michigan (Conference Chair)
Lashon B. Booker Navy Center for Applied Research in AI
Dave Davis Bolt Beranek and Newman Incorporated
Kenneth A. De Jong George Mason University
David E. Goldberg University of Alabama
John J. Grefenstette Navy Center for Applied Research in AI
Stephen F. Smith Carnegie-Mellon Robotics Institute
Stewart W. Wilson Rowland Institute for Science
------------------------------
Date: Tue, 6 Jan 87 17:11:33 pst
From: Vasudevan Jagannathan <juggy@BOEING.COM>
Subject: Conference - Workshop on Blackboard Systems
Call for Participation
Workshop on Blackboard Systems: Implementation Issues
In the past couple of years a wide variety of black-
board systems have been built to address a wide variety of
problems. The goal of this workshop is to study the design
and implementation issues in blackboard systems and to
understand the diversity which exists in such systems.
Specific issues that will be focused on are:
1. Control Issues: What is the approach taken to control
the problem solving and rationale for choice?
2. Organization Issues: What are the mechanisms available
for organizing knowledge in such systems? If the system is
distributed what are the communication issues that play a
critical role in the development of the system.
3. Parallelism and Concurrency Issues: What scope is
present in the system to exploit parallelism at the applica-
tion level, at the system level?
4. Performance issues: What benchmarks are available for
evaluating the performance, and what are the bottlenecks
affecting performance?
5. Development Environment: Does the system provide any
help in developing the actual application?
To encourage vigorous interaction and exchange of ideas
between those attending, the workshop will be limited to
approximately 30 participants. The workshop is scheduled on
July 13th, 1987, Monday, as a parallel activity during AAAI
1987, and will last for a day.
All submitted papers will be refereed with respect to
how well they identify and discuss the factors affecting the
design and implementation of blackboard systems. Authors
should discuss their design decisions (why a particular
approach was selected); what worked, what did not and why;
the advantages, disadvantages and limitations of their
approach; and what they would recommend to others developing
such systems. Preference will be given to those papers that
discuss approaches that have been demonstrated in real
applications.
Submission Details: Five copies of an extended abstract,
double spaced draft up to 4000 words, should be submitted to
the workshop chairman before April 1, 1987. Acceptances
will be mailed by May 1, 1987. Final copies of the extended
abstract will be required by June 1, 1987 so that they may
be informally bound together for distribution before the
workshop.
Workshop Chairman: V. Jagannathan, M/S 7L-64, The Boeing
Advanced Technology Center, Boeing Computer Services, P.O.
Box 24346, Seattle, WA 98124-0346. Telephone: (206)865-3240.
E-mail:juggy@boeing.com.
------------------------------
Date: Wed, 07 Jan 87 10:58:29 -0800
From: Pat Langley <langley@CIP.UCI.EDU>
Subject: Conference - Machine Learning Workshop
Fourth International Workshop on Machine Learning
Recently, machine learning has emerged as a central area of research in
artificial intelligence and cognitive science. In order to increase
communication between researchers in this growing field, the Fourth
International Workshop on Machine Learning will be held at the University
of California, Irvine during June 22-25, 1987.
In an attempt to maximize interaction at the workshop, attendance will be
limited and participation will be through invitation only. If you are active
in machine learning and if you are interested in receiving an invitation, we
encourage you to submit a one-page summary of your recent work in the area.
If you would like to present a paper at the meeting, include a title and
extended abstract. You may supplement this information with recent papers on
machine learning.
Invitations will be based on an informal review of the research summaries by
the organizing committee. Based on their abstracts, some attendees will be
invited to speak at the workshop and to contribute a paper to the workshop
proceedings. Each participant will receive a copy of the proceedings. The
organizing committee consists of: J. G. Carbonell (C-MU), R. H. Granger
(UCI), D. F. Kibler (UCI), P. Langley (UCI), T. M. Mitchell (C-MU), and R.
S. Michalski (Illinois).
The deadline for submission of research summaries is February 1, 1987.
Please send summaries, along with abstracts and optional papers, to: Pat
Langley, Program in Computation and Learning, Department of Information &
Computer Science, University of California, Irvine, CA 92717 USA. Applicants
will be informed of their status two weeks after submission.
------------------------------
End of AIList Digest
********************
∂11-Jan-87 2339 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #6
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 11 Jan 87 23:38:51 PST
Date: Sun 11 Jan 1987 21:37-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #6
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 12 Jan 1987 Volume 5 : Issue 6
Today's Topics:
Queries - AI and Software Engineering & Go,
Newsletter - Expert Systems,
Philosophy - Consciousness,
Conferences - Coupling Symbolic and Numeric Computing &
Unigroup AI Meeting &
AI and Law
----------------------------------------------------------------------
From: Rolf Pfeifer <pfeifer%ifi.unizh.chunet@RELAY.CS.NET>
Subject: references on AI and software engineering
I am looking for literature on AI and software engineering.
Please reply to:
pfeifer%ifi.unizh.chunet@csnet-relay.csnet
Thank you.
--Rolf Pfeifer
------------------------------
Date: Thu, 8 Jan 87 23:05 EST
From: Troy Shinbrot <900380%UMDD.BITNET@WISCVM.WISC.EDU>
Subject: Go
Rumor has it that programs which play Go on personal computers have recently
become available. Because Go is more complex than Chess, for example, and
because of a long standing interest in Go, I would be greatly appreciative
to anyone who can refer me to either the programs, their sources or literature
concerning Go and the programming of a computer to play same.
Thanks in advance.
- Troy Shinbrot (aka. 900380@umdd.bitnet)
------------------------------
Date: 9 Jan 87 14:53:44 GMT
From: Allan Black <mcvax!cs.strath.ac.uk!allan@seismo.CSS.GOV>
Subject: Newsletter on Expert Systems
A newsletter on the application of expert systems to information
science and information management has been launched by the
Department of Information Science
University of Strathclyde
26 Richmond Street
Glasgow G1 1XH
UK
ALANET 1158
BT GOLD 79:GOW006
Further information from Forbes Gibb, #6.00 for 3 issues,
#10.00 overseas
------------------------------
Date: Thu, 08 Jan 87 18:30:09 n
From: DAVIS%EMBL.BITNET@WISCVM.WISC.EDU
Subject: Minksy's Mind(s)
from: princeton!mind!harnad@seismo.CSS.GOV
subject: response to Minsky on Mind(s).
> The real burden is to show why ANY [mental processes]
> of them are concious.
I'm not convinced that this is quite the case. The problem, if one exists
in the area of research/design strategy, is to show HOW any of them are
concious. There is almost no doubt that toothache could be dealt with by
an automaton - the fact that that it appears in at least one case (author
listed above] to be conciously experienced must surely provoke both
questions. However, the question of why conciousness has emerged is surely
in the area of evolutionary biology (and to be sure workers like Armstrong
have made some very interesting suggestions as to the reasons for concious-
ness emerging). In the domain of AI, the only question that makes sense
about conciousness is the most fundamental of all - how is it possible
to know (aka:be aware of, be concious of) ANYTHING at all ?
But in the meantime, I would re - echo the final sentiments expressed: just
get on with building superb, rich and complicated machines - leave the
installation of the 'conciousness chip' to good luck.....
.....paul
------------------------------
Date: Fri, 9 Jan 87 09:44:44 PST
From: Steven L. Speidel <speidel%cod@nosc.ARPA>
Subject: Discussion of "consciousness"
I would say that if one is "conscious" of an event, then
the features/schema of that event are available to his
goal-setter/planner for planning of future behavior ( and
vice-versa ).
------------------------------
Date: 7 Jan 87 01:36:30 GMT
From: ssc-vax!bcsaic!tedk@beaver.cs.washington.edu (Ted Kitzmiller)
Subject: Conference - Coupling Symbolic and Numeric Computing
CALL FOR PARTICIPATION
----------------------
Workshop on Coupling Symbolic and Numeric Computing
in Knowledge-based Systems
The second workshop on coupling symbolic and numeric computing in
knowledge-based systems will be held the 20-24 of July 1987 at the
Boeing Advanced Technology Center, Bellevue, Washington. This
workshop will be jointly sponsored by the American Association for
Artificial Intelligence (AAAI) and Boeing Computer Services (BCS).
Many real-life problems encountered in science and industry require solution
techniques that combine AI and conventional computation methods (coupled
systems). Typically these problems have some major subproblems that are
amenable to conventional techniques - such as numerical analysis, statistics,
quantitative modeling - but others for which these techniques are not
appropriate.
This workshop will attempt to build upon last year's workshop and improve
our understanding of the issues involved in developing coupled systems.
During the workshop the methodology of designing and developing coupled
systems will be explored by assessing alternative approaches. The primary
goals of the workshop will be to establish criteria and guidelines for those
involved in the design and implemention of coupled systems and to define the
state-of-the-art and the future research needs in this area.
To encourage a vigorous interaction and exchange of ideas between those
attending, the workshop will be limited to approximately 35 participants.
Ample time will be provided during the workshop for the presentation of
technical papers and discussions of the material presented. Participation
will be by invitation and will be based upon the referee of a submitted paper.
Submittals are invited for consideration on the following topics: software and
hardware architectures that facilitate the development and use of coupled
systems (or those that don't), approaches to designing and developing coupled
systems, deep reasoning involving quantitative models or numeric algorithms,
representation of knowledge within coupled systems, generic coupled system
languages/shells, and novel or state-of-the-art applications.
All submitted papers will be refereed with respect to how well they identify
and discuss the factors affecting the design and implementation of coupled
systems. Authors should discuss their design decisions (why a particular
approach or development environment was selected); what worked, what didn't
and why; the advantages, disadvantages and limitations of their approach; and
what they would recommend to others developing coupled systems. Preference
will be given to those papers that discuss approaches that have been
demonstrated in real applications.
Four copies of a full-length paper (or extended abstract), double spaced draft
up to 5000 words, should be submitted to the workshop chairman before 1 March
1987 (please notify the chairman by 30 January 1987 of your intent to submit).
Acceptances will be mailed by 1 May 1987. Final papers will be required by 1
July 1987 so they may be bound together for distribution before or at the
workshop. Potential attendees should also indicate their interest in chairing
or participating in special discussion sessions.
Workshop Chairman: C.T. Kitzmiller,
MS: 7J-63, Boeing Advanced Technology Center, Boeing Computer Services,
PO Box 24346, Seattle, Washington, 98124-0346.
Telephone: (206) 865-3227.
E-mail: tedk@boeing.com or bcsaic!tedk@uw-june.arpa
------------------------------
Date: 8 Jan 87 00:43:32 GMT
From: mcnc!philabs!tg!len@seismo.css.gov (Len Schmirl)
Subject: Presentation - Unigroup AI Meeting
Artificial Intelligence and Expert Systems
Wednesday, January 14, 1987
Shimmel Center for the Performing Arts
Pace University, Park Row, New York, NY
6:00 - 7:00pm - Registration/Refreshments/Vendor Demos
7:00 - 9:30pm - Speakers and Vendor Presentaions
Speaker: Karl M. Wiig - Director, AI Application Center
Arthur D. Little, Inc.
Vendors: The Carnegie Group, Pittsburgh, PA, will be displaying
Knowledge Craft, a software environment for building expert
systems, and Language Craft, a tool for producing a natural
language front end for expert systems.
Construction Software, Alameda, CA, will be displaying WProlog,
a window and graphics oriented version of the Prolog language
suitable for the development of AI applications.
Inference, Los Angeles, CA, will be displaying ART, an applications
development environment for the development of industrial
grade expert systems.
Intellicorp, Mountain View, CA, will be displaying KEE (Knowledge
Engineering Environment). KEE is designed to assist system
developers in building knowledge based applications.
Silogic, Los Angeles, CA, will be displaying their Knowledge
WorkBench, which is designed to assist in the development of
expert systems.
Annual membership: $50.00
January 14 meeting only: $15.00
For further information, please contact:
UNIGROUP of New York, Inc.
GPO Box 1931
New York, NY 10116
uucp: {attunix, philabs, cubsvax}!pencom!unigroup
UNIGROUP of New York, the New York Area UNIX Users Group, is an association of
UNIX users dedicated to advancing their understanding of the UNIX system as
well as the solutions it can provide. Through bimonthly meetings, newsletter,
electronic bulletin board and other avenues of communication, our members
interact and exchange valuable information and insight into the UNIX system.
All individuals and corporations interested in the UNIX system are welcome to
participate in the educational and social activities of UNIGROUP of New York.
Please attend our next meeting and experience first hand how valuable the
largest regional UNIX users group can be to you and your business.
--
Len Schmirl uucp: philabs!tg!len
Townsend-Greenspan & Co., Inc. attmail: tg!len
120 Wall Street
New York, NY 10005
------------------------------
Date: 8 Jan 87 14:30:33 EST
From: MCCARTY@RED.RUTGERS.EDU
Subject: Conference - AI and Law
FINAL CALL FOR PAPERS:
First International Conference on
ARTIFICIAL INTELLIGENCE AND LAW
May 27-29, 1987
Northeastern University
Boston, Massachusetts, USA
In recent years there has been an increased interest in the applications of
artificial intelligence to law. Some of this interest is due to the potential
practical applications: A number of researchers are developing legal expert
systems, intended as an aid to lawyers and judges; other researchers are
developing conceptual legal retrieval systems, intended as a complement to the
existing full-text legal retrieval systems. But the problems in this field are
very difficult. The natural language of the law is exceedingly complex, and it
is grounded in the fundamental patterns of human common sense reasoning. Thus,
many researchers have also adopted the law as an ideal problem domain in which
to tackle some of the basic theoretical issues in AI: the representation of
common sense concepts; the process of reasoning with concrete examples; the
construction and use of analogies; etc. There is reason to believe that a
thorough interdisciplinary approach to these problems will have significance
for both fields, with both practical and theoretical benefits.
The purpose of this First International Conference on Artificial Intelligence
and Law is to stimulate further collaboration between AI researchers and
lawyers, and to provide a forum for the latest research results in the field.
The conference is sponsored by the Center for Law and Computer Science at
Northeastern University. The General Chair is: Carole D. Hafner, College of
Computer Science, Northeastern University, 360 Huntington Avenue, Boston MA
02115, USA; (617) 437-5116 or (617) 437-2462; hafner.northeastern@csnet-relay.
Authors are invited to contribute papers on the following topics:
- Legal Expert Systems
- Conceptual Legal Retrieval Systems
- Automatic Processing of Natural Legal Texts
- Computational Models of Legal Reasoning
In addition, papers on the relevant theoretical issues in AI are also invited,
if the relationship to the law can be clearly demonstrated. It is important
that authors identify the original contributions presented in their papers, and
that they include a comparison with previous work. Each submission will be
reviewed by at least three members of the Program Committee (listed below), and
judged as to its originality, quality and significance.
Authors should submit six (6) copies of an Extended Abstract (6 to 8 pages) by
January 15, 1987, to the Program Chair: L. Thorne McCarty, Department of
Computer Science, Rutgers University, New Brunswick NJ 08903, USA; (201)
932-2657; mccarty@rutgers.arpa. Notification of acceptance or rejection will
be sent out by March 1, 1987. Final camera-ready copy of the complete paper
(up to 15 pages) will be due by April 15, 1987.
Conference Chair: Carole D. Hafner Northeastern University
Program Chair: L. Thorne McCarty Rutgers University
Program Committee: Donald H. Berman Northeastern University
Michael G. Dyer UCLA
Edwina L. Rissland University of Massachusetts
Marek J. Sergot Imperial College, London
Donald A. Waterman The RAND Corporation
------------------------------
End of AIList Digest
********************
∂19-Jan-87 0119 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #7
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 19 Jan 87 01:15:05 PST
Date: Sun 18 Jan 1987 23:16-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #7
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 19 Jan 1987 Volume 5 : Issue 7
Today's Topics:
Queries - Character Recognition & Lisp Machine Window Systems &
Scheme & TOOLKIT,
Games - Go,
Sources - Postings from AI EXPERT Magazine,
Magazine - Canadian Artificial Intelligence,
Report - Learning to Predict
----------------------------------------------------------------------
Date: 13 Jan 87 13:30:41 GMT
From: lerouf.dec.com!denis@decwrl.dec.com (MICHEL DENIS, @KALAMAZOO@VBO)
Subject: Character recognition.
About CHARACTER RECOGNITION :
Has anybody a list of books and publications related to character/words
recognition and its algorithms ? Also especially any piece of software which
implements some of those techniques would be useful for a start !
Thanks in advance and regards,
Michel.
ps: please mail me on :
(DEC E-NET) LEROUF::DENIS
(UUCP) ...decvax!decwrl!dec-rhea!dec-lerouf!denis
(ARPA) denis%lerouf.DEC@decwrl.ARPA
[For a starter, try Srihari's IEEE tutorial on Computer Text Recognition
and Error Correction. The annual conferences on Pattern Recogniton are
good, and there are always some papers on character recognition in the
annual conferences on Computer Vision and Pattern Recognition (formerly
Pattern Recognition and Image Processing). -- KIL]
------------------------------
Date: Thu, 15 Jan 87 09:58:16 PST
From: TAYLOR%PLU@ames-io.ARPA
Subject: Request for Info on Lisp Machine Window Systems
We have been developing a user interface for a planning/scheduling
application on the Symbolics, using Version 6.1 windows and flavors.
For future long term development of the user interface, we are
considering a possible change of the window system, before converting
to Genera 7.0 Dynamic windows and Presentation types. We have heard
mention of XWINDOWS and are interested in knowing about it and other
"generic" window systems and the trade-offs between specialized
features and portability.
Issues we are looking at:
o will window system be compatible with a future Common
lisp window standard
o will window system be portable between lisp machines and
AI work stations, e.g. Symbolics, TI, LMI, Xerox, Sun, ..
o how much conversion will be required to go from current
implementation, now running under Genera 7.0, to a new
window system
o what are advantages/disadvantages of potential window
systems as far as ease of implementation, facilities
available to present information to user, use of object
oriented techniques, etc
o availability of potential window systems on the Symbolics
Opinions and recommendations are solicited from Lisp machine users
as to their experience and preferences. Please respond by e-mail.
I will summarize for this bboard if requested and sufficient responses
are received.
Thanks - Will
Will Taylor - Sterling Software, MS 244-7,
NASA-Ames Research Center, Moffett Field, CA 94035
arpanet: taylor%plu@ames-io.ARPA
uusenet: ..!ames!pluto.decnet!taylor
phone : (415)694-6525
------------------------------
Date: 15 Jan 87 19:42:44 GMT
From: crawford@husc4.harvard.edu (alexander crawford)
Subject: Re: IEEE Computer Society Meeting on AI Workstation (in Denver)
In article <729@druxv.UUCP> sandy@druxv.UUCP (BishSL) talks about
getting a copy of text on the SCHEME language. Does anyone know if
this is available on PC's yet?
---Alec Crawford
------------------------------
Date: Sat, 17 Jan 87 12:55 EST
From: Hoebel@RADC-MULTICS.ARPA
Subject: TOOLKIT
Anyone who has used Richard Cullingford's TOOLKIT and would
like to share experiences/knowledge with our natural language group at
Rome Air Development Center, please contact Walter at RADC-TOPS20 or
Hoebel at RADC-MULTICS.
------------------------------
Date: 15 Jan 87
From: vnend@ukecc.uky.csnet (D. W. James)
Reply-to: vnend@ukecc.UUCP (D. W. James)
Subject: Re: Go
Forwarded by: <cbosgd!ecc.engr.uky.csnet!edward@seismo.CSS.GOV>
"Edward C. Bennett" <ukecc!edward@seismo.CSS.GOV>
In article <8701120553.AA08679@ucbvax.Berkeley.EDU> 900380@UMDD.BITNET
(Troy Shinbrot) writes:
>Rumor has it that programs which play Go on personal computers have recently
>become available.
>- Troy Shinbrot (aka. 900380@umdd.bitnet)
The one encounter that I have had with a GO program was very
disappointing. The program is titled simply "Go" and is from Hayden
Software (Sargon III, among others). I am not an experianced player,
less than 50 games vs human opponents and a little reading, and I had
no problem beating it even with a 9 stone handicap.
Later y'all, Vnend Ignorance is the Mother of Adventure.
UUCP:cbosgd!ukma!ukecc!vnend; or vnend@engr.uky.csnet; or cn0001dj@ukcc.BITNET
------------------------------
Date: 14 Jan 87 23:30:08 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: source postings from AI EXPERT magazine
The following was posted to mod.sources, but that group seems to be
somewhat back logged.
I have the following sources from AI EXPERT magazine and will post
them if there is enough interest, my intention is to do this on a
monthly basis and i need feedback as to:
a) is this desired
b) should i just post the index and post the sources (in arc format)
only if there is interest
c) should i post the sources every month and assume there is enough
interest to justify the network traffic
and now for this month's list of software, for now send me email if
you want the sources and if i get enough requests i will post the
whole arc file.
=======+=======+=======+=======+=======+=======+=======+=======+=======+=====
Articles and Departments that have
Additional On-Line Files
AI EXPERT
January 1987
(Note: Contents page is in file CONTNT.JAN)
ARTICLES RELEVANT FILES
January Table of Contents CONTNT.JAN
Adding Rete Net to Your OPS5 Toolbox OPSNET.JAN
by Dan Neiman
Perceptrons & Neural Nets PERCEP.JAN
by Peter Reece
DEPARTMENTS
Expert's Toolbox EXPERT.JAN
"Using Smalltalk to Implement Frames"
by Marc Rettig
AI Apprentice AIAPP.JAN
"Creating Expert Systems from Examples"
by Beverly and Bill Thompson
C'est la vie, C'est la guerre, C'est la pomme de terre
Mail: Imagen Corp. 2650 San Tomas Expressway Santa Clara, CA 95052-8101
UUCP: ...{decvax,ucbvax}!decwrl!imagen!turner AT&T: (408) 986-9400
------------------------------
Date: Tue, 13 Jan 87 17:56:49 est
From: Graeme Hirst <gh%ai.toronto.edu@RELAY.CS.NET>
Subject: /Canadian Artificial Intelligence/ magazine
The January 1987 issue of /Canadian Artificial Intelligence/ has just been
mailed, and all members of CSCSI/SCEIO should be receiving it soon (Canada
Post willing).
/Canadian A.I./ is a quarterly magazine sent to all members of CSCSI/SCEIO,
the Canadian artificial intelligence society. The society, founded in 1973,
has over 1000 members, and sponsors the bienniel Canadian A.I. conference as
well as the magazine. (The next conference is in Edmonton, May 1988.)
If you aren't a member and would like to be (and everyone working in A.I. in
Canada should be!), then send $25* (students $15*) to:
CSCSI/SCEIO, c/o CIPS
243 College Street, 5th floor
Toronto, Ont
CANADA M5T 2Y1
Ask for your membership to start with the January 1987 issue.
No, you don't have to be a Canadian to be a member. Anyone who wants to know
what's going on in A.I. in Canada is welcome!
*Prices are in Canadian dollars; U.S. funds accepted at current exchange rates:
full membership, US$18.50; student membership US$11.25.
Graeme Hirst
Senior Editor
------------------------------
Date: Fri, 16 Jan 87 17:24:25 EST
From: Rich Sutton <rich%gte-labs.csnet@RELAY.CS.NET>
Subject: TR Abstract -- Learning to Predict
------------------------------------------------------------------------
LEARNING TO PREDICT
BY THE METHODS OF TEMPORAL DIFFERENCES
Richard S. Sutton
GTE Labs
Waltham, MA 02254
Rich@GTE-Labs.CSNet
This technical report introduces and provides the first formal results
in the theory of TEMPORAL-DIFFERENCE METHODS, a class of statistical
learning procedures specialized for prediction---that is, for using past
experience with an incompletely known system to predict its future
behavior. Whereas in conventional prediction-learning methods the error
term is the difference between predicted and actual outcomes, in
temporal-difference methods it is the difference between temporally
successive predictions. Although temporal-difference methods have been
used in Samuel's checker-player, Holland's Bucket Brigade, and the
author's Adaptive Heuristic Critic, they have remained poorly
understood. Here we prove the convergence and optimality of
temporal-difference methods for special cases, and relate them to
supervised-learning procedures. For most real-world prediction
problems, temporal-difference methods require less memory and peak
computation than conventional methods AND produce more accurate
predictions. It is argued that most problems to which supervised
learning is currently applied are really prediction problems of the sort
to which temporal-difference methods can be applied to advantage.
--------------------------------------------------------------------------
p.s. Those who have previously requested a paper on "bootstrap learning"
are already on my mailing list and should receive the paper sometime next week.
------------------------------
End of AIList Digest
********************
∂19-Jan-87 0255 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #8
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 19 Jan 87 02:55:18 PST
Date: Sun 18 Jan 1987 23:29-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #8
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 19 Jan 1987 Volume 5 : Issue 8
Today's Topics:
Seminars - General Logic (SRI) &
Using Fast and Slow Weights (UCB) &
An Implementation of Adaptive Search (SRI) &
The Semantics of Clocks (CSLI) &
Intelligent Database Systems (SRI) &
Formal Theories of Action (SU) &
Mid-Atlantic Math Logic Seminar (UPenn),
Conference - Directions & Implications of Advanced Computing
----------------------------------------------------------------------
Date: Wed 14 Jan 87 11:26:56-PST
From: Jose Meseguer <MESEGUER@CSL.SRI.COM>
Subject: Seminar - General Logic (SRI)
GENERAL LOGIC
by
Prof. Gordon Plotkin
C.S. Dept. Univ. of Edinburgh, Scotland
WHEN: Thursday Jan. 15, at 1:30 pm
WHERE: SRI, Room AA298
A wide variety of logics have been proposed for use in Computer
Science , such as first-order , higher-order , type theories , temporal and
modal logics , dynamic logic etc etc . One would like to write proof-checkers
and (semi-) automatic theorem provers for them , but implementing any one is
a major undertaking and it is very hard to vary the logic once work is
underway . We propose a general syntactic theory of logic building on
work of Martin-Lof and employing a lambda calculus of dependent types.It
enables one to use a signature to enter the syntax and rules , in natural
deuction style. It seems likely to allow the efficient production of basic
proof checkers from the signature and to provide the user the tools to
write theorem provers.
------------------------------
Date: Thu, 15 Jan 87 10:35:57 PST
From: admin%cogsci.Berkeley.EDU@berkeley.edu (Cognitive Science
Program)
Subject: Seminar - Using Fast and Slow Weights (UCB)
BERKELEY COGNITIVE SCIENCE PROGRAM
SPRING - 1987
Cognitive Science Seminar - IDS 237B
Tuesday, January 27, 11:00 - 12:30
2515 Tolman Hall
Discussion: 12:30 - 1:30
2515 Tolman Hall
``Using fast weights to deblur old memories and assimilate new ones."
Geoff Hinton
Computer Science
Carnegie Mellon
Connectionist models usually have a single weight on each connection. Some
interesting new properties emerge if each connection has two
weights -- a slow, plastic weight which stores long-term
knowledge and a fast, elastic weight which stores temporary
knowledge and spontaneously decays towards zero. Suppose that a
network learns a set of associations, and then subsequently
learns more associations. Associations in the first set will be-
come "blurred", but it is possible to deblur all the associations
in the first set by rehearsing on just a few of them. The
rehearsal allows the fast weights to take on values that cancel
out the changes in the slow weights caused by the subsequent
learning.
Fast weights can also be used to minimize interference by minim-
izing the changes to the slow weights that are required to as-
similate new knowledge. The fast weights search for the smallest
change in the slow weights that is capable of incorporating the
new knowledge. This is equivalent to searching for analogies
that allow the new knowledge to be represented as a minor varia-
tion of the old knowledge.
---------------------------------------------------------------
UPCOMING TALKS
Feb 10: Anne Treisman, Psychology Department, UC Berkeley.
---------------------------------------------------------------
ELSEWHERE ON CAMPUS
Geoff Hinton will speak at the SESAME Colloquium on Monday Jan. 26, in
Tolman 2515 from 4-6.
------------------------------
Date: Thu, 15 Jan 87 16:56:24 PST
From: lansky@sri-venice.ARPA (Amy Lansky)
Subject: Seminar - An Implementation of Adaptive Search (SRI)
AN IMPLEMENTATION OF ADAPTIVE SEARCH
Takashi Sakuragawa (TAKASHI@IBM.COM)
IBM T. J. Watson Research Center and Kyoto University
3:00 PM, FRIDAY, January 16
SRI International, Building E, Room EK242
The Adaptive Optimizer is a program that optimizes Prolog programs by
reordering clauses. It is an implementation of Natarajan's adaptive
search algorithm that reorders the subproblems of a disjunctive
problem and minimizes the expected search effort. This talk will
describe implementation details as well as how the efficiency of an
example tree search program is improved. In this particular example,
the execution speed of the optimized program is more than 200 times
faster than the original one. The speed improvement observed is for
an artificial example and is not necessarily representative of what
might be obtained from real applications.
------------------------------
Date: Wed 14 Jan 87 17:45:10-PST
From: Emma Pease <Emma@CSLI.STANFORD.EDU>
Subject: Seminar - The Semantics of Clocks (CSLI)
The Semantics of Clocks
Brian Smith
January 22
Clocks participate in their subject matter. Temporal by nature, they
also represent time. And yet, like other representational systems,
clocks have been hard to build, and can be wrong. For these and other
reasons clocks are a good foil with which to explore issues in AI and
cognitive science about computation, mind, and the relation between
semantics and mechanism.
An analysis will be presented of clock face content and the
function of clockworks, and of various notions of chronological
correctness. The results are intended to illustrate a more general
challenge to the formality of inference, to widen our conception of
computation, and to clarify the conditions governing representational
systems in general.
Please note that this Thursday's Seminar will be in the Ventura
Trailer Classroom, not in Redwood G-19. Future Thursday Seminars will
also meet in the Ventura Trailer Classroom until a better room can be
found.
------------------------------
Date: Fri 16 Jan 87 17:10:18-PST
From: Amy Lansky <LANSKY@SRI-VENICE.ARPA>
Subject: Seminar - Intelligent Database Systems (SRI)
INTELLIGENT DATABASE SYSTEMS
Matthew Morgenstern (MORGENSTERN@SRI-CSL)
SRI International
11:00 AM, THURSDAY, January 22
SRI International, Building E, Room EK242
The goal is to create databases which are more intelligent about the
application they serve and more active as part of an overall system. Our
approach builds upon expert systems and other A.I. techniques to develop
capabilities for: (1) knowledge-based support for managing data,
(2) integrity and fault tolerance of the database, (3) interactive
formation and evaluation of what-if scenarios (plans), and (4) offloading
data-oriented activities and requirements from application programs --
thus aiding the software development process by providing a higher level
interface to the database.
We also are interested in (5) the relationship between inference and DB
security -- that is, detecting potential violations of security in a
multi-level database due to inference of high level data from visible
lower level data; and (6) support for heterogeneous distributed databases.
These capabilities require that the database be augmented with knowledge
of the application. We utilize constraints to describe the structure,
behavior, and requirements (semantics) of the application. Collections of
rules are associated with these constraints and automatically invoked in
response to database activity to enforce the application requirements.
------------------------------
Date: 17 Jan 87 2119 PST
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Formal Theories of Action (SU)
Commonsense and Nonmonotonic Reasoning Seminar
FORMAL THEORIES OF ACTION
Vladimir Lifschitz
Thursday, January 22, 4pm
Bldg. 160, Room 161K
We apply circumscription to formalizing reasoning about the effects
of actions in the framework of situation calculus. An axiomatic description
of causal connections between actions and changes allows us to solve the
qualification problem and the frame problem using only simple forms of
circumscription.
In this talk the method is illustrated by constructing a
circumscriptive theory of the blocks world in which blocks can be moved
and painted. We show that the theory allows us to compute the result of
the execution of any sequential plan.
------------------------------
Date: Fri, 16 Jan 87 19:04:25 EST
From: dale@linc.cis.upenn.edu (Dale Miller)
Subject: Seminar - Mid-Atlantic Math Logic Seminar (UPenn)
MID-ATLANTIC MATHEMATICAL LOGIC SEMINAR
PHILADELPHIA, FEBRUARY 21-22, 1987
This meeting will be held at the University of Pennsylvania, Alumni Room,
Towne Building. Please use ground level entrance on the west side just off
Smith Walk, between 33rd and 34th Streets, south of Walnut Street.
SATURDAY, FEBRUARY 21
12 noon Coffee and snacks
1:00 - 2:00 Dana S. Scott, Carnegie-Mellon University
HOW DESIRABLE IS THE REALIZABILITY UNIVERSE?
2:10 - 3:10 Albert R. Meyer, Massachusetts Institute of Technology
FIXED POINT AND LOOPING COMBINATORS IN POLYMORPHIC LAMBDA
CALCULUS
3:40 - 4:40 Peter J. Freyd, University of Pennsylvania
CATEGORIES AND POLYMORPHIC LAMBDA CALCULUS
4:50 - 5:50 John C. Mitchell, A.T.&T. Bell Laboratories
KRIPKE STRUCTURES AND TYPED LAMBDA CALCULUS
SUNDAY, FEBRUARY 22
8:30 Coffee and doughnuts
9:00 - 10:00 Speaker T.B.A., Cornell University
RECURSIVE TYPES IN THE NUPRL PROOF DEVELOPMENT SYSTEM
10:10 - 11:10 Garrel Pottinger, Odyssey Research Associates, Inc.
STRONG NORMALIZATION FOR TERMS OF THE COQUAND-HUET THEORY
OF CONSTRUCTIONS
11:25 - 12:25 Gaisi Takeuti, University of Illinois at Urbana-Champaign
BOUNDED ARITHMETIC AND A WEAK CONSISTENCY
12:35 - 1:35 Scott Weinstein, University of Pennsylvania
SOME RECENT RESULTS IN THE THEORY OF MACHINE INDUCTIVE
INFERENCE
ACCOMMODATIONS
A block of 10 rooms has been set aside at the Sheraton Inn University City,
Chestnut and 36th Streets (215/387-8000) for the participants of the "Logic
Meeting", Saturday night, February 21. The price per room is $64 if you make
your reservation by February 7. Private accommodations will be available for
up to 10 people with sleeping bags. Please call at least 3 days in advance
215/898-8475 or 215/545-5443.
Andre Scedrov
ARPANET: Andre@cis.upenn.edu
------------------------------
Date: 12 Jan 87 20:56:26 GMT
From: jade!iris.berkeley.edu!michael@ucbvax.Berkeley.EDU (Tom Slone
[(415)486-5954])
Subject: Conference - Directions & Implications of Advanced Computing
DIRECTIONS AND IMPLICATIONS OF ADVANCED COMPUTING
Seattle, Washington
July 12, 1987
The adoption of current computing technology, and of technologies that seem
likely to emerge in the near future, will have a significant impact on the
military, on financial affairs, on privacy and civil liberty, on the medical
and educational professions, and on commerce and business.
The aim of the symposium is to consider these influences in a social and
political context as well as a technical one. The social implications of
current computing technology, particularly in artificial intelligence, are such
that attempts to separate science and policy are unrealistic. We therefore
solicit papers that directly address the wide range of ethical and moral
questions that lie at the junction of science and policy.
Within this broad context, we request papers that address the following
particular topics. The scope of the topics includes, but is not limited to, the
sub-topics listed.
RESEARCH FUNDING: Sources; Effects; Funding alternatives.
DEFENSE APPLICATIONS: Machine autonomy and the conduct of war; Practical limits
on the automation of war; Can an automated defense system make war
obsolete?
COMPUTING IN A DEMOCRATIC SOCIETY: Community access; Computerized voting; Civil
liberties; Computing and the future of work; Risks of the new technology
COMPUTERS IN THE PUBLIC INTEREST: Computing access for handicapped people;
Resource modeling; Arbitration and conflict resolution; Educational,
medical and legal software
Submissions will be read by members of the program committee, with the
assistance of outside referees. Tentative program committee includes Andrew
Black (U.Wa), Alan Borning (U.Wa), Jonathan Jacky (U.Wa), Nancy Leveson (UCI),
Abbe Mowshowitz (CCNY), Herb Simon (CMU) and Terry Winograd (Stanford).
Complete papers, not exceeding 6000 words, should include an abstract, and a
heading indicating to which topic it relates. Papers related to AI and/or
in-progress work will be favored. Submissions will be judged on clarity,
insight, significance, and originality. Papers (3 copies) are due by April 1.
Notices of acceptance or rejection will by mailed by May 1. Camera ready copy
will by due by June 1.
Proceedings will be distributed at the Symposium, and will be on sale during the
1987 AAAI conference.
For further information contact Jonathan Jacky (206-548-4117) or Doug Schuler
(206-783-0145).
Sponsored by Computer Professionals for Social Responsibility, P.O. Box 85481,
Seattle, WA 98105.
michael@ucbiris.berkeley.edu michael%ucbiris@berkeley.arpa
{bellcore|cbosgd|decvax|hplabs|ihnp4| \
nbires|sdcsvax|tektronix|ulysses}!ucbvax!ucbiris!michael
"If there's going to be a bloodbath, let's get it over with." --Reagan
------------------------------
End of AIList Digest
********************
∂20-Jan-87 0036 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #9
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 20 Jan 87 00:36:32 PST
Date: Mon 19 Jan 1987 22:22-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #9
To: AIList@SRI-STRIPE.ARPA
AIList Digest Tuesday, 20 Jan 1987 Volume 5 : Issue 9
Today's Topics:
Queries - Math and Learning Programming &
Proposals to Host IJCAI-91 Outside of North America,
Humor - Clock Seminar,
Philosophy - Minds & Inten(s/t)ion, Introspection
----------------------------------------------------------------------
Date: 19 Jan 87 13:29:06 GMT
From: atux01!jlc@rutgers.rutgers.edu (J. Collymore)
Subject: Math & Learning Programming: Cognitive Aspects
I am posting this query for a friend of mine who does not have access to the
net. Any of you who can provide help, please send e-mail to me and I will
have it forwarded. Thank you.
Jim Collymore
================================================================================
In computer science, mathematical expressions are used to describe
events or objects. One of the difficulties that novice programmers may
have in learning programming logic is that they do not understand that
mathematical expressions model real situations or, if they do understand
that then they don't understand how to go about setting up such an
expression correctly for their application.
I'm wondering if anyone out there in CRTville has references to how
people come to understand these relationships between mathematical
expressions and reality.
Thanks.
Jonthan Levine
------------------------------
Date: Mon, 19 Jan 87 14:13:35 est
From: walker@flash.bellcore.com (Don Walker)
Subject: REQUEST FOR PROPOSALS TO HOST IJCAI-91 OUTSIDE OF NORTH AMERICA
PROPOSALS FOR SITES FOR IJCAI-91 SOLICITED
The site for IJCAI-91 will be selected at the IJCAI-87 in Milan this
coming summer (23-28 August). Because of the size of the conferences,
it is now necessary to plan four years in advance. The selection
process has become more complicated for the same reason. As a result,
it will be necessary for countries that would like to host IJCAI-91 to
submit detailed proposals describing their plans for the meeting and
to prepare thorough budget estimates in advance. It will be necessary
for an officially recognized AI organization in the country selected
to sign an agreement with IJCAII that establishes a formal commitment
to hold the conference and that defines mutual responsibilities.
IJCAI conferences are organized every two years, usually in August,
and they alternate between North America and other parts of the world.
Since IJCAI-89 will be held in Detroit, Michigan, USA, IJCAI-91 will be
held outside of North America.
Proposals will be evaluated in relation to a number of site selection
criteria:
1. National, regional, and local AI community support.
2. National, regional, and local government and industry support.
3. Accessibility, attractiveness, and desirability of proposed site.
4. Appropriateness of proposed dates.
5. Adequacy of conference and exhibit facilities for anticipated number
of registrants (currently 7500-10000 for North America; 2000-3000
or more elsewhere, depending on the location).
6. Adequacy of residence accommodations and food services in a range of
price categories.
7. Adequacy of budget projections.
Prospective hosts should request a detailed list of site information
required and a set of budget categories as soon as possible. Initial
draft proposals should be submitted by 15 April 1987; final proposals
must be distributed to the Executive Committee by 15 July 1987.
Direct requests for proposal information to the IJCAII Secretary-Treasurer:
Dr. Donald E. Walker (IJCAII)
Bell Communications Research
435 South Street, MRE 2A379
Morristown, NJ 07960-1961, USA
+1 201 829-4312
telex: 275209 BELL UR
arpanet: walker@flash.bellcore.com
usenet: {ucbvax, ihnp4, mcvax, or ... }!bellcore!walker
------------------------------
Date: Mon, 19 Jan 87 12:46:55 pst
From: laurieed%lapis.Berkeley.EDU@BERKELEY.EDU (Laurie Edwards)
Subject: Re: AIList Digest V5 #8
I found it amusing that Brian Smith's talk on the Semantics of Clocks was
posted without a time being mentioned!
More seriously, it is an intriguing topic - I remember a seminar given by
Gregory Bateson in 1974 in which the intial assignment was to say what
a clock is ...
[I believe the omission of the seminar time was my fault.
The event had already taken place, though. -- KIL]
------------------------------
Date: Tue, 13 Jan 1987 01:55 EST
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #4
I don't believe that the phenomenon of "first order cosciousness"
exists, that Harnad talks about. The part of the mind that speaks is
not experiencing the toothache, but is reacting to signals that were
sent some small time ago from other parts of the brain. I think
Harnad's phenomenology is too simple-minded to take seriously. If he
has ever had a toothache, he will remember that one is not conscious
of it all the time, even if it is very painful; one become aware of it
in episodes of various lengths. I suppose he'll argue that he remains
unconsciously conscious of it. I don't want to carry on, only to ask
him to review his insistence that ANTHING can happen instantaneously -
no matter how convincing the illusion is, for example that you are
seeing what is happening before your eyes, now, rather than something
that happened d/c seconds ago, or that signals travel from one part of
the brain/mind to another faster than light. As for that "mind/body
problem" I repeat my slogan, "Minds are simply what brains do."
------------------------------
Date: Tue, 13 Jan 87 09:00 MST
From: Mandel%pco@HI-MULTICS.ARPA (Mark A. Mandel)
Reply-to: Mandel%pco@HI-MULTICS.ARPA (Mark A. Mandel)
Subject: Discussion of "consciousness"
> I would say that if one is "conscious" of an event, then
> the features/schema of that event are available to his
> goal-setter/planner for planning of future behavior ( and
> vice-versa ).
This is true, but its (in this context) implied converse is not.
Clinical psychology furnishes ample examples of goalsetting/planning
that is not accessible to the person's conscious awareness in the usual
ways. Q: "Why did you walk into that restaurant?" A: "No particular
reason, I just suddenly felt like having a cup of coffee." Further
probing by the therapist brings forth the awareness that certain
circumstances of weather, recent experience, and hearing a song on the
radio, all associated with an emotion-packed memory of a dead friend,
had "caused" the person to attempt to reproduce an occasion on which he
had met with that friend.
The example is wholly fictitious, but this sort of hidden cause comes up
all the time in therapy. Evidently some process in the person planned
to meet the friend by going into the restaurant, although the person was
not consciously aware of the plan or the conditions that had produced
it; if he had been, he would certainly have recognized the impossibility
of meeting someone who is dead. And if we say that he was aware of the
conditions and planned consciously, but immediately forgot the entire
operation, how do we explain (except by special pleading) his failure to
recognize the unreality of the plan? The only solution is to accept
unconscious planning.
So we cannot use "subject has access to event X for purposes of
planning" as a criterion for "subject is conscious of event X."
------------------------------
Date: Wed, 14 Jan 87 23:21:03 pst
From: ucsbcsl!uncle@ucbvax.Berkeley.EDU
Subject: minds and minsky
[The following message is in the style of comments on comments
on quoted text that was common on the Phil-Sci list at MIT.
While I recognize that the potential for such annotation is
a major advantage of online discussion, I hope that members
of the list will show restraint in order to keep the traffic
volume down. A well-reasoned argument is preferable to several
quoted paragraphs and a one-line comment. -- KIL ]
QUESTIONS (-->> ...) re: QUESTIONS (> ...) re: M.M.
ANNOTATIONS TO THE ARTICLE:
From harnad@seismo.CSS.GOV@mind.UUCP Sat Feb 5 22:28:16 2↓06
On mod.ai, MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU (Marvin Minsky) wrote:
> the phenomena we call consciousness are involved with our
> short term memories. This explains why... it makes little sense to
> attribute consciousness to rocks.
I agree that rocks probably don't have short-term memories. But I
don't see how having a short-term memory explains why we're conscious
and rocks aren't. In particular, why are any of our short-term
memories conscious, rather than all being unconscious?
-->> ?? maybe because `consciousness' has something to do with
discriminating changes in a temporal sequence of events
whose time scale is more like the duration of a heartbeat
than the duration of a whole life or an eon ??
The extracts from Marvin Minsky's new book look as if they will be
very insightful correlative accounts of the phenomenology of (i) subjective
experience and (ii) the objective processes going on in machines that can be
interpreted as analogous to (i) in various ways. What none of the
extracts he has presented even hints at is (a) why interpreting any of
these processes (and the performance they subserve) as conscious is
warranted, and (b) why even our own processes and performance should
be conscious, rather than completely unconscious. [...]
[...]
(2) Before claiming with conviction that one has shown "why" a certain
performance is accomplished by a process that is validly interpreted
as a conscious one, one should indicate why the very same performance could
not be accomplished by the very same process, perfectly UNconsciously
(thereby rendering the conscious interpretation supererogatory).
> although people usually assume that consciousness is knowing
> what is happening in the minds, right at the
> present time, consciousness never is really concerned with the
> present, but with how we think about the records of our recent
> thoughts... how thinking about our short term memories changes them!
-->> ?? I think I agree with `>', is he not saying here something about
discriminating changes in a temporal sequence on a short
time scale ??
[...]
My question concerns how the memory hypothesis -- or any other --
accounts for the fact that what is going on there in real time is
conscious rather than unconscious; how does it account for my
EXPERIENCE of pain?) And once that's answered, the second question is
(2) why couldn't all that have been accomplished completely
unconsciously? [...]
-->> ?? Hmmmmm: THINKING and FEELING or rather:
COMPUTING and FEELING . As a marginal intelligence,
artificial or otherwise, I can only grab at a straw such
as the organizational/functional notion `goal'. Experience and
Feeling are functions which evaluate elements of the short-term
temporal sequence of events/representations with respect
to `goals'. Hmmmmm, do planaria think? THE BIG QUESTION
THAT DISTURBS ME IS MORE OR LESS IN LINE WITH THE QUESTIONER
ABOVE:
WHY SHOULD MATTER THINK?????? This, of course
has nothing to do with the real universe where some
material aggregates DO think;
however, if the universe wants to blow up,
convert itself into successive populations of stars etc
etc, and then implode, why does it need to have us think
about it?
[...]
[Let me also add that there are good reasons why it is called the
"mind/body" problem and not the "mindS/body" problem, as Marvin Minsky's
tacit pluralizations would seem to imply. The phenomenological fact is that,
at any instant, I (singular) have a toothache experience (singular).
Having this (singular) conscious experience is what one calls having a
(singular) mind. Now it may well be that one can INFER multiple processes
underlying the capacity to have such singular experiences. But the processes
are unconscious ones, not directly EXPERIENCED ones, hence they are not plural
minds, properly speaking.
-->> ?? HOLD ON, aren't you indulging in a kind of , what is the word,
psychologism, based upon a linguistic prejudice? The
get-food-subsystem doesn't go through a speech-act trip
ending in the formulation of the well formed english
phrase `i'm hungry', but it knows what it wants and
communicates its wishes by making `OUR' stomach hurt ??
[...]
> Our brains have various agencies that learn to
> recognize - and even name - various patterns of external sensations.
> Similarly, there must be other agencies that learn to recognize
> events *inside* the brain - for example, the activities of the
> agencies that manage memories. And those, I claim, are the bases
> of the awarenesses we recognize as consciousness... I claim that to
> understand what we call consciousness, we must understand the
> activities of the agents that are engaged in using and changing our
> most recent memories.
You need an argument for (1) why any process you propose is correctly
interpreted as the basis of 1st-order awareness of anything --
external or internal -- rather than just a mindless process, and (2)
why the functions you describe it as accomplishing in the way it does
need to be accomplished consciously at all, rather than mindlessly.
-->> ?? But (some) matter DOES think and we know that! Explaining
WHY (some) matter should be conscious is like explaining why
the universe is as it is. As for the question of HOW
it is conscious, it seems quite plausible that
evolution changed MOTILITY into MOTIVATION and when
motivation got hold of adequate methods and representations,
je pense, donc clyde est un elephant! ??
[...]
> When people ask, "Could a machine ever be conscious?" I'm often
> tempted to ask back, "Could a person ever be conscious?"
> ...we can design our new machines as we wish, and
> provide them with better ways to keep and examine records of their
> own activities - and this means that machines are potentially capable
> of far more consciousness than we are.
-->> Sounds plausible to me!
[...]
> To "notice" change requires the ability to resist it, in order
> to sense what persists through time, but one can do this only
> by being able to examine and compare descriptions from the recent past.
-->> ?? Yes! ??
Why should a process that allows a device to notice (respond to,
encode, store) change, resist it, examine, compare, describe, remember,
etc. be interpreted as (1) a conscious process, and (2) why couldn't it
accomplish the exact same things unconsciously?
-->> ?? We already traversed this semantic loophole!!! ??
I am not, by the way, a spokesman for the point of view advocated by
Dreyfus or by Searle. In asking these pointed question I am trying to
show that the mind/body problem is a red herring for cognitive
science. I recommend methodological epiphenomenalism and performance
modeling as (what I believe is) the correct research strategy. Instead
of spending our time trying to build metaphorical perpetual motion
machines, I believe we should try to build real machines that capture our
total performance capacity (the Total Turing Test).
-------
--->> ?? methodological epiphenomenalism \?\? I don't know the
exact significance of that as a Flachausdruck, but perhaps
M.M. is describing just the epiphenomenon you are looking
for\? ??
------------------------------
Date: 16 Jan 87 19:44:42 GMT
From: berke@locus.ucla.edu
Subject: inten(s/t)ion, introspection
A couple of brief responses to postings:
1) 'Intention' is derived from 'intend' and should not be confused
with 'intension'. People intend to do things and so can be said to
have intentions. Intensional objects versus extensional objects is
a distinction made by Mill and Frege in distinguishing connotations
or senses of names from denotations, the (sometimes concrete) objects named by
names. I believe that Carnap introduced the terms 'intensional' and
'extensional' to correspond to the distinction between properties
and the sets to which the properties apply.
It has to do with the identity criteria for properties, usually
represented by singulary propositional functions. If you feel
that, or require in your formal theory, that two functions are identical
if they are true of (have the same value for)
the same objects, then you are taking functions
"in extension." If you feel that two functions can still be different
even though they are true of the same objects, you are taking functions
"in intension." That is to say that "intensional objects" have stronger
identity criteria (there are more of them) than "extensional objects."
There seem to be levels of degrees of intensionality, depending on the
strength of your identity criteria.
The spelling similarity
(s/t) and identical pronunciation don't necessarily imply a confusion
of the concepts expressed by the different words 'intention' and
'intension', though, given the state of semantics these days, we
may want to make an explicit connection between them. That would
require showing how desires give rise to conepts, or vice versa.
2) I thought introspection was out since Freud demonstrated "the"
unconcious.
(Frege's single quotes used to denote a word rather than
it's meaning (whatever that is), double quotes to
denote the usual meaning of a word, but to emphasize the fact that
enclosed words are used in a technical sense.)
------------------------------
Date: 18 Jan 87 19:17:00 GMT
From: mcvax!ukc!rjf@seismo.css.gov (R.J.Faichney)
Subject: Re: inten(s/t)ion, introspection
In article <3784@curly.ucla-cs.UCLA.EDU> berke@CS.UCLA.EDU (Peter Berke) writes:
>[..]
>2) I thought introspection was out since Freud demonstrated "the"
>unconcious.
>
>(Frege's single quotes used to denote a word rather than
>it's meaning (whatever that is), double quotes to
>denote the usual meaning of a word, but to emphasize the fact that
>enclosed words are used in a technical sense.)
Can 'introspection' be 'out'? Surely you are "thinking" of 'extraspection'.
More seriously: I don't follow the reasoning which implies that the existence
of the unconscious invalidates introspection. Having glanced at the history
of psychology, I was under the impression that it was the rise of behaviour-
ism - and associated attempts to make psychology wholly objective and
respectable - which had caused the (temporary) eclipse of the introspective
method.
--
Robin Faichney ("My employers don't know anything about this.")
UUCP: ...mcvax!ukc!rjf Post: RJ Faichney,
Computing Laboratory,
JANET: rjf@uk.ac.ukc The University,
Canterbury,
Phone: 0227 66822 Ext 7681 Kent.
CT2 7NF
------------------------------
End of AIList Digest
********************
∂21-Jan-87 0048 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #10
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 21 Jan 87 00:47:54 PST
Date: Tue 20 Jan 1987 23:11-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #10
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 21 Jan 1987 Volume 5 : Issue 10
Today's Topics:
Queries - CMS Shells & Modelling Resource Allocation & Distributed Kalah,
AI Tools - Scheme for PC,
Correction - Brian Smith's Talk,
Literature - Catalogue of AI Techniques
----------------------------------------------------------------------
Date: 20 January 87 13:28-EDT
From: ATSWAF%UOFT01.BITNET@WISCVM.WISC.EDU
Subject: CMS Shells
Does anyone know of any expert system shells available to run on
an IBM computer in CMS? Please send any information regarding price
and manufacturer to:
Krzysztof Cios
FAC1765@UOFT01.BITNET
Thanks
------------------------------
Date: 20 Jan 87 11:55 PST
From: Gail Slemon <sigart@LOGICON.ARPA>
Subject: Theoretical framework for modelling resource allocation.
We are looking for a theoretical (cognitive science) framework
for modelling a resource allocation problem for training purposes.
Has anyone applied Jens Rasmussen's theory to training? We'd
appreciate critiques of his theory. Any other candidates or
suggestions are very welcome!
Please reply to: sigart@logicon.arpa
or
Gail Slemon
c/o Logicon, Inc.
P.O. Box 85158
San Diego, CA 92138-5158
------------------------------
Date: Wed, 21 Jan 87 00:28:47 +0100
From: Hakon Styri <styri%vax.runit.unit.uninett@NTA-VAX.ARPA>
Subject: Query - Distributed Kalah
I'm writing a Kalah-playing program for a small number of transputers,
using a simple alpha/beta algorithm with a few enhancements to cut
down the communication cost. I would appreciate to receive information
on any comparable work, i.e. parallel game-playing on less than 10
processors.
Haakon Styri,
RUNIT,
The Foundation for Scientific and Industrial Research at
the Norwegian Institute of Technology (SINTEF)
------------------------------
Date: Tue, 20 Jan 87 9:25:42 EST
From: Kenneth Van Camp -FSAC- <kvancamp@ARDEC.ARPA>
Subject: Scheme for PC
Alexander Crawford wanted to know if Scheme Lisp was available for the
IBM PC. Yes, Texas Instruments puts out a version.
--Ken Van Camp <kvancamp@ARDEC.ARPA>
------------------------------
Date: Tue, 20 Jan 87 15:56:22 pst
From: ladkin@kestrel.ARPA (Peter Ladkin)
Subject: brian smith's talk
on clocks is actually this thursday, i believe. you intimated
in the digest that it had passed.
cheers,
peter
[Rats! Mea culp. Here is the correct listing. -- KIL]
Date: Wed 14 Jan 87 17:45:10-PST
From: Emma Pease <Emma@CSLI.STANFORD.EDU>
Subject: CSLI Calendar, January 15, No.12
2:15 p.m. CSLI Seminar
Classroom The Semantics of Clocks
Ventura Trailers Brian Smith
(BrianSmith.pa@xerox.com)
NEXT WEEK'S SEMINAR
The Semantics of Clocks
Brian Smith
January 22
Clocks participate in their subject matter. Temporal by nature, they
also represent time. And yet, like other representational systems,
clocks have been hard to build, and can be wrong. For these and other
reasons clocks are a good foil with which to explore issues in AI and
cognitive science about computation, mind, and the relation between
semantics and mechanism.
An analysis will be presented of clock face content and the
function of clockworks, and of various notions of chronological
correctness. The results are intended to illustrate a more general
challenge to the formality of inference, to widen our conception of
computation, and to clarify the conditions governing representational
systems in general.
------------------------------
Date: Tue, 20 Jan 87 17:31:27 GMT
From: Alan Bundy <bundy%aiva.edinburgh.ac.uk@Cs.Ucl.AC.UK>
Subject: Catalogue of AI Techniques: revised call for entries
THE CATALOGUE OF ARTIFICIAL INTELLIGENCE TECHNIQUES
Alan Bundy
The Catalogue of Artificial Intelligence Techniques is a kind
of mail order catalogue. Its purpose is to promote interaction
between members of the AI community. It does this by announcing the
existence of AI techniques, and acting as a pointer into the
literature. Thus the AI community will have access to a common,
extensional definition of the field, which will: promote a common
terminology, discourage the reinvention of wheels, and act as a
clearing house for ideas and algorithms.
The catalogue is a reference work providing a quick guide to
the AI techniques available for different jobs. It is not intended to
be a textbook like the Artificial Intelligence Handbook. It,
intentionally, only provides a brief description of each technique,
with no extended discussion of its historical origin or how it has
been used in particular AI programs.
The original version of the catalogue, was hastily built in
1983 as part of the UK SERC-DoI, IKBS, Architecture Study. It has now
been adopted by the UK Alvey Programme and is both kept as an on-line
document undergoing constant revision and refinement and published as
a paperback by Springer Verlag. Springer Verlag have agreed to reprint
the Catalogue at frequent intervals in order to keep it up to date.
The on-line and paperback versions of the catalogue meet
different needs and differ in the entries they contain. In
particular, the on-line version was designed to promote UK interaction
and contains all the entries which we received that meet the criteria
defined below. Details of how to access the on-line version are
available from John Smith of the Rutherford-Appleton Laboratory,
Chilton, Didcot, Oxon OX11 OQX. The paperback version was designed to
serve as a reference book for the international community, and does
not contain entries which are only of interest in a UK context.
By `AI techniques' we mean algorithms, data (knowledge)
formalisms, architectures, and methodological techniques, which can be
described in a precise, clean way. The catalogue entries are intended
to be non-technical and brief, but with a literature reference. The
reference might not be the `classic' one. It will often be to a
textbook or survey article. The border between AI and non-AI
techniques is fuzzy. Since the catalogue is to promote interaction
some techniques are included because they are vital parts of many AI
programs, even though they did not originate in AI.
We have not included in the catalogue separate entries for
each slight variation of a technique, nor have we included
descriptions of AI programs tied to a particular application, nor of
descriptions of work in progress. The catalogue is not intended to be
a dictionary of AI terminology, nor to include definitions of AI
problems, nor to include descriptions of paradigm examples.
Entries are short (abstract length) descriptions of a
technique. They include: a title, list of aliases, contributor's
name, paragraph of description, and references. The contributor's
name is that of the original author of the entry. Only occasionally
is the contributor of the entry also the inventor of the technique.
The reference is a better guide to the identity of the inventor. Some
entries have been subsequently modified by the referees and/or
editorial team, and these modifications have not always been checked
with the original contributor, so (s)he should not always be held
morally responsible, and should never be held legally responsible.
The original version of the catalogue was called "The
Catalogue of Artificial Intelligence Tools" and also contained
descriptions of portable software, e.g. expert systems shells and
knowledge representation systems. Unfortunately, we found it
impossible to maintain a comprehensive coverage of either all or only
the best such software. New systems were being introduced too
frequently and it required a major editorial job to discover all of
them, to evaluate them and to decide what to include. It would also
have required a much more frequent reprinting of the catalogue than
either the publishers, editors or readers could afford. Also expert
systems shells threatened to swamp the other entries. We have,
therefore, decided to omit software entries from future editions and
rename the catalogue to reflect this. The only exception to this is
programming languages, for which we will provide generic entries. Any
software entries sent to us will be passed on to Graeme Pub. Co., who
publish a directory of AI vendors and products.
If you would like to submit an entry for the catalogue then
please fill in the attached form and send it to:
Alan Bundy,
Department of Artificial Intelligence,
University of Edinburgh, Tel: 44-31-225-7774 ext 242
80 South Bridge,
Edinburgh, EH1 1HN, JANet: Bundy@UK.Ac.Edinburgh
Scotland. ARPAnet: Bundy@Rutgers.Edu
CATALOGUE OF ARTIFICIAL INTELLIGENCE TECHNIQUES:
FORMAT FOR ENTRIES
Title:
Alias:
Abstract: <Paragraph length description of technique>
Contributor: <Your name>
References: <Aim for the most helpful rather than the `classic' one.
Just one reference is the norm.>
------------------------------
End of AIList Digest
********************
∂21-Jan-87 0233 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #11
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 21 Jan 87 02:33:04 PST
Date: Tue 20 Jan 1987 23:15-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #11
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 21 Jan 1987 Volume 5 : Issue 11
Today's Topics:
Philosophy - Inten(s/t)ion, Introspection & Consciousness
----------------------------------------------------------------------
Date: 19 Jan 87 15:52:37 GMT
From: ritcv!rocksvax!rocksanne!sunybcs!rapaport@rochester.arpa
(William J. Rapaport)
Subject: Re: inten(s/t)ion, introspection
But also please note that 'intentionality' is ambiguous:
Intentionality is the feature that Brentano cited as the mark of the
mental, viz., the fact that mental acts (thinking, believing, etc.) are
always "directed" to an object, whether or not that object exists or is
true.
Intentionality also refers to the feature of certain physical acts that
we do them intentionally, i.e., we mean to do them rather than doing
them by accident.
Obviously, there are etymological connections here.
Note, too, that it is often claimed that intentionality in the Brentano
sense is strongly related to intensionality.
William J. Rapaport
Assistant Professor
Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260
(716) 636-3193, 3180
uucp:
.!{allegra,boulder,decvax,mit-ems,nike,rocksanne,sbcs,watmath}!sunybcs!rapaport
csnet: rapaport@buffalo.csnet
bitnet: rapaport@sunybcs.bitnet
------------------------------
Date: Tue, 20 Jan 87 16:14:59 est
From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>
Subject: More on Minsky on Minds(s)
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #4
> I don't believe that the phenomenon of "first order consciousness"
> exists, that Harnad talks about. The part of the mind that speaks is
> not experiencing the toothache, but is reacting to signals that were
> sent some small time ago from other parts of the brain.
There seems to be a contradiction in the above set of statements. If
the meaning of "first order consciousness" (call it "C-1") has been
understood, then one cannot at the same time say one does not believe
C-1 exists AND that "the part of the mind that speaks is not
experiencing the toothache" -- unless of course one believes NO part
of the mind is experiencing the toothache; for whatever part of
the mind IS experiencing the toothache is the part of the mind having
C-1. If Minsky DOES mean that no part of the mind is experiencing the
toothache, then I wish to offer my own humble experience as a
counterexample: I (and therefore, a fortiori, some part of my mind)
certainly do experience toothache.
To minimize cross-talk and misunderstanding, I will explicitly
define C-1 and C-2 ("2nd order consciousness"):
To have (or be) C-1 is to have ANY qualitative experience at all; to
feel, see, hear. Philosophers call having C-1 "having qualia."
A helpful portmanteau we owe to the philosopher Tom Nagel is
that whenever one has C-1 -- i.e., whenever one experiences
anything at all -- there is something it is "like" to have that
experience, and we experience what that something is like directly.
Note: Everyone who is not in the grip of some theoretical
position knows EXACTLY what I mean by the above, and I use
the example of having a current toothache merely as a standard
illustration.
To have (or be) C-2 (or C-N) is to be aware of having a
lower-order experience, such as C-1. The distinction between
C-1 and C-2 is often formulated as the distinction between
"being aware of something" (say, having a toothache) and "being
aware of being aware of something" (including, say, remembering,
thinking about or talking about having a toothache, or about
what it's like to have a toothache).
My critiques of the extracts from Minsky's book were based on the
following simple point: His hypotheses about the functional
substrates of consciousness are all based on analogies between things
that can go on in machines (and perhaps brains) and things that seem to
go on in C-2. But C-2 is really just a 2nd-order frill on the mind/body
problem, compared with the problem of capturing the machine/brain
substrates of C-1. Worse than that, C-2 already presupposes C-1. You can't
have awareness-of-awareness without having awareness -- i.e., direct,
first-order experiences like toothaches -- in the first place. This
led directly to my challenge to Minsky: Why do any of the processes he
describes require C-1 (and hence any level of C) at all? Why can't all
the functions he describes be accomplished without being given the
interpretation that they are conscious -- i.e. that they are accompanied
by any experience -- at all? What is there about his scenario that could not
be accomplished COMPLETELY UNCONSCIOUSLY?
To answer the last question is finally to confront the real mind/body
problem. And if Minsky did so, he would find that the conscious
interpretation of all his machine processes is completely
supererogatory. There's no particular reason to believe that systems
with only the kinds of properties he describes would have (or be) C-1. Hence
there's no reason to be persuaded by the analogies between their inner
workings and some of our inferences and introspections about C-2 either.
To put it more concretely using Minsky's own example: There is perhaps
marginally more inclination to believe that systems with the inner workings
he describes [objectively, of course, minus the conscious interpretation
with which they are decorated] are more likely to be conscious
than a stone, but even this marginal additional credibility derives only
from the fact that such systems can (again, objectively) DO more than
a stone, rather than from the C-2 interpretations and analogies. [And
it is of course this performance criterion alone -- what I've called
elsewhere the Total Turing Test -- that I have argued is the ONLY
defensible criterion for inferring consciousness in any device other than
oneself.]
> I think Harnad's phenomenology is too simple-minded to take seriously.
> If he has ever had a toothache, he will remember that one is not
> conscious of it all the time, even if it is very painful; one becomes
> aware of it in episodes of various lengths. I suppose he'll argue that
> he remains unconsciously conscious of it. I...ask him to review his
> insistence that ANTHING can happen instantaneously - no matter how
> convincing the illusion is...
I hope no one will ever catch me suggesting that we can be "unconsciously
conscious" of anything, since I regard that as an unmitigated contradiction
in terms (and probably a particularly unhelpful Nachlass from Freud).
I am also reasonably confident that my simple-minded phenomenology is
shared by anyone who can pry himself loose from prior theoretical
commitments.
I agree that toothaches fade in and out, and that conscious "instants"
are not punctate, but smeared across a fuzzy interval. But so what?
Call Delta-T one of those instants of consciousness of a toothache. It
is when I'm feeling that toothache RIGHT NOW that I am having a 1st
order conscious experience. Call it Delta-C-1 if you prefer, but it's
still C-1 (i.e., experiencing pain now) and not just C-2 (i.e.,
remembering, describing, or reflecting on experiencing pain) that's
going on then. And unless you can make a case for C-1, the case for C-2
is left trying to elevate itself by its boot-straps.
I also agree, of course, that conscious experiences (both C-1 and C-2)
involve illusions, including temporal illusions. [In an article in
Cognition and Brain Theory (5:29-47, 1982) entitled "Consciousness: An
Afterthought" I tried to show how an experience might be a pastische
of temporal and causal illusions.] But one thing's no illusion, and
that's the fact THAT we're having an experience. The toothache I feel
I'm having right now may in fact have its causal origin in a tooth
injury that happened 90 seconds ago, or a brain event that happened 30
milliseconds ago, but what I'm feeling when I feel it is a
here-and-now toothache, and that's real. It's even real if there's no
tooth injury at all. The point is that the temporal and causal
CONTENTS of an experience may be illusory in their relation to, or
representation of, real time and real causes, but they can't be illusions
AS experiences. And it is this "phenomenological validity" of
conscious experience (C-1 in particular) that is the real burden of
any machine/brain theory of consciousness.
It's a useful constraint to observe the following dichotomy (which
corresponds roughly to the objective/subjective dichotomy): Keep
behavioral performance and the processes that generate it on the
objective side (O) of the ledger, and leave them uninterpreted. On the
subjective (S) side, place conscious experience (1st order and
higher-order) and its contents, such as they are; these are of course
necessarily interpreted. You now need an argument for interpreting any
theory of O in terms of S. In particular, you must show why the
uninterpreted O story ALONE will not work (i.e., why ALL the processes
you posit cannot be completely unconscious). [The history of the
mind/body problem to date -- in my view, at least -- is that no one
has yet managed to do the latter in any remotely rigorous or
convincing way.]
Consider the toothache. On the O side there may (or may not) be
tooth injury, neural substrates of tooth injury, verbal and nonverbal
expressions of pain, and neural substrates of verbal and nonverbal
expressions of pain. These events may be arranged in real time in
various ways. On the S side there is my feeling -- fading
in and out, smeared across time, sometimes vocalized sometimes just
silently suffered -- of having a toothache.
The mind/body problem then becomes the problem of how (and why) to
equate those objective phenomena (environmental events, neural events,
behaviors) with those subjective phenomena (feelings of pain, etc.).
My critique of the excerpts from Minsky's book was that he was conferring
the subjective interpretation on his proposed objective processes and
events without any apparent argument about why the VERY SAME objective
story could not be told with equal objective validity WITHOUT the
subjective interpretation. [If that sounds like a Catch-22, then I've
succeeded in showing the true face of the mind/body problem at last.
It also perhaps shows why I recommend methodological epiphenomenalism --
i.e., not trying to account for consciousness, but only for the
objective substrates of our total performance capacity -- in place of
subjective over-interpretations of those same processes: Because, at
worst, the hermeneutic embellishments will mask or distract from
performance weaknesses, and at best they are theoretically (i.e.,
objectively) superfluous.
> As for that "mind/body problem" I repeat my slogan, "Minds are simply
> what brains do."
Easier said than done. And, as I've suggested, even when done, it's no
"solution."
Stevan Harnad
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
(609)-921-7771
------------------------------
Date: Tue 20 Jan 87 22:04:27-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Subject: C-2 as C-1
From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>:
Worse than that, C-2 already presupposes C-1. You can't
have awareness-of-awareness without having awareness -- i.e., direct,
first-order experiences like toothaches -- in the first place.
A quibble: It would be possible to remember having a toothache
without actually having one. It is also possible, as Minsky seems
to suggest, that my entire conscious perception of a current toothache
is an "illusory pain" based on the memory of a neural signal
of a moment ago. These views do not solve the problem, of course;
the C-2 consciousness must be explained even if the C-1 experience
was an illusion. My conscious memory of the event is more than
just an uninterpreted memory of a memory of a memory ...
-- Ken Laws
------------------------------
Date: Tue, 20 Jan 87 15:57:00 PST
From: Steven L. Speidel <speidel%trout@nosc.ARPA>
Subject: Discussion of "consciousness"
Original statement of hypothesis:
If one is "conscious" of an event, then
the features/schema of that event are available to his
goal-setter/planner for planning of future behavior
( and vice-versa ).
Further discussion:
This is true, but its ( in this context ) implied converse is not.
Clinical psychology furnishes ample examples of goalsetting/planning
that is not accessable to the person's conscious awareness in the
usual ways...
So we cannot use "subject has access to event X for purposes of
planning" as a criterion for "subject is conscious of event X."
Suppose we were to say that the therapist's evaluations of the subjects
consciousness was based on the subjects ability or inability to present
the pertinent material to the therapist. Perhaps the function of
communication resides elsewhere in the brain (or requires additional
connections) than mere consciousness and involves another process
which the subject may or may not have performed as yet, though he is
nevertheless "conscious" of the material on a low level. Once the
subject of therapy is prompted to "express" the material in communicable
form and that process is completed (or in progress) it is the therapists
subjective evaluation that the person has become "conscious" of it.
In this case, the hypothesis of interest would apply to the low-level
consciousness associated with an individual as opposed to an "expressed
consciousness" which may be shared with other individuals.
Following this tack a little further, one would associate the label
"unconscious" with things like reflex, control of peristalsis,
some kinds of sensory processing, etc.
As an aside, the concept of shared consciousness is an intriguing
one, isn't it? It could make it easier to explain how man accomplishes
what he does.
------------------------------
End of AIList Digest
********************
∂22-Jan-87 0027 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #12
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 22 Jan 87 00:27:35 PST
Date: Wed 21 Jan 1987 22:14-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #12
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 22 Jan 1987 Volume 5 : Issue 12
Today's Topics:
Query - Antiquity of AI,
Discussion Lists - X windows and Lisp,
Conference - University Demos at AAAI,
Philosophy - Consciousness
----------------------------------------------------------------------
Date: Tue, 20 Jan 87 17:23 EDT
From: STANKULI%cs.umass.edu@RELAY.CS.NET
Subject: Antiquity of AI
THE ANTIQUITY OF AI
As we are all probably aware, the term 'robot' was coined by Carel Kapek
(circa 1930's AD), but the concept of manufacturing intelligent, speaking,
humanoid, machines for labor dates back into antiquity. I have come upon
the following passage in Homer's Iliad (circa 725 BC). I would like to
know if anyone could send me other passages related to AI which predate the
Renaissance (circa 1500's AD). Particularly, is this the earliest known
reference to artificial intelligence?
To set the scene, Hephaistos is working in his laboratory when he
receives an unexpected visit from Thetis. (English translation will
follow.)
E KAI AP' AKMOTHETOIO PELOR AIETON ANESTE CHOLEUON;
HYPO DE KNEMAI ROONTO ARAIAI.
PHYSAS MEN RH' APANEUTHE TITHEI PUROS,
HOPLA TE PANTA LARNAK' ES ARGUREEN SULLEXATO, TOIS EPONEITO.
SPONGO D'AMPHI PROSOPA KAI AMPHO CHEIR' APOMORGNU
AUCHENA TE STIBARON KAI STETHEA LACHNEENTA.
DU DE CHITON',
HELLE DE SKEPTRON PACHU,
BE DE THYRAZE CHOLEUON.
HYPO D'AMPHIPOLOI RHOONTO ANAKTI
CHRUSEIAI,
ZOESI NEENISIN EIOIKUIAI.
TES EN MEN NOOS ESTI META PHRESIN,
EN DE KAI AUDE KAI STHENOS,
ATHANATON DE THEON APO ERGA ISASIN.
HAI MEN HYPAITHA ANAKTOS EPOIPNUON;
AUTAR HO ERRON PLESION, ENTHA THETIS PER,
EPI THRONMOU HIZE PHAEINOU.
EN T'ARA HOI PHU CHERI,
EPOS T'EPHAT EK T'ONOMAZE,
"TIPTE, THETI, TANUPEPLE,
HIKANEIS HEMETERON DO?"
HE SPOKE, AND TOOK THE HUGE BLOWER OFF THE ANVIL, LIMPING;
BENEATH HIM, SHRUNKEN LEGS MOVED LIGHTLY.
HE SET THE BELLOWS AWAY FROM THE FIRE,
GATHERED ALL THE TOOLS IN A SILVER STRONGBOX, WITH WHICH HE WORKED.
WITH A SPONGE HE WIPED HIS FOREHEAD AND BOTH HANDS,
HIS MASSIVE NECK AND HAIRY CHEST,
PUT ON A TUNIC,
TOOK UP A HEAVY STICK,
WENT TO THE DOORWAY, LIMPING.
IN SUPPORT OF THEIR MASTER MOVED HIS ATTENDENTS.
THESE ARE GOLDEN,
IN APPEARANCE LIKE LIVING YOUNG WOMEN.
AND THERE IS INTELLIGENCE IN THEIR HEARTS,
AND THERE IS SPEECH IN THEM AND STRENGTH,
FROM THE GODS THEY HAVE LEARNED HOW TO DO THINGS.
THESE STIRRED NIMBLY IN SUPPORT OF THEIR MASTER,
MOVING NEAR TO WHERE THETIS SAT
IN HER SHINING CHAIR,
AND TAKING HER BY THE HAND,
CALLED HER BY NAME AND SPOKE A WORD TO HER:
"WHY IS IT, THETIS OF THE LIGHT ROBES,
YOU HAVE COME TO OUR HOUSE NOW?"
I know the Romans used intricate machinations in their circuses and
theatricals, but I have found no reference of them ever being imagined as
anything other than amusing gear boxes. I have found nothing of the
Egyptians ever considering a device more complicated than a hand tool. Yet
Homer seems to have most of the essentials of AI described quite clearly.
Well, perhaps the earliest inference engine was the scales on which Thoth
weighed the human heart against the feather of truth.
stan
[Actually, "robot" was coined by Josef Capek in his story Opilec
(Drunkard) in 1917, rather than by Carel Capek in his 1920 R.U.R.
It apparently comes from the Czech word for "unpleasant work",
rather than the oft-cited "worker". -- KIL ]
------------------------------
Date: Wed 21 Jan 87 13:10:32-PST
From: Mark Richer <RICHER@SUMEX-AIM.STANFORD.EDU>
Subject: X windows & Lisp
There is a mailing list on commonlisp windows that discusses issues
such as the ones you raise and a bunch of people that use or are interestsed
in X windows are on the list. I have remailed your message, perhaps you will
get a response from someone there. It would be appropriate if this
discussion moved there.
The list is cl-windows@sail.stanford.edu To get on send a request to
cl-windows-request@sail.stanford.edu.
There is also a list on X called xpert@athena.mit.edu. Send to xpert-request
to get on that one.
Mark
------------------------------
Date: Wed 21 Jan 87 11:50:25-PST
From: AAAI <AAAI-OFFICE@SUMEX-AIM.STANFORD.EDU>
Subject: University Demos
ANNOUNCEMENT
University and research institutes are invited to participate in the
1987 Exhibit Program at the National Conference on Artificial
Intelligence. Booth space is free, and equipment vendors will loan
hardware for your demonstrations.
Last year the AAAI introduced this innovation and it was considered
one of the highlights of the conference.
For more information, please contact:
Mr. Steve Taglio
AAAI
445 Burgess Drive
Menlo Park, CA 94025-3496
AAAI-office@sumex-aim.arpa
------------------------------
Date: 21 Jan 87 07:13:00 EST
From: "CUGINI, JOHN" <cugini@icst-ecf>
Reply-to: "CUGINI, JOHN" <cugini@icst-ecf>
Subject: consciousness as a non-superfluous concept
In general, I quite agree with most of Harnad's comments contra
Minsky, but he and others keep asking a question which deserves
a response - namely why do we NEED the concept of consciousness
to explain anything:
> Harnad:
>
> It's a useful constraint to observe the following dichotomy (which
> corresponds roughly to the objective/subjective dichotomy): Keep
> behavioral performance and the processes that generate it on the
> objective side (O) of the ledger, and leave them uninterpreted. On the
> subjective (S) side, place conscious experience (1st order and
> higher-order) and its contents, such as they are; these are of course
> necessarily interpreted. You now need an argument for interpreting any
> theory of O in terms of S. In particular, you must show why the
> uninterpreted O story ALONE will not work (i.e., why ALL the processes
> you posit cannot be completely unconscious). [The history of the
> mind/body problem to date -- in my view, at least -- is that no one
> has yet managed to do the latter in any remotely rigorous or
> convincing way.]
But elsewhere:
> I also agree, of course, that conscious experiences (both C-1 and C-2)
> involve illusions, ...But one thing's no illusion, and
> that's the fact THAT we're having an experience. The toothache I feel
> I'm having right now may in fact have its causal origin in a tooth
> injury that happened 90 seconds ago, or a brain event that happened 30
> milliseconds ago, but what I'm feeling when I feel it is a
> here-and-now toothache, and that's real. It's even real if there's no
> tooth injury at all.
Hmmm...so the toothache is "real" but "subjective" - well OK, we need some
terminology to distinguish the class of inner/experiential/subjective/
conscious/private events vs. external/public..etc.
But the point is, if we believe in the existence of both classes, if
both are real, then we know why we need consciousness as a concept-
because without it we cannot explain/talk about the former class of
events - even if the latter class is entirely explicable in its own
terms. Ie, why should we demand of consciousness that it have
explanatory power for objective events? It's like demanding that
magnetism be acoustically detectible before we accept it as a valid
concept.
I can well understand how those who deny the reality of experiences
(eg, toothaches) would then insist on the superfluousness of the
concept of consciousness - but Harnad clearly is not one such.
So...we need consciousness, not to explain public, objective events,
such as neural activity, but to explain, or at least discuss, private
subjective events. If it be objected that the latter are outside the
proper realm of science, so be it, call it schmience or philosophy or
whatever you like. - but surely anything that is REAL, even if subjective,
can be the proper object for some sort of rational study, no?
John Cugini <Cugini@icst-ecf>
------------------------------
Date: 20 Jan 87 13:29:05 PST (Tue)
From: Tom Hester <hester%ai.cel.fmc.com@RELAY.CS.NET>
Subject: Re: AIList Digest V5 #9
In response to: berke@locus.ucla.edu on inten(s/t)ion, introspection
Intension comes from the same Greek root as the English word intense
(meanings are more intens(iv)e in intensions), and the distinction
between intension and extension goes all the way back to Aristotle.
Anybody really interested in Aristotle's characterization of the
distinction can send me an E-mail message and I will be glad to reply.
Furthermore, semanticists have argued for many years that intensions and
intentions are related. See the work of B.C. Van Fraassen for example.
Finally, R.J. Faichney is absolutely correct. It was not Freud that
side tracked psychology from introspection. Rather it was the "dust
bowl empiricists" that rode behaviorism to fame and fortune that did it.
"Don't touch that! When you are this far inside the human brain, you
don't know what it might be connected to." B. Bonzai
Tom Hester
------------------------------
Date: Wed, 21 Jan 1987 23:53 EST
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #11
Steve Harnad says:
Note: Everyone who is not in the grip of some theoretical
position knows EXACTLY what I mean by the above, and I use
the example of having a current toothache merely as a standard
illustration.
I like this because it is so EXACTLY the opposite of what I think,
namely, that unless a person IS in the grip of some "theoretical
position" - that is, some system of ideas, however inconsistent, they
can't "know" what anything "means"
The distinction between C-1 and C-2 is often formulated as the
distinction between "aware of something" (say, having a
toothache) and "being aware of being aware of something"
(including, say, remembering, thinking about or talking about
having a toothache, or about what it's like to have a toothache).
But note that Steve included "say, remembering..." My point was that
you can't think about, talk about, or remember anything that leaves no
temporary trace in some part of your mind. In other words, I agree
that you can't have C-2 without C-1 - but you can't have think, say,
or remember that you have C-1 without C-2! So, assuming that I know
EXACTLY what he means, I understand PERFECTLY that that meaning is
vacuous.
------------------------------
Date: Thu, 22 Jan 87 00:06:21 est
From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>
Subject: No C-2 without C-1
Ken Laws <Laws@SRI-STRIPE.ARPA> wrote in mod.ai:
> A quibble: It would be possible to remember having a toothache
> without actually having one. It is also possible, as Minsky seems
> to suggest, that my entire conscious perception of a current toothache
> is an "illusory pain" based on the memory of a neural signal
> of a moment ago. These views do not solve the problem, of course;
> the C-2 consciousness must be explained even if the C-1 experience
> was an illusion. My conscious memory of the event is more than
> just an uninterpreted memory of a memory of a memory ...
There is still no C-2 without C-1. For accompanying every C-2 episode
is a C-1 as substrate. Not only is there something it's like to have a
toothache (C-1), but there's also something it's like to REMEMBER
having a toothache (likewise C-1). The experience of remembering is a
qualitative experience too. The toothache may never actually have
happened. You may not even have a tooth. But the qualitative sense of
remembering it has the "phenomenological validity" that I claimed all
1st order conscious experience does. For if the C-2 episode is not a
qualitative experience, what qualifies it as conscious at all?
My point is subtle, but valid. I advise the perplexed to reread the
definitions of C-1 and C-2. Ken Laws's example of an "illusory" C-1
trades on the ambiguity between (a) the causal and temporal reality (i.e,
when, whether and why the tooth injury and neural events actually happened
in real time) of the CONTENTS of a conscious experience and (b) their
phenomenological validity (i.e., what you experienced them AS). The
memory of my toothache may be illusory in relation to the toothache I
never in reality had, but it is no illusion that I am having such a
memory now -- and that experience is the ineluctible C-1 substrate on
which any C-2 or higher must piggy-back. (And there's no point doing
another deferred-temporal number on THAT experience, analogous to the
one on the toothache -- misremembering remembering, or some such --
because it only leads to infinite regress, and still logically
requires an ongoing C-1 to justify calling it conscious.) No C-2
without an underlying C-1 too.
------------------------------
End of AIList Digest
********************
∂23-Jan-87 0152 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #13
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 23 Jan 87 01:49:47 PST
Date: Thu 22 Jan 1987 23:16-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #13
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 23 Jan 1987 Volume 5 : Issue 13
Today's Topics:
Philosophy - Introspection & Consciousness
----------------------------------------------------------------------
Date: Tue, 20 Jan 87 21:17:02 CST
From: Girish Kumthekar <kumthek%lsu.csnet@RELAY.CS.NET>
Subject: Another Lengthy Philosopical ....
I can see a storm brewing on the horizon about minds, consciousness etc....
AILIST readers beware!!!! Remember Turing Machines,...... etc ?
Possible future contributers, PLEASE limit your contributions to an
unclutterable volume!!
Girish Kumthekar
kumthek%lsu@CSNET-RELAY.CSNET
------------------------------
Date: Thu, 22 Jan 87 15:51:42 PST
From: kube%cogsci.Berkeley.EDU@berkeley.edu (Paul Kube)
Subject: The sidetracking of introspection
>From: hester@ai.cel.fmc.com (Tom Hester):
>Finally, R.J. Faichney is absolutely correct. It was not Freud that
>side tracked psychology from introspection. Rather it was the "dust
>bowl empiricists" that rode behaviorism to fame and fortune that did it.
On the chance that it's worth arguing about the intellectual
history of phsychology on AIList:
The behaviorists didn't just sidetrack introspection; they sidetracked
mentalism---engine, car, and caboose, so to speak. Introspection was
already demoted from the position it had had as infallible source of
psychological truth by James (he called his Principles of Psychology
"little more than a collection of illustrations of the difficulty of
discovering by direct introspection exactly what our feelings and
their relations are"). But James believed there are not any unconscious
mental states; Freud should get some credit for further demoting
introspection by arguing so influentially that there are.
Mentalism is back on track now in the post-behaviorist era, but a
principled skepticism about introspection remains.
A fascinating contemporary survey on the topic is Nisbett & Ross,
"Telling more than we can know: verbal reports on mental processes",
Psych. Rev. May 1977. From the abstract: "Evidence is reviewed
which suggests that there may be little or no direct introspective
access to higher order cognitive processes."
--Paul Kube
kube@cogsci.berkeley.edu, ...!ucbvax!kube
------------------------------
Date: Thu, 22 Jan 87 10:38:21 est
From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>
Subject: Objective vs. Subjective Inquiry
"CUGINI, JOHN" <cugini@icst-ecf> wrote on mod.ai:
> ...so the toothache is "real" but "subjective"...
> But...if both [subjective and objective phenomena] are real,
> then we know why we need consciousness as a concept --
> because without it we cannot explain/talk about the former class of
> events - even if the latter class is entirely explicable in its own
> terms. Ie, why should we demand of consciousness that it have
> explanatory power for objective events? It's like demanding that
> magnetism be acoustically detectible before we accept it as a valid
> concept.
Fortunately, there is a simple answer to this: Explanation itself is
(or should be) purely an objective matter. Magnetism, and all other
tractable physical phenomena are (in principle) objectively
explainable, so the above analogy simply does not work. Nagel has shown
that all of the other reductions in physics have always been
objective-to-objective. The mind/body problem is an exception
precisely because it resists subjective-to-objective reduction. Now if
there's something (subjectively) real and irreducible left over that
is left out of an objective account, we have to learn to live with
that explanatory incompleteness, rather than wishing it away by
hopeless mixing of categories and hopeful pumping of analogies, images
and interpretations. (In fact, I think that if all the objective
manifestations of consciousness -- performance capacity and neural
substrate -- are indeed "entirely explicable [in their own objective]
terms," as I believe and Cugini seems to concede, then why not get on
to explaining them thus, rather than indulging in subjective
overinterpretation and wishful thinking, which can only obscure or
even retard objective progress?)
[Please do not pounce on the parenthetic "subjectively" that preceded
"real," above. The problem of the objective status of consciousness
IS the mind/body problem, and to declare that subjectively-real =
objectively-real is just to state an empty obiter dictum. It happens
to be a correlative fact that all detectable physical phenomena --
i.e., all objective observables -- have subjective manifestations.
That's what we MEAN by observability, intersubjectivity, etc. But the
fact that the objective always piggy-backs on the subjective still
doesn't settle the objective status of the subjective itself. I'll go
even further. I'm not a solipsist. I'm as confident as I am of any
objective inference I have made that other people really exist and have
experiences like my own. But even THAT sense of the "reality" of the
subjective does not help when it comes to trying to give an objective
account of it. As to subjective accounts -- well, I don't go in much
for hermeneutics...]
> I can well understand how those who deny the reality of experiences
> (eg, toothaches) would then insist on the superfluousness of the
> concept of consciousness - but Harnad clearly is not one such.
> So...we need consciousness, not to explain public, objective events,
> such as neural activity, but to explain, or at least discuss, private
> subjective events. If it be objected that the latter are outside the
> proper realm of science, so be it, call it schmience or philosophy or
> whatever you like. - but surely anything that is REAL, even if
> subjective, can be the proper object for some sort of rational
> study, no?
Some sort, no doubt. But not an objective sort, and that's the point.
Empirical psychology, neuroscience and artificial intelligence are
all, I presume, branches of objective inquiry. I know that this is
also the heyday of hermeneutics, but although I share with a vengeance
the belief that philosophy can make a substantive contribution to the
cognitive sciences today, I don't believe that that contribution will
be hermeneutic. Rather, I think it will be logical, methodological
and foundational, pointing out hidden complexities, incoherencies and
false-starts. Let's leave the subjective discussion of private events
to lit-crit, where it belongs.
Stevan Harnad
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
(609)-921-7771
------------------------------
Date: 23 Jan 87 02:29:51 GMT
From: mcvax!cwi.nl!lambert@seismo.CSS.GOV (Lambert Meertens)
Subject: Submission for mod-ai
Path: mcvax!lambert
From: lambert@mcvax.cwi.nl (Lambert Meertens)
Newsgroups: mod.ai
Subject: Re: C-2 as C-1
Summary: Long again--please skip this article
Keywords: mind, consciousness, memory
Message-ID: <7259@boring.mcvax.cwi.nl>
Date: 23 Jan 87 02:29:51 GMT
References: <424@mind.UUCP> <12272599850.11.LAWS@SRI-STRIPE.ARPA>
Reply-To: lambert@boring.UUCP (Lambert Meertens)
Organization: CWI, Amsterdam
Lines: 104
In article <12272599850.11.LAWS@SRI-STRIPE.ARPA> Laws@SRI-STRIPE.ARPA
(Ken Laws) writes:
>> From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>:
>>
>> Worse than that, C-2 already presupposes C-1. You can't
>> have awareness-of-awareness without having awareness [...].
>
> A quibble: It would be possible [...] that my entire conscious
> perception of a current toothache is an "illusory pain" [...].
I agree.
> These views do not solve the problem, of course; the C-2 consciousness
> must be explained even if the C-1 experience was an illusion. My conscious
> memory of the event is more than just an uninterpreted memory of a memory
> of a memory ...
Here I am not so sure. To start with, the only evidence we have of
organisms having C-1 is if they are on the C-2 level, that is, if they
*claim* they experience something. Even granting them that they are not
lying in the sense of a conscious :-) misrepresentation, why should we (in
our quality of scientific enquirers) believe them on their word? After
all, more than a few people truly believe they have the most incredible
psychic powers.
Now how can we know that the "awareness-of-awareness" is a conscious thing?
There seems to be a hidden assumption that if someone utters a statement
(like "It is getting late"), then the same organisms is consciously aware
of the fact expressed in the statement. Normally, I would grant you that,
because that is the normal everyday meaning of "conscious" and "aware", but
not in the current context in which these words are isolated from their
original function to just provide an expedient way to express certain things.
[You will find that people in general have no problem in saying that a fly
is aware of something, or experiences pain, even though for all we know
there is no higher (coordinating) neural centre in this organism that would
provide a physiological substrate. Many people even have no problem in
ascribing consciousness to trees. I claim that if people (but not young
children) do have qualms in saying that an automaton experiences something,
it is because they have been *taught* that consciousness is limited to
animate, organic, objects.]
So the mere speech act "It is getting late" does not by itself imply a
conscious awareness of it getting late. Otherwise, we are forced to
ascribe consciousness of the occurrence of a syntax error to a compiler
mumbling "*** syntax error". Likewise, not only does someone saying "I
have a toothache" not imply that the speaker is experiencing a toothache,
it also does not imply that the speaker is consciously aware of the
(possibly illusionary) fact of experiencing one. The only evidence of that
would be a C-3 act, someone saying: "I am aware of the fact that I am aware
of experiencing a toothache." But again, why should we believe them? (And
so on, ad nauseam.)
This is getting so complicated mainly because of the inadequacy of words.
Allow me to try again. You, reader, are having a toothache. You are
really having one. I can tell, because you are visibly in pain, and,
moreover, I am your dentist, and you are in my chair with your mouth open
into which I am prodding and probing, and boy, you should have a toothache
if anyone ever had one. At this point, I cannot know for sure if you are
consciously experiencing that pain. Maybe neural pathways connect your
exposed pulpa with the centre innervating your grimacing and squirming
muscles while bypassing the centre of consciousness. I retract my
instruments from your mouth, giving you a chance to say "That really hurt,
doctor. I'll pay all my bills in time from now on if only you won't do
that again." Firmly brushing aside the empathy that threatens to
compromise my scientific attitude, I realize that this still does not mean
that you consciously experienced that pain just a minute ago. All I know
is that you remember it (for if you did not, you wouldn't have said that).
So some symbolic representation, "@#$%@*!" say, may have been stored in
your memory--also bypassing your centre of consciousness--which is now
retrieved and interpreted (maybe illusionary) as "conscious experience of
pain--just now". This interpretation act need not mean that you experience
the pain now, after the fact. So it is entirely possible that you did not
consciously experience the pain at any time. Now were you conscious then,
while making that silly promise, of at least the memory of the--by itself
possibly unconscious--suffering of pain? If you are still with me, then
you will probably agree that that is not necessarily the case. Just like
P = <neural event of pain>, even though leaving a trace in memory, need not
imply consciousness of P, so R(P) = <neural event of remembering P> need
not imply consciousness of R(P) itself. However, R(P) can again leave a
trace in memory--what with your Silly Promise and dentists' bills being as
they are, you are bound to trigger R(SP) and therefore, by association,
R(R(P)), many times in the future.
If we had two unconnected memory stores, and a switch would now connect to
one, now to the other store, we would become two personalities in one body
with two "consciousnesses". If we could somehow censor either the storing
or the retrieval of pain events, we would truly, honestly believe that we
are incapable of consciously experiencing pain--notwithstanding the fact
that we would probably have the same *immediate* reaction to pain as other
people--and we wouldn't make such promises to our dentists anymore.
Wrapping it all up, I still maintain that "conscious experience" is a term
that is ascribed *in retrospect* to any neural event NE that has been
stored in memory, at the time R(NE) occurs. Stronger, R(NE) is the
*only*--as I hope I have shown insufficient--evidence of "consciousness"
about NE in a more metaphysical or whatever sense. For all we know and can
know, all consciousness in the sense of being conscious of something *while
it happens* is an "illusion", whether C-1, C-2 or C-17.
--
Lambert Meertens, CWI, Amsterdam; lambert@mcvax.UUCP
------------------------------
Date: Thu, 22 Jan 87 12:30:35 est
From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>
Subject: Minsky on Mind(s)
MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU wrote in mod.ai (AIList Digest V5 #11):
> unless a person IS in the grip of some "theoretical
> position" - that is, some system of ideas, however inconsistent, they
> can't "know" what anything "means"
I agree, of course. I thought it was obvious that I was referring to a
theoretical position on the mind/body problem, not on the conventions
of language and folk physics that are needed in order to discourse
intelligibly at all. There is of course no atheoretical talk. As to
atheoretical "knowledge," that's another matter. I don't think a dog
shares any of my theories, but we both know when we feel a toothache
(though he can't identify or describe it, nor does he have a theory of
nerve impulses, etc.). But we both share the same (atheoretical)
experience, and that's C-1. Now it's a THEORY that comes in and says:
"You can't have that C-1 without C-2." I happen to have a rival theory
on that. But never mind, let's just talk about the atheoretical
experience I, my rival and the dog share...
> My point was that
> you can't think about, talk about, or remember anything that leaves no
> temporary trace in some part of your mind. In other words, I agree
> that you can't have C-2 without C-1 - but you can't have, think, say,
> or remember that you have C-1 without C-2! So, assuming that I know
> EXACTLY what he means, I understand PERFECTLY that that meaning is
> vacuous.
Fine. But until you've accounted for the C-1, your interpretation of
your processes as C-2 (rather than P-2, where P is just an unconscious
physical process that does the very same thing, physically and objectively)
has not been supported. It's hanging by a skyhook, and the label "C"
of ANY order is unwarranted.
I'll try another pass at it: I'll attempt to show how ducking or denying
the primacy of the C-1 problem gets one into infinite regress or
question-begging: There's something it's like to have the
experience of feeling a toothache. The experience may be an illusion.
You may have no tooth-injury, you may even have no tooth. You may be
feeling referred pain from your elbow. You may be hysterical,
delerious, hallucinating. You may be having a flashback to a year ago,
a minute ago, 30 milliseconds ago, when the physical and neural causes
actually occurred. But if at T-1 in real time you are feeling that
pain (let's make T-1 a smeared interval of Delta-T-1, which satisfies
both our introspective phenomenology AND the theory that there can be no
punctate, absolutely instantaneous experience), where does C-2 come into it?
Recall that C-2 is an experience that takes C-1 as its object, in the
same way C-1 takes its own phenomenal contents as object. To be
feeling-a-tooth-ache (C-1) is to have a certain direct experience; we all
know what that's like. To introspect on, reflect on, remember, think about
or describe feeling-a-toothache (all instances of C-2) is to have
ANOTHER direct experience -- say, remembering-feeling-a-toothache, or
contemplating-feeling-a-toothache. The subtle point is that this
2nd-order experience always has TWO aspects: (1) It takes a 1st order
experience (real or imagined) as object, and is for that reason
2nd-order, and (2) it is ITSELF an experience, which is of course
1st-order (call that C-1'). The intuition is that there is something
it is like to be aware of feeling pain (C-1), and there's ALSO something
it's like to be aware of being-aware-of-feeling-pain. Because a C-1 is
the object of the latter experience, the experience is 2nd order (C-2); but
because it's still an EXPERIENCE -- i.e., there's something it's LIKE to
feel that way -- every C-2 is always also a C-1' (which can in turn become
the object of a C-3, which is then also a C-1'', etc.).
I'm no phenomenologist, nor an advocate of doing phenomenology as we
just did above. I'm also painfully aware that the foregoing can hardly be
described as "atheoretical." It would seem that only direct experience
at the C-1-level can be called atheoretical; certainly formulating a
distinction between 1st and higher-order experience is a theoretical
enterprise, although I believe that the raw phenomenology bears me
out, if anyone has the patience to introspect it through. But the
point I'm making is simple:
It's EASY to tell a story in which certain physical processes play the
role of the contents of our experience -- toothaches, memories of
toothaches, responses to toothaches, etc. All this is fine, but
hopelessly 2nd-order. What it leaves out is why there should be any
EXPERIENCE for them to be contents OF! Why can't all these processes
just be unconscious processes -- doing the same objective job as our
conscious ones, but with no qualitative experience involved? This is
the question that Marvin keeps ignoring, restating instead his
conviction that it's taken care of (by some magical property of "memory
traces," as far as I can make out), and that my phenomenology is naive
in suggesting that there's still a problem, and that he hasn't even
addressed it in his proposal. But if you pull out the C-1
underpinnings, then all those processes that Marvin interprets as C-2
are hanging by a sky-hook. You no longer have conscious toothaches and
conscious memories of toothaches, you merely have tooth-damage, and
causal sequelae of tooth-damage, including symbolic code, storage,
retrieval, response, etc.. But where's the EXPERIENCE? Why should I
believe any of that is CONSCIOUS? There's the C-2 interpretation, of
course, but that's all it is: an interpretation. I can intepret a
thermostat (and, with some effort, even a rock) that way. What
justifies the interpretation?
Without a viable C-1 story, there can be no justification. And my
conjecture is that there can be no viable C-1 story. So back to
methodological epiphenomenalism, and forget about C of any order.
[Admonition to the ambitious: If you want to try to tell a C-1 story,
don't get too fancy. All the relevant constraints are there if you can
just answer the following question: When the dog's tooth is injured,
and it does the various things it does to remedy this -- inflamation
reaction, release of white blood cells, avoidance of chewing on that
side, seeking soft foods, giving signs of distress to his owner, etc. etc.
-- why do the processes that give rise to all these sequelae ALSO need to
give rise to any pain (or any conscious experience at all) rather
than doing the very same tissue-healing and protective-behavioral job
completely unconsciously? Why is the dog not a turing-indistinguishable
automaton that behaves EXACTLY AS IF it felt pain, etc, but in reality
does not? That's another variant of the mind/body problem, and it's what
you're up against when you're trying to justify interpreting physical
processes as conscious ones. Anything short of a convincing answer to
this amounts to mere hand-waving on behalf of the conscious interpretation
of your proposed processes.]
Stevan Harnad
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
(609)-921-7771
------------------------------
Date: Thu 22 Jan 87 21:30:13-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Subject: WHY of Pain
From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>
-- why do the processes that give rise to all these sequelae ALSO need
to give rise to any pain (or any conscious experience at all) rather
than doing the very same tissue-healing and protective-behavioral job
completely unconsciously?
I know what you mean, but ... Given that the dog >>is<< conscious,
the evolutionary or teleological role of the pain stimulus seems
straightforward. It is a way for bodily tissues to get the attention
of the reasoning centers. Instead of just setting some "damaged
tooth" bit, the injured nerve grabs the brain by the lapels and says
"I'm going to make life miserable for you until you solve my problem."
Animals might have evolved to react in the same way without the
conscious pain (denying the "need to" in your "why" question), but
the current system does work adequately.
Why (or, more importantly, how) the dog is conscious in the first place,
and hence >>experiences<< the pain, is the problem you are pointing out.
Some time ago I posted an analogy between the brain and a corporation,
claiming that the natural tendency of everyone to view the CEO as the
center of corporate conscious was evidence for emergent consciousness
in any sufficiently complex hierarchical system. I would like to
refute that argument now by pointing out that it only works if the
CEO and perhaps the other processing elements in the hierarchy are
themselves conscious. I still claim that such systems (which I can't
define ...) will appear to have centers of consciousness (and may well
pass Harnad's Total Turing Test), and that the >>system<< may even
>>be conscious<< in some way that I can't fathom, but if the CEO is
not itself conscious no amount of external consensus can make it so.
If it is true that a [minimal] system can be conscious without having
a conscious subsystem (i.e., without having a localized soul), we
must equate consciousness with some threshold level of functionality.
(This is similar to my previous argument that Searle's Chinese Room
understands Chinese even though neither the occupant nor his printed
instructions do.) I believe that consciousness is a quantitative
phenomenon, so the difference between my consciousness and that of
one of my neurons is simply one of degree. I am not willing to ascribe
consciousness to the atoms in the neuron, though, so there is a bottom
end to the scale. What fraction of a neuron (or of its functionality)
is required for consciousness is below the resolving power of my
instruments, but I suggest that memory (influenced by external conditions)
or learning is required. I will even grant a bit of consciousness
to a flip-flop :-). The consciousness only exists in situ, however: a
bit of memory is only part of an entity's consciousness if it is used
to interpret the entity's environment.
Fortunately, I don't have my heart set on creating conscious systems.
I will settle for creating intelligent ones, or even systems that are
just a little less unintelligent than the current crop.
-- Ken Laws
------------------------------
End of AIList Digest
********************
∂25-Jan-87 2351 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #14
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 25 Jan 87 23:51:36 PST
Date: Sun 25 Jan 1987 21:57-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #14
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 26 Jan 1987 Volume 5 : Issue 14
Today's Topics:
AI Tools - Scheme for Mac and IBM PCs &
Expert System Shell on PCDOS and Unix,
Mythology - Antiquity of AI,
Seminars - Presenting Intuitive Deductions (UPenn) &
New Themes in Data Structure Design (SU) &
AI and Software Engineering (BTL) &
Learning Internal Disjunctive Concepts (SRI),
Conference - MidAltantic Logic Seminar
----------------------------------------------------------------------
Date: Wed, 21 Jan 87 22:38:34 PST
From: larry@Jpl-VLSI.ARPA
Subject: Scheme for Mac & IBM PCs
Scheme can be gotten for Apple Macs and IBM PCs. MacScheme is $125 and can
be gotten from Semantic Microsystems in Oregon, 503/643-4359. The Texas
Inst. version costs $95; their phone # is 800/527-3500. A review from last
Feb. is appended for those who did not see it before. Larry @ jpl-vlsi.arpa
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
From: Rob Pettengill <CAD.PETTENGILL@MCC.ARPA> [69 lines]
I recently purchased an implementation of the Scheme dialect of lisp for my
PC. I am familiar with GC Lisp, IQ Lisp, and Mu Lisp for the PC. I use
Lambdas and 3600s with ZetaLisp at work.
TI PC Scheme is a very complete implementation of scheme for the IBM and TI
personal computers and compatibles. It combines high speed code execution,
a good debugging and editing environment, and very low cost.
The Language:
* Adheres faithfully to the Scheme standard.
* Has true lexical scoping.
* Prodedures and environments are first class data objects.
* Is properly tail recursive - there is no penalty compared
to iteration.
* Includes window and graphics extensions.
The Environment:
* An incremental optimizing compiler (not native 8086 code)
* Top level read-compile-print loop.
* Interactive debugger allows run time error recovery.
* A minimal Emacs-like full screen editor with a scheme mode
featuring parethesis matching and auto indenting of lisp code.
* An execute DOS command or "push" to DOS capability - this is
only practical with a hard disk because of the swap file PCS writes.
* A DOS based Fast Load file format object file conversion utility.
* A fast 2 stage garbage collector.
First Impressions:
Scheme seems to be much better sized to a PC class machine than the other
standard dialects of lisp because of its simplicity. The TI implementation
appears to be very solid and complete. The compiled code that it produces
(with debugging switches off) is 2 to 5 times faster than the other PC lisps
that I have used. With the full screen editor loaded (there is also a
structure editor) there seems to be plenty of room for my code in a 640k PC.
TI recommends 320k or 512k with the editor loaded. The documentation is of
professional quality (about 390 pages), but not tutorial. Abelson and
Sussman's "Structure and Interpretation of Computer Programs" is a very
good companion for learning scheme as well as the art and science of
cprogramming in general.
My favorite quick benchmark -
(define (test n)
(do
((i 0 (1+ i))
(r () (cons i r)))
((>= i n) r)))
runs (test 10000) in less than 10 seconds with the editor loaded - of course
it takes a couple of minutes to print out the ten thousand element list that
results.
The main lack I find is that the source code for the system is not included-
one gets used to that in good lisp environments. I have hit only a couple
of minor glitches, that are probably pilot error, so far. Since the system
is compiled with debugging switches off it is hard to get much useful
information about the system from the dubugger.
Based on my brief, but very positive experience with TI PC scheme and its
very low price of $95 - I recommend it to anyone interested in a PC based
lisp. (Standard disclaimers about personal opinions and having no
commercial interest in the product ...)
------------------------------
Date: 22 Jan 87 17:21:04 GMT
From: felix!fritz!kumar@hplabs.hp.com (John Kumar)
Subject: Expert System Shell on PCDOS and Unix
I got requests to send a summary of the responses I got to my enquiry. The
only useful one I got, I am including below.
The Shell offered by EXSYS (505)836-6676 will be up and running in unix by
mid February. It already runs on VMS. EXSYS has learned a lot about user
friendly recently, and offers superior features to Insight 2+ in the new
release about to come out, including: context sensitive help, backup to
last question, full blackboard, very fast operation, "fairly vanilla"
default display graphics, and powerful shell interface. I know some of
those features also exist in Insight 2+, but it's 4:00 in the morning and
if I could back up in this file, I'd reword my paragraph. EXSYS also offers
an online data dictionary and detects collision between similar rules.
Since it assigns serial numbers to rules, objects, and attributes, you
don't have to make up "meaningful" names for all your rules.
John, we are working on several expert systems for software diagnosis. We
are delivering networked expert systems on the PC now and started development
last month of a series of projects to run on 3B machines.
If you would like to talk, I'd be happy to share information both in my
capacity at Pacific Bell and representing my outside consulting/training
company. RSVP to:
John Girard
AI Systems Engineer
Pacific Bell
(415)823-1961
Meta (Inference) Services, Inc.
P.O. Box 635
San Ramon, CA 94583-0635
(415)449-5745
{dual,cbosgd,bellcore,ihnp4,qantel,pyramid}!ptsfa!jeg
------------------------------
Date: 22 Jan 87 10:26:00 EST
From: "*BROWN, MARK" <mbrown@ari-hq1.ARPA>
Reply-to: "*BROWN, MARK" <mbrown@ari-hq1.ARPA>
Subject: antiquity of AI
There may be a reference that relates to AI in the Story of Gilgamish
the King, a Summarian legend from about 2500 B.C.
Neil Maclay
MACLAY@ARI-HQ1.ARPA
------------------------------
Date: Tue, 20 Jan 87 10:58:55 EST
From: dale@linc.cis.upenn.edu (Dale Miller)
Subject: Seminar - Presenting Intuitive Deductions (UPenn)
Penn Math/CS Logic Seminar
26 January
Presenting Intuitive Deductions
Frank Pfenning
(pfenning@theory.cs.cmu.edu)
Carnegie-Mellon University
A deduction of a theorem may be viewed as an explanation why the theorem
holds. Unfortunately the automated theorem proving community has
concentrated almost exclusively on determining whether a proposed theorem is
provable - the proofs themselves were secondary. We will explore how
convincing explanations may be obtained from almost any kind of machine
proof. This extends work by Dale Miller and Amy Felty (who present
deductions in the sequent calculus) to a natural deduction system. Also,
our deductions will generally not be normal, that is, they make use of
lemmas which are so frequent in mathematical practice and everyday
reasoning. We will also briefly discuss possible applications of the
methods in the field which may be called "Inferential Programming".
Math Seminar Room, 4th floor Math/Physics Building, 11:00am
------------------------------
Date: Wed 21 Jan 87 11:21:12-PST
From: Alejandro Schaffer <SCHAFFER@Sushi.Stanford.EDU>
Subject: Seminar - New Themes in Data Structure Design (SU)
annual Forsythe Lecture of general interest
Robert Tarjan
Princeton University and AT&T Bell Laboratories
New Themes in Data Structure Design
Wednesday, January 28 at 7:30
Fairchild Auditorium
(just southwest of Stanford Medical Center off Campus Drive)
This talk will cover recent work by the speaker and his colleagues
concerning the design and analysis of data structures. The talk will
focus on persistent data structures, which allow access to any
version of the structure, past or present. Applications of such
structures in computational geometry and other areas will be
discussed.
(There will be a reception in the Fairchild Auditorium foyer immediately
following the lecture.)
------------------------------
Date: Tue 20 Jan 1987 18:20:20
From: dlm.allegra%btl.csnet@RELAY.CS.NET
Subject: Seminar - AI and Software Engineering (BTL)
Title: Artificial Intelligence and Software Engineering
Speaker: Dave Barstow
Affiliation: Schlumberger-Doll Research
Date: January 20, 1987
Location: AT&T Bell Laboratories - Murray Hill
Sponsor: Pamela Zave
Abstract:
Artificial Intelligence techniques ought to help us to manage the extensive
knowledge needed for software engineering, but two decades of research have
produced few demonstrations of utility. This is due in part to the narrow
focus of previous research. This talk discusses important issues that remain
to be addressed, describes a practical experiment, and suggests profound
implications for software engineering.
------------------------------
Date: Thu, 22 Jan 87 18:32:33 PST
From: lansky@sri-venice.ARPA (Amy Lansky)
Subject: Seminar - Learning Internal Disjunctive Concepts (SRI)
LEARNING INTERNAL DISJUNCTIVE CONCEPTS
David Haussler (HAUSSLER%UCSC@CSNET-RELAY)
Dept. of Computer and Information Sciences, UC Santa Cruz
11:00 AM, TUESDAY, January 27
SRI International, Building E, Room EK242
Much of artificial intelligence research on concept learning from
examples has focussed on heuristic learning techniques that have not
been susceptible to rigorous analysis. Here we present a simple
heuristic algorithm for learning a particular type of concept
identified by Michalski (internal disjunctive concepts) and analyze
its performance using the learning performance model recently proposed
by Valiant. This analysis shows that the algorithm will be effective
and efficient in a wide variety of real-world learning situations.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Thu, 22 Jan 87 16:20:22 EST
From: dale@linc.cis.upenn.edu (Dale Miller)
Subject: Conference - MidAltantic Logic Seminar
If you plan to attend the Mid Atlantic Mathematical Logic Seminar, you
might consider the following hotels in the Univ of Pennsylvania area.
o Divine Tracy Hotel, 20 South 36th Street, $15/night, 0.5 miles from
meeting, 215/382-4310
o Quality Inn, 22nd St (north of Parkway), $45/night, 2 miles from
meeting, 800/228-5151
o Hilton Hotel, Civic Center Blvd & 34th, $60/night, 215/387-8333, 0.2
miles from the meetings
o Sheraton Inn University City, 36th & Chestnut, $64/night, 0.5 miles
from meeting, 215/387-8000
The prices are approximate. Notice: there are no plans to publish
proceedings of this conference.
------------------------------
End of AIList Digest
********************
∂26-Jan-87 0147 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #15
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 26 Jan 87 01:47:04 PST
Date: Sun 25 Jan 1987 22:12-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #15
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 26 Jan 1987 Volume 5 : Issue 15
Today's Topics:
Philosophy - Consciousness
----------------------------------------------------------------------
Date: Fri, 23 Jan 87 03:59:40 cst
From: goldfain@uxe.cso.uiuc.edu (Mark Goldfain )
Subject: For the AIList "Consciousness" Discussion
*************************************************************************
* *
* Consciousness is like a large ribosome, working its way along the *
* messenger RNA of our perceptual inputs. Or again, it is like a *
* multi-headed Turing machine, with the heads marching in lock step *
* down the great input tape of life. *
* *
*************************************************************************
Lest anyone think I am saying more than I actually am, please understand
that these are both meant as metaphors. I am not making ANY claim that mRNA
is the chemical of brain activities, nor that we are finite-state machines, et
cetera ad nauseum. I am only trying to get us off of square zero in our
characterization of how "being conscious" can be understood.
It must be something which has a "window" of a finite time period, for we
can sense the "motion" of experiences "through" our consciousness. It must be
more involved than a ribosome or a basic Turing device, since in addition to
being able to access the "present", it continually spins off things that we
call "memories", and ties these things down into a place that allows them to
be pulled back into the consciousness. (Actually, the recall of long term
memory is more like the process of going into a dark room with a tuning fork,
giving it a whack, then listening for something that resonates, going over to
the sound, and picking it up ... so perhaps the memories are not "tied down"
with pointers at all.)
------------------------------
Date: 23 Jan 87 21:15:22 GMT
From: ihnp4!cuae2!ltuxa!cuuxb!mwm@ucbvax.Berkeley.EDU (Marc W.
Mengel)
Subject: Re: More on Minsky on Mind(s)
In article <460@mind.UUCP> Sevan Harnad (harnad@mind.UUCP) writes:
> [ discussion of C-1 and C-2]
It seems to me that the human conciousness is actually more
of a C-n; C-1 being "capable of experiencing sensation",
C-2 being "capable of reasoning about being C-1", and C-n
being "capable of reasoning about C-1..C-(n-1)" for some
arbitrarily large n... Or was that really the intent of
the Minsky C-2?
--
Marc Mengel
...!ihnp4!cuuxb!mwm
------------------------------
Date: 23 Jan 87 16:10:53 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: Minsky on Mind(s)
Ken Laws <Laws@SRI-STRIPE.ARPA> wrote on mod.ai:
> Given that the dog >>is<< conscious,
> the evolutionary or teleological role of the pain stimulus seems
> straightforward. It is a way for bodily tissues to get the attention
> of the reasoning centers.
Unfortunately, this is no reply at all. It is completely steeped in
the anthropomorphic interpretation to begin with, whereas the burden
is to JUSTIFY that interpretation: Why do tissues need to get the
"attention" of reasoning centers? Why can't this happen by brute
cuasality, like everything else, simple or complicated?
Nor is the problem of explaining the evolutionary function of consciousness
any easier to solve than justifying a conscious interpretation of machine
processes. For every natural-selectional scenario -- every
nondualistic one, that is, i.e., one that doesn't give consciousness
an independent, nonphysical causal force -- is faced with the problem
that the scenario is turing-indistinguishable from the exact same ecological
conditions, with the organisms only behaving AS IF they were
conscious, while in reality being insentient automata. The very same
survival/advantage story would apply to them (just as the very same
internal mechanistic story would apply to a conscious device and a
turing-indistinguishable as-if surrogate).
No, evolution won't help. (And "teleology" of course begs the
question.) Consciousness is just as much of an epiphenomenal
fellow-traveller in the Darwinian picture as in the cognitive one.
(And saying "it" was a chance mutation is again to beg the what/why
question.)
> Why (or, more importantly, how) the dog is conscious in the first place,
> and hence >>experiences<< the pain, is the problem you are pointing out.
That's right. And the two questions are intimately related. For when
one is attempting to justify a conscious interpretation of HOW a
device is working, one has to answer WHY the conscious interpretation
is justified, and why the device can't do exactly the same thing (objectively
speaking, i.e., behaviorally, functionally, physically) without the
conscious interpretation.
> an analogy between the brain and a corporation,
> ...the natural tendency of everyone to view the CEO as the
> center of corporate conscious was evidence for emergent consciousness
> in any sufficiently complex hierarchical system.
I'm afraid that this is mere analogy. Everyone knows that there's no
AT&T to stick a pin into, and to correspondingly feel pain. You can do
that to the CEO, but we already know (modulo the TTT) that he's
conscious. You can speak figuratively, and even functionally, of a
corporation as if it were conscious, but that still doesn't make it so.
> my previous argument that Searle's Chinese Room
> understands Chinese even though neither the occupant nor his printed
> instructions do.
Your argument is of course the familiar "Systems Reply." Unfortunately,
it is open to (likewise familiar) rebuttals -- rebuttals I consider
decisive, but that's another story. To telescope the intuitive sense
of the rebuttals: Do you believe rooms or corporations feel pain, as
we do?
> I believe that consciousness is a quantitative
> phenomenon, so the difference between my consciousness and that of
> one of my neurons is simply one of degree. I am not willing to ascribe
> consciousness to the atoms in the neuron, though, so there is a bottom
> end to the scale.
There are serious problems with the quantitative view of
consciousness. No doubt my alertness, my sensory capacity and my
knowledge admit of degrees. I may feel more pain or less pain, more or
less often, under more or fewer conditions. But THAT I feel pain, or
experience anything at all, seems an all-or-none matter, and that's
what's at issue in the mind/body problem.
It also seems arbitrary to be "willing" to ascribe consciousness to
neurons and not to atoms. Sure, neurons are alive. And they may even
be conscious. (So might atoms, for that matter.) But the issue here
is: what justifies interpreting something/someone as conscious? The
Total Turing Test has been proposed as our only criterion. What
criterion are you using with neurons? And even if single cells are
conscious -- do feel pain, etc. -- what evidence is there that this is
RELEVANT to their collective function in a superordinate organism?
Organs can be replaced by synthetic substances with the relevant
functional properties without disturbing the consciousness of the
superordinate organism. It's a matter of time before this can be done
with the nervous system. It can already be done with minor parts of
the nervous system. Why doesn't replacing conscious nerve cells with
synthetic molecules matter? (To reply that synthetic substances with the
same functional properties must be conscious under these conditions is
to beg the question.)
[If I sound like I'm calling an awful lot of gambits "question-begging,"
it's because the mind/body problem is devilishly subtle, and the
temptation to capitulate by slipping consciousness back into one's
premises is always there. I'm just trying to make these potential
pitfalls conscious... There have been postings in this discussion
to which I have given up on replying because they've fallen so deeply
into these pits.]
> What fraction of a neuron (or of its functionality)
> is required for consciousness is below the resolving power of my
> instruments, but I suggest that memory (influenced by external
> conditions) or learning is required. I will even grant a bit of
> consciousness to a flip-flop :-).
> The consciousness only exists in situ, however: a
> bit of memory is only part of an entity's consciousness if it is used
> to interpret the entity's environment.
What instruments are you using? I know only the TTT. You (like Minsky
and others) are placing a lot of faith in "memory" and "learning." But
we already have systems that have remember and learn, and the whole
point of this discussion concerns whether and why this is sufficient to
justify interpreting them as conscious. To reply that it's again a matter
of degree is again to obfuscate. [The only "natural" threshold is the
TTT, and that's not just a cognitive increment in learning/memory, but
complete functional robotics. And of course even that is merely a
functional goal for the theorist and an intuitive sop for the amateur
(who is doing informal turing testing). The philosopher knows that
it's no solution to the other-minds problem.]
What you say about flip-flops of course again prejudges or begs the
question.
> Fortunately, I don't have my heart set on creating conscious systems.
> I will settle for creating intelligent ones, or even systems that are
> just a little less unintelligent than the current crop.
If I'm right, this is the ONLY way to converge on a system that passes
the TTT (and therefore might be conscious). The modeling must be ambitious,
taking on increasingly life-size chunks of organisms' performance
capacity (a more concrete and specific concept than "intelligence").
But attempting to model conscious phenomenology, or interpreting toy
performance and its underlying function as if it were doing so, can
only retard and mask progress. Methodological Epiphenomenalism.
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: 23 Jan 87 08:15:00 EST
From: "CUGINI, JOHN" <cugini@icst-ecf>
Reply-to: "CUGINI, JOHN" <cugini@icst-ecf>
Subject: consciousness as a superfluous concept, but so what
> Stevan Harnad:
>
> ...When the dog's tooth is injured,
> and it does the various things it does to remedy this -- inflamation
> reaction, release of white blood cells, avoidance of chewing on that
> side, seeking soft foods, giving signs of distress to his owner, etc. etc.
> -- why do the processes that give rise to all these sequelae ALSO need to
> give rise to any pain (or any conscious experience at all) rather
> than doing the very same tissue-healing and protective-behavioral job
> completely unconsciously? Why is the dog not a turing-indistinguishable
> automaton that behaves EXACTLY AS IF it felt pain, etc, but in reality
> does not? That's another variant of the mind/body problem, and it's what
> you're up against when you're trying to justify interpreting physical
> processes as conscious ones. Anything short of a convincing answer to
> this amounts to mere hand-waving on behalf of the conscious interpretation
> of your proposed processes.
This seems an odd way to put it - why does X "need" to produce Y ?
Why do spinning magnets "need" to generate electric currents? I
don't think that's quite the right question to ask about causes and
events - sounds vaguely anthrpomorphic to me. It's enough to say
that, in fact, certain types of events (spinning magnets, active
brains) do in fact cause, give rise to, certain other types of events
(electric currents, experiences). Now, now, don't panic, I know that
the epistemological justification for believing in the existence and
causes of experiences (one's own and that of others) is quite
different from that for electric currents. I tried to outline the
epistemology in the longish note I sent a month or so ago (the one
with events A1, B1, C1, which talked about brains as a more important
criterion for consciousness than performance, etc.).
Do I sense here the implicit premise that there must be an evolutionary
explanation for the existence of consciousness? And that consciousness
is a rationally justified concept iff such an evolutionary role for it
can be found? But sez who? Consciousness may be as superflouous (wrt
evolution) as earlobes. That hardly goes to show that it ain't there.
The point is, given a satisfactory justification for believing that
a) experiences exist and b) are (in the cases we know of) caused by
the brain, I don't see why a "pro-consciousness" person should feel
obligated to answer why this NEEDS to be so. I don't think it does
NEED to be so. It just is so.
John Cugini <Cugini@icst-ecf>
------------------------------
End of AIList Digest
********************
∂26-Jan-87 0341 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #16
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 26 Jan 87 03:41:23 PST
Date: Sun 25 Jan 1987 22:15-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #16
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 26 Jan 1987 Volume 5 : Issue 16
Today's Topics:
Reviews - Spang Robinson Report Volume 3, No. 1, January 1987 &
Canadian Artificial Intelligence,
Conferences - AI at Upcoming Conferences
----------------------------------------------------------------------
Date: WED, 10 oct 86 17:02:23 CDT
From: leff%smu@csnet-relay
Subject: Summary of Spang Robinson Report Volume 3, No. 1, January
1987
The first Article: The AI Winter?
This is a discussion of whether the "AI industry" has "losts its momentum" or
is it a changing market. There is also a discussion of the possibilities of
AI being done in conventional programming languages.
____________________________________________________________________________
Investors Viewpoint
Interview with Montgomery Venture on the possibilities of venture capital
for AI companies.
___________________________________________________
New Products
Borland has introduced a Prolog toolbox to go with its Prolog. It includes
features to assist in the user interface, to import data from various
other microcomputer programs such as 1-2-3, parser generators, serial
communications.
________________________________________________________________________
Japan Watch
The Japanese Manufacturing industry is now using 500 AI work stations.
These included 153 Symbolics 3600 series, 15 Lambda series, 50 Fujitsu
Facom Systems, 300 Xerox 1121's and seven TI Explorers.
The Japanese AI Market is 3.125 million dollars.
The Japanese hosted the Sixth Medical Information Study Conference.
Japanese Hospitals are using SURGIST-AI from Fujitsu and EXCORE from NEC.
Nihon Electronics technology Institute of Tokyo has a two year
course for "knowledge engineering."
NEC will be releasing a new AI system called Co-operative HIgh
performance Inference machine (CHI).
_____________________________________________________________________
Japanese Construction Applications
Fudo Construction is developing a design support system for the entire
phase of building construction. Tokyo construction has
developed the Land Development Provisions Consultation Expert System.
Mitsui is planning to develop several AI systems. Asahi Glass is developing
a production planning system for plate glas sprocessing. Nihon cement
will develop a cement manufacturing expert system.
_______________________________________________________________________
Shorts:
One third of the nation's largest insurance companies are using or are
in the process of gearing up to use expert systems. However only
two per cent have actually put expert systems into use.
Lucid has completed a 4.5 million dollar second round of financing.
______________________________________________________________________
Reviews of Applying Expert Systems in Business by Dimitris Chorafas,
Expert Systems TEchniques Tools and Applications by Philip Klahr and
Donald A. Waterman, Artificial Intelligence and Expert Systems by
V. Daniel Hunt, Advances in Cognitive Science 1 edited by N. E.
Sharkey and Explanation Patterns; Understanding Mechanically and
creatively by Roger C. Shank.
------------------------------
Date: WED, 10 oct 86 17:02:23 CDT
From: leff%smu@csnet-relay
Subject: summary of Canadian ARtificial Intelligence
January 1987 Canadian Artificial Intelligence No. 10
Letter about progress on Japanese Fifth Generation.
The DELTA database machine, which earlier was described
as being non-functional and abandoned, was in fact fast
but had ease of use problems. A new version is under development.
The operating sytem/programming environment for the Personal Sequential
Interface by Mitsubishi is 160,000 lines and took 80 man years to develop.
19 Japanese companies have formed the Artificial Intelligence Joint
Research Society to train researchers and undertake joint development efforts.
__________________________________________________
Review of AI research at Queen's University.
They have developed a language for called Nial and a tool kit. They
are working on database models and interfaces, fuzzy logic, inference
engines, natural language parsing, window packages, rule systems,
built in editing, and educational environments.
__________________________________________________
A review discussion the issue of "What is AI" with a list
of those efforts that could be considered artificial intelligence.
__________________________________________________
Reports on the Seventh European Conference on Artificial Intelligence (ECAI-86)
and the International Workshop on User Modelling.
Some of the expert systems demonstrated at ECAI-86 include
- a system to monitor the operation of a steam condensor at a thermal power
plant
- a system to process alarms in the vacuum distillation tower of a refinery
Some of the papers covered
- a system to keep a consulting session with an expert system on target
- a review of machine translation research. Pre and post-editing
translation editing aids are quite successful. Three of the more
advanced systems are METAL (University of Texas), MU (Kyoto University)
and Eurotra (European Community). The latter is supposed to
cover nine Europ[ean languages.
- The UCLA system has an intelligent tutor for UNIX. After several
minutes of processing on an Apollo the system was able to have the
following dialogue:
User: I tried to remove a file with the "rm" command. The file was
not removed, and the error message was "permisssion denied" I
checked and I own the file
Acqua: To remove a file, you need to be able to write into the directory
containing it. To remove a file, you do not need to own it.
- Paul Jacobs developed a new natural language generator called KING.
- Professor Prini predicted that Europe's stable growth rate is a good
opportunity for Artificial INtelligence, particularly in dealing with
a software production capacity shortage that is due soon.
- Harold Kahn demonstrated computer generated pictures. His later works
demonstrated quite a bit of realism including one of the Statue of
liberty complete with Rococo festivity of the 18th century
- Clive Sinclair preicted that intelligent androids would be widely used
by the year 2010.
__________________________________________________
Reviews of "Implementing Mathematics with the Nuprl Proof Development
system" by R. L. Constable This text is aimed at mathematics and
computer science undergraduates.
Also Readings in Artificial Intelligence and Software Engineering"
by Charles Rich and Richard C. Waters.
------------------------------
Date: WED, 10 oct 86 17:02:23 CDT
From: leff%smu@csnet-relay
Subject: AI at upcoming conferences
1987 Society for Computer Simulation Multiconference 1987
Modeling and Simulation on Microcomputers
Individual Face Classification by Computer Vision
Robert A. Campbell, Scott Cannon, Greg Jones, Neil Morgan, Utah State Universi
ty
AI and Simulation
Preliminary Screening of Wastewater Treatment Alternatives Using Personal Consul
tant Plus
Giles G. Patry, Bruce Gall, McMaster University
The impact of embedding AI tools in a control system simulator
Norman R. Nielson SRI International
An Expert System for the Controller
James A. Sena, L. Murphy Smith,Texas A&M University
Application of Artificial Intelligence Techniques to Simulation
Pauline A. Langen, Carrier Corporation
The Expert System Applicability Question
Louis R. Gieszi
An Intelligent Interface for Continuous System Simulation
Wanda M. ustin The Aerospace Corporation Behrokh Khoshnevis University of Sout
hern
California
Logic Progrmming and Discrete Event Simulation
Robert G. Sargent, Ashvin, Radiya, Syracuse University
Expet Systems for Interactive Simulation of Computer System Dynamics
Axel Lehmann, University of Karlsruhe
An Automated Simulation Modeling System Based on AI Techniques
Behrokh Khoshnevis, An-Pin Chen, University of Southern California
Design of a Flexible Extendible Modeling Environment
Robert J. Pooley University of Edinburgh
Prolog for Simulation
Expert System Shellw ith System Simulation Capabilities
Ivan Futo, Computer Research Institute
Languages for Distributed Simulation
Brian Unger, Xining Li, University of Calgary
Process Oriented Simulation in Prolog
Jeans Vaucher, University of Montreal
Application of Artificial Intelligence Techniques to Simulation
Pauline A. Langen, Carrier Corporation
Computer Integrated Manufacturing Systems and robotics
A Data Modeling Approach to Improve System's Intelligence in Automated Manufactu
ring
Lee-Eng Shirley Lin, Yun-Baw Lin, Tamkang University
KARMA - A Knowledge-Based Robot Manipulation Graphics Simulation
Richard H. Kirschbrown, Consultant
Development of questions-answers simulator for real-time scheduling and control
in
flexible manufacturing system using Prolog
Lee-Eng Shirley Lin, Tamkang Unviersity, Chang Yung Lui, National Sun Yat-Sen
University
Simulation of uncertainty and product structure in MRP
Louis Brennan, Surendra Mohan Gupta, Northeastern University
__________________________________________________________________________
The University of ARizona Fourth Symposium on Modeling and Simulation Methodolo
gy
January 19-23 1987
AI and Simulation I, R. V. Reddy
AI and Simulation II, B. P. Zeigler
(Object Oreinted/AI Programming, Combining Discrete Event and Symbolic Models,
Hierarchical, Modular Modelling/Multiprocessor Simulation)
AI and Simulation III, T. I. Oren
cognizant Simulation Systems, AI and Quality Assurance Methodology
AI and Simulation IV
Environments for AI and Simulation, Interfacing Lisp Machines and Simulation E
ngines
Special Sessions on Model-basedDiagnosis and Expert Systems Training, Inductive
Modelling,
Goal Directed, Variable-Structure Models, AI and Simulation in Education
__________________________________________________
Compcon 87 Cathedral Hill Hotel, San Francisco, February 23-27
Tutorial Number 3 on AI Machines: INstructor David Elliot Shaw of the
Columbia University Non-Von Project
Tutorial Number 7: Managing Knowledge Systems Development: Instructor
Avron Barr
10:30-12:00 February 24
Use of an Advanced Expert Systems Tool for Fault Free Analysis in Nuclear
Power Plants - B. Frogner Expert-Easy Systems
Expert System Tool with Fact/Model Representation Environment on PSI
H. Kubono: ICOT
Towards an Expert System for Logic Circuits Synthesis A. DiStefano
Universita Di Catania
1:30-3:00 February 24
Expert Systems Development Environments - Issues and Future Directions
(Titles and Authors TOBA)
3:30 - 5:00 Tuesday
The Xenologic X1
A Coprocessor for AI, LISP, Prolog and Databases T. Dobry
Integration of the Xenologic X1 AI Coprocessor With General Purpose
Computers R. Ribler
System Level Performance Using AI Coprocessors A. Despain
(all authors with Xenologic, Inc.)
Intelligent Systems for Management Decision Support, Joseph Fiksel Chair
of Panel
8:30-10:00 Wednesday February 25
Changing the Nature of CAD/CAM with AI C. Kempf: FMC Corp.
Knowledge-based Engineering for PRoduction Planning and Control
I. Johnson Garegie Group (sic)
Digital's Knowledge Network - F. Lynch: DEC.
1:30 - 3:00 February 25
A Neural Based Knowledge Processor - J. Vovodsky Neuro Logic Inc.
Connectionists, Symbol Processsing in Neural Based Architectures
D. Touretzky, Carnegie-Mellon Univ.
Drawbacks with Neural Based Architectures - D. Partridge New Mexico State
University
Timing Dependencies in Sentence Comprehension - H. Gigly, University of
New Hampshire
3:30 - 5:00 Wednesday February 25
Plentary Talk - "Trends in Knowledge Processing: From Expert Systems to
INtelligent Systems Engineering" Dr. Frederick Hayes-Roth
8:30 - 10:00 Thursday February 26
Intelligent Assistance Without Artificial Intelligence - G. Caiser
3:30 - 5:00 Thursday February 26
Lisp Machine Architecture Issues - R. Lim NASA Ames Research Center
High Level Language LISP Processor - S. Krueger: TI
Kyoto Common LISP - F. Giunchiglia IBUKI Inc.
Optical Neural Networks D. Psaltis: California Institute of Technology
Attendee's Open Mike - Mim Warren
(Ten Minutes to present proposals, ideas, etc.)
__________________________________________________
Third International Conference on Data Engineering February 2-6, 1987
Pacifica Hotel, Los Angeles, California
February 4, 1987
2 - 3:30 Panel on Symbolic Procesing
H. Barsamian, UC Irvine, A. Cardenas, UCLA, D. Kibler, UC Irvine,
B. Wah, University of Illinois, T. Welch, International Software Systems
4:00 -6:00 February 4, 1987
M. Stonebraker, E. Hanson, C. HOng
The Design of hte Postgres Rules Systems
M. Kifer, E. L. Lozinskii
Implementing Logic Programs as a Database System
M. Lenzernini
Covering and Disjointness Constraints in Type Networks
11:12:30 February 5, 1987
P. Crews
tbt Expert: A Case Study in Integrating Expert System Technology with
Computer Assisted Instruction
__________________________________________________
ACM SIGCSE, February 19-20 1987, St. Louis Missouri
9:54 Friday February 20
A Course on "Expert Systems" for Electrical Engineering Students
___________________________________________________
Principles of Database Systems March 22-25, 1987 San Diego, California
Monday March 23, 1986 9:00 - 10:35 AM
Logic Programming with Sets G. M. Kuper, IBM T. J. Watson Research Center
Sets and Negation in a Logic Database Language LDL1 C. Beeri (Hebrew
University,) S. Naqvi (MCC), R. Ramakrishnan (University of Texas at
Austin and MCC), O. Shmueli, and S. Tsur (MCC)
Monday March 23, 1986, 10:35 AM - 11:00 AM
Logical Design of Relational Database Schemes
L. Y. Yuan University of Southern Louisiana
Z. M. Oxsoyoglu, Case Wetern Reserve University
Monday March 23, 1986 3:45 PM - 5:25 PM
A Knowledge-Theoretic Analysis of Atomic Comittment Protocols
V. Hadzilacos, University of Toronto
Tuesday March 24, 1986, 9:00 AM - 10:35 AM
Perspectives in Deductive Databases
J. MInker, University of Maryland
Maintenance of Stratified Databases Viewed as a Belief Revision System
K. Apt (Ecole NOrmal Suprerieure and Universite Paris 7)
J. M. Pugin (BULL Reserch Center)
Tuesday March 24, 1986, 3:15 PM - 3:45 PM
Bounds on the PRopagation of Selection into Logic Programs
C. Beeri (Hebrew University)
P. Kanellakis (Brown University)
F. Bancilhon (IRIA and MCC)
R. Ramakrishnnan(University of Texas at Austi.n and MCC)
Decidability and Expressiveness Aspects of Logic Queries
O. Shmueli (Technion and MCC)
Wednesday March 25, 1986 11:00 - 12:15
Worst Case Complexity Analysis of Methods for Logic Query Implementation
A. Marchetti-Spaccamella, A. Pelaggi (Universita "La Sapenza" di ROma) and
D. Sacca (CRAI, Italy)
Wednesday March 25 , 1986 2:00 PM - 4:35 PM
Safety of recursive Horn Clauses with Infinite Relations
R. Ramkrishanan (University of Texas at Austin and MCC)
F. Bancilhon (INRIA and MCC))
A. Silberschatz (University of Texas at Austi.n)
Optimizing Datalog Programs
Y. Sagiv (Hebrew University)
------------------------------
End of AIList Digest
********************
∂27-Jan-87 0224 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #17
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 27 Jan 87 02:23:50 PST
Date: Mon 26 Jan 1987 23:46-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #17
To: AIList@SRI-STRIPE.ARPA
AIList Digest Tuesday, 27 Jan 1987 Volume 5 : Issue 17
Today's Topics:
Psychology - Objective Measurement of Subjective Variables,
Philosophy - Quantitative Consciousness
----------------------------------------------------------------------
Date: 25 Jan 87 15:15:06 GMT
From: clyde!burl!codas!mtune!mtund!adam@rutgers.rutgers.edu (Adam V. Reed)
Subject: Objective measurement of subjective variables
John Cugini:
>> .... to explain, or at least discuss, private
>> subjective events. If it be objected that the latter are outside the
>> proper realm of science, so be it, call it schmience or philosophy or
>> whatever you like. - but surely anything that is REAL, even if
>> subjective, can be the proper object for some sort of rational
>> study, no?
Stevan Harnad:
> Some sort, no doubt. But not an objective sort, and that's the point.
> Empirical psychology, neuroscience and artificial intelligence are
> all, I presume, branches of objective inquiry.
> .... Let's leave the subjective discussion of private events
> to lit-crit, where it belongs.
Stevan Harnad makes an unstated assumption here, namely, that subjective
variables are not amenable to objective measurement. But if by
"objective" Steve means, as I think he does, "observer-invariant", than
this assumption is demonstrably false. I shall proceed to demonstrate
this in two parts: (1) private events are amenable to parametric
measurement; and (2) relevant results of such measurement can be
observer-invariant.
(1) Whether or not a stimulus is experienced as belonging to some target
category is clearly a private event. Now data for the measurement of d',
the detection-theoretic measure of discriminability, are usually
gathered using overt behavior, such as pressing "target" and
"non-target" buttons. But in principle, d' can be measured without any
resort to externally observable behavior. Suppose I program a computer
to present a sequence of stimuli and, following enough time after
each stimulus to allow the observer to mentally classify the experience
as target or non-target, display the actual category of the preceding
stimulus. The observer would use this information to maintain a mental
count of hits and false alarms. The category feedback for the last
stimulus could be followed by a display of a table for the conversion of
hit and false alarm rates into d'. Thus, the observer would be able to
mentally compute d' without engaging in any externally observable
behavior whatever.
(2) In some well-defined contexts, the variation of d' with an
independent variable is as lawful as anything in the "known to be
objective" sciences such as physics (see Reed, Memory and Cognition
1976, 4(4), 453-458, equation 5 and bottom panel of figure 1, for an
example of this). The parameters of such lawful relationships will
differ from observer to observer, but their form is observer-invariant.
In principle, two investigators could perform the experiment as in (1)
above, and obtain objective (in the sense of observer-independent)
results as to the form of the resulting lawful relationships between,
for example, d' and memory retention time, *without engaging in any
externally observable behavior until it came time to compare results*.
The following analogy (proposed, if I remember correctly, by Robert
Efron) may illuminate what is happening here. Two physicists, A and B,
live in countries with closed borders, so that they may never visit each
other's laboratories and personally observe each other's experiments.
Relative to each other's personal perception, their experiments are
as private as the conscious experiences of different observers. But, by
replicating each other's experiments in their respective laboratories,
they are capable of arriving at objective knowledge. This is also true,
I submit, of the psychological study of private, "subjective"
experience.
Adam Reed
mtund!adam,attmail!adamreed
------------------------------
Date: 24 Jan 87 15:34:27 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: More on Minsky on Mind(s)
mwm@cuuxb.UUCP (Marc W. Mengel) of AT&T-IS, Software Support, Lisle IL
writes:
> It seems to me that the human conciousness is actually more
> of a C-n; C-1 being "capable of experiencing sensation",
> C-2 being "capable of reasoning about being C-1", and C-n
> being "capable of reasoning about C-1..C-(n-1)" for some
> arbitrarily large n... Or was that really the intent of
> the Minsky C-2?
It's precisely this sort of overhasty overinterpretation that my critique
of the excerpts from Minsky's forthcoming book was meant to counteract. You
can't help yourself to higher-order C's until you've handled 1st-order C
-- unless you're satisfied with hanging them on a hermeneutic sky-hook.
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: Sun 25 Jan 87 22:08:34-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Reply-to: AIList-Request@SRI-AI.ARPA
Subject: Quantitative Consciousness
Stevan Harnad:
Everyone knows that there's no
AT&T to stick a pin into, and to correspondingly feel pain. You can do
that to the CEO, but we already know (modulo the TTT) that he's
conscious. You can speak figuratively, and even functionally, of a
corporation as if it were conscious, but that still doesn't make it so.
[...] Do you believe [...] corporations feel pain, as we do?
They sure act like it when someone puts arsenic in their capsules.
I'm inclined to grant a limited amount of consciousness to corporations
and even to ant colonies. To do so, though, requires rethinking the
nature of pain and pleasure (to something related to homeostatis).
I don't know of any purely mechanical systems that approach consciousness,
but computer operating systems and adaptive communications networks are
close. The issue is partly one of complexity, partly of structure,
partly of function. I am assuming that neurons and other "simple"
systems are C-1 but not C-2 -- and C-2 is the kind of consciousness
that people are really interested in. C-2 consciousness seems to
require that at least one subsystem be "wired" to reason about its
own existence, although I gather that this may be denied in the
theory of situated automata. The mystery for me is why only >>one<<
subsystem in my brain seems to have that introspective property -- but
multiple personalities or split-brain subjects may be examples that
this is not a necessary condition.
There are serious problems with the quantitative view of
consciousness. No doubt my alertness, my sensory capacity and my
knowledge admit of degrees. I may feel more pain or less pain, more or
less often, under more or fewer conditions. But THAT I feel pain, or
experience anything at all, seems an all-or-none matter, and that's
what's at issue in the mind/body problem.
An airplane either can fly or it can't. (And there's no way half a
B-52 can fly, no matter how you choose your half.) Yet there are
simpler forms of flight used by other entities -- kites, frisbees,
paper airplanes, butterflies, dandelion seeds, ... My own opinion
is that insects and fish feel pain, but often do so in a generalized,
nonlocalized way that is similar to a feeling of illness in humans.
Octopi seem to be conscious, but with a psychology like that of spiders
(i.e., if hungry, conserve energy and wait for food to come along).
I assume that lower forms experience lower forms of consciousness
along with lower levels of intelligence. Such continuua seem natural
to me. If you wish to say that only humans and TTT-equivalents are
conscious, you shoud bear the burden of establishing the existence
and nature of the discontinuity.
It also seems arbitrary to be "willing" to ascribe consciousness to
neurons and not to atoms.
When someone demonstrates that atoms can learn, I'll reconsider.
(Incidentally, this raises the metaphysical question of whether God
can be conscious if He already knows everything.) You are questioning
my choice of discontinuity, but mine is easy to defend (or give up)
because I assume that the scale of consciousness tapers off into
meaninglessness. Asking whether atoms are conscious is like asking
whether aircraft bolts can fly.
The issue here is: what justifies interpreting something/someone as
conscious? The Total Turing Test has been proposed as our only criterion.
What criterion are you using with neurons?
Your TTT has been put forward as the only justifiable means of deciding
that an entity is conscious. I can't force myself to believe that,
although you have already punched holes in arguments far more cogent
than I could have raised. Still, I hope you're not insisting that
no entity can be conscious without passing the TTT. Even a rock could
be conscious without our having any justifiable means of deciding so.
And even if single cells are
conscious -- do feel pain, etc. -- what evidence is there that this is
RELEVANT to their collective function in a superordinate organism?
What evidence is there that it isn't? Evolved and engineered systems
generally support the "form follows function" dictum. Aircraft parts
have to be airworthy whether or not they can fly on their own.
Why doesn't replacing conscious nerve cells with
synthetic molecules matter? (To reply that synthetic substances with the
same functional properties must be conscious under these conditions is
to beg the question.)
I beg your pardon? Or rather, I beg to beg your question. I presume
that a synthetic replica of myself, or any number of such replicas,
would continue my consciousness.
If I sound like I'm calling an awful lot of gambits "question-begging,"
it's because the mind/body problem is devilishly subtle, and the
temptation to capitulate by slipping consciousness back into one's
premises is always there.
Perhaps professional philosophers are able to strive for a totally
consistent world view. We armchair amateurs have to settle for
tackling one problem at a time. A standard approach is to open
back doors and try to push the problem through; if no one push back,
the problem is [temporarily] solved. (Another approach is to duck
out the back way ourselves, leaving the problem unsolved: Why is
there Being instead of Nothingness? Who cares?) I'm glad you've
been guarding the back doors and I appreciate your valiant efforts
to clarify the issues. I have to live with my gut feelings, though,
and they remain unconvinced that the TTT is of any use. If I had to
build an aircraft, I would not begin by refuting theological arguments
about Man being given dominion over the Earth rather than the Heavens.
I would start from a premise that flight was possible and would
try to derive enabling conditions. Perhaps the attempt would be
futile. Perhaps I would invent only the automobile and the rocket,
and fail to combine them into an aircraft. But I would still try.
-- Ken Laws
------------------------------
End of AIList Digest
********************
∂28-Jan-87 0247 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #18
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 28 Jan 87 02:47:26 PST
Date: Tue 27 Jan 1987 22:05-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #18
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 28 Jan 1987 Volume 5 : Issue 18
Today's Topics:
Code - AI Expert Magazine Sources (Part 1 of 22)
----------------------------------------------------------------------
Date: 19 Jan 87 03:36:40 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: AI Expert Magazine Sources (Part 1 of 22)
here it is and rather lengthly, cat all nine parts together and shar
it, don't forget to remove my .signature at the end of the file.
[I had to reformat this. The file lengths may have been
altered, and I stripped out initial tabs. -- KIL]
#! /bin/sh
# This is a shell archive, meaning:
# 1. Remove everything above the #! /bin/sh line.
# 2. Save the resulting text in a file.
# 3. Execute the file with /bin/sh (not csh) to create:
# AIAPP.JAN
# CONTNT.JAN
# EXPERT.JAN
# FILES.JAN
# OPSNET.JAN
# PERCEP.JAN
# This archive created: Sun Jan 18 19:24:39 1987
# By: D'arc Angel (The Houses of the Holy)
export PATH; PATH=/bin:/usr/bin:$PATH
echo shar: "extracting 'AIAPP.JAN'" '(29884 characters)'
if test -f 'AIAPP.JAN'
then
echo shar: "will not over-write existing file 'AIAPP.JAN'"
else
sed 's/↑X//' << \SHAR_EOF > 'AIAPP.JAN'
X
X
X AI Apprentice
X by Bill Thompson and Bev Thompson
X "Creating Expert Systems from Examples"
X January 1987 AI EXPERT
X
X
X
XFigure 1.
X
X batch# part# power symptom Problem
X
X b 312 ac no power powersupply
X a 312 ac weak gear bad
X c 412 dc sparking powersupply
X d 412 ac no power wiring
X c 212 dc sparking powersupply
X c 412 ac weak wiring
X a 212 ac no power gear bad
X b 412 dc weak wiring
X b 212 ac weak gear bad
X
X
X
XFigure 2 - A decision tree produced from the data in Table 1.
X
X
X batch# part# power symptom Result
X
X b 412 ac weak gear bad
X a 212 dc weak powersupply
X d 212 dc sparking wiring
X d 412 ac no power powersupply
X
X
X
XTable 1 - A training set of data for a repair problem.
X
X If batch# is a
X then result is gear bad.
X
X If batch# is b
X and part# is 212
X then result is gear bad.
X
X If batch# is b
X and part# is 312
X then result is powersupply.
X
X If batch# is b
X and part# is 412
X then result is wiring.
X
X If batch# is c
and power is ac
X then result is wiring.
X
X If batch# is c
X and power is dc
X then result is powersupply.
X
X If batch# is d
X then result is wiring.
X
X
X batch# ?
X a: ---------------------------------------------gear bad
X b:part# ?
X 212: ---------------------------------------- gear bad
X 312: ---------------------------------------- powersupply
X 412: ---------------------------------------- wiring
X c:power??
X ac: ----------------------------------------- wiring
X dc: ----------------------------------------- powersupply
X d: --------------------------------------------- wiring
X
X
X
XTable 2 - A new set of data collected for the repair problem. This data
X is used for validation of the solution.
X
X
Xclinical descript distribution group Result
X
Xfever upper resp. epidemic respiratory parainfluenza
Xchills lower resp. local enteric adenovirus
Xrash mid resp. children exanthems mumps
Xswelling hospital latent rhinovirus
Xmalaise youngadults echo
Xheadache universal coxasackie
Xcough varicella
X
X
X rubella
X
XTable 3 - Definitions of results and attributes for identifying viruses.
X
Xlevel type of subject programming cover type basic Author
X software matter covered language
Xintro/adv gen/spec gen/spec no/yes soft/hard no/yes
X1. 1. 4. 3. soft 5. Jones
X2. 5. 5. 4. soft 1. Smith
X1. 1. 1. 3. soft 1. Fisher
X1. 1. 1. 3. hard 5. Mitchell
X1. 1. 1. 1. soft 1. Argyle
X5. 1. 5. 5. hard 1. Chang
X
X
X
Table 4 - An example set for selecting a textbook. This set was produced
X using the Flexigrid program.
X
Xsubject matter ? (gen/spec)
X < 2.50: programming covered ? (no/yes)
X < 2.00: ---------------------------------- Concepts
X >=2.00: cover ?
X hard: -------------------------- Today's
X soft: -------------------------- Information
X >=2.50: level ? (intro/adv)
X < 1.50: -------------------------------- Society
X >=1.50: level ? (intro/adv)
X < 3.50: ------------------------ Applications
X >=3.50: ------------------------ Data_structures
X
X
Xupply of serotinous cones
X.
X
Xprompt 10/acre adequate
XAre 10 trees per acre adequate to seed the area ?
X.
X
Xtrans 10/acre adequate
X10 per acre is /not/ adequate
X.
X
Xprompt burning planned
XHas a prescribed burning been planned ?
X.
X
Xtrans burning planned
Xburning is /not/ planned
X.
X
Xtrans use seed tree
XYou should /not/ use seed trees to seed the area
X.
X
15
Xif branch 11 is yes
Xand pine desired is yes
Xand pine suited is yes
Xand desirable seed is yes
Xand serotinous cones is yes
Xand 10/acre adequate is yes
Xand burning planned is no
Xthen silviculture method is clearcut
Xand branch 17 is yes .
X
Xtrans silvaculture method
Xthe best silviculture method to use
X.
X
X16
Xif branch 11 is yes
Xand pine desired is yes
Xand pine suited is yes
Xand desirable seed is yes
Xand serotinous cones is yes
Xand 10/acre adequate is no
Xthen silviculture method is clearcut
Xand branch 17 is yes .
X
X17
Xif branch 11 is yes
Xand pine desired is yes
Xand pine suited is yes
Xand desirable seed is yes
Xand serotinous cones is no
Xand two harvests wanted is yes
Xand two harvests possible is yes
Xthen silviculture method is shelterwood
Xand branch 17 is yes .
X
Xprompt two harvests wanted
XDo you want to do two commercial harvests on this area ?
X.
X
Xtrans two harvests wanted
Xtwo commercial harvests are /not/ wanted
X.
X
Xprompt two harvests possible
XIs it possible to get two harvests from this area ?
X.
X
Xtrans two harvests possible
Xtwo harvests can /not/ be done on this area
X.
X
X18
Xif branch 11 is yes
Xand pine desired is yes
Xand pine suited is yes
Xand desirable seed is yes
Xand serotinous cones is no
Xand two harvests wanted is yes
Xand two harvests possible is no
then silviculture method is clearcut
Xand branch 17 is yes .
X
X19
Xif branch 11 is yes
Xand pine desired is yes
Xand pine suited is yes
Xand desirable seed is yes
Xand serotinous cones is no
Xand two harvests wanted is no
Xthen silviculture method is clearcut
Xand branch 17 is yes .
X
X20
Xif branch 11 is yes
Xand pine desired is yes
Xand pine suited is yes
Xand desirable seed is no
Xthen silviculture method is clearcut
Xand branch 17 is yes .
X
X21
Xif branch 11 is yes
Xand pine desired is yes
Xand pine suited is no
Xthen convert is yes
Xand recommend is convert .
X
Xtrans convert
Xyou should /not/ convert the area to some more desirable kind of tree
X.
X
X22
Xif branch 11 is yes
Xand pine desired is no
Xthen convert is yes
Xand recommend is convert .
X
X
X26
Xif branch 17 is yes
Xand adequate seedbed is yes
Xthen branch 18 is yes .
X
Xprompt adequate seedbed
XIs there an adequate seedbed for planting ?
X.
X
Xtrans adequate seedbed
Xthere is /not/ an adequate seedbed for planting
X.
X
X27
Xif branch 17 is yes
Xand adequate seedbed is no
Xthen prepare site is yes
Xand branch 18 is yes .
X
trans prepare site
Xthe site should /not/ be prepared before planting
X.
X
X28
Xif branch 18 is yes
Xand silviculture method is shelterwood
Xthen use natural seeding is yes
Xand recommend is use natural seeding .
X
Xtrans use natural seeding
Xnatural seeding techniques should /not/ be used
X.
X
X29
Xif branch 18 is yes
Xand silviculture method is clearcut
Xand improved stock is yes
Xthen plant is yes
Xand recommend is plant .
X
Xprompt improved stock
XIs there improved planting stock available ?
X.
X
Xtrans improved stock
Xthere is /not/ improved stock available
X.
X
Xtrans plant
Xsince there is better stock available you can /not/ plant using that stock
X.
X
X30
Xif branch 18 is yes
Xand silviculture method is clearcut
Xand improved stock is no
Xand good cone supply is yes
Xthen scatter cones is yes
Xand recommend is scatter cones .
X
Xprompt good cone supply
XIs there a good supply of serotinous cones on the area ?
X.
X
Xtrans good cone supply
Xthere is /not/ a good cone supply
X.
X
Xtrans scatter cones
Xyou should /not/ scatter the supply of serotinous cones over the area
X.
X
X31
Xif branch 18 is yes
Xand silviculture method is clearcut
Xand improved stock is no
Xand good cone supply is no
Xthen direct seed is yes
Xand recommend is direct seed .
X
Xtrans direct seed
XSince the cone supply is inadequate, you should /not/ directly seed the
area
X.
X
X
X-------------------------------------------------------------------------
X
XThe following comments are not a part of the knowledge base. If you
Xtry to run the knowledge base this part of the file should be removed
X
X
XAbbreviated KEY
X
X1. stocking good is yes ............................. 2
X1. stocking good is no ............................. 10
X 2. avg < 5 is yes ................................ 3
X 2. avg < 5 is no ................................. 4
X3. 2000 + per acre is yes ..........WEED OR CLEAN.... 8
X3. 2000 + per acre is no ............................ 8
X 4. age is mature ................................. 11
X 4. age is immature ............................... 5
X5. site index > 60 is yes ........................... 6
X5. site index > 60 is no ............................ 9
X 6. product size is large ......................... 7
X 6. product size is small ......................... 9
X7. 120 + basal area is yes .........THIN............. 9
X7. 120 + basal area is no ........................... 9
X 8. severe competition is yes ....RELEASE.......... 9
X 8. severe competition is no ...................... 9
X9. high risk is yes ................................. CONTROL IF FEASIBLE
X9. high risk is no .................................. WAIT
X 10. other resources is yes ....................... MAINTAIN
X 10. other resources is no ........................ 11
X11. pine suitable is yes ............................. 12
X11. pine suitable is no .............................. CONVERT
X 12. desirable seed is yes ........................ 13
X 12. desirable seed is no ........USE CLEARCUT..... 17
X13. serotinous cones is yes .......................... 14
X13. serotinous cones is no ........................... 16
X 14. 10/acre adequate is yes ...................... 15
X 14. 10/acre adequate is no ......USE CLEARCUT..... 17
X15. burning planned is yes ........................... USE SEED TREE
X15. burning planned is no ...........USE CLEARCUT..... 17
X 16. two harvests wanted is yes ..USE SHELTERWOOD.. 17
X 16. two harvests wanted is no ...USE CLEARCUT..... 17
X17. adequate seedbeds is yes ......................... 18
X17. adequate seedbeds is no .........PREPARE SITE..... 18
X 18. silviculture method is shelterwood ........... USE NATURAL SEEDING
X 18. silviculture method is clearcut .............. 19
X19. improved stock is yes ............................ PLANT
X19. improved stock is no ............................. 20
X 20. good cone supply is yes ...................... SCATTER CONES
X 20. good cone supply is no ....................... DIRECT SEED
X
X
X
XThe purpose of this exercise is to show how a knowledge base can be
designed to directly follow a key. There are several places where the
XKB could have been made more efficient, but this would have meant
Xdeparting from the order of the key. You might find it an interesting
Xexercise to explore other ways this same information could have been
Xrepresented in the KB.
X
XThe key appears in the Managers Handbood for Jack Pine in the North Central
XStates. The Handbook was produced by the North Central Forest Experiment
XStation of the Forest Service of the U.S. Dept. of Agriculture. Our
Xintention in writing this knowledge base is to show the structure of a
Xknowledge base written for a backward chaining inference engine directly
Xfrom an existing document. If this KB were to be actually used, it would
Xneed to have clearer questions and more explanations to the user. These
Xexplanations are provided in the handbook and could be easily incorporated
Xinto the knowledge base.
X
XThe knowledge base will run on the expert system shell MicroExpert which is
Xan example of a backward chaining inference engine. MicroExpert is
Xavailable from McGraw-Hill for $49.95 and can be ordered by calling 1-800-
X628-0004 or, in NY, 212-512-2999 . The knowledge base is described in the
Xcolumn AI Apprentice which appears in the November issue of AI Expert
Xmagazine. The design details of the inference engine which runs the KB is
Xdescribed in the article "Inside an Expert System" in the April 1985
Xisuue of BYTE magazine.
X
XMicroExpert, AI Apprentice and "Inside an Expert System" are all written
Xby Bev and Bill Thompson . We're always happy to hear about your thoughts
Xand comments, good or bad on any of our work. Contact us at the address
Xbelow, on Compuserve or BIX. Our Compuserve id is 76703,4324 and we can be
Xreached by Easyplex or in the AI Expert Forum. Our BIX id is bbt and we
Xmay be contacted via BIXmail or by leaving comments in the MicroExpert
Xconference.
X
XBill and Bev Thompson
XR.D. 2 Box 430
XNassau, N.Y. 12123
X
X
X TREES.PRO
X PROLOG program
X
X
X/* This PDPROLOG program implements a knowledge base based upon the
X following key:
X
X To run the program type "go."
X Caution - This program can be very S L O W.
X
XAbbreviated KEY
X
X1. stocking good is yes ............................. 2
X1. stocking good is no ............................. 10
X 2. avg < 5 is yes ................................ 3
X 2. avg < 5 is no ................................. 4
X3. 2000 + per acre is yes ..........WEED OR CLEAN.... 8
3. 2000 + per acre is no ............................ 8
X 4. age is mature ................................. 11
X 4. age is immature ............................... 5
X5. site index > 60 is yes ........................... 6
X5. site index > 60 is no ............................ 9
X 6. product size is large ......................... 7
X 6. product size is small ......................... 9
X7. 120 + basal area is yes .........THIN............. 9
X7. 120 + basal area is no ........................... 9
X 8. severe competition is yes ....RELEASE.......... 9
X 8. severe competition is no ...................... 9
X9. high risk is yes ................................. CONTROL IF FEASIBLE
X9. high risk is no .................................. WAIT
X 10. other resources is yes ....................... MAINTAIN
X 10. other resources is no ........................ 11
X11. pine suitable is yes ............................. 12
X11. pine suitable is no .............................. CONVERT
X 12. desirable seed is yes ........................ 13
X 12. desirable seed is no ........USE CLEARCUT..... 17
X13. serotinous cones is yes .......................... 14
X13. serotinous cones is no ........................... 16
X 14. 10/acre adequate is yes ...................... 15
X 14. 10/acre adequate is no ......USE CLEARCUT..... 17
X15. burning planned is yes ........................... USE SEED TREE
X15. burning planned is no ...........USE CLEARCUT..... 17
X 16. two harvests wanted is yes ..USE SHELTERWOOD.. 17
X 16. two harvests wanted is no ...USE CLEARCUT..... 17
X17. adequate seedbeds is yes ......................... 18
X17. adequate seedbeds is no .........PREPARE SITE..... 18
X 18. silviculture method is shelterwood ........... USE NATURAL SEEDING
X 18. silviculture method is clearcut .............. 19
X19. improved stock is yes ............................ PLANT
X19. improved stock is no ............................. 20
X 20. good cone supply is yes ...................... SCATTER CONES
X 20. good cone supply is no ....................... DIRECT SEED
X
X
X
XThe purpose of this exercise is to show how an expert system can be
Xdesigned to directly follow a key. There are several places where the
Xprogram could have been made more efficient, but this would have meant
Xdeparting from the order of the key. You might find it an interesting
Xexercise to explore other ways this same information could have been
Xrepresented in the program.
X
XThe key appears in the Managers Handbood for Jack Pine in the North Central
XStates. The Handbook was produced by the North Central Forest Experiment
XStation of the Forest Service of the U.S. Dept. of Agriculture. Our
Xintention in writing this knowledge base is to show the structure of a
Xknowledge base written for a backward chaining inference engine directly
Xfrom an existing document. If this KB were to be actually used, it would
Xneed to have clearer questions and more explanations to the user. These
Xexplanations are provided in the handbook and could be easily incorporated
Xinto the knowledge base.
X
This program is similar to the KB for the expert system shell
XMicroExpert which is an example of a backward chaining inference engine.
XMicroExpert is available from McGraw-Hill for $49.95 and can be ordered
Xby calling 1-800-628-0004 or, in NY, 212-512-2999 .
XThe knowledge base is described in the AI Apprentice column which appears
Xin the November issue of AI Expert magazine.
XThe design details of the inference engine which runs the KB is
Xdescribed in the article "Inside an Expert System" in the April 1985
Xisuue of BYTE magazine.
X
XMicroExpert, AI Apprentice and "Inside an Expert System" are all written
Xby Bev and Bill Thompson . We're always happy to hear about your thoughts
Xand comments, good or bad on any of our work. Contact us at the address
Xbelow, on Compuserve or BIX. Our Compuserve id is 76703,4324 and we can be
Xreached by Easyplex or in the AI Expert Forum. Our BIX id is bbt and we
Xmay be contacted via BIXmail or by leaving comments in the MicroExpert
Xconference.
X
XBill and Bev Thompson
XR.D. 2 Box 430
XNassau, N.Y. 12123 */
X
X/* Control - In MicroExpert terms, the goal of the consultation is
X recommendation */
X
Xgo :- clear_kb,
X give_advice.
Xgive_advice :- recommendation(X),
X fail.
Xgive_advice :- print_advice.
------------------------------
End of AIList Digest
********************
∂28-Jan-87 0704 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #19
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 28 Jan 87 07:03:49 PST
Date: Tue 27 Jan 1987 22:28-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #19
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 28 Jan 1987 Volume 5 : Issue 19
Today's Topics:
AI Expert Magazine Sources (Part 2 of 22)
----------------------------------------------------------------------
Date: 19 Jan 87 03:36:40 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: AI Expert Magazine Sources (Part 2 of 22)
X
X/* The rules -
X These are implemented this way to mimic the MicroExpert rule set.
X Looking at them side by side should show the similarities. */
X
Xfact(branch8,yes) :- fact('stocking good',yes),
X fact('avg < 5',yes),
X fact('2000+ per acre',yes),
X recommend('The stand of jack pine must be weeded and cleaned.').
Xfact(branch8,yes) :- fact('stocking good',yes),
X fact('avg < 5',yes),
X fact('2000+ per acre',no).
Xfact(branch9,no) :- fact('stocking good',yes),
X fact('avg < 5',no),
X fact(age,mature),
X assertz(fact(branch11,yes)).
Xfact(branch11,yes) :- fact('stocking good',yes),
X fact('avg < 5',no),
X fact(age,mature),
X assertz(fact(branch9,no)).
Xfact(branch9,yes) :- fact('stocking good',yes),
X fact('avg < 5',no),
X fact(age,immature),
X fact('site index > 60',yes),
X fact('product size',large),
fact('120+ basal area',yes),
X recommend('It is important to thin the area').
Xfact(branch9,yes) :- fact('stocking good',yes),
X fact('avg < 5',no),
X fact(age,immature),
X fact('site index > 60',yes),
X fact('product size',large),
X fact('120+ basal area',no).
Xfact(branch9,yes) :- fact('stocking good',yes),
X fact('avg < 5',no),
X fact(age,immature),
X fact('site index > 60',yes),
X fact('product size',large).
Xfact(branch9,yes) :- fact('stocking good',yes),
X fact('avg < 5',no),
X fact(age,immature),
X fact('site index > 60',yes).
Xrecommendation(maintain) :-
X fact('stocking good',no),
X fact('other resources',yes),
X recommend('You should maintain the stand in its present condition').
Xfact(branch11,yes) :- fact('stocking good',no),
X fact('other resources',no).
Xfact(branch9,yes) :- fact(branch8,yes),
X fact('severe competition',yes),
X recommend('Competing trees should be eliminated.').
Xfact(branch9,yes) :- fact(branch8,yes),
X fact('severe competition',no).
Xrecommendation(control) :-
X fact(branch9,yes),
X fact('high risk',yes),
X recommend('The current area should be controlled, if at all feasible.').
Xrecommendation(wait) :-
X fact(branch9,yes),
X fact('high risk',no),
X recommend('You should wait before doing anything else to this stand.').
Xrecommendation('use seed tree') :-
X fact(branch11,yes),
X fact('pine desired',yes),
X fact('pine suited',yes),
X fact('desirable seed',yes),
X fact('serotinous cones',yes),
X fact('10/acres adequate',yes),
X fact('burning planned',yes),
X recommend('You should use seed trees to seed the area.').
Xfact(branch17,yes) :-
X fact(branch11,yes),
X fact('pine desired',yes),
X fact('pine suited',yes),
X fact('desirable seed',yes),
X fact('serotinous cones',yes),
X fact('10/acres adequate',yes),
X fact('burning planned',no),
X add_fact(silvaculture,clearcut),
X recommend('The best silvaculture method to use is clearcut.').
fact(branch17,yes) :-
X fact(branch11,yes),
X fact('pine desired',yes),
X fact('pine suited',yes),
X fact('desirable seed',yes),
X fact('serotinous cones',yes),
X fact('10/acres adequate',no),
X add_fact(silvaculture,clearcut),
X recommend('The best silvaculture method to use is clearcut.').
Xfact(branch17,yes) :-
X fact(branch11,yes),
X fact('pine desired',yes),
X fact('pine suited',yes),
X fact('desirable seed',yes),
X fact('serotinous cones',no),
X fact('two harvests wanted',yes),
X fact('two harvests possible',yes),
X add_fact(silvaculture,shelterwood),
X recommend('The best silvaculture method to use is the shlterwood method.').
Xfact(branch17,yes) :-
X fact(branch11,yes),
X fact('pine desired',yes),
X fact('pine suited',yes),
X fact('desirable seed',yes),
X fact('serotinous cones',no),
X fact('two harvests wanted',yes),
X fact('two harvests possible',no),
X add_fact(silvaculture,clearcut),
X recommend('The best silvaculture method to use is clearcut.').
Xfact(branch17,yes) :-
X fact(branch11,yes),
X fact('pine desired',yes),
X fact('pine suited',yes),
X fact('desirable seed',yes),
X fact('serotinous cones',no),
X fact('two harvests wanted',no),
X add_fact(silvaculture,clearcut),
X recommend('The best silvaculture method to use is clearcut.').
Xfact(branch17,yes) :-
X fact(branch11,yes),
X fact('pine desired',yes),
X fact('pine suited',yes),
X fact('desirable seed',no),
X add_fact(silvaculture,clearcut),
X recommend('The best silvaculture method to use is clearcut.').
Xrecommendation(convert) :-
X fact(branch11,yes),
X fact('pine desired',yes),
X fact('pine suited',no),
X recommend(
X 'You should convert the area to some more desirable kind of tree.').
Xrecommendation(convert) :-
X fact(branch11,yes),
X fact('pine desired',no),
X recommend(
X 'You should convert the area to some more desirable kind of tree.').
Xfact(branch18,yes) :-
fact(branch17,yes),
X fact('adequate seedbed',yes).
Xfact(branch18,yes) :-
X fact(branch17,yes),
X fact('adequate seedbed',no),
X recommend('The site should be prepared before planting.').
Xrecommendation('natural seeding') :-
X fact(branch18,yes),
X fact(silvaculture,shelterwood),
X recommend('The natural seeding technique should be used.').
Xrecommendation(plant) :-
X fact(branch18,yes),
X fact(silvaculture,clearcut),
X fact('improved stock',yes),
X recommend(
X 'Since there is better stock available, you can plant using that stock.').
Xrecommendation('scatter cones') :-
X fact(branch18,yes),
X fact(silvaculture,clearcut),
X fact('improved stock',no),
X fact('good cone supply',yes),
X recommend('You should scatter the serotinous cones over the area.').
Xrecommendation('direct seed') :-
X fact(branch18,yes),
X fact(silvaculture,clearcut),
X fact('improved stock',no),
X fact('good cone supply',no),
X recommend('You should directly seed the area.').
X
X/* These routines add new facts to the internal knowledge base - kb */
X
Xfact(X,Y) :- kb(X,Y),! .
Xfact(X,Y) :- not(kb(X,Anything)),
X question(X,Answer),
X assertz(kb(X,Answer)),
X Y = Answer.
X
Xadd_fact(X,Y) :- kb(X,Y),!.
Xadd_fact(X,Y) :- assertz(kb(X,Y)).
X
Xrecommend(X) :- add_fact(advice,X).
X/* Questions to ask the user */
X
Xquestion('stocking good',Ans) :-
X print('Is the stocking of the jack pine stand currently'),nl,
X print('at least minimum ? '),nl,nl,
X print('If you are unsure of how to determine stocking,'),nl,
X print('see page 4 in the Managers Handbook for Jack Pine'),
X nl,
X ask('',Ans,[ yes , no ]).
Xquestion('avg < 5',Ans) :-
X ask('Is the average diameter of the trees less than 5 inches ?',
X Ans,[yes,no]).
Xquestion('2000+ per acre',Ans) :-
X ask('Are there 2000 or more trees per acre ?',Ans,[yes,no]).
question(age,Ans) :-
X ask('Is the age of the stand mature or immature ?',
X Ans,[mature,immature]).
Xquestion('site index > 60',Ans) :-
X ask('Is the site index greater than 60 ?',Ans,[yes,no]).
Xquestion('product size',Ans) :-
X ask('Do you want to manage the timber for large or small products ?',
X Ans,[large,small]).
Xquestion('120+ basal area',Ans) :-
X ask('Is the basal area per acre at least 120 square feet ?',
X Ans,[yes,no]).
Xquestion('other resources',Ans) :-
X ask('Do you want to maintain this condition to support other resources?',
X Ans,[yes,no]).
Xquestion('severe competition',Ans) :-
X ask('Is there severe overstory competition ?',Ans,[yes,no]).
Xquestion('high risk',Ans) :-
X ask('Is there a high risk of loss or injury ?',Ans,[yes,no]).
Xquestion('pine desired',Ans) :-
X ask('Do you want to keep jack pine in this area ?',Ans,[yes,no]).
Xquestion('pine suited',Ans) :-
X ask('Is jack pine well suited to this site ?',Ans,[yes,no]).
Xquestion('desirable seed',Ans) :-
X ask('Is there a desirable jack pine seed source on the area ?',
X Ans,[yes,no]).
Xquestion('serotinous cones',Ans) :-
X ask('Do the trees on the site have serotinous cones ?',Ans,[yes,no]).
Xquestion('10/acres adequate',Ans) :-
X ask('Are 10 trees per acre adequate to seed the area ?',Ans,[yes,no]).
Xquestion('burning planned',Ans) :-
X ask('Has a prescribed burning been planned ?',Ans,[yes,no]).
Xquestion('two harvests wanted',Ans) :-
X ask('Do you want two commercial harvests on this area ?',Ans,[yes,no]).
Xquestion('two harvests possible',Ans) :-
X ask('Is it possible to get two harvests from this area ?',Ans,[yes,no]).
Xquestion('adequate seedbed',Ans) :-
X ask('Is there an adequate seedbed for planting ?',Ans,[yes,no]).
Xquestion('improved stock',Ans) :-
X ask('Is there an improved planting stock available ?',Ans,[yes,no]).
Xquestion('good cone supply',Ans) :-
X ask('Is there a good supply of serotinous cones in the area ?',
X Ans,[yes,no]).
X
X/* Utility Routines - to be useful, we should add some routines to allow
X the user to ask "How" and "Why" */
X
Xdisplay_kb :- kb(X,Y),
X print(X,' is ',Y),
X nl,
X fail.
Xdisplay_kb.
X
X
Xprint_advice :-
X nl,nl,
print('Based upon your responses, the following is recommended :'),nl,nl,
X show_advice.
Xshow_advice :-
X kb(advice,X),
X print(X),
X nl,
X fail.
Xshow_advice :-
X nl,print('To see the complete set of derived facts,'),
X print('type "display_kb."').
X
X
Xclear_kb :- retract(kb(_,_)),
X fail .
Xclear_kb.
X
Xmember(X,[X|_]).
Xmember(X,[_|Y]) :- member(X,Y).
X
Xask(Ques,Ans,LegalResponses) :-
X nl,print(Ques,' '),
X read(Ans),
X member(Ans,LegalResponses),!.
Xask(Ques,Ans,LegalResponses) :-
X nl,nl,nl,
X print('Please respond with : ',LegalResponses),nl,nl,
X ask(Ques,Ans,LegalResponses).
X
X
X
X
X
X
X
X Listings and Figures
X printed in AI EXPERT magazine
X
X
X1. Jack pine stand with minimum or higher stocking .................. 2
X1. Jack pine stand with less than minimum stocking .................. 10
X
X 2. Average tree diameter less than 5 inches ..................... 3
X 2. Average tree diameter 5 inches or more ....................... 4
X
X3. 2,000 or more trees per acre ..................WEED OR CLEAN ..... 8
X3. Less than 2,000 trees per acre ................................... 8
X
X 4. Stand is mature .............................................. 11
X 4. Stand is not mature .......................................... 5
X
XFigure 1 - Key for forest management taken from USDA Forest Service
X Handbook
X
X
X
X |-- yes ===> weed or clean
X | and do # 8
X |-- yes --- 2000+ per acre-|
X | |-- no ===> do # 8
X |-- yes -- diameter-|
X | < 5 in. | |-- mature ===> do # 11
Xminimum | |-- no -- age-|
Xstocking-| |-- young ===> do # 5
X |
X |
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then
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X
X Contents -- AI EXPERT
X January 1987
X
X
XARTICLES
X--------
X
XPlanning with TWEAK
Xby Jonathan Amsterdam
X
XLike all exploratory work in the sciences, AI research proceeds
Xin cycles of 'scruffy' exploration and 'neat' consolidation.
XAfter years of exploration into different planning algorithm
Xdesign strategies, M.I.T.'s David Chapman may have created a new
Xera in planning research with his neat summary of more than a
Xdecade of scruffy work on an algorithm called TWEAK.
X
X
XRete Match Algorithm
Xby Charles L. Forgy and Susan Shepard
X
XThe Rete Match algorithm is a fast method for comparing a set of
Xpatterns to a set of objects to determine all possible matches.
XIt may be the most efficient algorithm for performing the match
Xoperation on single processor. Developed by Charles L. Forgy in
X1974, it has been implemented in several languages in both
Xresearch and commercial grade systems.
X
X
XImperative Pattern Matching in OPS5
Xby Dan Neiman
X
XSurely the Rete Match algorithm is an efficient data structure
Xfor implementing production systems. But what else can it be
Xused for? Let's look at the OPS5 language as a case study of
Xthe Rete net as an experimental tool kit. Then we'll present a
Xtechnique that will show the programmer how to use Rete Match as
Xa general purpose pattern matching tool.
X
X
XPerceptrons and Neural Nets
Xby Peter Reece
X
XThere are at least ten billion neurons handling over one million
Xinput messages per second in the human brain. With many of the
Xearlier hardware and software obstacles now overcome, let's look
Xback to one of the most successful pattern classification
Xcomputers---the Perceptron---and show how you can implement a
Xsimple Perceptron on your home computer.
X
X
XDEPARTMENTS
X-----------
X
XBrain Waves
X"AI for Competitive Advantage"
Xby Eugene Wang, Gold Hill Computers
X
XAI INSIDER
X
XEXPERT'S TOOLBOX
X"Using Smalltalk to Implement Frames"
Xby Marc Rettig
X
XAI APPRENTICE
X"Creating Expert Systems from Examples"
Xby Beverly and Bill Thompson
X
XIN PRACTICE
X"Air Traffic Control: A Challenge for AI"
Xby Nicholas Findler
X
XHARDWARE REVIEW
X"A LISP Machine Profile: Symbolics 3650"
Xby Douglas Schuler, et. al.
X
XSOFTWARE REVIEW
X"Expertelligence's PROLOG for the Mac:
XExperPROLOG II"
X
X
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SHAR_EOF
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fi
fi
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if test -f 'EXPERT.JAN'
then
echo shar: "will not over-write existing file 'EXPERT.JAN'"
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sed 's/↑X//' << \SHAR_EOF > 'EXPERT.JAN'
X
X Expert's Toolbox
X January 1987
X "Using Smalltalk to Implement Frames"
X by Marc Rettig
X
X
X
XListing 1
X
XDEFINITION OF CLASS SLOT
X
XDictionary variableSubclass: #Slot
X instanceVariableNames: ''
X classVariableNames: ''
X poolDictionaries: ''
X
XMETHODS FOR CLASS SLOT
X
XsetFacet:facetName with:aValue
X self at:facetName put:aValue
X ↑aValue
X
XgetFacet: facetName
X ↑self at:facetName ifAbsent:[nil]
X
XsetValue:aValue
X self setFacet:'value' with:aValue
X
XgetValue
X ↑self getFacet:'value'
X
X_________________________________________
XDEFINITION OF CLASS FRAME
X
XDictionary variableSubclass: #Frame
X instanceVariableNames: ''
X classVariableNames: ''
X poolDictionaries: ''
X
XMETHODS FOR CLASS FRAME
X
XsetSlot:slotName facet:facetName contents:aValue
X | tempSlot |
X tempSlot := self at:slotName
X ifAbsent:[self at:slotName put: Slot new].
X tempSlot setFacet:facetName with:aValue.
X ↑aValue
X
XgetSlot:slotName facet:facetName
X ↑(self includesKey:slotName)
X ifTrue: [(self at:slotName) getFacet:facetName]
X ifFalse:[nil]
X
XsetSlot:slotName value:aValue
X ↑self setSlot:slotName facet:'value' contents:aValue
XgetSlotValue:slotName
X "Get the value facet of a slot. If no such slot, look up the AKO
X inheritance chain. It that's no good, run a demon to get the value."
X | temp |
X ((temp := self getSlot:slotName) isNil)
X ifTrue: [((temp := self lookUpAkoChain:slotName) isNil)
X ifTrue: [↑self runDemonForValue:slotName]
X ifFalse:[↑temp getValue]]
X ifFalse:[(temp includesKey:'value')
X ifTrue: [↑temp getValue]]
X ifFalse:[↑self runDemonForValue:slotName]]
X
XgetSlot:slotName
X ↑self at:slotName ifAbsent:[nil]
X
XsetSlot:slotName with:aSlot
X ↑self at:slotName put:aSlot
X
XlookUpAkoChain:slotName
X "Look up the inheritance chain for a slot with the name in slotName.
X If you find it, return the Slot."
X ↑(self includesKey:'AKO')
X ifTrue: [((self isAKO) includesKey:slotName)
X ifTrue: [↑(self isAKO) getSlot:slotName]
X ifFalse:[↑(self isAKO) lookUpAkoChain:slotName]]
X ifFalse:[nil]
X
XisAKO
X ↑self getSlot:'AKO' facet:'value'
X
XisAKO:aFrame
X self setSlot:'AKO' value:aFrame
X
X____________________________________
XSOME SAMPLE METHODS FOR DEMONS
X
XaddDemon:aBlock slot:slotName type:demonType
X (#('ifNeeded' 'ifAdded' 'ifRemoved') includes:demonType)
X ifTrue: [self setSlot:slotName facet:demonType with:aBlock]
X ifFalse:[self error:'Invalid Demon Type']
X
XrunDemonForValue:slotName
X | aBlock |
X aBlock := self getSlot:slotName facet:'ifNeeded'.
X (aBlock isNil)
X ifTrue: [↑nil]
X ifFalse:[↑self setSlot:slotName value:(aBlock value)]
X
X
X
XListing 2
X
XA SAMPLE HIERARCHY OF FRAMES, SHOWING USE OF DEMONS
X
| mammal dog firstDog askDemon |
Xmammal := Frame new.
Xmammal setSlot:'hide' value:'hairy'.
Xmammal setSlot:'blood' value:'warm'.
X
Xdog := Frame new.
Xdog isAKO:mammal.
Xdog setSlot 'numberOfLegs' value:4.
X
X" Here is a simple if-needed demon, which will ask the
X user for a value,while suggesting a default value."
XaskDemon := [Prompter prompt:'What is this doggie''s name?
X default:'Phydeaux'].
X
XfirstDog := Frame new.
XfirstDog addDemon:askDemon slot:'name' type:'ifNeeded'.
XfirstDog isAKO:dog.
XfirstDog setSlot:'color' value:'brown'.
X
X"This message would cause the demon to be fired off..."
Xfido getSlotValue:'name'
X
X
XFRAME.CLS
X
XDictionary variableSubclass: #Frame
X instanceVariableNames: ''
X classVariableNames: ''
X poolDictionaries: '' !
X
X!Frame class methods ! !
X
X
X!Frame methods !
X
XaddDemon:aBlock slot:slotName type:demonType
X (#('ifNeeded' 'ifAdded' 'ifRemoved') includes:demonType)
X ifTrue: [self setSlot:slotName facet:demonType with:aBlock]
X ifFalse:[self error:'Invalid Demon Type']!
X
XgetSlot:slotName
X "return the slot object corresponding to slotName."
X
X ↑self at: slotName ifAbsent: [nil]!
X
XgetSlot: slotName facet: facetName
X
X ↑(self includesKey: slotName)
X ifTrue: [(self at:slotName) getFacet:facetName]
X ifFalse: [nil]!
X
XgetSlotValue:slotName
X "get the value facet of a slot. If no such slot, look up AKO chain.
X If that's no good, run a demon to get the value."
X
X | temp |
X ((temp := self getSlot: slotName) isNil)
X ifTrue: [((temp := self lookUpAkoChain: slotName) isNil)
X ifTrue: [↑self runDemonForValue:slotName]
X ifFalse:[↑temp getValue]]
X ifFalse:[(temp includesKey: 'value')
X ifTrue: [↑temp getValue]
X ifFalse:[↑self runDemonForValue:slotName]]!
------------------------------
End of AIList Digest
********************
∂28-Jan-87 1156 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #20
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 28 Jan 87 11:55:15 PST
Date: Tue 27 Jan 1987 22:45-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #20
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 28 Jan 1987 Volume 5 : Issue 20
Today's Topics:
AI Expert Magazine Sources (Part 3 of 22)
----------------------------------------------------------------------
Date: 19 Jan 87 03:36:40 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: AI Expert Magazine Sources (Part 3 of 22)
X
XisAKO
X ↑self getSlot: 'AKO' facet:'value'!
X
XisAKO: aFrame
X "set the AKO slot of a frame"
X
X self setSlot:'AKO' value:aFrame!
X
XlookUpAkoChain: slotName
X "Look up the inheritance chain for a slot with the name in slotName.
X If you find it, return the Slot"
X
X ↑(self includesKey: 'AKO')
X ifTrue:[((self isAKO) includesKey:slotName)
X ifTrue: [↑(self isAKO) getSlot: slotName]
X ifFalse:[↑(self isAKO) lookUpAkoChain: slotName]]
X ifFalse:[nil]!
X
XremoveSlot: slotName
X ↑self removeKey:slotName ifAbsent:[nil]!
X
XrunDemonForValue: slotName
X
X | aBlock |
X aBlock := self getSlot: slotName facet: 'ifNeeded'.
X (aBlock isNil)
X ifTrue: [↑nil]
X ifFalse:[↑self setSlot:slotName value:(aBlock value)]!
X
XsetSlot: slotName facet: facetName with: value
X
X | tempSlot |
X tempSlot := self at:slotName
X ifAbsent: [self at:slotName put: Slot new].
X tempSlot setFacet: facetName with: value.
X ↑value!
X
XsetSlot:slotName value:aValue
X "set the value facet of a slot"
X
X ↑self setSlot:slotName facet:'value' with:aValue.!
X
XsetSlot:slotName with: aSlot
X "associate the slot aSlot with the name slotName. "
X
X ↑self at: slotName put: aSlot! !
X
X
XFRMTRM.TXT
X
X| mammal dog fido s askDemon t |
X" Examples of frame and slot classes in use.
X Select and DOIT."
X
Xmammal := Frame new.
Xmammal setSlot: 'hide' value: 'hairy'.
Xmammal setSlot: 'bloodType' value: 'warm'.
X
Xdog := Frame new.
Xdog isAKO: mammal.
Xdog setSlot: 'numberLegs' value: 4.
X
XaskDemon := [Prompter prompt:'What is this dog''s name?' default: 'Bruno'].
Xdog addDemon:askDemon slot:'name' type:'ifNeeded'.
X
Xfido := Frame new.
Xfido addDemon:askDemon slot:'name' type:'ifNeeded'.
Xfido isAKO:dog.
Xfido setSlot:'color' value:'brown'.
X
X" Let's see the demon fire "
Xfido getSlotValue:'name'.
X
X
XSLOT.CLS
X
XDictionary variableSubclass: #Slot
X instanceVariableNames: ''
X classVariableNames: ''
X poolDictionaries: '' !
X
X!Slot class methods ! !
X
X
X!Slot methods !
X
XgetFacet: facetName
X ↑self at: facetName ifAbsent: [nil]!
X
XgetValue
X ↑self getFacet: 'value'!
X
XremoveFacet: facetName
X ↑self removeKey:facetName ifAbsent:[nil]!
X
XsetFacet: facetName with: aValue
X
X self at: facetName put: aValue.
X ↑aValue!
X
XsetValue: aValue
X self setFacet: 'value' with: aValue! !
X a
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SHAR_EOF
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then
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X
X
X Articles and Departments that have
X Additional On-Line Files
X
X AI EXPERT
X January 1987
X (Note: Contents page is in file CONTNT.JAN)
X
X
X
X
XARTICLES RELEVANT FILES
X-------- --------------
X
XJanuary Table of Contents CONTNT.JAN
X
XAdding Rete Net to Your OPS5 Toolbox OPSNET.JAN
Xby Dan Neiman
X
XPerceptrons & Neural Nets PERCEP.JAN
Xby Peter Reece
X
X
XDEPARTMENTS
X
XExpert's Toolbox EXPERT.JAN
X"Using Smalltalk to Implement Frames"
Xby Marc Rettig
X
XAI Apprentice AIAPP.JAN
X"Creating Expert Systems frm Examples"
Xby Beverly and Bill Thompson
X
SHAR_EOF
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X
X
X Adding the Rete Net to Your OPS5 Toolbox
X (Supplemental files arranged by filename headings)
X January 1987 AI EXPERT
X by Dan Neiman
X
X
X
XEditor's Note:
X
XAdditional notes and clarifications for Imperative Pattern Match code,
Xas described in January '87 issue of AI/Expert.
X
XThe code described in AI/Expert is still evolving (i.e. the more I use it,
the more
Xfeatures I add), and there was not sufficient space to give complete
instructions in
Xthe magazine, so the following notes should be used as a supplement to the
Xarticle.
X
XTo use the Rete net modifications, load the code into an existing Common
Lisp OPS5
Ximage. Then use the pmatch and map-pmatch functions as described in the
article.
X
X
XIt was probably not made clear in the article, but both pmatch and map-pmatch
Xreturn the values of the last expression evaluated in the righthand side.
So,
Xfor example, to get the names of all employees making 30K a year, you might
use the
Xcode:
X?(map-pmatch (employees ↑name <emp> ↑salary > 30000)
X -->
X ?<emp> )
X
XThe RHS of the above function just evaluates and returns the binding
of <emp>.
XBecause the function used was map-pmatch, a list of *all* employees
satisfying the
Xgiven constraints is returned.
X
XThe syntax of the pmatch and map-pmatch commands has been modified slightly
since
Xthe article went to press. The method described for passing Lisp variables
to a
Xpattern match function proved to be inexpressibly awkward for lexically bound
Lisps
X(the system was originally written in Franz). The following modification
makes it
Xconsiderably easier to pass arguments to the pattern match routines.
X
XBecause the pattern match is compiled, the only way to interactively match
a particular
Xvalue is to write that value into working memory, and include that working
memory element
Xin the pattern match. This is fairly awkward to do by hand, so I've
incorporated a macro
Xinto the pmatch and map-pmatch commands which do it automagically. The
arguments are passed
Xby following the pmatch function with an argument list. The argument
list is distinguished
Xfrom a pattern by the "args" keyword. The syntax is:
X
X(pmatch (args arg1 arg2 ... argN)
X (condition element 1)
X (condition element 2)
X -->
X RHS)
X
XAfter macro expansion, the result is effectively
X (let ((tt (make ipm$data arg1 arg2 ... argN)))
X (query1 (ipm$data <arg1> <arg2> <arg3>)
X (condition element 1)
X (condition element 2)
X : : :
X -->
X RHS)
X (oremove tt) )
X
XNote that the working memory element is added and deleted automatically.
X
XAs an example, the code to locate all children of a couple might look like
this
X(defun children(mother father)
X ?(map-pmatch (args mother father)
X (mother ↑name <mother> ↑child <child>)
X (father ↑name <father> ↑child <child>)
X -->
X (make parents ↑name <child> ↑father <father> ↑mother <mother>)
X ?<child>)
X
Xand given the working memory:
X(mother ↑name ann ↑child bob)
X(father ↑name fred ↑child bob)
X(mother ↑name sue ↑child alex)
X(father ↑name fred ↑child john)
X(mother ↑name ann ↑child john)
X(father ↑name fred ↑child cheryl)
X
X(children 'ann 'fred) would return (bob john)
X
Xand create the working memory elements
X
X(parents ↑name bob ↑father fred ↑mother ann)
X(parents ↑name john ↑father fred ↑mother ann)
X
XDebugging code: As is the case with OPS5 productions, if you recompile
a pmatch
Xor map-pmatch function, you must remove working memory and replace it.
A pattern match
Xwill only work on data which has been added after compilation. This does
tend to
Xmake debugging tedious.
X
XEverytime a pmatch operation is recompiled, it generates a new body bound
to a variable of
Xthe form queryN. Because queries are not explictly named, it's difficult
to automatically
Xexcise them. So the net will tend to fill with superfluous nodes during
debugging.
XThe function exquery will excise all existing queries. Executing the
sequence,
X(oremove *)
X(exquery)
X(i-g-v)
X
Xwill remove all working memory and queries and reset all global variables.
X
XIf a pmatch or map-pmatch function blows up while evaluating its RHS, reset
the
Xglobal variable *in-rhs* to nil before proceeding.
X
XQuestions about this code can be directed to:
XDan Neiman
XCompuServe 72277,2604
XCSNET dann@UMASS-CS.csnet
X
Xor c/o COINS Dept.
X Lederle Graduate Research Center
X University of Massachusetts
X Amherst, MA 01003
X
X
XIndex to software:
X
XCLSUP.LSP : Common Lisp support functions to define some canonical
X functions missing in Common Lisp.
X
XOPSMODS.L : The OPS5 modifications described in the article.
X
XCOMMON.OPS : OPS5 for Common Lisp
XTI.OPS : OPS5 for TI Explorers
XFRANZ.OPS : OPS5 for Franz Lisp
X
XMONK.OPS : Test file for OPS5
XPRTOWER.OPS : Test file for OPS5
X
X
XNEWOPS.L
X
X;OPS5 modifications for Common Lisp
X; by: Dan Neiman
X; Original idea conceived at ITT ATC May, 1986
X; Converted to Common Lisp and expanded at COINS Dept., UMASS Fall 1986
X
X;Copyright notice: Much of this code is modified or original OPS5 code
; which is
X;copyrighted by C. Lanny Forgy of CMU, and is used with his permission.
; The rest is
X;Copyright (c) Daniel Neiman, COINS Dept. UMass. Permission is given to
; use this
X;code freely for personal, educational, or research applications. It is
; not to be
X;sold, or incorporated into a for-profit product without permission of
; the author.
X;The purpose of this code is to illustrate alternative uses of the Rete
; net and
X;alternative control structures in OPS5. No guarantees are made about
; its fitness
X;any particular application, and no claim is made about the presence or
; absence of
X;bugs.
X;Version of 12/12/86
X
X;This file contains the necessary OPS5 modifications to perform
X;the RHS pattern matching/control function described in the
X;accompanying January '87 AI/Expert article. The code is a supplement
; to OPS5 and is
X;intended to be loaded into a Common Lisp OPS5 image.
X
X;Note: The idea behind this modification is to add memory to the &p node
; and create
X;functions to interrogate that memory at will. Sort of an elegant idea.
; But, because
X;it has to be patched into an implementation which was not designed to do
; so, there's a
X;lot of fairly nasty looking code here. Take heart, most of it is just
; slightly modified
X;ops5 code and can be pretty much ignored.
X
X;This variable is used to determine if we encountered a pmatch
X;or map-pmatch in top-level lisp code or while compiling an
X;OPS5 production.
X
X(proclaim '(special *compiling-rhs* *qnames* *cmp-p-context-stack*
X *system-state-stack* *NMATCHES* *ipm-data-stack*))
X(setq *qnames* nil)
X(setq *system-state-stack* nil)
X(setq *cmp-p-context-stack* nil)
X(setq *compiling-rhs* nil)
X(setq *ipm-data-stack* nil)
X
X;Read macro for variable evaluation on "RHS" of pattern match
X;All &whatever macros on the righthand side must be preceded by
X;a ?. This will expand to ($varbind '&whatever)
X;To avoid having a plethora of read macros, ? will be double-duty.
X;If ? precedes a ?(pmatch ....), then the expression is evaluated
X;and the appropriate match stuff is placed in the rete net. The
;code is replaced by (query queryN pattern-body).
X
X;Read macro ? executes the following function.
X(defun $$ipm$$dofunc$$(strm chr)
X (let ((inp (read strm t nil t)))
X (cond ((atom inp)
X (if (eq '#\< (char (string inp) 0)) ;is it an OPS variable?
X `($varbind ',inp)
X (intern (concatenate 'string "?" (princ-to-string inp)))))
X ((member (car inp) '(map-pmatch pmatch) :test #'eq)
X (eval inp))
X (t
X inp))))
X
X
X;make ? a read macro
X(set-macro-character #\? #'$$ipm$$dofunc$$ t)
X
X(defun &query (rating name var-dope ce-var-dope rhs frhs)
X (prog (fp dp)
X (cond (*sendtocall*
X (setq fp *flag-part*)
X (setq dp *data-part*))
X (t
X (setq fp *alpha-flag-part*)
X (setq dp *alpha-data-part*)))
X (and (member fp '(nil old))
X (ipm-removepm name dp))
X (and fp (ipm-insertpm name dp))))
X
X
X; each conflict set element is a list of the following form:
X; ((p-name . data-part) (sorted wm-recency) special-case-number)
X
X;I'm storing the results of the pattern matches on a property list, pmatches.
X
X;modified OPS5 removecs
X;remove results of the pattern match
X
X(defun ipm-removepm (name cr-data)
X (prog (inst cs pmtchs)
X(setq pmtchs (setq cs (get name 'pmatches)))
X l(cond ((null cs)
X (return nil)))
X(setq inst (car cs))
X(setq cs (cdr cs))
X(and (not (top-levels-eq inst cr-data)) (go l))
X(putprop name (remove inst pmtchs)
X 'pmatches)
X))
X
X;modified OPS5 insertcs
X;store the results of the pattern match
X;Stored as (data ) rather than original conflict set format
X;of ((name . data) (order tags) rating)
X(defun ipm-insertpm (name data)
X (let ((pmtch (get name 'pmatches)))
X (setq pmtch (get name 'pmatches))
X (and (atom pmtch) (setq pmtch nil))
X (setq pmtch (cons data pmtch))
X (putprop name pmtch 'pmatches)
X pmtch
X ))
X
X;PMATCH is the RHS/LISP equivalent of the (p rule) macro. When used from Lisp,
X;it should always be preceded by the ? read macro, so as to force evaluation
X;at read time. Otherwise, the Rete net won't be set up correctly.
X
X(defmacro pmatch(&rest z)
X `(let ((pname (newsym query))
X (level (newsym level)))
X (finish-literalize)
X (princ '*)
X (cond ((and (listp (car ',z)) (eq (caar ',z) 'args))
X (ipm-compile-production pname (add-data-to-prod pname ',z ))
X `(let ((tt (make-ipm-data ',pname ,@(cdar ',z) ))
X (ans (query ',pname)))
X(restore-ipm-data tt)
X ans))
X (t
X (ipm-compile-production pname ',z)
X `(query ',pname)))))
X
X(defun restore-ipm-data(current)
X (let ((inrhsflg *in-rhs*)
X (old (pop *ipm-data-stack*)))
X (setq *in-rhs* nil)
X (eval (list 'oremove current))
X (setq *in-rhs* inrhsflg)
X (if old
X (add-to-wm (car old) (cdr old)))))
X
X;Note, the only way to pass input to the pattern matcher is to create a
X;working memory element containing that input. The following utility
; functions
X;automagically create the ipm$data working memory element and modify the
X;production to use it.
X
X;MAKE-DATA: Make data takes a list of values and a unique level specifier
X;and creates a working memory element of the form (ipm$data val1 val2
; val3 .. )
X;Saves old ipm$data elements on stack so that no interference results.
X(defun make-ipm-data(&rest arglst)
X (let ((inrhsflg *in-rhs*)
X (old (car (get 'ipm$data 'wmpart*))))
X (if old (push old *ipm-data-stack*))
X (setq *in-rhs* nil)
X (eval (list 'oremove (cdr old))) ;needs in-rhs to be nil
X (setq *in-rhs* inrhsflg)
X ($reset)
X ($change 'ipm$data)
(mapc #'(lambda(tab val)
X ($tab tab)
X ($change val))
X '(a b c d e f g h i j k l) (cdr arglst))
X ($tab 'for) ;target data for particular query
X ($change (car arglst))
X ($assert)))
X
X;Modify the production so that it accesses the data passed by the ipm$data wme
X(defun add-data-to-prod(pname prod)
X (let ((args (cdar prod))
X (body (cdr prod)))
X (cons
X `(ipm$data ,@(mapcan #'(lambda(slot arg) (list '↑ slot (concat
'\< arg '\> )))
X '(a b c d e f g h i j k l) args)
X ↑for ,pname)
X body)))
X
X
X;Finish-literalize: modified to define special wme type ipm$data which
; is used to
X;transfer lisp arguments to working memory.
X(defun finish-literalize nil
X (cond ((not (null *class-list*))
X (cond ((not (member 'ipm$data *class-list*))
X (literalize ipm$data a b c d e f g h i j k l for)))
X (mapc (function note-user-assigns) *class-list*)
X (mapc (function assign-scalars) *class-list*)
X (mapc (function assign-vectors) *class-list*)
X (mapc (function put-ppdat) *class-list*)
X (mapc (function erase-literal-info) *class-list*)
X (setq *class-list* nil)
X (setq *buckets* nil))))
X
X
X
X;Map the RHS across all matching data.
X(defmacro map-pmatch(&rest z)
X `(let ((pname (newsym query))
X (level (newsym level)))
X (finish-literalize)
X (princ '*)
X (cond ((and (listp (car ',z)) (eq (caar ',z) 'args))
X (ipm-compile-production pname (add-data-to-prod pname ',z ))
X `(let ((tt (make-ipm-data ',pname ,@(cdar ',z) ))
X (ans (map-query ',pname)))
X(restore-ipm-data tt)
Xans))
X (t
X (ipm-compile-production pname ',z)
X `(map-query ',pname)))))
X
X
X(defun ipm-compile-production (name matrix)
X (prog (erm)
X (setq *p-name* name)
(cond (*compiling-rhs*
X (setq erm (catch (ipm-cmp-p-recursive name matrix) '!error!)))
X (t
X (setq erm (catch (ipm-cmp-p name matrix) '!error!))))
X; following line is modified to save production name on *qnames*
X (pushnew name *qnames*)
X(return erm)))
X
X
X;save globals *feature-count *ce-count* *vars* *ce-vars* *rhs-bound-vars*
X;*rhs-bound-ce-vars* *last-branch* on a push-down stack.
X
X;Push global variables takes a stack name, and a list of global variables,
; creates a
X;list of lists of the form ((varname value) (varname value) ... ) and
; pushes it onto
X;the indicated stack.
X
X(defun push-global-variables(stack &rest vars)
X (push
X (mapcar #'(lambda(var)
X (cons var (eval var))) ;copy may not be needed, but
; better safe....
X vars)
X (symbol-value stack)))
X
X;Pop global variables takes a stack name, pops most recent entry off
; the stack,
X;and resets the values of the variables.
X(defun pop-global-variables(stack)
X (mapcar #'(lambda(varbinding)
X (set (car varbinding) (cdr varbinding)))
X (pop stack)) )
------------------------------
End of AIList Digest
********************
∂29-Jan-87 0254 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #21
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 29 Jan 87 02:50:19 PST
Date: Wed 28 Jan 1987 21:43-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #21
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 29 Jan 1987 Volume 5 : Issue 21
Today's Topics:
Queries - Learning Programs & CMU's "GRAPES" &
1987 Society for Computer Simulation Multiconference,
Seminars - Circumscriptive Query Answering (SU) &
Automation in Seismic Interpretation (SMU) &
A Four-Valued Semantics for Terminological Logics (AT&T) &
Learning when Irrelevant Variables Abound (IBM),
Conference - AI and Law
----------------------------------------------------------------------
Date: 26 Jan 87 17:36:23 GMT
From: carlson@lll-tis-b.arpa (John Carlson)
Subject: Learning programs wanted [Public Domain preferred]
Can anyone give me pointers to programs that learn? In
particular, does anyone have an copy of the "Marvin"
program that appeared in Byte a couple of months ago?
John Carlson
--
INTERNET carlson@lll-tis-b.ARPA
UUCP ...lll-crg!styx!carlson
------------------------------
Date: 27 Jan 87 20:12:07 GMT
From: gatech!mcnc!rti-sel!hlw@hplabs.hp.com (Hal Waters)
Subject: Info wanted on CMU's "GRAPES"
I wish to get information on CMU's "GRAPES".
Specifically, who wrote the software?
Is it a tool/shell for creating Intelligent Tutoring Systems?
Is it a Cognitive Simulation Model?
Is it Public Domain?
If so, or if not, how can I get a copy of the software?
Please mail responses to me at hlw@rti-sel.
Thanks in advance!
Hal Waters
------------------------------
Date: 27 Jan 87 11:48:00 EST
From: "MATHER, MICHAEL" <mather@ari-hq1.ARPA>
Reply-to: "MATHER, MICHAEL" <mather@ari-hq1.ARPA>
Subject: 1987 Society for Computer Simulation Multiconference
Information on the 1987 Society for Computer Simulation Multiconference was
published in the last AIList. Does anyone know if this conference has already
taken place or, if not, when and where will it take place?
------------------------------
Date: 26 Jan 87 1434 PST
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Circumscriptive Query Answering (SU)
Commonsense and Nonmonotonic Reasoning Seminar
A QUERY ANSWERING ALGORITHM
FOR CIRCUMSCRIPTIVE AND CLOSED-WORLD THEORIES
Teodor C. Przymusinski
University of Texas at El Paso
<ft00@utep.bitnet>
Thursday, January 29, 4pm
Bldg. 160, Room 161K
McCarthy's theory of circumscription appears to be the most powerful
among various non-monotonic logics designed to handle incomplete and
negative information in knowledge representation systems. In this
presentation we will describe a query answering algorithm for
circumscriptive theories.
The algorithm is based on a modified version of ordered linear resolution
(OL-resolution), which we call a MInimal model Linear Ordered resolution
(MILO-resolution). MILO-resolution constitutes a sound and complete procedure
to determine the existence of minimal models satisfying a given formula.
Our algorithm is the first query evaluation algorithm for general
circumscriptive theories. The Closed-World Assumption (CWA) and its
generalizations, the Generalized Closed-World Assumption (GCWA) and
the Extended Closed-World Assumption (ECWA), can be considered as
special forms of circumscription. Consequently, our algorithm also
applies to answering queries in theories using the Closed-World Assumption
and its generalizations. Similarly, since prioritized circumscription
is equivalent to a conjunction of (parallel) circumscriptions, the
algorithm can be used to answer queries in theories circumscribed by
prioritized circumscription.
------------------------------
Date: WED, 10 oct 86 17:02:23 CDT
From: leff%smu@csnet-relay
Subject: Seminar - Automation in Seismic Interpretation (SMU)
January 28, 1987, 1:30PM, 315SIC Computer Science Department,
Southern Methodist Univeristy, Dallas, Texas
AUTOMATION IN SEISMIC INTERPRETATION
Bruce Flinchbaugh
Texas Instruments
ABSTRACT
Interpreting three-dimensional seismic data is important for oil and
gas exploration. Part of the problem is perception-intensive (experts
spend much of their time looking at the data), and part of the problem
is more cognition-intensive (experts reconcile perceived structures
with knowledge of plausible geology and other sources of information).
This talk will present a simple overview of the seismic data
acquisition and processing required to produce three-dimensional
seismic data volumes. Then a variety of tools for assisting in the
interpretation of the data will be discussed. For the most part
today's useful tools are aimed at solving the perception-intensive
problems. Finally some open problems in seismic interpretation will
be described.
BIOGRAPHY
Dr. Flinchbaugh is a Senior Member of Technical Staff at T.I. in the
Computer Science Center Artificial Intelligence Laboratory, where he
is currently tackling semiconductor manufacturing automation problems.
Also at T.I. he has invented techniques assisting in the processing
and structural interpretation of three-dimensional seismic data.
Previous research in artificial intelligence, at M.I.T. and The Ohio
State University, addressed computational vision problems involving
the interpretation of motion and color. Dr. Flinchbaugh received his
Ph.D. in computer and information science from The Ohio State
University in 1980.
------------------------------
Date: Thu, 22 Jan 87 10:46:34 est
From: allegra!dlm
Subject: Seminar - A Four-Valued Semantics for Terminological Logics
(AT&T)
[Forwarded from the NL-KR Digest.]
Title: A Four-Valued Semantics for Terminological Logics
Speaker: Peter F. Patel-Schneider
Affiliation: Schlumberger Palo Alto Research
Date: Monday, February 2, 1987
Location: AT&T Bell Laboratories - Murray Hill 3D-473
Sponsor: Ron Brachman
Terminological logics (also called frame-based description languages)
are a clarification and formalization of some of the ideas underlying
semantic networks and frame-based systems. The fundamental
relationship in these logics is whether one concept (frame, class) is
more general than (subsumes) another. This relationship forms the
basis for important operations, including recognition, classification,
and realization, in knowledge representation systems incorporating
terminological logics.
However, determining subsumption is computationally intractable under
the standard semantics for terminological logics, even for languages
of very limited expressive power. Several partial solutions to this
problem are used in knowledge representation systems, such as NIKL,
that incorporate terminological logics, but none of these solutions
are satisfactory if the system is to be of general use in representing
knowledge.
A new solution to this problem is to use a weaker, four-valued
semantics for terminological logics, thus legitimizing a smaller set
of subsumption relationships. In this way a computationally tractable
knowledge representation system incorporating a more expressively
powerful terminological logic can be built.
------------------------------
Date: Tue 27 Jan 87 20:05:30-PST
From: Ramsey Haddad <HADDAD@Sushi.Stanford.EDU>
Subject: Seminar - Learning when Irrelevant Variables Abound (IBM)
Next BATS will be at IBM Almaden Research Center on Friday, February 13.
Following is a preliminary schedule:
9:45 - 10:00 Coffee + +
10:00 - 11:00 "Algebraic Methods in the Theory of Lower Bounds
for Boolean Circuit Complexity"
Norman Smolensky, U.C. Berkeley.
11:00 - 12:00 " The Decision Problem for the Probabilities
of Higher-Order Properties".
Phokion Kolaitis, IBM Almaden.
1:00 - 2:00 "Learning When Irrelevant Features Abound"
Nick Littlestone, U.C. Santa Cruz.
2:00 - 3:00 "Fast Parallel Algorithms for Chordal Graphs"
Alejandro A. Schaffer, Stanford University.
===================================================================
"Learning When Irrelevant Features Abound"
Nick Littlestone
U.C. Santa Cruz
Valiant and others have studied the problem of learning various classes
of Boolean functions from examples. Here we discuss on-line learning of
these functions. In on-line learning, the learner responds to each
example according to a current hypothesis. Then the learner updates the
hypothesis, if necessary, based on the correct classification of the
example. This is the form of the Perceptron learning algorithms, in
which updates to the weights occur after each mistake. One natural
measure of the quality of learning in the on-line setting is the number
of mistakes the learner makes. For suitable classes of functions,
on-line learning algorithms are available which make a bounded number of
mistakes, with the bound independent of the number of examples seen by
the learner. We present one such algorithm, which learns disjunctive
Boolean functions. The algorithm can be expressed as a linear-threshold
algorithm. If the examples include a large number of irrelevant
variables, the algorithm does very well, the number of mistakes
depending only logarithmically on the number of irrelevant variables.
More specifically, if the function being learned is of the form $f ( x
sub 1 ,..., x sub n )~=~x sub {i sub 1} orsign ... orsign x sub {i sub
k} then the mistake bound is $O ( k log n )$. If $k = O ( log n )$ then
this bound is significantly better than that given by the Perceptron
convergence theorem.
------------------------------
Date: 8 Jan 87 14:30:33 EST
From: MCCARTY@RED.RUTGERS.EDU
Subject: Conference - AI and Law
FINAL CALL FOR PAPERS:
First International Conference on
ARTIFICIAL INTELLIGENCE AND LAW
May 27-29, 1987
Northeastern University
Boston, Massachusetts, USA
In recent years there has been an increased interest in the applications of
artificial intelligence to law. Some of this interest is due to the potential
practical applications: A number of researchers are developing legal expert
systems, intended as an aid to lawyers and judges; other researchers are
developing conceptual legal retrieval systems, intended as a complement to the
existing full-text legal retrieval systems. But the problems in this field are
very difficult. The natural language of the law is exceedingly complex, and it
is grounded in the fundamental patterns of human common sense reasoning. Thus,
many researchers have also adopted the law as an ideal problem domain in which
to tackle some of the basic theoretical issues in AI: the representation of
common sense concepts; the process of reasoning with concrete examples; the
construction and use of analogies; etc. There is reason to believe that a
thorough interdisciplinary approach to these problems will have significance
for both fields, with both practical and theoretical benefits.
The purpose of this First International Conference on Artificial Intelligence
and Law is to stimulate further collaboration between AI researchers and
lawyers, and to provide a forum for the latest research results in the field.
The conference is sponsored by the Center for Law and Computer Science at
Northeastern University. The General Chair is: Carole D. Hafner, College of
Computer Science, Northeastern University, 360 Huntington Avenue, Boston MA
02115, USA; (617) 437-5116 or (617) 437-2462; hafner.northeastern@csnet-relay.
Authors are invited to contribute papers on the following topics:
- Legal Expert Systems
- Conceptual Legal Retrieval Systems
- Automatic Processing of Natural Legal Texts
- Computational Models of Legal Reasoning
In addition, papers on the relevant theoretical issues in AI are also invited,
if the relationship to the law can be clearly demonstrated. It is important
that authors identify the original contributions presented in their papers, and
that they include a comparison with previous work. Each submission will be
reviewed by at least three members of the Program Committee (listed below), and
judged as to its originality, quality and significance.
Authors should submit six (6) copies of an Extended Abstract (6 to 8 pages) by
January 15, 1987, to the Program Chair: L. Thorne McCarty, Department of
Computer Science, Rutgers University, New Brunswick NJ 08903, USA; (201)
932-2657; mccarty@rutgers.arpa. Notification of acceptance or rejection will
be sent out by March 1, 1987. Final camera-ready copy of the complete paper
(up to 15 pages) will be due by April 15, 1987.
Conference Chair: Carole D. Hafner Northeastern University
Program Chair: L. Thorne McCarty Rutgers University
Program Committee: Donald H. Berman Northeastern University
Michael G. Dyer UCLA
Edwina L. Rissland University of Massachusetts
Marek J. Sergot Imperial College, London
Donald A. Waterman The RAND Corporation
------------------------------
End of AIList Digest
********************
∂29-Jan-87 0737 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #22
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 29 Jan 87 07:36:42 PST
Date: Wed 28 Jan 1987 22:44-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #22
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 29 Jan 1987 Volume 5 : Issue 22
Today's Topics:
Policy - AI Magazine Code,
Philosophy - Methodological Epiphenomenalism & Consciousness,
Psychology - Objective Measurement of Subjective Variables
----------------------------------------------------------------------
Date: Wed 28 Jan 87 10:26:52-PST
From: PAT <HAYES@SPAR-20.ARPA>
Reply-to: HAYES@[128.58.1.2]
Subject: Re: AIList Digest V5 #18
Weve had some bitches about too much philosophy, but I never expected
to be sent CODE to read.
Pat Hayes
PS Especially with price lists in the comments. Anyone who is willing to pay
$50.00 for a backward chaining program shouldnt be reading AIList Digest.
------------------------------
Date: 28 Jan 87 14:57:08 est
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: AIList Digest V5 #20
AIList Digest Wednesday, 28 Jan 1987 Volume 5 : Issue 20
Today's Topics:
AI Expert Magazine Sources (Part 3 of 22)
I can't believe you're really sending 22 of these moby messages to the
entire AIList. Surely you could have collected requests from
interested individuals and then sent it only to them.
------------------------------
Date: Wed 28 Jan 87 22:12:59-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Reply-to: AIList-Request@SRI-AI.ARPA
Subject: Code Policy
The bulk of this code mailing does bother me, but there seems to be
at least as much interest in it as in the seminar notices, bibliographies,
and philosophy discussions. AIList reaches thousands of students, and
a fair proportion are no doubt interested in examining the code. The
initial offer of the code drew only positive feedback, so far as I
know. Even the mailing of the entire stream (in nine 50-K files) on
the comp.ai distribution drew no public protest. I'm still open to
discussion, but I'll continue the series unless there is substantial
protest. Keeping up with current issues of AI Magazine will be much
less disruptive once this backlog is cleared up.
The mailing process is much more efficient for batched addresses
than for individual mailings (which send multiple copies through
many intermediate and destination hosts), so individual replies
seem out of the question -- and I can't afford to condense hundreds
of requests into a batch distribution list. (Can't somebody invent
an AI program to do that?)
It would be nice if the code could be distributed by FTP, but that
only works for the Arpanet readership. Most of the people signing
on in the last year or two are on BITNET. I still haven't gotten
around to finding BITNET relay sites, so there is no convenient way
to split the mailing. Anyway, that would still force hundreds of
Arpanet readers to go through the FTP process, and it is probably
more cost effective to just mail out the code and let uninterested
readers ignore it.
Suggestions are welcome.
-- Ken Laws
------------------------------
Date: 26 Jan 87 18:55:54 GMT
From: clyde!watmath!sunybcs!colonel@rutgers.rutgers.edu (Col. G. L.
Sicherman)
Subject: Re: Minsky on Mind(s)
> ... It is a way for bodily tissues to get the attention
> of the reasoning centers. Instead of just setting some "damaged
> tooth" bit, the injured nerve grabs the brain by the lapels and says
> "I'm going to make life miserable for you until you solve my problem."
This metaphor seems to suggest that consciousness wars with itself. I
would prefer to say that the body grabs the brain by the handles, like
a hedge clipper or a geiger counter. In other words, just treat the
mind as a tool, without any personality of its own. After all, it's the
body that is real; the mind is only an abstraction.
By the way, it's well known that if the brain has a twist in it, it
needs only one handle. Ask any topologist!
--
Col. G. L. Sicherman
UU: ...{rocksvax|decvax}!sunybcs!colonel
CS: colonel@buffalo-cs
BI: colonel@sunybcs, csdsiche@ubvms
------------------------------
Date: Mon, 26 Jan 87 23:57:40 est
From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>
Subject: Methodological Epiphenomenalism
"CUGINI, JOHN" <cugini@icst-ecf> wrote on mod.ai"
> Subject: Consciousness as a Superfluous Concept, But So What?
So methodological epiphenomenalism.
> Consciousness may be as superflouous (wrt evolution) as earlobes.
> That hardly goes to show that it ain't there.
Agreed. It only goes to show that methodological epiphenomalism may
indeed be the right research strategy. (The "why" is a methodological
and logical question, not an evolutionary one. I'm arguing that no
evolutionary scenario will help. And it was never suggested that
consciousness "ain't there." If it weren't, there would be no
mind/body problem.)
> I don't think it does NEED to be so. It just is so.
Fine. Now what are you going to do about it, methodologically speaking?
Stevan Harnad
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
(609)-921-7771
------------------------------
Date: 27 Jan 87 19:44:16 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: Objective measurement of subjective variables
adam@mtund.UUCP (Adam V. Reed), of AT&T ISL Middletown NJ USA, wrote:
> Stevan Harnad makes an unstated assumption... that subjective
> variables are not amenable to objective measurement. But if by
> "objective" Steve means, as I think he does, "observer-invariant", then
> this assumption is demonstrably false.
I do make the assumption (let me state it boldly) that subjective
variables are not objectively measurable (nor are they objectively
explainable) and that that's the mind/body problem. I don't know what
"observer-invariant" means, but if it means the same thing as in
physics -- which is that the very same physical phenomenon can
occur independently of any particular observation, and can in
principle be measured by any observer, then individuals' private events
certainly are not such, since the only eligible observer is the
subject of the experience himself (and without an observer there is no
experience -- I'll return to this below). I can't observe yours and you
can't observe mine. That's one of the definitive features of the
subjective/objective distinction itself, and it's intimately related to
the nature of experience, i.e., of subjectivity, of consciousness.
> Whether or not a stimulus is experienced as belonging to some target
> category is clearly a private event...[This is followed by an
> interesting thought-experiment in which the signal detection parameter
> d' could be calculated for himself by a subject after an appropriate
> series of trials with feedback and no overt response.]... the observer
> would be able to mentally compute d' without engaging in any externally
> observable behavior whatever.
Unfortunately, this in no way refutes the claim that subjective experience
cannot be objectively measured or explained. Not only is there (1) no way
of objectively testing whether the subject's covert calculations on
that series of trials were correct, not only is there (2) no way of
getting any data AT ALL without his overt mega-response at the end
(unless, of course, the subject is the experimenter, which makes the
whole exercise solipsistic), but, worst of all, (3) the very same
performance data could be generated by presenting inputs to a
computer's transducer, and no matter how accurately it reported its
d', we presumably wouldn't want to conclude that it had experienced anything
at all. So what's OBJECTIVELY different about the human case?
At best, what's being objectively measured happens to correlate
reliably with subjective experience (as we can each confirm in our own
cases only -- privately and subjectively). What we are actually measuring
objectively is merely behavior (and, if we know what to look for, also
its neural substrate). By the usual objective techniques of scientific
inference on these data we can then go on to formulate (again objective)
hypotheses about underlying functional (causal) mechanisms. These should
be testable and may even be valid (all likewise objectively). But the
testability and validity of these hypotheses will always be objectively
independent of any experiential correlations (i.e., the presence or
absence of consciousness).
To put it my standard stark way: The psychophysics of a conscious
organism (or device) will always be objectively identical to that
of a turing-indistinguishable unconscious organism (or device) that
merely BEHAVES EXACTLY AS IF it were conscious. (It is irrelevant whether
there are or could be such organisms or devices; what's at issue here is
objectivity. Moreover, the "reliability" of the correlations is of
course objectively untestable.) This leaves subjective experience a
mere "nomological dangler" (as the old identity theorists used to call
it) in a lawful psychophysical account. We each (presumably) know it's
there from our respective subjective observations. But, objectively speaking,
psychophysics is only the study of, say, the detecting and discriminating
capacity (i.e., behavior) of our trandsucer systems, NOT the qualities of our
conscious experience, no matter how tight the subjective correlation.
That's no limit on psychophysics. We can do it as if it were the study
of our conscious experience, and the correlations may all be real,
even causal. But the mind/body problem and the problem of objective
measurement and explanation remain completely untouched by our findings,
both in practise and in principle.
So even in psychophysics, the appropriate research strategy seems to
be methodological epiphenomenalism. If you disagree, answer this: What
MORE is added to our empirical mission in doing psychophysics if we
insist that we are not "merely" trying to account for the underlying
regularities and causal mechanisms of detection, discrimination,
categorization (etc.) PERFORMANCE, but of the qualitative experience
accompanying and "mediating" it? How would someone who wanted to
undertake the latter rather than merely the former go about things any
differently, and how would his methods and findings differ (apart from
being embellished with a subjective interpretation)? Would there be any
OBJECTIVE difference?
I have no lack of respect for psychophysics, and what it can tell us
about the functional basis of categorization. (I've just edited and
contributed to a book on it.) But I have no illusions about its being
in any better a position to make objective inroads on the mind/body
problem than neuroscience, cognitive psychology, artificial
intelligence or evolutionary biology -- and they're in no position at all.
> In principle, two investigators could perform the [above] experiment
> ...and obtain objective (in the sense of observer-independent)
> results as to the form of the resulting lawful relationships between,
> for example, d' and memory retention time, *without engaging in any
> externally observable behavior until it came time to compare results*.
I'd be interested in knowing how, if I were one of the experimenters
and Adam Reed were the other, he could get "objective
(observer-independent) results" on my experience and I on his. Of
course, if we make some (question-begging) assumptions about the fact
that the experience of our respective alter egos (a) exists, (b) is
similar to our own, and (c) is veridically reflected by the "form" of the
overt outcome of our respective covert calculations, then we'd have some
agreement, but I'd hardly dare to say we had objectivity.
(What, by the way, is the difference in principle between overt behavior
on every trial and overt behavior after a complex-series-of-trials?
Whether I'm detecting individual signals or calculating cumulating d's
or even more complex psychophysical functions, I'm just an
organism/device that's behaving in a certain way under certain
conditions. And you're just a theorist making inferences about the
regularities underlying my performance. Where does "experience" come
into it, objectively speaking? -- And you're surely not suggesting that
psychophyics be practiced as a solipsistic science, each experimenter
serving as his own sole subject: for from solipsistic methods you can
only arrive at solipsistic conclusions, trivially observer-invariant,
but hardly objective.)
> The following analogy (proposed, if I remember correctly, by Robert
> Efron) may illuminate what is happening here. Two physicists, A and B,
> live in countries with closed borders, so that they may never visit each
> other's laboratories and personally observe each other's experiments.
> Relative to each other's personal perception, their experiments are
> as private as the conscious experiences of different observers. But, by
> replicating each other's experiments in their respective laboratories,
> they are capable of arriving at objective knowledge. This is also true,
> I submit, of the psychological study of private, "subjective"
> experience.
As far as I can see, Efron's analogy casts no light at all.
It merely reminds us that even normal objectivity in science (intersubjective
repeatability) happens to be piggy-backing on the existence of
subjective experience. We are not, after all, unconscious automata. When we
perform an "observation," it is not ONLY objective, in the sense that
anyone in principle can perform the same observation and arrive at the
same result. There is also something it is "like" to observe
something -- observations are also conscious experiences.
But apart from some voodoo in certain quantum mechanical meta-theories,
the subjective aspect of objective observations in physics seems to be
nothing but an innocent fellow-traveller: The outcome of the
Michelson-Morley Experiment would presumably be the same if it were
performed by an unconscious automaton, or even if WE were unconscious automata.
This is decidely NOT true of the (untouched) subjective aspect of a
psychophysical experiment. Observer-independent "experience" is a
contradiction in terms.
(Most scientists, by the way, do not construe repeatability to require
travelling directly to one another's labs; rather, it's a matter of
recreating the same objective conditions. Unfortunately, this does not
generalize to the replication of anyone else's private events, or even
to the EXISTENCE of any private events other than one's own.)
Note that I am not denying that objective knowledge can be derived
from psychophysics; I'm only denying that this can amount to objective
knowledge about anything MORE than psychophysical performance and its
underlying causal substrate. The accompanying subjective phenomenology is
simply not part of the objective story science can tell, no matter how, and
how tightly, it happens to be coupled to it in reality. That's the
mind/body problem, and a fundamental limit on objective inquiry.
Methodological epiphenomenalism recommends we face it and live with
it, since not that much is lost. The "incompleteness" of an objective
account is, after all, just a subjective problem. But supposing away
the incompleteness -- by wishful thinking, hopeful over-interpretation,
hidden (subjective) premises or blurring of the objective/subjective
distinction -- is a logical problem.
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: Mon, 26 Jan 87 23:25:17 est
From: mnetor!dciem!mmt@seismo.CSS.GOV
Subject: Necessity of consciousness
Newsgroups: mod.ai
Subject: Re: Minsky on Mind(s)
Summary:
Expires:
References: <8701221730.AA04257@seismo.CSS.GOV>
Sender:
Reply-To: mmt@dciem.UUCP (Martin Taylor)
Followup-To:
Distribution:
Organization: D.C.I.E.M., Toronto, Canada
Keywords:
I tried to send this direct to Steve Harnad, but his signature is
incorrect: seismo thinks princeton is an "unknown host". Also mail
to him through allegra bounced.
===============
>just answer the following question: When the dog's tooth is injured,
>and it does the various things it does to remedy this -- inflamation
>reaction, release of white blood cells, avoidance of chewing on that
>side, seeking soft foods, giving signs of distress to his owner, etc. etc.
>-- why do the processes that give rise to all these sequelae ALSO need to
>give rise to any pain (or any conscious experience at all) rather
>than doing the very same tissue-healing and protective-behavioral job
>completely unconsciously? Why is the dog not a turing-indistinguishable
>automaton that behaves EXACTLY AS IF it felt pain, etc, but in reality
>does not? That's another variant of the mind/body problem, and it's what
>you're up against when you're trying to justify interpreting physical
>processes as conscious ones. Anything short of a convincing answer to
>this amounts to mere hand-waving on behalf of the conscious interpretation
>of your proposed processes.]
I'm not taking up your challenge, but I think you have overstated
the requirements for a challenge. Okham's razor demands only that
the simplest explanation be accepted, and I take this to mean inclusive
of boundary conditions AND preconceptions. The acceptability of a
hypothesis must be relative to the observer (say, scientist), since
we have no access to absolute truth. Hence, the challenge should be
to show that the concept of consciousness in the {dog|other person|automaton}
provides a simpler description of the world than the elimination of
the concept of consciousness does.
The whole-world description includes your preconceptions, and a hypothesis
that demands you to change those precoceptions is FROM YOUR VIEWPOINT
more complex than one that does not. Since you start from the
preconception that consciousness need not (or perhaps should not)
be invoked, you need stronger proof than would, say, an animist.
Your challenge should ask for a demonstration that the facts of observable
behaviour can be more succinctly described using consciousness than not
using it. Obviously, there can be no demonstration of the necessity of
consciousness, since ALL observable behaviour could be the result of
remotely controlled puppetry (except your own, of course). But this
hypothesis is markedly more complex than a hypothesis derived from
psychological principles, since every item of behaviour must be separately
described as part of the boundary conditions.
I have a mathematization of this argument, if you are interested. It is
about 15 years old, but it still seems to hold up pretty well. Ockham's
razor isn't just a good idea, it is informationally the correct means
of selecting hypotheses. However, like any other razor, it must
be used correctly, and that means that one cannot ignore the boundary
conditions that must be stated when using the hypothesis to make specific
predictions or descriptions. Personally, I think that hypotheses that
allow other people (and perhaps some animals) to have consciousness are
simpler than hypotheses that require me to describe myself as a special
case. Hence, Ockham's razor forces me to prefer the hypothesis that other
beings have consciousness. The same does not hold true for silicon-based
behaving entities, because I already have hypotheses that explain their
behaviour without invoking consciousness, and these hypotheses already
include the statement that silicon-based beings are different from me.
Any question of silon-based consciousness must be argued on a different
basis, and I think such arguments are likely to turn on personal preference
rather than on the facts of behaviour.
------------------------------
End of AIList Digest
********************
∂30-Jan-87 0217 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #23
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 30 Jan 87 02:16:40 PST
Date: Thu 29 Jan 1987 22:56-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #23
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 30 Jan 1987 Volume 5 : Issue 23
Today's Topics:
Code - AI Expert Magazine Sources (Part 4 of 22)
----------------------------------------------------------------------
Date: 19 Jan 87 03:36:40 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: AI Expert Magazine Sources (Part 4 of 22)
X
X
X;This version of cmp-p is used when compiling patterns on the
X;righthand side in which we want variable bindings consistent
X;with variable bindings on the LHS. Effectively, the RHS
X;pattern is just treated as a continuation of the LHS
X;pattern, except, of course, that the results of the RHS
X;pattern match will not affect the firing of the production.
X(defun ipm-cmp-p-recursive (name matrix)
X (prog (m bakptrs srhs frhs)
X (push-global-variables '*cmp-p-context-stack* '*matrix*
X '*feature-count* '*ce-count*
X '*vars* '*ce-vars*
X '*rhs-bound-vars* '*rhs-bound-ce-vars*
X '*last-branch* '*last-node*)
X (prepare-lex matrix)
X(setq *rhs-bound-vars* nil)
X(setq *rhs-bound-ce-vars* nil)
X (setq m (rest-of-p))
X l1 (and (end-of-p) (\%error '|no '-->' in production| m))
X (cmp-prin)
X (setq bakptrs (cons *last-branch* bakptrs))
X (or (eq '--> (peek-lex)) (go l1))
X (lex)
X(setq srhs (rest-of-p)) ; get righthand side
X(if (setq frhs (cdr (memq '<-- srhs)))
(setq srhs (remove-frhs srhs)))
X(ipm-check-rhs srhs)
X;note, we change the structure of the &query node to have a tail
X;component. This is the action to take on a failed pattern match
X (link-new-node (list '&query
X *feature-count*
X name
X (encode-dope)
X (encode-ce-dope)
X (cons 'progn srhs)
X (cons 'progn frhs)))
X (putprop name (cdr (nreverse bakptrs)) 'backpointers)
X(putprop name matrix 'production)
X (putprop name *last-node* 'topnode)
X(pop-global-variables *cmp-p-context-stack*)
X))
X
X;Extract failed pattern match rhs actions from production.
X(defun remove-frhs(rhs)
X (do ((lis nil (append lis (list inp)))
X(inp (car rhs) (car rhs)))
X ((eq inp '<--)
X(return lis))
X (setq rhs (cdr rhs))
X ))
X
X;;Modified version of OPS5 cmp-p, compiles pattern match and links
X;&query node into Rete net. If pmatch occurs in the righthand side of the
; rule, then
X;nodes are linked to tree generated by rule's LHS.
X(defun ipm-cmp-p (name matrix)
X (prog (m bakptrs srhs frhs)
X (prepare-lex matrix)
X (excise-p name)
X (setq bakptrs nil)
X (setq *pcount* (1+ *pcount*))
X (setq *feature-count* 0.)
X(setq *ce-count* 0)
X (setq *vars* nil)
X (setq *ce-vars* nil)
X(setq *rhs-bound-vars* nil)
X(setq *rhs-bound-ce-vars* nil)
X (setq *last-branch* nil)
X (setq m (rest-of-p))
X l1 (and (end-of-p) (\%error '|no '-->' in production| m))
X (cmp-prin)
X (setq bakptrs (cons *last-branch* bakptrs))
X (or (eq '--> (peek-lex)) (go l1))
X (lex)
X(setq srhs (rest-of-p)) ; get righthand side
X(if (setq frhs (cdr (memq '<-- srhs)))
X (setq srhs (remove-frhs srhs)))
X(ipm-check-rhs srhs)
X;note, we change the structure of the &query node to have a tail
X;component. This is the action to take on a failed pattern match
X (link-new-node (list '&query
*feature-count*
X name
X (encode-dope)
X (encode-ce-dope)
X (cons 'progn srhs)
X (cons 'progn frhs)))
X(terpri)
X (putprop name (cdr (nreverse bakptrs)) 'backpointers)
X(putprop name matrix 'production)
X (putprop name *last-node* 'topnode)))
X
X;Modified OPS5 code, sets *compiling-rhs* variable.
X(defun check-rhs (rhs)
X (setq *compiling-rhs* t)
X (mapc (function check-action) rhs)
X (setq *compiling-rhs* nil))
X
X
X;rhs part to be evaluated upon pattern match failure
X
X(defun frhs-part (pnode) (car (last pnode)))
X
X;;returns value of last expression in RHS
X(defun query (qname)
X (ipm-eval-query qname (car (get qname 'pmatches))))
X
X;IPM-EVAL-QUERY: Given a pointer to a query and the associated data,
; this function
X;sets up the appropriate environment to evaluate the RHS of the pattern match.
X;This is a modified eval-rhs from OPS5.
X
X(defun ipm-eval-query (pname data)
X (let ((node (get pname 'topnode))
X (ans nil)
X (saved nil))
X (if (setq saved *in-rhs*) ;in case of recursive call,save system state and
X (save-system-state)) ;set saved flag
X (setq *data-matched* data)
X (setq *p-name* pname)
X (setq *last* nil)
X (setq node (get pname 'topnode))
X (ipm-init-var-mem (var-part node))
X (ipm-init-var-nmatches pname)
X (ipm-init-ce-var-mem (ce-var-part node))
X (setq *in-rhs* t)
X (setq ans
X (if (neq *NMATCHES* 0) ;if match failed, execute failpart, if any
X(eval (rhs-part node))
X(eval (frhs-part node)) ))
X (setq *in-rhs* nil)
X (if saved
X (restore-system-state))
X ans
X))
X
X;map-query is just like query, except that we are performing the
;eval operation for each match. Therefore, some of the initialization
X;must be factored out of ipm-eval-map-query.
X(defun map-query(qname)
X (let* ((node (get qname 'topnode))
X (ans nil)
X (saved nil))
X (if (setq saved *in-rhs*) ;in case of recursive call,save system state and
X (save-system-state)) ;set saved flag
X (setq *p-name* qname)
X (setq *last* nil)
X (setq ans
X (if (> (length (get qname 'pmatches)) 0)
X (mapcar '(lambda(qinstance)
X (ipm-eval-map-query qname qinstance node))
X (get qname 'pmatches))
X (eval (frhs-part node)) ))
X (if saved
X (restore-system-state))
X ans))
X
X(defun ipm-eval-map-query (qname data node)
X (let ((ans))
X (setq *data-matched* data)
X (setq node (get qname 'topnode))
X (ipm-init-var-mem (var-part node))
X (ipm-init-var-nmatches qname)
X (ipm-init-ce-var-mem (ce-var-part node))
X (setq *in-rhs* t)
X (setq ans (eval (rhs-part node)))
X (setq *in-rhs* nil)
X ans
X ))
X
X
X;the variable &nmatches is bound to the number of production
X;matches in each query. Useful for counting applications and
X;deciding if any matches succeeded.
X
X(defun ipm-init-var-nmatches(pname)
X (setq *NMATCHES* (length (get pname 'pmatches)))
X (setq *variable-memory* ;remove previous number of matches
X (remove (assoc '\<NMATCHES\> *variable-memory*) *variable-memory*))
X (setq *variable-memory* ;set up &NMATCHES environ. variable
X (cons (cons '\<NMATCHES\> *NMATCHES*)
X*variable-memory*)))
X
X;More modified OPS5 code. Initializes the variable and ce-variable bindings
X;to be consistent with the results of the pattern match.
X(defun ipm-init-var-mem (vlist)
X (prog (v ind r)
X(or *in-rhs* ;if we're in rhs, then global is already set
X (setq *variable-memory* nil))
X top (and (atom vlist) (return nil))
X (setq v (car vlist))
X (setq ind (cadr vlist))
(setq vlist (cddr vlist))
X (setq r (gelm *data-matched* ind))
X (setq *variable-memory* (cons (cons v r) *variable-memory*))
X (go top)))
X
X(defun ipm-init-ce-var-mem (vlist)
X (prog (v ind r)
X(or *in-rhs* ;if we're in rhs, then global is already set
X (setq *ce-variable-memory* nil))
X top (and (atom vlist) (return nil))
X (setq v (car vlist))
X (setq ind (cadr vlist))
X (setq vlist (cddr vlist))
X (setq r (ce-gelm *data-matched* ind))
X (setq *ce-variable-memory*
X (cons (cons v r) *ce-variable-memory*))
X (go top)))
X
X(defun save-system-state()
X (push-global-variables '*system-state-stack* '*ce-variable-memory*
'*data-matched*
X '*variable-memory* '*NMATCHES* '*p-name* '*in-rhs*))
X
X(defun restore-system-state()
X (pop-global-variables *system-state-stack*))
X
X;changed OPS5 code to accept &query
X(defun link-new-node (r)
X (cond ((not (member (car r) '(&query &p &mem &two &and ¬)))
X (setq *feature-count* (1+ *feature-count*))))
X (setq *virtual-cnt* (1+ *virtual-cnt*))
X (setq *last-node* (link-left *last-node* r)))
X
X(defun ipm-check-rhs (rhs)
X (setq *compiling-rhs* t)
X (mapc (function ipm-check-action) rhs)
X (setq *compiling-rhs* nil))
X
X(defun myreplace(x y)
X (rplaca x (car y))
X (rplacd x (cdr y)))
X
X;This check-action is called by pmatch or map-pmatch macros
X(defun ipm-check-action (x)
X (prog (a)
X (cond ((atom x)
X (%warn '|atomic action| x)
X (return nil)))
X (setq a (setq *action-type* (car x)))
X (cond ((eq a 'bind) (check-bind x))
X ((eq a 'query) nil) ;never happens?
X ((eq a 'map-query) nil) ;never happens?
X ;if we come across an unexpanded pmatch, expand and compile it.
X ;replace with result
X ((eq a 'pmatch) (myreplace x (eval x)))
X ((eq a 'map-pmatch) (myreplace x (eval x)))
((eq a 'cbind) (check-cbind x))
X ((eq a 'make) (check-make x))
X ((eq a 'modify) (check-modify x))
X ((eq a 'remove) (check-remove x))
X ((eq a 'write) (check-write x))
X ((eq a 'call) (check-call x))
X ((eq a 'halt) (check-halt x))
X ((eq a 'openfile) (check-openfile x))
X ((eq a 'closefile) (check-closefile x))
X ((eq a 'default) (check-default x))
X ((eq a 'build) (check-build x))
X (t nil) ;in a pmatch rhs, code is not restricted to OPS rhs actions.
X )))
X
X;This check action is just modified so that pmatch or map-pmatch
X;are acceptable right-hand sides.
X(defun check-action (x)
X (prog (a)
X (cond ((atom x)
X (%warn '|atomic action| x)
X (return nil)))
X (setq a (setq *action-type* (car x)))
X (cond ((eq a 'bind) (check-bind x))
X ((eq a 'query) nil) ;never happens
X ((eq a 'map-query) nil) ;never happens
X ;if we come across an unexpanded pmatch, expand and compile it.
X ;replace with result
X ((eq a 'pmatch) (myreplace x (eval x)))
X ((eq a 'map-pmatch) (myreplace x (eval x)))
X ((eq a 'cbind) (check-cbind x))
X ((eq a 'make) (check-make x))
X ((eq a 'modify) (check-modify x))
X ((eq a 'remove) (check-remove x))
X ((eq a 'write) (check-write x))
X ((eq a 'call) (check-call x))
X ((eq a 'halt) (check-halt x))
X ((eq a 'openfile) (check-openfile x))
X ((eq a 'closefile) (check-closefile x))
X ((eq a 'default) (check-default x))
X ((eq a 'build) (check-build x))
X (t (%warn '|undefined rhs action| a)))))
X
X
X;add-to-wm: modified to return timetag number of item added
X(defun add-to-wm (wme override)
X (prog (fa z part timetag port)
X (setq *critical* t)
X (setq *current-wm* (1+ *current-wm*))
X (and (> *current-wm* *max-wm*) (setq *max-wm* *current-wm*))
X (setq *action-count* (1+ *action-count*))
X (setq fa (wm-hash wme))
X (or (memq fa *wmpart-list*)
X (setq *wmpart-list* (cons fa *wmpart-list*)))
X (setq part (get fa 'wmpart*))
X (cond (override (setq timetag override))
(t (setq timetag *action-count*)))
X (setq z (cons wme timetag))
X (putprop fa (cons z part) 'wmpart*)
X (record-change '=>wm *action-count* wme)
X (match 'new wme)
X (setq *critical* nil)
X (cond ((and *in-rhs* *wtrace*)
X (setq port (trace-file))
X (terpri port)
X (princ '|=>wm: | port)
X (ppelm wme port)))
X (and *in-rhs* *mtrace* (setq *madeby*
X (cons (cons wme *p-name*) *madeby*)))
X (return timetag)))
X
X(defun &old (&rest a) nil) ;a null function used for deleting node
X
X
X;MAKESYM: Does the same thing as gensym, but allows a symbol to be passed, so
X; the resulting symbol is meaningful.
X(defun makesym(x)
X (prog(numb)
X (and (not (setq numb (get x '$cntr)))
X (setq numb 0))
X (putprop x (add1 numb) '$cntr)
X (return (concat x numb))))
X
X;CONCAT: Make a symbol from a number of symbols
X(defun concat(&rest x)
X (do ((lst x (cdr lst))
X (strng nil))
X ((null lst)
X (intern strng))
X (setq strng (concatenate 'string strng (princ-to-string (car lst))))
X ))
X
X;A general purpose gensym function. Input is
X; [atom], output is [atom]N, where N is a unique integer.
X; ie. (newsym baz) ==> baz1
X; (newsym baz) ==> baz2, etc.
X
X(defmacro newsym(x)
X `(makesym ',x))
X
X
X(defun exquery()
X (mapc #'(lambda(q) (eval `(excise ,q))) *qnames*)
X (setq *qnames* nil))
X
X;The following is a minimal test for the opsmods programs.
X;To use it, uncomment it, and load it. The code should load without
X;blowing up. Complaints about atomic actions in RHS are OK, ignore them.
X;Type
X;(setup)
X;(cs) -- foo and baz should be in the conflict set.
;Type (run 1), the program should print out a list of blocks.
X;(run) should continue until only chartreuse blocks are left.
X;While simple, this code tests for nested use of pattern matches,
; recursive calls,
X;and use of pmatch in the rhs of OPS productions.
X;(i-g-v)
X;(literalize block a b c)
X
X
X;(p baz
X; { <a> (block ↑a <colour> ) }
X; (block ↑a <> <colour>)
X; -->
X; (pmatch (block ↑a <> <colour> )
X; -->
X; (find-block-colors ?<colour> )
X; (oremove <a> ))
X; (make block ↑a chartreuse))
X
X;Test for recursive use of pmatch. (find-block-colors uses map-pmatch and
X;appears in a RHS of another pmatch)
X;(defun rtest(a )
X; ?(pmatch (args a )
X; (block ↑a <a> <numb>)
X; -->
X; (find-block-colors 'green)
X; (format t "Block color ~a is ~a~%" ?<a> ?<numb>)))
X
X;(defun find-block-colors (color)
X; ?(map-pmatch (args color)
X; (block ↑a <color> <numb>)
X; -->
X; (format t "~%Find-block-colors ~a ~a~%" ?<color> ?<numb>)))
X
X;(defun setup()
X; (setq *in-rhs* nil)
X; (oremove *)
X; (make block ↑a green 1)
X; (make block ↑a green 2)
X; (make block ↑a green 3)
X; (make block ↑a green 4)
X; (make block ↑a green 5)
X; (make block ↑a red 6)
X; (make block ↑a red 7)
X; (make block ↑a yellow 8)
X; (make block ↑a blue 9)
X; )
X
X
XCLSUP.LIS
X
X;Common Lisp Support Functions:
X;These functions are not defined in vanilla Common Lisp, but are used
X;in the OPSMODS.l code and in OPS5.
X
X(defun putprop(name val att)
X (setf (get name att) val))
X
X(defun memq(obj lis)
X (member obj lis :test #'eq))
X
X(defun fix(num)
X (round num))
X
X
X(defun assq(item alist)
X (assoc item alist :test #'eq))
X
X(defun ncons(x) (cons x nil))
X
X(defun neq(x y) (not (eq x y)))
X
X(defun delq(obj list)
X (delete obj list :test #'eq))
X
X(defmacro comment(&optional &rest x) nil) ;comment is a noop
X
X(defun plus(x y)
X (+ x y))
X
X(defun quotient(x y)
X (/ x y))
X
X(defun flatc(x)
X (length (princ-to-string x)))
X
X
X
XCOMMON.OPS
X
X; VPS2 -- Interpreter for OPS5
X;
X; Copyright (C) 1979, 1980, 1981
X; Charles L. Forgy, Pittsburgh, Pennsylvania
X
X
X
X; Users of this interpreter are requested to contact
X
X;
X; Charles Forgy
X; Computer Science Department
X; Carnegie-Mellon University
X; Pittsburgh, PA 15213
X; or
X; Forgy@CMUA
X;
X; so that they can be added to the mailing list for OPS5. The mailing list
X; is needed when new versions of the interpreter or manual are released.
X
X
X
X;;; Definitions
X
X#+ vax (defun putprop(name val att)
X (setf (get name att) val))
X
X
X
X(proclaim '(special *matrix* *feature-count* *pcount* *vars* *cur-vars*
X *curcond* *subnum* *last-node* *last-branch* *first-node*
X *sendtocall* *flag-part* *alpha-flag-part* *data-part*
X *alpha-data-part* *ce-vars* *virtual-cnt* *real-cnt*
X *current-token* *c1* *c2* *c3* *c4* *c5* *c6* *c7* *c8* *c9*
X *c10* *c11* *c12* *c13* *c14* *c15* *c16* *c17* *c18* *c19*
X *c20* *c21* *c22* *c23* *c24* *c25* *c26* *c27* *c28* *c29*
X *c30* *c31* *c32* *c33* *c34* *c35* *c36* *c37* *c38* *c39*
X *c40* *c41* *c42* *c43* *c44* *c45* *c46* *c47* *c48* *c49*
X *c50* *c51* *c52* *c53* *c54* *c55* *c56* *c57* *c58* *c59*
X *c60* *c61* *c62* *c63* *c64* *record-array* *result-array*
X *max-cs* *total-cs* *limit-cs* *cr-temp* *side*
X *conflict-set* *halt-flag* *phase* *critical*
X *cycle-count* *total-token* *max-token* *refracts*
X *limit-token* *total-wm* *current-wm* *max-wm*
X *action-count* *wmpart-list* *wm* *data-matched* *p-name*
X *variable-memory* *ce-variable-memory*
X *max-index* ; number of right-most field in wm element
X *next-index* *size-result-array* *rest* *build-trace* *last*
X *ptrace* *wtrace* *in-rhs* *recording* *accept-file* *trace-file*
X *mtrace* *madeby* ; used to trace and record makers of elements
X *write-file* *record-index* *max-record-index* *old-wm*
X *record* *filters* *break-flag* *strategy* *remaining-cycles*
X *wm-filter* *rhs-bound-vars* *rhs-bound-ce-vars* *ppline*
X *ce-count* *brkpts* *class-list* *buckets* *action-type*
X *literals* ;stores literal definitions
X *pnames* ;stores production names
X *externals* ;tracks external declarations
X *vector-attributes* ;list of vector-attributes
X ))
X
X;(declare (localf ce-gelm gelm peek-sublex sublex
X; eval-nodelist sendto and-left and-right not-left not-right
X; top-levels-eq add-token real-add-token remove-old
X; remove-old-num remove-old-no-num removecs insertcs dsort
X; best-of best-of* conflict-set-compare =alg ))
X
X
X;;; Functions that were revised so that they would compile efficiently
X
X
X;* The function == is machine dependent\!
X;* This function compares small integers for equality. It uses EQ
X;* so that it will be fast, and it will consequently not work on all
X;* Lisps. It works in Franz Lisp for integers in [-128, 127]
X
X
X;(defun == (&rest z) (= (cadr z) (caddr z)))
X(defun == (x y) (= x y))
X
X; =ALG returns T if A and B are algebraicly equal.
X
X(defun =alg (a b) (= a b))
X
X(defmacro fast-symeval (&rest z)
X `(cond ((eq ,(car z) '*c1*) *c1*)
X ((eq ,(car z) '*c2*) *c2*)
X ((eq ,(car z) '*c3*) *c3*)
X ((eq ,(car z) '*c4*) *c4*)
X ((eq ,(car z) '*c5*) *c5*)
X ((eq ,(car z) '*c6*) *c6*)
X ((eq ,(car z) '*c7*) *c7*)
X (t (eval ,(car z))) ))
X
X; getvector and putvector are fast routines for using one-dimensional
X; arrays. these routines do no checking; they assume
X; 1. the array is a vector with 0 being the index of the first
X; element
X; 2. the vector holds arbitrary list values
X;defun versions are useful for tracing
X
X; Example call: (putvector array index value)
X
X(defmacro putvector (array_ref ind var)
X `(setf (aref ,array_ref ,ind) ,var))
X
X;(defun putvector (array_ref ind var)
X; (setf (aref array_ref ind) var))
X
X; Example call: (getvector name index)
X
X;(defmacro getvector(&rest z)
X; (list 'cxr (caddr z) (cadr z)))
X
X(defmacro getvector(array_ref ind)
X `(aref ,array_ref ,ind))
X
X;(defun getvector (array_ref ind)
X ; (aref array_ref ind))
X
X(defun ce-gelm (x k)
X (prog nil
X loop (and (== k 1.) (return (car x)))
X (setq k (1- k))
X (setq x (cdr x))
X (go loop)))
X
X; The loops in gelm were unwound so that fewer calls on DIFFERENCE
X; would be needed
X
X(defun gelm (x k)
X (prog (ce sub)
X (setq ce (floor (/ k 10000)))
X (setq sub (- k (* ce 10000)))
X celoop (and (== ce 0) (go ph2))
X (setq x (cdr x))
X (and (== ce 1) (go ph2))
X (setq x (cdr x))
X (and (== ce 2) (go ph2))
X (setq x (cdr x))
X (and (== ce 3) (go ph2))
X (setq x (cdr x))
X (and (== ce 4) (go ph2))
X (setq ce (- ce 4))
X (go celoop)
X ph2 (setq x (car x))
X subloop (and (== sub 0) (go finis))
X (setq x (cdr x))
X (and (== sub 1) (go finis))
X (setq x (cdr x))
X (and (== sub 2) (go finis))
X (setq x (cdr x))
X (and (== sub 3) (go finis))
X (setq x (cdr x))
X (and (== sub 4) (go finis))
X (setq x (cdr x))
X (and (== sub 5) (go finis))
X (setq x (cdr x))
X (and (== sub 6) (go finis))
X (setq x (cdr x))
X (and (== sub 7) (go finis))
X (setq x (cdr x))
X (and (== sub 8) (go finis))
X (setq sub (- sub 8))
X (go subloop)
X finis (return (car x))))
X
X
------------------------------
End of AIList Digest
********************
∂30-Jan-87 0507 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #24
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 30 Jan 87 05:07:42 PST
Date: Thu 29 Jan 1987 23:06-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #24
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 30 Jan 1987 Volume 5 : Issue 24
Today's Topics:
Code - AI Expert Magazine Sources (Part 5 of 22)
----------------------------------------------------------------------
Date: 19 Jan 87 03:36:40 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: AI Expert Magazine Sources (Part 5 of 22)
X;;; Utility functions
X
X
X
X(defun printline (x) (mapc (function printline*) x))
X
X(defun printline* (y) (princ '| |) (print y))
X
X(defun printlinec (x) (mapc (function printlinec*) x))
X
X(defun printlinec* (y) (princ '| |) (princ y))
X
X; intersect two lists using eq for the equality test
X
X(defun interq (x y)
X (intersection x y :test #'eq))
X
X(defun enter (x ll)
X (and (not (member x ll :test #'equal))
X (push x ll)))
X
X
X;Hack read-macro tables to accept single characters -- right out of CL book.
X(defun single-macro-character (stream char)
X (declare (ignore stream))
X (character char))
X
X(defun i-g-v nil
X (prog (x)
X (set-macro-character #\{ #'single-macro-character )
X (set-macro-character #\} #'single-macro-character )
X (set-macro-character #\↑ #'single-macro-character )
X; (setsyntax '\{ 66.) ;These are already normal characters in CL
X; (setsyntax '\} 66.)
X; (setsyntax '↑ 66.)
X (setq *buckets* 64.) ; OPS5 allows 64 named slots
X (setq *accept-file* nil)
X (setq *write-file* nil)
X (setq *trace-file* nil)
X (and (boundp '*class-list*)
X (mapc #'(lambda(class) (putprop class nil 'att-list)) *class-list*))
X (setq *class-list* nil)
X (setq *brkpts* nil)
X (setq *strategy* 'lex)
X (setq *in-rhs* nil)
X (setq *ptrace* t)
X (setq *wtrace* nil)
X (setq *mtrace* t) ; turn on made-by tracing
X (setq *madeby* nil) ; record makers of wm elements
X (setq *recording* nil)
X (setq *refracts* nil)
X (setq *real-cnt* (setq *virtual-cnt* 0.))
X (setq *max-cs* (setq *total-cs* 0.))
X (setq *limit-token* 1000000.)
X (setq *limit-cs* 1000000.)
X (setq *critical* nil)
X (setq *build-trace* nil)
X (setq *wmpart-list* nil)
X (setq *pnames* nil)
X (setq *literals* nil) ; records literal definitions
X (setq *externals* nil) ; records external definitions
X (setq *vector-attributes* nil) ;records vector attributes
X (setq *size-result-array* 127.)
X (setq *result-array* (make-array 128))
X (setq *record-array* (make-array 128))
X (setq x 0)
X (setq *pnames* nil) ; list of production names
X loop (putvector *result-array* x nil)
X (setq x (1+ x))
X (and (not (> x *size-result-array*)) (go loop))
X (make-bottom-node)
X (setq *pcount* 0.)
X (initialize-record)
X (setq *cycle-count* (setq *action-count* 0.))
X (setq *total-token*
X (setq *max-token* (setq *current-token* 0.)))
X (setq *total-cs* (setq *max-cs* 0.))
X (setq *total-wm* (setq *max-wm* (setq *current-wm* 0.)))
X (setq *conflict-set* nil)
X (setq *wmpart-list* nil)
X (setq *p-name* nil)
X (setq *remaining-cycles* 1000000)
X))
X
X; if the size of result-array changes, change the line in i-g-v which
X; sets the value of *size-result-array*
X
X(defun %warn (what where)
X (prog nil
X (terpri)
X (princ '?)
X (and *p-name* (princ *p-name*))
X (princ '|..|)
X (princ where)
X (princ '|..|)
X (princ what)
X (return where)))
X
X(defun %error (what where)
X (%warn what where)
X (throw '!error! nil))
X
X
X(defun top-levels-eq (la lb)
X (prog nil
X lx (cond ((eq la lb) (return t))
X ((null la) (return nil))
X ((null lb) (return nil))
X ((not (eq (car la) (car lb))) (return nil)))
X (setq la (cdr la))
X (setq lb (cdr lb))
X (go lx)))
X
X
X;;; LITERAL and LITERALIZE
X
X(defmacro literal (&rest z)
X `(prog (atm val old args)
X (setq args ',z)
X top (and (atom args) (return 'bound))
X (or (eq (cadr args) '=) (return (%warn '|wrong format| args)))
X (setq atm (car args))
X (setq val (caddr args))
X (setq args (cdddr args))
X (cond ((not (numberp val))
X (%warn '|can bind only to numbers| val))
X ((or (not (symbolp atm)) (variablep atm))
X (%warn '|can bind only constant atoms| atm))
X ((and (setq old (literal-binding-of atm)) (not (equal old val)))
X (%warn '|attempt to rebind attribute| atm))
X (t (putprop atm val 'ops-bind )))
X (go top)))
X
X(defmacro literalize (&rest l)
X `(prog (class-name atts)
X (setq class-name (car ',l))
X (cond ((have-compiled-production)
X (%warn '|literalize called after p| class-name)
X (return nil))
X ((get class-name 'att-list)
X (%warn '|attempt to redefine class| class-name)
X (return nil)))
X (setq *class-list* (cons class-name *class-list*))
X (setq atts (remove-duplicates (cdr ',l)))
X (test-attribute-names atts)
X (mark-conflicts atts atts)
X (putprop class-name atts 'att-list)))
X
X(defmacro vector-attribute (&rest l)
X `(cond ((have-compiled-production)
X (%warn '|vector-attribute called after p| ',l))
X (t
X (test-attribute-names ',l)
X (mapc (function vector-attribute2) ',l))))
X
X(defun vector-attribute2 (att) (putprop att t 'vector-attribute)
X (setq *vector-attributes*
X (enter att *vector-attributes*)))
X
X(defun is-vector-attribute (att) (get att 'vector-attribute))
X
X(defun test-attribute-names (l)
X (mapc (function test-attribute-names2) l))
X
X(defun test-attribute-names2 (atm)
X (cond ((or (not (symbolp atm)) (variablep atm))
X (%warn '|can bind only constant atoms| atm))))
X
X(defun finish-literalize nil
X (cond ((not (null *class-list*))
X (mapc (function note-user-assigns) *class-list*)
X (mapc (function assign-scalars) *class-list*)
X (mapc (function assign-vectors) *class-list*)
X (mapc (function put-ppdat) *class-list*)
X (mapc (function erase-literal-info) *class-list*)
X (setq *class-list* nil)
X (setq *buckets* nil))))
X
X(defun have-compiled-production nil (not (zerop *pcount*)))
X
X(defun put-ppdat (class)
X (prog (al att ppdat)
X (setq ppdat nil)
X (setq al (get class 'att-list))
X top (cond ((not (atom al))
X (setq att (car al))
X (setq al (cdr al))
X (setq ppdat
X (cons (cons (literal-binding-of att) att)
X ppdat))
X (go top)))
X (putprop class ppdat 'ppdat)))
X
X; note-user-assigns and note-user-vector-assigns are needed only when
X; literal and literalize are both used in a program. They make sure that
X; the assignments that are made explicitly with literal do not cause problems
X; for the literalized classes.
X
X(defun note-user-assigns (class)
X (mapc (function note-user-assigns2) (get class 'att-list)))
X
X(defun note-user-assigns2 (att)
X (prog (num conf buck clash)
X (setq num (literal-binding-of att))
X (and (null num) (return nil))
X (setq conf (get att 'conflicts))
X (setq buck (store-binding att num))
X (setq clash (find-common-atom buck conf))
X (and clash
X (%warn '|attributes in a class assigned the same number|
X (cons att clash)))
X (return nil)))
X
X(defun note-user-vector-assigns (att given needed)
X (and (> needed given)
X (%warn '|vector attribute assigned too small a value in literal| att)))
X
X(defun assign-scalars (class)
X (mapc (function assign-scalars2) (get class 'att-list)))
X
X(defun assign-scalars2 (att)
X (prog (tlist num bucket conf)
X (and (literal-binding-of att) (return nil))
X (and (is-vector-attribute att) (return nil))
X (setq tlist (buckets))
X (setq conf (get att 'conflicts))
X top (cond ((atom tlist)
X (%warn '|could not generate a binding| att)
X (store-binding att -1.)
X (return nil)))
X (setq num (caar tlist))
X (setq bucket (cdar tlist))
X (setq tlist (cdr tlist))
X (cond ((disjoint bucket conf) (store-binding att num))
X (t (go top)))))
X
X(defun assign-vectors (class)
X (mapc (function assign-vectors2) (get class 'att-list)))
X
X(defun assign-vectors2 (att)
X (prog (big conf new old need)
X (and (not (is-vector-attribute att)) (return nil))
X (setq big 1.)
X (setq conf (get att 'conflicts))
X top (cond ((not (atom conf))
X (setq new (car conf))
X (setq conf (cdr conf))
X (cond ((is-vector-attribute new)
X (%warn '|class has two vector attributes|
X (list att new)))
X (t (setq big (max (literal-binding-of new) big))))
X (go top)))
X (setq need (1+ big))
X (setq old (literal-binding-of att))
X (cond (old (note-user-vector-assigns att old need))
X (t (store-binding att need)))
X (return nil)))
X
X(defun disjoint (la lb) (not (find-common-atom la lb)))
X
X(defun find-common-atom (la lb)
X (prog nil
X top (cond ((null la) (return nil))
X ((member (car la) lb :test #'eq) (return (car la)))
X (t (setq la (cdr la)) (go top)))))
X
X(defun mark-conflicts (rem all)
X (cond ((not (null rem))
X (mark-conflicts2 (car rem) all)
X (mark-conflicts (cdr rem) all))))
X
X(defun mark-conflicts2 (atm lst)
X (prog (l)
X (setq l lst)
X top (and (atom l) (return nil))
X (conflict atm (car l))
X (setq l (cdr l))
X (go top)))
X
X(defun conflict (a b)
X (prog (old)
X (setq old (get a 'conflicts))
X (and (not (eq a b))
X (not (member b old :test #'eq))
X (putprop a (cons b old) 'conflicts ))))
X
X;(defun remove-duplicates (lst)
X; (cond ((atom lst) nil)
X; ((member (car lst) (cdr lst) :test #'eq)
(remove-duplicates (cdr lst)))
X; (t (cons (car lst) (remove-duplicates (cdr lst))))))
X
X(defun literal-binding-of (name) (get name 'ops-bind))
X
X(defun store-binding (name lit)
X (putprop name lit 'ops-bind)
X (add-bucket name lit))
X
X(defun add-bucket (name num)
X (prog (buc)
X (setq buc (assoc num (buckets)))
X (and (not (member name buc :test #'eq))
X (rplacd buc (cons name (cdr buc))))
X (return buc)))
X
X(defun buckets nil
X (and (atom *buckets*) (setq *buckets* (make-nums *buckets*)))
X *buckets*)
X
X(defun make-nums (k)
X (prog (nums)
X (setq nums nil)
X l (and (< k 2.) (return nums))
X (setq nums (cons (cons k nil) nums))
X (setq k (1- k))
X (go l)))
X
X;(defun erase-literal-info (class)
X; (mapc (function erase-literal-info2) (get class 'att-list))
X; (remprop class 'att-list))
X
X; modified to record literal info in the variable *literals*
X(defun erase-literal-info (class)
X (setq *literals*
X (cons (cons class (get class 'att-list)) *literals*))
X (mapc (function erase-literal-info2) (get class 'att-list))
X (remprop class 'att-list))
X
X
X(defun erase-literal-info2 (att) (remprop att 'conflicts))
X
X
X;;; LHS Compiler
X
X(defmacro p (&rest z)
X `(progn
X (finish-literalize)
X (princ '*)
X ;(drain);drain probably drains a line feed
X (compile-production (car ',z) (cdr ',z))))
X
X(defun compile-production (name matrix)
X (prog (erm)
X (setq *p-name* name)
X (setq erm (catch '!error! (cmp-p name matrix) ))
X ; following line is modified to save production name on *pnames*
X (and (null erm) (setq *pnames* (enter name *pnames*)))
X (setq *p-name* nil)
X (return erm)))
X
X(defun peek-lex nil (car *matrix*))
X
X(defun lex nil
X (prog2 nil (car *matrix*) (setq *matrix* (cdr *matrix*))))
X
X(defun end-of-p nil (atom *matrix*))
X
X(defun rest-of-p nil *matrix*)
X
X(defun prepare-lex (prod) (setq *matrix* prod))
X
X
X(defun peek-sublex nil (car *curcond*))
X
X(defun sublex nil
X (prog2 nil (car *curcond*) (setq *curcond* (cdr *curcond*))))
X
X(defun end-of-ce nil (atom *curcond*))
X
X(defun rest-of-ce nil *curcond*)
X
X(defun prepare-sublex (ce) (setq *curcond* ce))
X
X(defun make-bottom-node nil (setq *first-node* (list '&bus nil)))
X
X(defun cmp-p (name matrix)
X (prog (m bakptrs)
X (cond ((or (null name) (listp name))
X (%error '|illegal production name| name))
X ((equal (get name 'production) matrix)
X (return nil)))
X (prepare-lex matrix)
X (excise-p name)
X (setq bakptrs nil)
X (setq *pcount* (1+ *pcount*))
X (setq *feature-count* 0.)
X (setq *ce-count* 0)
X (setq *vars* nil)
X (setq *ce-vars* nil)
X (setq *rhs-bound-vars* nil)
X (setq *rhs-bound-ce-vars* nil)
X (setq *last-branch* nil)
X (setq m (rest-of-p))
X l1 (and (end-of-p) (%error '|no '-->' in production| m))
X (cmp-prin)
X (setq bakptrs (cons *last-branch* bakptrs))
X (or (eq '--> (peek-lex)) (go l1))
X (lex)
X (check-rhs (rest-of-p))
X (link-new-node (list '&p
X *feature-count*
X name
X (encode-dope)
X (encode-ce-dope)
X (cons 'progn (rest-of-p))))
X (putprop name (cdr (nreverse bakptrs)) 'backpointers )
X (putprop name matrix 'production)
X (putprop name *last-node* 'topnode)))
X
X(defun rating-part (pnode) (cadr pnode))
X
X(defun var-part (pnode) (car (cdddr pnode)))
X
X(defun ce-var-part (pnode) (cadr (cdddr pnode)))
X
X(defun rhs-part (pnode) (caddr (cdddr pnode)))
X
X(defun excise-p (name)
X (cond ((and (symbolp name) (get name 'topnode))
X (printline (list name 'is 'excised))
X (setq *pcount* (1- *pcount*))
X (remove-from-conflict-set name)
X (kill-node (get name 'topnode))
X (setq *pnames* (delete name *pnames* :test #'eq))
X (remprop name 'production)
X (remprop name 'backpointers)
X (remprop name 'topnode))))
X
X(defun kill-node (node)
X (prog nil
X top (and (atom node) (return nil))
X (rplaca node '&old)
X (setq node (cdr node))
X (go top)))
X
X(defun cmp-prin nil
X (prog nil
X (setq *last-node* *first-node*)
X (cond ((null *last-branch*) (cmp-posce) (cmp-nobeta))
X ((eq (peek-lex) '-) (cmp-negce) (cmp-not))
X (t (cmp-posce) (cmp-and)))))
X
X(defun cmp-negce nil (lex) (cmp-ce))
X
X(defun cmp-posce nil
X (setq *ce-count* (1+ *ce-count*))
X (cond ((eq (peek-lex) #\{) (cmp-ce+cevar))
X (t (cmp-ce))))
X
X(defun cmp-ce+cevar nil
X (prog (z)
X (lex)
X (cond ((atom (peek-lex)) (cmp-cevar) (cmp-ce))
X (t (cmp-ce) (cmp-cevar)))
X (setq z (lex))
X (or (eq z #\}) (%error '|missing '}'| z))))
X
X(defun new-subnum (k)
X (or (numberp k) (%error '|tab must be a number| k))
X (setq *subnum* (round k)))
X
X(defun incr-subnum nil (setq *subnum* (1+ *subnum*)))
X
X(defun cmp-ce nil
X (prog (z)
X (new-subnum 0.)
X (setq *cur-vars* nil)
X (setq z (lex))
X (and (atom z)
X (%error '|atomic conditions are not allowed| z))
X (prepare-sublex z)
X la (and (end-of-ce) (return nil))
X (incr-subnum)
X (cmp-element)
X (go la)))
X
X(defun cmp-element nil
X (and (eq (peek-sublex) #\↑) (cmp-tab))
X (cond ((eq (peek-sublex) '#\{) (cmp-product))
X (t (cmp-atomic-or-any))))
X
X(defun cmp-atomic-or-any nil
X (cond ((eq (peek-sublex) '<<) (cmp-any))
X (t (cmp-atomic))))
X
X(defun cmp-any nil
X (prog (a z)
X (sublex)
X (setq z nil)
X la (cond ((end-of-ce) (%error '|missing '>>'| a)))
X (setq a (sublex))
X (cond ((not (eq '>> a)) (setq z (cons a z)) (go la)))
X (link-new-node (list '&any nil (current-field) z))))
X
X
X(defun cmp-tab nil
X (prog (r)
X (sublex)
X (setq r (sublex))
X (setq r ($litbind r))
X (new-subnum r)))
X
X(defun $litbind (x)
X (prog (r)
X (cond ((and (symbolp x) (setq r (literal-binding-of x)))
X (return r))
X (t (return x)))))
X
X(defun get-bind (x)
X (prog (r)
X (cond ((and (symbolp x) (setq r (literal-binding-of x)))
X (return r))
X (t (return nil)))))
X
X(defun cmp-atomic nil
X (prog (test x)
X (setq x (peek-sublex))
X (cond ((eq x '=) (setq test 'eq) (sublex))
X ((eq x '<>) (setq test 'ne) (sublex))
X ((eq x '<) (setq test 'lt) (sublex))
X ((eq x '<=) (setq test 'le) (sublex))
X ((eq x '>) (setq test 'gt) (sublex))
X ((eq x '>=) (setq test 'ge) (sublex))
X ((eq x '<=>) (setq test 'xx) (sublex))
X (t (setq test 'eq)))
X (cmp-symbol test)))
X
X(defun cmp-product nil
X (prog (save)
X (setq save (rest-of-ce))
X (sublex)
X la (cond ((end-of-ce)
X (cond ((member #\} save)
X (%error '|wrong contex for '}'| save))
X (t (%error '|missing '}'| save))))
X ((eq (peek-sublex) #\}) (sublex) (return nil)))
X (cmp-atomic-or-any)
X (go la)))
X
X(defun variablep (x) (and (symbolp x) (char-equal
(char (symbol-name x) 0) #\<)))
X
X(defun cmp-symbol (test)
X (prog (flag)
X (setq flag t)
X (cond ((eq (peek-sublex) '//) (sublex) (setq flag nil)))
X (cond ((and flag (variablep (peek-sublex)))
X (cmp-var test))
X ((numberp (peek-sublex)) (cmp-number test))
X ((symbolp (peek-sublex)) (cmp-constant test))
X (t (%error '|unrecognized symbol| (sublex))))))
X
X(defun concat3(x y z)
X (intern (format nil "~s~s~s" x y z)))
X
X(defun cmp-constant (test)
X (or (member test '(eq ne xx) )
X (%error '|non-numeric constant after numeric predicate| (sublex)))
X (link-new-node (list (concat3 't test 'a)
X nil
X (current-field)
X (sublex))))
X
X
X(defun cmp-number (test)
X (link-new-node (list (concat3 't test 'n)
X nil
X (current-field)
X (sublex))))
X
X(defun current-field nil (field-name *subnum*))
------------------------------
End of AIList Digest
********************
∂30-Jan-87 1230 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #25
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 30 Jan 87 12:30:14 PST
Date: Thu 29 Jan 1987 23:10-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #25
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 30 Jan 1987 Volume 5 : Issue 25
Today's Topics:
Code - AI Expert Magazine Sources (Part 6 of 22)
----------------------------------------------------------------------
Date: 19 Jan 87 03:36:40 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: AI Expert Magazine Sources (Part 6 of 22)
X
X(defun field-name (num)
X (cond ((= num 1.) '*c1*)
X ((= num 2.) '*c2*)
X ((= num 3.) '*c3*)
X ((= num 4.) '*c4*)
X ((= num 5.) '*c5*)
X ((= num 6.) '*c6*)
X ((= num 7.) '*c7*)
X ((= num 8.) '*c8*)
X ((= num 9.) '*c9*)
X ((= num 10.) '*c10*)
X ((= num 11.) '*c11*)
X ((= num 12.) '*c12*)
X ((= num 13.) '*c13*)
X ((= num 14.) '*c14*)
X ((= num 15.) '*c15*)
X ((= num 16.) '*c16*)
X ((= num 17.) '*c17*)
X ((= num 18.) '*c18*)
X ((= num 19.) '*c19*)
X ((= num 20.) '*c20*)
X ((= num 21.) '*c21*)
X ((= num 22.) '*c22*)
X ((= num 23.) '*c23*)
X ((= num 24.) '*c24*)
X ((= num 25.) '*c25*)
X ((= num 26.) '*c26*)
X ((= num 27.) '*c27*)
X ((= num 28.) '*c28*)
X ((= num 29.) '*c29*)
X ((= num 30.) '*c30*)
X ((= num 31.) '*c31*)
X ((= num 32.) '*c32*)
X ((= num 33.) '*c33*)
X ((= num 34.) '*c34*)
X ((= num 35.) '*c35*)
X ((= num 36.) '*c36*)
X ((= num 37.) '*c37*)
X ((= num 38.) '*c38*)
X ((= num 39.) '*c39*)
X ((= num 40.) '*c40*)
X ((= num 41.) '*c41*)
X ((= num 42.) '*c42*)
X ((= num 43.) '*c43*)
X ((= num 44.) '*c44*)
X ((= num 45.) '*c45*)
X ((= num 46.) '*c46*)
X ((= num 47.) '*c47*)
X ((= num 48.) '*c48*)
X ((= num 49.) '*c49*)
X ((= num 50.) '*c50*)
X ((= num 51.) '*c51*)
X ((= num 52.) '*c52*)
X ((= num 53.) '*c53*)
X ((= num 54.) '*c54*)
X ((= num 55.) '*c55*)
X ((= num 56.) '*c56*)
X ((= num 57.) '*c57*)
X ((= num 58.) '*c58*)
X ((= num 59.) '*c59*)
X ((= num 60.) '*c60*)
X ((= num 61.) '*c61*)
X ((= num 62.) '*c62*)
X ((= num 63.) '*c63*)
X ((= num 64.) '*c64*)
X (t (%error '|condition is too long| (rest-of-ce)))))
X
X
X;;; Compiling variables
X;
X;
X;
X; *cur-vars* are the variables in the condition element currently
X; being compiled. *vars* are the variables in the earlier condition
X; elements. *ce-vars* are the condition element variables. note
X; that the interpreter will not confuse condition element and regular
X; variables even if they have the same name.
X;
X; *cur-vars* is a list of triples: (name predicate subelement-number)
X; eg: ( (<x> eq 3)
X; (<y> ne 1)
X; . . . )
X;
X; *vars* is a list of triples: (name ce-number subelement-number)
X; eg: ( (<x> 3 3)
X; (<y> 1 1)
X; . . . )
X;
X; *ce-vars* is a list of pairs: (name ce-number)
X; eg: ( (ce1 1)
X; (<c3> 3)
X; . . . )
X
X(defun var-dope (var) (assoc var *vars* :test #'eq))
X
X(defun ce-var-dope (var) (assoc var *ce-vars* :test #'eq))
X
X(defun cmp-var (test)
X (prog (old name)
X (setq name (sublex))
X (setq old (assoc name *cur-vars* :test #'eq))
X (cond ((and old (eq (cadr old) 'eq))
X (cmp-old-eq-var test old))
X ((and old (eq test 'eq)) (cmp-new-eq-var name old))
X (t (cmp-new-var name test)))))
X
X(defun cmp-new-var (name test)
X (setq *cur-vars* (cons (list name test *subnum*) *cur-vars*)))
X
X(defun cmp-old-eq-var (test old)
X (link-new-node (list (concat3 't test 's)
X nil
X (current-field)
X (field-name (caddr old)))))
X
X(defun cmp-new-eq-var (name old)
X (prog (pred next)
X (setq *cur-vars* (delete old *cur-vars* :test #'eq))
X (setq next (assoc name *cur-vars* :test #'eq))
X (cond (next (cmp-new-eq-var name next))
X (t (cmp-new-var name 'eq)))
X (setq pred (cadr old))
X (link-new-node (list (concat3 't pred 's)
X nil
X (field-name (caddr old))
X (current-field)))))
X
X(defun cmp-cevar nil
X (prog (name old)
X (setq name (lex))
X (setq old (assoc name *ce-vars* :test #'eq))
X (and old
X (%error '|condition element variable used twice| name))
X (setq *ce-vars* (cons (list name 0.) *ce-vars*))))
X
X(defun cmp-not nil (cmp-beta '¬))
X
X(defun cmp-nobeta nil (cmp-beta nil))
X
X(defun cmp-and nil (cmp-beta '&and))
X
X(defun cmp-beta (kind)
X (prog (tlist vdope vname vpred vpos old)
X (setq tlist nil)
X la (and (atom *cur-vars*) (go lb))
X (setq vdope (car *cur-vars*))
X (setq *cur-vars* (cdr *cur-vars*))
X (setq vname (car vdope))
X (setq vpred (cadr vdope))
X (setq vpos (caddr vdope))
X (setq old (assoc vname *vars* :test #'eq))
X (cond (old (setq tlist (add-test tlist vdope old)))
X ((not (eq kind '¬)) (promote-var vdope)))
X (go la)
X lb (and kind (build-beta kind tlist))
X (or (eq kind '¬) (fudge))
X (setq *last-branch* *last-node*)))
X
X(defun add-test (list new old)
X (prog (ttype lloc rloc)
X (setq *feature-count* (1+ *feature-count*))
X (setq ttype (concat3 't (cadr new) 'b))
X (setq rloc (encode-singleton (caddr new)))
X (setq lloc (encode-pair (cadr old) (caddr old)))
X (return (cons ttype (cons lloc (cons rloc list))))))
X
X; the following two functions encode indices so that gelm can
X; decode them as fast as possible
X
X(defun encode-pair (a b) (+ (* 10000. (1- a)) (1- b)))
X
X(defun encode-singleton (a) (1- a))
X
X(defun promote-var (dope)
X (prog (vname vpred vpos new)
X (setq vname (car dope))
X (setq vpred (cadr dope))
X (setq vpos (caddr dope))
X (or (eq 'eq vpred)
X (%error '|illegal predicate for first occurrence|
X (list vname vpred)))
X (setq new (list vname 0. vpos))
X (setq *vars* (cons new *vars*))))
X
X(defun fudge nil
X (mapc (function fudge*) *vars*)
X (mapc (function fudge*) *ce-vars*))
X
X(defun fudge* (z)
X (prog (a) (setq a (cdr z)) (rplaca a (1+ (car a)))))
X
X(defun build-beta (type tests)
X (prog (rpred lpred lnode lef)
X (link-new-node (list '&mem nil nil (protomem)))
X (setq rpred *last-node*)
X (cond ((eq type '&and)
X (setq lnode (list '&mem nil nil (protomem))))
X (t (setq lnode (list '&two nil nil))))
X (setq lpred (link-to-branch lnode))
X (cond ((eq type '&and) (setq lef lpred))
X (t (setq lef (protomem))))
X (link-new-beta-node (list type nil lef rpred tests))))
X
X(defun protomem nil (list nil))
X
X(defun memory-part (mem-node) (car (cadddr mem-node)))
X
X(defun encode-dope nil
X (prog (r all z k)
X (setq r nil)
X (setq all *vars*)
X la (and (atom all) (return r))
X (setq z (car all))
X (setq all (cdr all))
X (setq k (encode-pair (cadr z) (caddr z)))
X (setq r (cons (car z) (cons k r)))
X (go la)))
X
X(defun encode-ce-dope nil
X (prog (r all z k)
X (setq r nil)
X (setq all *ce-vars*)
X la (and (atom all) (return r))
X (setq z (car all))
X (setq all (cdr all))
X (setq k (cadr z))
X (setq r (cons (car z) (cons k r)))
X (go la)))
X
X
X
X;;; Linking the nodes
X
X(defun link-new-node (r)
X (cond ((not (member (car r) '(&p &mem &two &and ¬)))
X (setq *feature-count* (1+ *feature-count*))))
X (setq *virtual-cnt* (1+ *virtual-cnt*))
X (setq *last-node* (link-left *last-node* r)))
X
X(defun link-to-branch (r)
X (setq *virtual-cnt* (1+ *virtual-cnt*))
X (setq *last-branch* (link-left *last-branch* r)))
X
X(defun link-new-beta-node (r)
X (setq *virtual-cnt* (1+ *virtual-cnt*))
X (setq *last-node* (link-both *last-branch* *last-node* r))
X (setq *last-branch* *last-node*))
X
X(defun link-left (pred succ)
X (prog (a r)
X (setq a (left-outs pred))
X (setq r (find-equiv-node succ a))
X (and r (return r))
X (setq *real-cnt* (1+ *real-cnt*))
X (attach-left pred succ)
X (return succ)))
X
X(defun link-both (left right succ)
X (prog (a r)
X (setq a (interq (left-outs left) (right-outs right)))
X (setq r (find-equiv-beta-node succ a))
X (and r (return r))
X (setq *real-cnt* (1+ *real-cnt*))
X (attach-left left succ)
X (attach-right right succ)
X (return succ)))
X
X(defun attach-right (old new)
X (rplaca (cddr old) (cons new (caddr old))))
X
X(defun attach-left (old new)
X (rplaca (cdr old) (cons new (cadr old))))
X
X(defun right-outs (node) (caddr node))
X
X(defun left-outs (node) (cadr node))
X
X(defun find-equiv-node (node list)
X (prog (a)
X (setq a list)
X l1 (cond ((atom a) (return nil))
X ((equiv node (car a)) (return (car a))))
X (setq a (cdr a))
X (go l1)))
X
X(defun find-equiv-beta-node (node list)
X (prog (a)
X (setq a list)
X l1 (cond ((atom a) (return nil))
X ((beta-equiv node (car a)) (return (car a))))
X (setq a (cdr a))
X (go l1)))
X
X; do not look at the predecessor fields of beta nodes; they have to be
X; identical because of the way the candidate nodes were found
X
X(defun equiv (a b)
X (and (eq (car a) (car b))
X (or (eq (car a) '&mem)
X (eq (car a) '&two)
X (equal (caddr a) (caddr b)))
X (equal (cdddr a) (cdddr b))))
X
X(defun beta-equiv (a b)
X (and (eq (car a) (car b))
X (equal (cddddr a) (cddddr b))
X (or (eq (car a) '&and) (equal (caddr a) (caddr b)))))
X
X; the equivalence tests are set up to consider the contents of
X; node memories, so they are ready for the build action
X
X;;; Network interpreter
X
X(defun match (flag wme)
X (sendto flag (list wme) 'left (list *first-node*)))
X
X; note that eval-nodelist is not set up to handle building
X; productions. would have to add something like ops4's build-flag
X
X(defun eval-nodelist (nl)
X (prog nil
X top (and (not nl) (return nil))
X (setq *sendtocall* nil)
X (setq *last-node* (car nl))
X (apply (caar nl) (cdar nl))
X (setq nl (cdr nl))
X (go top)))
X
X(defun sendto (flag data side nl)
X (prog nil
X top (and (not nl) (return nil))
X (setq *side* side)
X (setq *flag-part* flag)
X (setq *data-part* data)
X (setq *sendtocall* t)
X (setq *last-node* (car nl))
X (apply (caar nl) (cdar nl))
X (setq nl (cdr nl))
X (go top)))
X
X; &bus sets up the registers for the one-input nodes. note that this
X(defun &bus (outs)
X (prog (dp)
X (setq *alpha-flag-part* *flag-part*)
X (setq *alpha-data-part* *data-part*)
X (setq dp (car *data-part*))
X (setq *c1* (car dp))
X (setq dp (cdr dp))
X (setq *c2* (car dp))
X (setq dp (cdr dp))
X (setq *c3* (car dp))
X (setq dp (cdr dp))
X (setq *c4* (car dp))
X (setq dp (cdr dp))
X (setq *c5* (car dp))
X (setq dp (cdr dp))
X (setq *c6* (car dp))
X (setq dp (cdr dp))
X (setq *c7* (car dp))
X (setq dp (cdr dp))
X (setq *c8* (car dp))
X (setq dp (cdr dp))
X (setq *c9* (car dp))
X (setq dp (cdr dp))
X (setq *c10* (car dp))
X (setq dp (cdr dp))
X (setq *c11* (car dp))
X (setq dp (cdr dp))
X (setq *c12* (car dp))
X (setq dp (cdr dp))
X (setq *c13* (car dp))
X (setq dp (cdr dp))
X (setq *c14* (car dp))
X (setq dp (cdr dp))
X (setq *c15* (car dp))
X (setq dp (cdr dp))
X (setq *c16* (car dp))
X (setq dp (cdr dp))
X (setq *c17* (car dp))
X (setq dp (cdr dp))
X (setq *c18* (car dp))
X (setq dp (cdr dp))
X (setq *c19* (car dp))
X (setq dp (cdr dp))
X (setq *c20* (car dp))
X (setq dp (cdr dp))
X (setq *c21* (car dp))
X (setq dp (cdr dp))
X (setq *c22* (car dp))
X (setq dp (cdr dp))
X (setq *c23* (car dp))
X (setq dp (cdr dp))
X (setq *c24* (car dp))
X (setq dp (cdr dp))
X (setq *c25* (car dp))
X (setq dp (cdr dp))
X (setq *c26* (car dp))
X (setq dp (cdr dp))
X (setq *c27* (car dp))
X (setq dp (cdr dp))
X (setq *c28* (car dp))
X (setq dp (cdr dp))
X (setq *c29* (car dp))
X (setq dp (cdr dp))
X (setq *c30* (car dp))
X (setq dp (cdr dp))
X (setq *c31* (car dp))
X (setq dp (cdr dp))
X (setq *c32* (car dp))
X (setq dp (cdr dp))
X (setq *c33* (car dp))
X (setq dp (cdr dp))
X (setq *c34* (car dp))
X (setq dp (cdr dp))
X (setq *c35* (car dp))
X (setq dp (cdr dp))
X (setq *c36* (car dp))
X (setq dp (cdr dp))
X (setq *c37* (car dp))
X (setq dp (cdr dp))
X (setq *c38* (car dp))
X (setq dp (cdr dp))
X (setq *c39* (car dp))
X (setq dp (cdr dp))
X (setq *c40* (car dp))
X (setq dp (cdr dp))
X (setq *c41* (car dp))
X (setq dp (cdr dp))
X (setq *c42* (car dp))
X (setq dp (cdr dp))
X (setq *c43* (car dp))
X (setq dp (cdr dp))
X (setq *c44* (car dp))
X (setq dp (cdr dp))
X (setq *c45* (car dp))
X (setq dp (cdr dp))
X (setq *c46* (car dp))
X (setq dp (cdr dp))
X (setq *c47* (car dp))
X (setq dp (cdr dp))
X (setq *c48* (car dp))
X (setq dp (cdr dp))
X (setq *c49* (car dp))
X (setq dp (cdr dp))
X (setq *c50* (car dp))
X (setq dp (cdr dp))
X (setq *c51* (car dp))
X (setq dp (cdr dp))
X (setq *c52* (car dp))
X (setq dp (cdr dp))
X (setq *c53* (car dp))
X (setq dp (cdr dp))
X (setq *c54* (car dp))
X (setq dp (cdr dp))
X (setq *c55* (car dp))
X (setq dp (cdr dp))
X (setq *c56* (car dp))
X (setq dp (cdr dp))
X (setq *c57* (car dp))
X (setq dp (cdr dp))
X (setq *c58* (car dp))
X (setq dp (cdr dp))
X (setq *c59* (car dp))
X (setq dp (cdr dp))
X (setq *c60* (car dp))
X (setq dp (cdr dp))
X (setq *c61* (car dp))
X (setq dp (cdr dp))
X (setq *c62* (car dp))
X (setq dp (cdr dp))
X (setq *c63* (car dp))
X (setq dp (cdr dp))
X (setq *c64* (car dp))
X (eval-nodelist outs)))
X
X(defun &any (outs register const-list)
X (prog (z c)
X (setq z (fast-symeval register))
X (cond ((numberp z) (go number)))
X symbol (cond ((null const-list) (return nil))
X ((eq (car const-list) z) (go ok))
X (t (setq const-list (cdr const-list)) (go symbol)))
X number (cond ((null const-list) (return nil))
X ((and (numberp (setq c (car const-list)))
X (=alg c z))
X (go ok))
X (t (setq const-list (cdr const-list)) (go number)))
X ok (eval-nodelist outs)))
X
X(defun teqa (outs register constant)
X (and (eq (fast-symeval register) constant) (eval-nodelist outs)))
X
X(defun tnea (outs register constant)
X (and (not (eq (fast-symeval register) constant)) (eval-nodelist outs)))
X
X(defun txxa (outs register constant)
X (and (symbolp (fast-symeval register)) (eval-nodelist outs)))
X
X(defun teqn (outs register constant)
X (prog (z)
X (setq z (fast-symeval register))
X (and (numberp z)
X (=alg z constant)
X (eval-nodelist outs))))
X
X(defun tnen (outs register constant)
X (prog (z)
X (setq z (fast-symeval register))
X (and (or (not (numberp z))
X (not (=alg z constant)))
X (eval-nodelist outs))))
X
X(defun txxn (outs register constant)
X (prog (z)
X (setq z (fast-symeval register))
X (and (numberp z) (eval-nodelist outs))))
X
X(defun tltn (outs register constant)
X (prog (z)
X (setq z (fast-symeval register))
X (and (numberp z)
X (greaterp constant z)
X (eval-nodelist outs))))
X
X(defun tgtn (outs register constant)
X (prog (z)
X (setq z (fast-symeval register))
X (and (numberp z)
X (greaterp z constant)
X (eval-nodelist outs))))
X
X(defun tgen (outs register constant)
X (prog (z)
X (setq z (fast-symeval register))
X (and (numberp z)
X (not (greaterp constant z))
X (eval-nodelist outs))))
X
X(defun tlen (outs register constant)
X (prog (z)
X (setq z (fast-symeval register))
X (and (numberp z)
X (not (greaterp z constant))
X (eval-nodelist outs))))
X
X(defun teqs (outs vara varb)
X (prog (a b)
X (setq a (fast-symeval vara))
X (setq b (fast-symeval varb))
X (cond ((eq a b) (eval-nodelist outs))
X ((and (numberp a)
X (numberp b)
X (=alg a b))
X (eval-nodelist outs)))))
X
X(defun tnes (outs vara varb)
X (prog (a b)
X (setq a (fast-symeval vara))
X (setq b (fast-symeval varb))
X (cond ((eq a b) (return nil))
X ((and (numberp a)
X (numberp b)
X (=alg a b))
X (return nil))
X (t (eval-nodelist outs)))))
X
X(defun txxs (outs vara varb)
X (prog (a b)
X (setq a (fast-symeval vara))
X (setq b (fast-symeval varb))
X (cond ((and (numberp a) (numberp b)) (eval-nodelist outs))
X ((and (not (numberp a)) (not (numberp b)))
X (eval-nodelist outs)))))
X
X(defun tlts (outs vara varb)
X (prog (a b)
X (setq a (fast-symeval vara))
X (setq b (fast-symeval varb))
X (and (numberp a)
X (numberp b)
X (greaterp b a)
X (eval-nodelist outs))))
X
X(defun tgts (outs vara varb)
X (prog (a b)
X (setq a (fast-symeval vara))
X (setq b (fast-symeval varb))
X (and (numberp a)
X (numberp b)
X (greaterp a b)
X (eval-nodelist outs))))
X
X(defun tges (outs vara varb)
X (prog (a b)
X (setq a (fast-symeval vara))
X (setq b (fast-symeval varb))
X (and (numberp a)
X (numberp b)
X (not (greaterp b a))
X (eval-nodelist outs))))
X
X(defun tles (outs vara varb)
X (prog (a b)
X (setq a (fast-symeval vara))
X (setq b (fast-symeval varb))
X (and (numberp a)
X (numberp b)
X (not (greaterp a b))
X (eval-nodelist outs))))
X
X(defun &two (left-outs right-outs)
X (prog (fp dp)
X (cond (*sendtocall*
X (setq fp *flag-part*)
X (setq dp *data-part*))
X (t
X (setq fp *alpha-flag-part*)
X (setq dp *alpha-data-part*)))
X (sendto fp dp 'left left-outs)
X (sendto fp dp 'right right-outs)))
X
X(defun &mem (left-outs right-outs memory-list)
X (prog (fp dp)
X (cond (*sendtocall*
X (setq fp *flag-part*)
X (setq dp *data-part*))
X (t
X (setq fp *alpha-flag-part*)
X (setq dp *alpha-data-part*)))
X (sendto fp dp 'left left-outs)
X (add-token memory-list fp dp nil)
X (sendto fp dp 'right right-outs)))
X
X(defun &and (outs lpred rpred tests)
X (prog (mem)
X (cond ((eq *side* 'right) (setq mem (memory-part lpred)))
X (t (setq mem (memory-part rpred))))
X (cond ((not mem) (return nil))
X ((eq *side* 'right) (and-right outs mem tests))
X (t (and-left outs mem tests)))))
------------------------------
End of AIList Digest
********************
∂30-Jan-87 1703 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #26
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 30 Jan 87 17:02:48 PST
Date: Thu 29 Jan 1987 23:15-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #26
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 30 Jan 1987 Volume 5 : Issue 26
Today's Topics:
Code - AI Expert Magazine Sources (Part 7 of 22)
----------------------------------------------------------------------
Date: 19 Jan 87 03:36:40 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: AI Expert Magazine Sources (Part 7 of 22)
X
X(defun and-left (outs mem tests)
X (prog (fp dp memdp tlist tst lind rind res)
X (setq fp *flag-part*)
X (setq dp *data-part*)
X fail (and (null mem) (return nil))
X (setq memdp (car mem))
X (setq mem (cdr mem))
X (setq tlist tests)
X tloop (and (null tlist) (go succ))
X (setq tst (car tlist))
X (setq tlist (cdr tlist))
X (setq lind (car tlist))
X (setq tlist (cdr tlist))
X (setq rind (car tlist))
X (setq tlist (cdr tlist))
X ;the next line differs in and-left & -right
X (setq res (funcall tst (gelm memdp rind) (gelm dp lind)))
X (cond (res (go tloop))
X (t (go fail)))
X succ ;the next line differs in and-left & -right
X (sendto fp (cons (car memdp) dp) 'left outs)
X (go fail)))
X
X(defun and-right (outs mem tests)
X (prog (fp dp memdp tlist tst lind rind res)
X (setq fp *flag-part*)
X (setq dp *data-part*)
X fail (and (null mem) (return nil))
X (setq memdp (car mem))
X (setq mem (cdr mem))
X (setq tlist tests)
X tloop (and (null tlist) (go succ))
X (setq tst (car tlist))
X (setq tlist (cdr tlist))
X (setq lind (car tlist))
X (setq tlist (cdr tlist))
X (setq rind (car tlist))
X (setq tlist (cdr tlist))
X ;the next line differs in and-left & -right
X (setq res (funcall tst (gelm dp rind) (gelm memdp lind)))
X (cond (res (go tloop))
X (t (go fail)))
X succ ;the next line differs in and-left & -right
X (sendto fp (cons (car dp) memdp) 'right outs)
X (go fail)))
X
X
X(defun teqb (new eqvar)
X (cond ((eq new eqvar) t)
X ((not (numberp new)) nil)
X ((not (numberp eqvar)) nil)
X ((=alg new eqvar) t)
X (t nil)))
X
X(defun tneb (new eqvar)
X (cond ((eq new eqvar) nil)
X ((not (numberp new)) t)
X ((not (numberp eqvar)) t)
X ((=alg new eqvar) nil)
X (t t)))
X
X(defun tltb (new eqvar)
X (cond ((not (numberp new)) nil)
X ((not (numberp eqvar)) nil)
X ((greaterp eqvar new) t)
X (t nil)))
X
X(defun tgtb (new eqvar)
X (cond ((not (numberp new)) nil)
X ((not (numberp eqvar)) nil)
X ((greaterp new eqvar) t)
X (t nil)))
X
X(defun tgeb (new eqvar)
X (cond ((not (numberp new)) nil)
X ((not (numberp eqvar)) nil)
X ((not (greaterp eqvar new)) t)
X (t nil)))
X
X(defun tleb (new eqvar)
X (cond ((not (numberp new)) nil)
X ((not (numberp eqvar)) nil)
X ((not (greaterp new eqvar)) t)
X (t nil)))
X
X(defun txxb (new eqvar)
X (cond ((numberp new)
X (cond ((numberp eqvar) t)
X (t nil)))
X (t
X (cond ((numberp eqvar) nil)
X (t t)))))
X
X
X(defun &p (rating name var-dope ce-var-dope rhs)
X (prog (fp dp)
X (cond (*sendtocall*
X (setq fp *flag-part*)
X (setq dp *data-part*))
X (t
X (setq fp *alpha-flag-part*)
X (setq dp *alpha-data-part*)))
X (and (member fp '(nil old)) (removecs name dp))
X (and fp (insertcs name dp rating))))
X
X(defun &old (a b c d e) nil) ;a null function used for deleting node
X
X(defun ¬ (outs lmem rpred tests)
X (cond ((and (eq *side* 'right) (eq *flag-part* 'old)) nil)
X ((eq *side* 'right) (not-right outs (car lmem) tests))
X (t (not-left outs (memory-part rpred) tests lmem))))
X
X(defun not-left (outs mem tests own-mem)
X (prog (fp dp memdp tlist tst lind rind res c)
X (setq fp *flag-part*)
X (setq dp *data-part*)
X (setq c 0.)
X fail (and (null mem) (go fin))
X (setq memdp (car mem))
X (setq mem (cdr mem))
X (setq tlist tests)
X tloop (and (null tlist) (setq c (1+ c)) (go fail))
X (setq tst (car tlist))
X (setq tlist (cdr tlist))
X (setq lind (car tlist))
X (setq tlist (cdr tlist))
X (setq rind (car tlist))
X (setq tlist (cdr tlist))
X ;the next line differs in not-left & -right
X (setq res (funcall tst (gelm memdp rind) (gelm dp lind)))
X (cond (res (go tloop))
X (t (go fail)))
X fin (add-token own-mem fp dp c)
X (and (== c 0.) (sendto fp dp 'left outs))))
X
X(defun not-right (outs mem tests)
X (prog (fp dp memdp tlist tst lind rind res newfp inc newc)
X (setq fp *flag-part*)
X (setq dp *data-part*)
X (cond ((not fp) (setq inc -1.) (setq newfp 'new))
X ((eq fp 'new) (setq inc 1.) (setq newfp nil))
X (t (return nil)))
X fail (and (null mem) (return nil))
X (setq memdp (car mem))
X (setq newc (cadr mem))
X (setq tlist tests)
X tloop (and (null tlist) (go succ))
X (setq tst (car tlist))
X (setq tlist (cdr tlist))
X (setq lind (car tlist))
X (setq tlist (cdr tlist))
X (setq rind (car tlist))
X (setq tlist (cdr tlist))
X ;the next line differs in not-left & -right
X (setq res (funcall tst (gelm dp rind) (gelm memdp lind)))
X (cond (res (go tloop))
X (t (setq mem (cddr mem)) (go fail)))
X succ (setq newc (+ inc newc))
X (rplaca (cdr mem) newc)
X (cond ((or (and (== inc -1.) (== newc 0.))
X (and (== inc 1.) (== newc 1.)))
X (sendto newfp memdp 'right outs)))
X (setq mem (cddr mem))
X (go fail)))
X
X
X
X;;; Node memories
X
X
X(defun add-token (memlis flag data-part num)
X (prog (was-present)
X (cond ((eq flag 'new)
X (setq was-present nil)
X (real-add-token memlis data-part num))
X ((not flag)
X (setq was-present (remove-old memlis data-part num)))
X ((eq flag 'old) (setq was-present t)))
X (return was-present)))
X
X(defun real-add-token (lis data-part num)
X (setq *current-token* (1+ *current-token*))
X (cond (num (rplaca lis (cons num (car lis)))))
X (rplaca lis (cons data-part (car lis))))
X
X(defun remove-old (lis data num)
X (cond (num (remove-old-num lis data))
X (t (remove-old-no-num lis data))))
X
X(defun remove-old-num (lis data)
X (prog (m next last)
X (setq m (car lis))
X (cond ((atom m) (return nil))
X ((top-levels-eq data (car m))
X (setq *current-token* (1- *current-token*))
X (rplaca lis (cddr m))
X (return (car m))))
X (setq next m)
X loop (setq last next)
X (setq next (cddr next))
X (cond ((atom next) (return nil))
X ((top-levels-eq data (car next))
X (rplacd (cdr last) (cddr next))
X (setq *current-token* (1- *current-token*))
X (return (car next)))
X (t (go loop)))))
X
X(defun remove-old-no-num (lis data)
X (prog (m next last)
X (setq m (car lis))
X (cond ((atom m) (return nil))
X ((top-levels-eq data (car m))
X (setq *current-token* (1- *current-token*))
X (rplaca lis (cdr m))
X (return (car m))))
X (setq next m)
X loop (setq last next)
X (setq next (cdr next))
X (cond ((atom next) (return nil))
X ((top-levels-eq data (car next))
X (rplacd last (cdr next))
X (setq *current-token* (1- *current-token*))
X (return (car next)))
X (t (go loop)))))
X
X
X
X;;; Conflict Resolution
X;
X;
X; each conflict set element is a list of the following form:
X; ((p-name . data-part) (sorted wm-recency) special-case-number)
X
X(defun removecs (name data)
X (prog (cr-data inst cs)
X (setq cr-data (cons name data))
X (setq cs *conflict-set*)
X loop1 (cond ((null cs)
X (record-refract name data)
X (return nil)))
X (setq inst (car cs))
X (setq cs (cdr cs))
X (and (not (top-levels-eq (car inst) cr-data)) (go loop1))
X (setq *conflict-set* (delete inst *conflict-set* :test #'eq))))
X
X(defun insertcs (name data rating)
X (prog (instan)
X (and (refracted name data) (return nil))
X (setq instan (list (cons name data) (order-tags data) rating))
X (and (atom *conflict-set*) (setq *conflict-set* nil))
X (return (setq *conflict-set* (cons instan *conflict-set*)))))
X
X(defun order-tags (dat)
X (prog (tags)
X (setq tags nil)
X l1 (and (atom dat) (go l2))
X (setq tags (cons (creation-time (car dat)) tags))
X (setq dat (cdr dat))
X (go l1)
X l2 (cond ((eq *strategy* 'mea)
X (return (cons (car tags) (dsort (cdr tags)))))
X (t (return (dsort tags))))))
X
X; destructively sort x into descending order
X
X(defun dsort (x)
X (prog (sorted cur next cval nval)
X (and (atom (cdr x)) (return x))
X loop (setq sorted t)
X (setq cur x)
X (setq next (cdr x))
X chek (setq cval (car cur))
X (setq nval (car next))
X (cond ((> nval cval)
X (setq sorted nil)
X (rplaca cur nval)
X (rplaca next cval)))
X (setq cur next)
X (setq next (cdr cur))
X (cond ((not (null next)) (go chek))
X (sorted (return x))
X (t (go loop)))))
X
X(defun conflict-resolution nil
X (prog (best len)
X (setq len (length *conflict-set*))
X (cond ((> len *max-cs*) (setq *max-cs* len)))
X (setq *total-cs* (+ *total-cs* len))
X (cond (*conflict-set*
X (setq best (best-of *conflict-set*))
X (setq *conflict-set* (delete best *conflict-set* :test #'eq))
X (return (pname-instantiation best)))
X (t (return nil)))))
X
X(defun best-of (set) (best-of* (car set) (cdr set)))
X
X(defun best-of* (best rem)
X (cond ((not rem) best)
X ((conflict-set-compare best (car rem))
X (best-of* best (cdr rem)))
X (t (best-of* (car rem) (cdr rem)))))
X
X(defun remove-from-conflict-set (name)
X (prog (cs entry)
X l1 (setq cs *conflict-set*)
X l2 (cond ((atom cs) (return nil)))
X (setq entry (car cs))
X (setq cs (cdr cs))
X (cond ((eq name (caar entry))
X (setq *conflict-set* (delete entry *conflict-set* :test #'eq))
X (go l1))
X (t (go l2)))))
X
X(defun pname-instantiation (conflict-elem) (car conflict-elem))
X
X(defun order-part (conflict-elem) (cdr conflict-elem))
X
X(defun instantiation (conflict-elem)
X (cdr (pname-instantiation conflict-elem)))
X
X
X(defun conflict-set-compare (x y)
X (prog (x-order y-order xl yl xv yv)
X (setq x-order (order-part x))
X (setq y-order (order-part y))
X (setq xl (car x-order))
X (setq yl (car y-order))
X data (cond ((and (null xl) (null yl)) (go ps))
X ((null yl) (return t))
X ((null xl) (return nil)))
X (setq xv (car xl))
X (setq yv (car yl))
X (cond ((> xv yv) (return t))
X ((> yv xv) (return nil)))
X (setq xl (cdr xl))
X (setq yl (cdr yl))
X (go data)
X ps (setq xl (cdr x-order))
X (setq yl (cdr y-order))
X psl (cond ((null xl) (return t)))
X (setq xv (car xl))
X (setq yv (car yl))
X (cond ((> xv yv) (return t))
X ((> yv xv) (return nil)))
X (setq xl (cdr xl))
X (setq yl (cdr yl))
X (go psl)))
X
X
X(defun conflict-set nil
X (prog (cnts cs p z best)
X (setq cnts nil)
X (setq cs *conflict-set*)
X l1 (and (atom cs) (go l2))
X (setq p (caaar cs))
X (setq cs (cdr cs))
X (setq z (assoc p cnts :test #'eq))
X (cond ((null z) (setq cnts (cons (cons p 1.) cnts)))
X (t (rplacd z (1+ (cdr z)))))
X (go l1)
X l2 (cond ((atom cnts)
X (setq best (best-of *conflict-set*))
X (terpri)
X (return (list (caar best) 'dominates))))
X (terpri)
X (princ (caar cnts))
X (cond ((> (cdar cnts) 1.)
X (princ '| (|)
X (princ (cdar cnts))
X (princ '| occurrences)|)))
X (setq cnts (cdr cnts))
X (go l2)))
X
X
X
X;;; WM maintaining functions
X;
X; The order of operations in the following two functions is critical.
X; add-to-wm order: (1) change wm (2) record change (3) match
X; remove-from-wm order: (1) record change (2) match (3) change wm
X; (back will not restore state properly unless wm changes are recorded
X; before the cs changes that they cause) (match will give errors if
X; the thing matched is not in wm at the time)
X
X
X(defun add-to-wm (wme override)
X (prog (fa z part timetag port)
X (setq *critical* t)
X (setq *current-wm* (1+ *current-wm*))
X (and (> *current-wm* *max-wm*) (setq *max-wm* *current-wm*))
X (setq *action-count* (1+ *action-count*))
X (setq fa (wm-hash wme))
X (or (member fa *wmpart-list* :test #'eq)
X (setq *wmpart-list* (cons fa *wmpart-list*)))
X (setq part (get fa 'wmpart*))
X (cond (override (setq timetag override))
X (t (setq timetag *action-count*)))
X (setq z (cons wme timetag))
X (putprop fa (cons z part) 'wmpart*)
X (record-change '=>wm *action-count* wme)
X (match 'new wme)
X (setq *critical* nil)
X (cond ((and *in-rhs* *wtrace*)
X (setq port (trace-file))
X (terpri port)
X (princ '|=>wm: | port)
X (ppelm wme port)))
X (and *in-rhs* *mtrace* (setq *madeby*
X (cons (cons wme *p-name*) *madeby*)))))
X
X; remove-from-wm uses eq, not equal to determine if wme is present
X
X(defun remove-from-wm (wme)
X (prog (fa z part timetag port)
X (setq fa (wm-hash wme))
X (setq part (get fa 'wmpart*))
X (setq z (assoc wme part :test #'eq))
X (or z (return nil))
X (setq timetag (cdr z))
X (cond ((and *wtrace* *in-rhs*)
X (setq port (trace-file))
X (terpri port)
X (princ '|<=wm: | port)
X (ppelm wme port)))
X (setq *action-count* (1+ *action-count*))
X (setq *critical* t)
X (setq *current-wm* (1- *current-wm*))
X (record-change '<=wm timetag wme)
X (match nil wme)
X (putprop fa (delete z part :test #'eq) 'wmpart* )
X (setq *critical* nil)))
X
X; mapwm maps down the elements of wm, applying fn to each element
X; each element is of form (datum . creation-time)
X
X(defun mapwm (fn)
X (prog (wmpl part)
X (setq wmpl *wmpart-list*)
X lab1 (cond ((atom wmpl) (return nil)))
X (setq part (get (car wmpl) 'wmpart*))
X (setq wmpl (cdr wmpl))
X (mapc fn part)
X (go lab1)))
X
X(defmacro wm (&rest a)
X `(progn
X (mapc (function (lambda (z) (terpri) (ppelm z t)))
X (get-wm ',a))
X nil) )
X
X(defun get-wm (z)
X (setq *wm-filter* z)
X (setq *wm* nil)
X (mapwm (function get-wm2))
X (prog2 nil *wm* (setq *wm* nil)))
X
X(defun get-wm2 (elem)
X (cond ((or (null *wm-filter*) (member (cdr elem) *wm-filter*))
X (setq *wm* (cons (car elem) *wm*)))))
X
X(defun wm-hash (x)
X (cond ((not x) '<default>)
X ((not (car x)) (wm-hash (cdr x)))
X ((symbolp (car x)) (car x))
X (t (wm-hash (cdr x)))))
X
X(defun creation-time (wme)
X (cdr (assoc wme (get (wm-hash wme) 'wmpart*) :test #'eq)))
X
X(defun rehearse nil
X (prog nil
X (setq *old-wm* nil)
X (mapwm (function refresh-collect))
X (mapc (function refresh-del) *old-wm*)
X (mapc (function refresh-add) *old-wm*)
X (setq *old-wm* nil)))
X
X(defun refresh-collect (x) (setq *old-wm* (cons x *old-wm*)))
X
X(defun refresh-del (x) (remove-from-wm (car x)))
X
X(defun refresh-add (x) (add-to-wm (car x) (cdr x)))
X
X(defun trace-file ()
X (prog (port)
X (setq port t)
X (cond (*trace-file*
X (setq port ($ofile *trace-file*))
X (cond ((null port)
X (%warn '|trace: file has been closed| *trace-file*)
X (setq port t)))))
X (return port)))
X
X
X;;; Basic functions for RHS evaluation
X
X(defun eval-rhs (pname data)
X (prog (node port)
X (cond (*ptrace*
X (setq port (trace-file))
X (terpri port)
X (princ *cycle-count* port)
X (princ '|. | port)
X (princ pname port)
X (time-tag-print data port)))
X (setq *data-matched* data)
X (setq *p-name* pname)
X (setq *last* nil)
X (setq node (get pname 'topnode))
X (init-var-mem (var-part node))
X (init-ce-var-mem (ce-var-part node))
X (begin-record pname data)
X (setq *in-rhs* t)
X (eval (rhs-part node))
X (setq *in-rhs* nil)
X (end-record)))
X
X(defun time-tag-print (data port)
X (cond ((not (null data))
X (time-tag-print (cdr data) port)
X (princ '| | port)
X (princ (creation-time (car data)) port))))
X
X(defun init-var-mem (vlist)
X (prog (v ind r)
X (setq *variable-memory* nil)
X top (and (atom vlist) (return nil))
X (setq v (car vlist))
X (setq ind (cadr vlist))
X (setq vlist (cddr vlist))
X (setq r (gelm *data-matched* ind))
X (setq *variable-memory* (cons (cons v r) *variable-memory*))
X (go top)))
X
------------------------------
End of AIList Digest
********************
∂30-Jan-87 2034 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #27
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 30 Jan 87 20:34:42 PST
Date: Thu 29 Jan 1987 23:25-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #27
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 30 Jan 1987 Volume 5 : Issue 27
Today's Topics:
Code - AI Expert Magazine Sources (Part 8 of 22)
----------------------------------------------------------------------
Date: 19 Jan 87 03:36:40 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: AI Expert Magazine Sources (Part 8 of 22)
X(defun init-ce-var-mem (vlist)
X (prog (v ind r)
X (setq *ce-variable-memory* nil)
X top (and (atom vlist) (return nil))
X (setq v (car vlist))
X (setq ind (cadr vlist))
X (setq vlist (cddr vlist))
X (setq r (ce-gelm *data-matched* ind))
X (setq *ce-variable-memory*
X (cons (cons v r) *ce-variable-memory*))
X (go top)))
X
X(defun make-ce-var-bind (var elem)
X (setq *ce-variable-memory*
X (cons (cons var elem) *ce-variable-memory*)))
X
X(defun make-var-bind (var elem)
X (setq *variable-memory* (cons (cons var elem) *variable-memory*)))
X
X(defun $varbind (x)
X (prog (r)
X (and (not *in-rhs*) (return x))
X (setq r (assoc x *variable-memory* :test #'eq))
X (cond (r (return (cdr r)))
X (t (return x)))))
X
X(defun get-ce-var-bind (x)
X (prog (r)
X (cond ((numberp x) (return (get-num-ce x))))
X (setq r (assoc x *ce-variable-memory* :test #'eq))
X (cond (r (return (cdr r)))
X (t (return nil)))))
X
X(defun get-num-ce (x)
X (prog (r l d)
X (setq r *data-matched*)
X (setq l (length r))
X (setq d (- l x))
X (and (> 0. d) (return nil))
X la (cond ((null r) (return nil))
X ((> 1. d) (return (car r))))
X (setq d (1- d))
X (setq r (cdr r))
X (go la)))
X
X
X(defun build-collect (z)
X (prog (r)
X la (and (atom z) (return nil))
X (setq r (car z))
X (setq z (cdr z))
X (cond ((and r (listp r))
X ($value '\()
X (build-collect r)
X ($value '\)))
X ((eq r '\\) ($change (car z)) (setq z (cdr z)))
X (t ($value r)))
X (go la)))
X
X(defun unflat (x) (setq *rest* x) (unflat*))
X
X(defun unflat* nil
X (prog (c)
X (cond ((atom *rest*) (return nil)))
X (setq c (car *rest*))
X (setq *rest* (cdr *rest*))
X (cond ((eq c '\() (return (cons (unflat*) (unflat*))))
X ((eq c '\)) (return nil))
X (t (return (cons c (unflat*)))))))
X
X
X(defun $change (x)
X (prog nil
X (cond ((and x (listp x)) (eval-function x)) ;modified to check for nil
X (t ($value ($varbind x))))))
X
X(defun eval-args (z)
X (prog (r)
X (rhs-tab 1.)
X la (and (atom z) (return nil))
X (setq r (car z))
X (setq z (cdr z))
X (cond ((eq r #\↑)
X (rhs-tab (car z))
X (setq r (cadr z))
X (setq z (cddr z))))
X (cond ((eq r '//) ($value (car z)) (setq z (cdr z)))
X (t ($change r)))
X (go la)))
X
X
X(defun eval-function (form)
X (cond ((not *in-rhs*)
X (%warn '|functions cannot be used at top level| (car form)))
X (t (eval form))))
X
X
X;;; Functions to manipulate the result array
X
X
X(defun $reset nil
X (setq *max-index* 0)
X (setq *next-index* 1))
X
X; rhs-tab implements the tab ('↑') function in the rhs. it has
X; four responsibilities:
X; - to move the array pointers
X; - to watch for tabbing off the left end of the array
X; (ie, to watch for pointers less than 1)
X; - to watch for tabbing off the right end of the array
X; - to write nil in all the slots that are skipped
X; the last is necessary if the result array is not to be cleared
X; after each use; if rhs-tab did not do this, $reset
X; would be much slower.
X
X(defun rhs-tab (z) ($tab ($varbind z)))
X
X(defun $tab (z)
X (prog (edge next)
X (setq next ($litbind z))
X (and (floatp next) (setq next (round next)))
X (cond ((or (not (numberp next))
X (> next *size-result-array*)
X (> 1. next))
X (%warn '|illegal index after ↑| next)
X (return *next-index*)))
X (setq edge (- next 1.))
X (cond ((> *max-index* edge) (go ok)))
X clear (cond ((== *max-index* edge) (go ok)))
X (putvector *result-array* edge nil)
X (setq edge (1- edge))
X (go clear)
X ok (setq *next-index* next)
X (return next)))
X
X(defun $value (v)
X (cond ((> *next-index* *size-result-array*)
X (%warn '|index too large| *next-index*))
X (t
X (and (> *next-index* *max-index*)
X (setq *max-index* *next-index*))
X (putvector *result-array* *next-index* v)
X (setq *next-index* (1+ *next-index*)))))
X
X(defun use-result-array nil
X (prog (k r)
X (setq k *max-index*)
X (setq r nil)
X top (and (== k 0.) (return r))
X (setq r (cons (getvector *result-array* k) r))
X (setq k (1- k))
X (go top)))
X
X(defun $assert nil
X (setq *last* (use-result-array))
X (add-to-wm *last* nil))
X
X(defun $parametercount nil *max-index*)
X
X(defun $parameter (k)
X (cond ((or (not (numberp k)) (> k *size-result-array*) (< k 1.))
X (%warn '|illegal parameter number | k)
X nil)
X ((> k *max-index*) nil)
X (t (getvector *result-array* k))))
X
X
X;;; RHS actions
X
X
X(defmacro make(&rest z)
X `(prog nil
X ($reset)
X (eval-args ',z)
X ($assert)))
X
X(defmacro modify (&rest z)
X `(prog (old args)
X (setq args ',z)
X (cond ((not *in-rhs*)
X (%warn '|cannot be called at top level| 'modify)
X (return nil)))
X (setq old (get-ce-var-bind (car args)))
X (cond ((null old)
X (%warn '|modify: first argument must be an element variable|
X (car args))
X (return nil)))
X (remove-from-wm old)
X (setq args (cdr args))
X ($reset)
X copy (and (atom old) (go fin))
X ($change (car old))
X (setq old (cdr old))
X (go copy)
X fin (eval-args args)
X ($assert)))
X
X(defmacro bind (&rest z)
X `(prog (val)
X (cond ((not *in-rhs*)
X (%warn '|cannot be called at top level| 'bind)
X (return nil)))
X (cond ((< (length z) 1.)
X (%warn '|bind: wrong number of arguments to| ',z)
X (return nil))
X ((not (symbolp (car ',z)))
X (%warn '|bind: illegal argument| (car ',z))
X (return nil))
X ((= (length ',z) 1.) (setq val (gensym)))
X (t ($reset)
X (eval-args (cdr ',z))
X (setq val ($parameter 1.))))
X (make-var-bind (car ',z) val)))
X
X(defmacro cbind (&rest z)
X `(cond ((not *in-rhs*)
X (%warn '|cannot be called at top level| 'cbind))
X ((not (= (length ',z) 1.))
X (%warn '|cbind: wrong number of arguments| ',z))
X ((not (symbolp (car ',z)))
X (%warn '|cbind: illegal argument| (car ',z)))
X ((null *last*)
X (%warn '|cbind: nothing added yet| (car ',z)))
X (t (make-ce-var-bind (car ',z) *last*))))
X
X(defmacro oremove (&rest z)
X `(prog (old args)
X (setq args ',z)
X (and (not *in-rhs*)(return (top-level-remove args)))
X top (and (atom args) (return nil))
X (setq old (get-ce-var-bind (car args)))
X (cond ((null old)
X (%warn '|remove: argument not an element variable| (car args))
X (return nil)))
X (remove-from-wm old)
X (setq args (cdr args))
X (go top)))
X
X(defmacro ocall (&rest z)
X `(prog (f)
X (setq f (car ',z))
X ($reset)
X (eval-args (cdr ',z))
X (funcall f)))
X
X(defmacro owrite (&rest z)
X `(prog (port max k x needspace)
X (cond ((not *in-rhs*)
X (%warn '|cannot be called at top level| 'write)
X (return nil)))
X ($reset)
X (eval-args ',z)
X (setq k 1.)
X (setq max ($parametercount))
X (cond ((< max 1.)
X (%warn '|write: nothing to print| ',z)
X (return nil)))
X (setq port (default-write-file))
X (setq x ($parameter 1.))
X (cond ((and (symbolp x) ($ofile x))
X (setq port ($ofile x))
X (setq k 2.)))
X (setq needspace t)
X la (and (> k max) (return nil))
X (setq x ($parameter k))
X (cond ((eq x '|=== C R L F ===|)
X (setq needspace nil)
X (terpri port))
X ((eq x '|=== R J U S T ===|)
X (setq k (+ 2 k))
X (do-rjust ($parameter (1- k)) ($parameter k) port))
X ((eq x '|=== T A B T O ===|)
X (setq needspace nil)
X (setq k (1+ k))
X (do-tabto ($parameter k) port))
X (t
X (and needspace (princ '| | port))
X (setq needspace t)
X (princ x port)))
X (setq k (1+ k))
X (go la)))
X
X(defun default-write-file ()
X (prog (port)
X (setq port t)
X (cond (*write-file*
X (setq port ($ofile *write-file*))
X (cond ((null port)
X (%warn '|write: file has been closed| *write-file*)
X (setq port t)))))
X (return port)))
X
X
X(defun do-rjust (width value port)
X (prog (size)
X (cond ((eq value '|=== T A B T O ===|)
X (%warn '|rjust cannot precede this function| 'tabto)
X (return nil))
X ((eq value '|=== C R L F ===|)
X (%warn '|rjust cannot precede this function| 'crlf)
X (return nil))
X ((eq value '|=== R J U S T ===|)
X (%warn '|rjust cannot precede this function| 'rjust)
X (return nil)))
X (setq size (length (princ-to-string value )))
X (cond ((> size width)
X (princ '| | port)
X (princ value port)
X (return nil)))
X (do k (- width size) (1- k) (not (> k 0)) (princ '| | port))
X (princ value port)))
X
X(defun do-tabto (col port)
X (eval `(format ,port (concatenate 'string "~" (princ-to-string ,col) "T"))))
X
X; (prog (pos)
X; (setq pos (1+ (nwritn port)))
X; (cond ((> pos col)
X; (terpri port)
X; (setq pos 1)))
X; (do k (- col pos) (1- k) (not (> k 0)) (princ '| | port))
X; (return nil)))
X
X
X(defun halt nil
X (cond ((not *in-rhs*)
X (%warn '|cannot be called at top level| 'halt))
X (t (setq *halt-flag* t))))
X
X(defmacro build (&rest z)
X `(prog (r)
X (cond ((not *in-rhs*)
X (%warn '|cannot be called at top level| 'build)
X (return nil)))
X ($reset)
X (build-collect ',z)
X (setq r (unflat (use-result-array)))
X (and *build-trace* (funcall *build-trace* r))
X (compile-production (car r) (cdr r))))
X
X(defun infile(file)
X (open file :direction :input))
X
X(defun outfile(file)
X (open file :direction :output))
X
X(defmacro openfile (&rest z)
X `(prog (file mode id)
X ($reset)
X (eval-args ',z)
X (cond ((not (equal ($parametercount) 3.))
X (%warn '|openfile: wrong number of arguments| ',z)
X (return nil)))
X (setq id ($parameter 1))
X (setq file ($parameter 2))
X (setq mode ($parameter 3))
X (cond ((not (symbolp id))
X (%warn '|openfile: file id must be a symbolic atom| id)
X (return nil))
X ((null id)
X (%warn '|openfile: 'nil' is reserved for the terminal| nil)
X (return nil))
X ((or ($ifile id)($ofile id))
X (%warn '|openfile: name already in use| id)
X (return nil)))
X (cond ((eq mode 'in) (putprop id (infile file) 'inputfile))
X ((eq mode 'out) (putprop id (outfile file) 'outputfile))
X (t (%warn '|openfile: illegal mode| mode)
X (return nil)))
X (return nil)))
X
X(defun $ifile (x)
X (cond ((and x (symbolp x)) (get x 'inputfile))
X (t *standard-input*)))
X
X(defun $ofile (x)
X (cond ((and x (symbolp x)) (get x 'outputfile))
X (t *standard-output*)))
X
X
X(defmacro closefile (&rest z)
X `(progn
X ($reset)
X (eval-args ',z)
X (mapc (function closefile2) (use-result-array))))
X
X(defun closefile2 (file)
X (prog (port)
X (cond ((not (symbolp file))
X (%warn '|closefile: illegal file identifier| file))
X ((setq port ($ifile file))
X (close port)
X (remprop file 'inputfile))
X ((setq port ($ofile file))
X (close port)
X (remprop file 'outputfile)))
X (return nil)))
X
X(defmacro default (&rest z)
X `(prog (file use)
X ($reset)
X (eval-args ',z)
X (cond ((not (equal ($parametercount) 2.))
X (%warn '|default: wrong number of arguments| ',z)
X (return nil)))
X (setq file ($parameter 1))
X (setq use ($parameter 2))
X (cond ((not (symbolp file))
X (%warn '|default: illegal file identifier| file)
X (return nil))
X ((not (member use '(write accept trace)))
X (%warn '|default: illegal use for a file| use)
X (return nil))
X ((and (member use '(write trace))
X (not (null file))
X (not ($ofile file)))
X (%warn '|default: file has not been opened for output| file)
X (return nil))
X ((and (eq use 'accept)
X (not (null file))
X (not ($ifile file)))
X (%warn '|default: file has not been opened for input| file)
X (return nil))
X ((eq use 'write) (setq *write-file* file))
X ((eq use 'accept) (setq *accept-file* file))
X ((eq use 'trace) (setq *trace-file* file)))
X (return nil)))
X
X
X
X;;; RHS Functions
X
X(defmacro accept (&rest z)
X `(prog (port arg)
X (cond ((> (length ',z) 1.)
X (%warn '|accept: wrong number of arguments| ',z)
X (return nil)))
X (setq port t)
X (cond (*accept-file*
X (setq port ($ifile *accept-file*))
X (cond ((null port)
X (%warn '|accept: file has been closed| *accept-file*)
X (return nil)))))
X (cond ((= (length ',z) 1)
X (setq arg ($varbind (car ',z)))
X (cond ((not (symbolp arg))
X (%warn '|accept: illegal file name| arg)
X (return nil)))
X (setq port ($ifile arg))
X (cond ((null port)
X (%warn '|accept: file not open for input| arg)
X (return nil)))))
X (cond ((= (tyipeek port) -1.)
X ($value 'end-of-file)
X (return nil)))
X (flat-value (read port))))
X
X(defun flat-value (x)
X (cond ((atom x) ($value x))
X (t (mapc (function flat-value) x))))
X
X(defun span-chars (x prt)
X (do ((ch (tyipeek prt) (tyipeek prt))) ((not (member ch x #'char-equal)))
(read-char prt)))
X
X(defmacro acceptline (&rest z)
X `(prog ( def arg port)
X (setq port t)
X (setq def ',z)
X (cond (*accept-file*
X (setq port ($ifile *accept-file*))
X (cond ((null port)
X (%warn '|acceptline: file has been closed|
X *accept-file*)
X (return nil)))))
X (cond ((> (length def) 0)
X (setq arg ($varbind (car def)))
X (cond ((and (symbolp arg) ($ifile arg))
X (setq port ($ifile arg))
X (setq def (cdr def))))))
X (span-chars '(9. 41.) port)
X (cond ((member (tyipeek port) '(-1. 10.))
X (mapc (function $change) def)
X (return nil)))
X lp1 (flat-value (read port))
X (span-chars '(9. 41.) port)
X (cond ((not (member (tyipeek port) '(-1. 10.))) (go lp1)))))
X
X(defmacro substr (&rest l)
X `(prog (k elm start end)
X (cond ((not (= (length ',l) 3.))
X (%warn '|substr: wrong number of arguments| ',l)
X (return nil)))
X (setq elm (get-ce-var-bind (car ',l)))
X (cond ((null elm)
X (%warn '|first argument to substr must be a ce var|
X ',l)
X (return nil)))
X (setq start ($varbind (cadr ',l)))
X (setq start ($litbind start))
X (cond ((not (numberp start))
X (%warn '|second argument to substr must be a number|
X ',l)
X (return nil)))
X ;if a variable is bound to INF, the following
X ;will get the binding and treat it as INF is
X ;always treated. that may not be good
X (setq end ($varbind (caddr ',l)))
X (cond ((eq end 'inf) (setq end (length elm))))
X (setq end ($litbind end))
X (cond ((not (numberp end))
X (%warn '|third argument to substr must be a number|
X ',l)
X (return nil)))
X ;this loop does not check for the end of elm
X ;instead it relies on cdr of nil being nil
X ;this may not work in all versions of lisp
X (setq k 1.)
X la (cond ((> k end) (return nil))
X ((not (< k start)) ($value (car elm))))
X (setq elm (cdr elm))
X (setq k (1+ k))
X (go la)))
X
X
X(defmacro compute (&rest z) `($value (ari ',z)))
X
X; arith is the obsolete form of compute
X(defmacro arith (&rest z) `($value (ari ',z)))
X
X(defun ari (x)
X (cond ((atom x)
X (%warn '|bad syntax in arithmetic expression | x)
X 0.)
X ((atom (cdr x)) (ari-unit (car x)))
X ((eq (cadr x) '+)
X (+ (ari-unit (car x)) (ari (cddr x))))
X ((eq (cadr x) '-)
X (difference (ari-unit (car x)) (ari (cddr x))))
X ((eq (cadr x) '*)
X (times (ari-unit (car x)) (ari (cddr x))))
X ((eq (cadr x) '//)
X (/ (ari-unit (car x)) (ari (cddr x))))
X ((eq (cadr x) '\\)
X (mod (round (ari-unit (car x))) (round (ari (cddr x)))))
X (t (%warn '|bad syntax in arithmetic expression | x) 0.)))
X
X(defun ari-unit (a)
X (prog (r)
X (cond ((listp a) (setq r (ari a)))
X (t (setq r ($varbind a))))
X (cond ((not (numberp r))
X (%warn '|bad value in arithmetic expression| a)
X (return 0.))
X (t (return r)))))
X
X(defun genatom nil ($value (gensym)))
X
X(defmacro litval (&rest z)
X `(prog (r)
X (cond ((not (= (length ',z) 1.))
X (%warn '|litval: wrong number of arguments| ',z)
X ($value 0)
X (return nil))
X ((numberp (car ',z)) ($value (car ',z)) (return nil)))
X (setq r ($litbind ($varbind (car ',z))))
X (cond ((numberp r) ($value r) (return nil)))
X (%warn '|litval: argument has no literal binding| (car ',z))
X ($value 0)))
X
X
X(defmacro rjust (&rest z)
X `(prog (val)
X (cond ((not (= (length ',z) 1.))
X (%warn '|rjust: wrong number of arguments| ',z)
X (return nil)))
X (setq val ($varbind (car ',z)))
X (cond ((or (not (numberp val)) (< val 1.) (> val 127.))
X (%warn '|rjust: illegal value for field width| val)
X (return nil)))
X ($value '|=== R J U S T ===|)
X ($value val)))
X
X
X(defmacro crlf()
X ($value '|=== C R L F ===|))
X
X(defmacro tabto (&rest z)
X `(prog (val)
X (cond ((not (= (length ',z) 1.))
X (%warn '|tabto: wrong number of arguments| ',z)
X (return nil)))
X (setq val ($varbind (car ',z)))
X (cond ((or (not (numberp val)) (< val 1.) (> val 127.))
X (%warn '|tabto: illegal column number| ',z)
X (return nil)))
X ($value '|=== T A B T O ===|)
X ($value val)))
X
X
X
X;;; Printing WM
X
X(defmacro ppwm (&rest z)
X `(prog (next a avlist)
X (setq avlist ',z)
X (setq *filters* nil)
X (setq next 1.)
X l (and (atom avlist) (go print))
X (setq a (car avlist))
X (setq avlist (cdr avlist))
X (cond ((eq a #\↑)
X (setq next (car avlist))
X (setq avlist (cdr avlist))
X (setq next ($litbind next))
X (and (floatp next) (setq next (round next)))
X (cond ((or (not (numberp next))
X (> next *size-result-array*)
X (> 1. next))
X (%warn '|illegal index after ↑| next)
X (return nil))))
X ((variablep a)
X (%warn '|ppwm does not take variables| a)
X (return nil))
X (t (setq *filters* (cons next (cons a *filters*)))
X (setq next (1+ next))))
X (go l)
X print (mapwm (function ppwm2))
X (terpri)
X (return nil)))
X
X(defun ppwm2 (elm-tag)
X (cond ((filter (car elm-tag)) (terpri) (ppelm (car elm-tag) t))))
X
X(defun filter (elm)
X (prog (fl indx val)
X (setq fl *filters*)
X top (and (atom fl) (return t))
X (setq indx (car fl))
X (setq val (cadr fl))
X (setq fl (cddr fl))
X (and (ident (nth (1- indx) elm) val) (go top))
X (return nil)))
X
X(defun ident (x y)
X (cond ((eq x y) t)
X ((not (numberp x)) nil)
X ((not (numberp y)) nil)
X ((=alg x y) t)
X (t nil)))
X
X; the new ppelm is designed especially to handle literalize format
X; however, it will do as well as the old ppelm on other formats
X
------------------------------
End of AIList Digest
********************
∂02-Feb-87 0129 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #28
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 2 Feb 87 01:25:46 PST
Date: Sun 1 Feb 1987 22:30-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #28
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 2 Feb 1987 Volume 5 : Issue 28
Today's Topics:
Queries- OPS5 for 4.2BSD & Tutorial References & Common Lisp Code,
Policy - Revised Policy on AI Expert Sources,
Description - Telesophy Project,
Seminars - Knowledge-Based Reasoning Toolkit (CMU) &
Understanding How Devices Work (CMU),
Conference - Conceptual Information Processing
----------------------------------------------------------------------
Date: 29 Jan 87 20:02:25 GMT
From: Bill Roberts <bill%ncar.csnet@RELAY.CS.NET>
Subject: OPS5 for 4.2BSD?
Does anyone know of a public domain version of OPS5 (with Lisp as its
implementation language) that runs under UNIX 4.2/4.3BSD? We have 4.2BSD with
Franz Lisp and I would like to port some "stuff" from my Mac over to the VAX.
Thanks in advance for information on this.
Bill Roberts
NCAR/HAO
Boulder, CO
UUCP:...!hao!bill
------------------------------
Date: 29 Jan 87 19:52:14 GMT
From: atux01!jlc@rutgers.rutgers.edu (J. Collymore)
Subject: Need References to VERY BASIC Concepts of AI & Preferred
Comp. Langs.
I am interested in being pointed in the right direction to some VERY BASIC
concepts of how AI is used, what has gone before, which computer languages are
used for AI development, which aren't and why, basic concepts of mathematical
models used for simulating cognitive judgements and appropriate responses
(e.g. I feel bad vs. I don't feel too bad).
If you know of some good books in this area, please send me e-mail. If any-
one else is interested, I'll post my responses.
Thanks.
Jim Collymore
------------------------------
Date: Sat 31 Jan 87 18:31:04-EST
From: John C. Akbari <AKBARI@CS.COLUMBIA.EDU>
Subject: common lisp code
anyone have common lisp or zetalisp versions of any (or all) of the
code from the yale group, a la SAM, PAM, CA, etc... from
Schank,R. & Riesbeck,C. _Inside Computer Understanding: Five programs
Plus Miniatures_. Erlbaum 1981.
also, a cl or zetalisp implementation of a reasonable ATN implementation
would be appreciated.
thanks in advance.
john c akbari
akbari@cs.columbia.edu
------------------------------
Date: Fri 30 Jan 87 08:17:26-PST
From: Stephen Barnard <BARNARD@SRI-IU.ARPA>
Subject: enough already
These listings really are outrageous. Is this a plot to make
philosophical tracts seem amusing?
------------------------------
Date: 31 Jan 87 16:40 EST (Sat)
From: Tom Fawcett <FAWCETT@RED.RUTGERS.EDU>
Subject: Code on AIList
>The bulk of this code mailing does bother me, but there seems to be
>at least as much interest in it as in the seminar notices, bibliographies,
>and philosophy discussions. AIList reaches thousands of students, and
>a fair proportion are no doubt interested in examining the code. The
>initial offer of the code drew only positive feedback, so far as I
>know.
> ...
>
>Suggestions are welcome.
> -- Ken Laws
OK, here's one - resurrect the idea of splitting the AIList.
One list for code and philosophy, another for seminar notices and real
discussion.
Ironically, the people who like the endless discussions about consciousness
are probably the same people who would be interested in this vast amount of
code.
-Tom Fawcett
------------------------------
Date: 28 Jan 87 18:42:31 GMT
From: pyramid!amdahl!meccts!meccsd!mecc!sewilco@decwrl.dec.com (Scot
E. Wilcoxon)
Subject: Re: posting of AI Expert magazine sources
Unfortunately, putting those interesting (to me) sources in comp.ai required
that I save them manually. The source groups are archived automatically here
and at many other sites. Scattering sources makes them harder to keep.
If these sources will be regularly posted, a comp.ai.sources group will
help the problem.
--
Scot E. Wilcoxon Minn Ed Comp Corp {quest,dayton,meccts}!mecc!sewilco
(612)481-3507 sewilco@MECC.COM ihnp4!meccts!mecc!sewilco
"Who's that lurking over there? Is that Merv Griffin?"
------------------------------
Date: Sun 1 Feb 87 17:50:48-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Reply-to: AIList-Request@SRI-AI.ARPA
Subject: Revised Code Policy
OK, I give up. I've only received about ten comments, and the
negative ones are balanced by ones like this:
By the way, discussions of consciousness, code, lengthy
rebuttals, bibliographies, etc.: I love it all.
but the volume of the code messages has started to offend even
my sensibilities. I'll halt distribution through the Arpanet
mail channels unless I get too many requests for copies of the
full text. Arpanetters who still want the code can FTP the
files <AILIST>AIE*.TXT from SRI-STRIPE (using ANONYMOUS login)
where * ranges from 1 through 22. (1 through 8 have been sent.)
Others who want the original nine 50K-char mesage files can send a
request to AIList-Request@SRI-STRIPE.ARPA. Try not to make multiple
requests from one site, although I realize that there's no good
coordination mechanism.
The lesson here seems to be that the AIList is a discussion
list rather than a distribution list. The code met my previous
criteria for inclusion -- it was a noncommercial submission,
relevant to AI, and of interest to a reasonable proportion of
the list membership. I had thought that the bulk was acceptable
for a one-shot event; this seems to have been the case on the
Usenet half of AIList, but not on the Arpanet half. There really
should be separate Arpanet lists for discussion and for seminar
and conference notices, bibliographies, code, and the like. (I'm
still waiting for volunteers ...)
I apologize for the awkwardness of this resolution. Having
started to provide the material, I find myself in the situation
of the man with the donkey who learned he couldn't please
everyone. There won't be an easy remedy for these situations
until someone develops netwide fileservers and FTP, or at
least a coordinated list system that allows people to register
their interest profiles without human intervention.
I should also point out that Usenet has its comp.sources distribution,
but that the Arpanet lacks any broadcast channel for sharing code.
Perhaps it shouldn't have one, given the current U.S. paranoia about
technology export, but there are definite advantages for shared
subroutine libraries over having each student, researcher, or
engineer reinvent from scratch. This exposure to "real code" may
also have had the beneficial effect of popping some illusions about
the nature of expert systems code, permitting the advantages of other
approaches (C, ADA, software engineering, sharable libraries, etc.)
to compete against the AI mystique.
-- Ken Laws
------------------------------
Date: 30 Jan 87 00:47:31 GMT
From: imagen!turner@ucbvax.Berkeley.EDU (D'arc Angel)
Subject: posting of AI expert sources
When i offered to post the AI Expert source listings, I received a
few weeks of please post or please email or both, as i result i am
unsure who asked for mailings and got the subsequent postings and
who did not receive them, so... could the people who did not get
them off of comp.ai or were missing parts please send me email so i
can make sure everybody got what they wanted.
Also due to my unfamiliarity with IBM PC format (that's where they
came from) i included trailing CR's (↑M) in the shar file, this
caused unshar to complain about missing control codes. to the best
of my knowledge this had no effect on the sources and future
postings will have the CR's stripped.
C'est la vie, C'est le guerre, C'est la pomme de terre
Mail: Imagen Corp. 2650 San Tomas Expressway Santa Clara, CA 95052-8101
UUCP: ...{decvax,ucbvax}!decwrl!imagen!turner AT&T: (408) 986-9400
------------------------------
Date: Mon, 26 Jan 87 14:40 EST
From: Tim Finin <Tim@cis.upenn.edu>
Subject: source postings from AI EXPERT magazine
If anyone is interested in the source code which goes with my AI EXPERT
articles on frame-based representation languages (Nov. and Dec '87, it can
be FTP'd from linc.cis.upenn.edu. The file ~tim/pfl/pfltar contains a tar
tape of all of neccessary files.
Tim
------------------------------
Date: Thu, 29 Jan 87 11:55:12 est
From: schatz@thumper.bellcore.com (Bruce R. Schatz at
thumper.bellcore.com)
Subject: Telesophy Project
Readers of this newsgroup may be interested in the following:
The Telesophy Project at Bell Communications Research is a
research effort to understand how to provide uniform access
to AnyThing AnyWhere and thus permit browsing the WorldNet.
A telesophy system transparently stores and retrieves
information of different types from different locations.
We have built a prototype on Sun workstation hardware, which
accesses multiple datatypes from multiple databases on multiple machines.
A set of databases have been obtained, ranging from Netnews
to journal citations to full-text magazines to color pictures,
and we are beginning to use the system on a daily basis.
The prototype attempts to achieve the full potential of networks of
bitmapped workstations. It provides a content-addressable distributed file
system coupled with local multi-media editing. Building such an
end-to-end system requires finding some workable solution to a myriad of
unsolved research problems.
We are seeking new colleagues to help build the telesophy prototype.
[...]
Bruce Schatz
schatz@bellcore.com
(decvax,ihnp4,ucbvax)!bellcore!schatz
------------------------------
Date: 30 Jan 87 10:39:15 EST
From: Marcella.Zaragoza@isl1.ri.cmu.edu
Subject: Seminar - Knowledge-Based Reasoning Toolkit (CMU)
AI SEMINAR
TOPIC: Knowledge-Based Reasoning at the Right Level of Abstraction:
A Generic Task Toolkit
SPEAKER: B. Chandrasekaran
Laboratory for Artificial Intelligence Research
Department of Computer and Information Science
The Ohio State University
Columbus, Ohio 43210
PLACE: Wean Hall 5409
DATE: Tuesday, February 3, 1987
TIME: 3:30 pm
ABSTRACT:
The first part of the talk is a critique of the level of abstraction of much
of the current discussion on knowledge-based systems. It will be argued
that the discussion at the level of rules-logic-frames-networks is the
"civil engineering" level, and there is a need for a level of abstraction
that corresponds to what the discipline of architecture does for
construction of buildings. The constructs in architecture, viewed as a
language of habitable spaces, can be @i(implemented ) using the constructs
of civil engineering, but are not reducible to them. Similarly, the level
of abstraction that we advocate is the language of generic tasks, types of
knowledge and control regimes.
In the second part of the talk, I will outline the elements of a framework
at this level of abstraction for expert system design that we have been
developing in our research group over the last several years. Complex
knowledge-based reasoning tasks can often be decomposed into a number of
@i(generic tasks each with associated types of knowledge and family of
control regimes). At different stages in reasoning, the system will
typically engage in one of the tasks, depending upon the knowledge available
and the state of problem solving. The advantages of this point of view are
manifold: (i) Since typically the generic tasks are at a much higher level
of abstraction than those associated with first generation expert system
languages, knowledge can be represented directly at the level appropriate to
the information processing task. (ii) Since each of the generic tasks has
an appropriate control regime, problem solving behavior may be more
perspicuously encoded. (iii) Because of a richer generic vocabulary in
terms of which knowledge and control are represented, explanation of problem
solving behavior is also more perspicuous. We briefly describe six generic
tasks that we have found very useful in our work on knowledge-based
reasoning: classification, state abstraction, knowledge-directed retrieval,
object synthesis by plan selection and refinement, hypothesis matching, and
assembly of compound hypotheses for abduction.
Finally, we will describe how the above approach leads naturally to
a new technology: a toolbox which helps one to build expert systems
by using higher level building blocks. We will review the toolbox,
and outline what sorts of systems can be build using the toolbox,
and what advantages accrue from this approach.
------------------------------
Date: 30 Jan 87 10:45:09 EST
From: Marcella.Zaragoza@isl1.ri.cmu.edu
Subject: Seminar - Understanding How Devices Work (CMU)
AI SEMINAR
TOPIC: Understanding How Devices Work: Functional Representation
of Devices and Compilation of Diagnostic Knowledge
SPEAKER: B. Chandrasekaran
Department of Computer & Information Science
The Ohio State University
Columbus, OH 43210
PLACE: Wean Hall 4605
DATE: Wednesday, February 4, 1987
TIME: 10:00 a.m.
ABSTRACT:
Where does diagnostic knowledge -- knowledge about malfunctions and their
relation to observations -- come from? One source of it is an agent's
understanding of how devices work, what has been called a ``deep model.''
We distinguish between deep models in the sense of scientific first
principles and deep cognitive models where the problem solver has a
qualitative symbolic representation of the system or device that accounts
qualtitatively for how the system ``works.'' We provide a typology of
different knowledge structures and reasoning processes that play a role in
qualitative or functional reasoning. We indicate where the work of Kuipers,
de Kleer and Brown, Davis, Forbus, Bylander, Sembugamoorthy and
Chandrasekaran fit in this typology and what types of information each of
them can produce. We elaborate on functional representations as deep
cognitive models for some aspects of causal reasoning in medicine.
Causal reasoning about devices or physical systems involves multiple types
of knowledge structures and reasoning mechanisms. Two broad types of
approaches can be distinguished. In one, causal reasoning is viewed mainly
as an ability to reason at different levels of detail: the work of Weiss and
Kulikowski, Patil and Pople come to mind. Any hierarchies in this line of
work have as organizing principle different levels of detail. In the other
strand of work, causal reasoning is viewed as reasoning from @i(structure)
of a device to its @i(behavior), from behavior to its @i(function), and from
all this to diagnostic conclusions. In this approach, the hierarchical
organization of the device or system naturally results in an ability to move
into more or less levels of detail. We discuss the primitives of such a
functional representation and show how it organizes an agent's understanding
of how a systems functions result from the behavior of the device, and how
such behavior results from the functions of the components and the structure
of the device. We also indicate how device-independent compilers can
process this representation and produce diagnostic knowledge organized in a
hiererchy that mirrors the functional hierarchy. Sticklen, Chandrasekaran
and Smith have work in progress that applies these notions to the medical
domain.
If you wish to meet with Dr. Chandrasekaran, please contact Marce at
x8818, or send mail to mlz@d.
------------------------------
Date: Fri, 30 Jan 87 14:28:03 EST
From: Jim Hendler <hendler@brillig.umd.edu>
Subject: Conference - Conceptual Information Processing
Call for Participation
Fourth Annual Workshop
on
Theoretical Issues in Conceptual Information Processing
Washington, D.C.
June 4-5, 1987
Sponsored by
American Association for Artificial Intelligence
and
University of Maryland Institute for
Advanced Computer Studies
Objectives:
The goal of the investigations under the title "conceptual information
processing" has been understanding intelligence and cognition
computationally, rather than merely the construction of performance programs
or formalization per se. Thus, this workshop will focus on an exploration
of issues common to representation and organization of knowledge and memory
for natural language understanding, planning, problem solving, explanation,
learning and other cognitive tasks. The approaches to be covered are united
by a concern with representation, organization and processing of conceptual
knowledge with an emphasis on empirical investigation of these phenomena by
experimentation and implementation of computer programs.
Format:
The TICIP workshop will be comprised of a combination of panels, invited
paper presentations, and "debates" designed to encourage lively and active
discussion. Not all participants will be invited to present, but all will
be expected to interact.
Attendance:
In order to maximize the interactive nature of this workshop, attendance
will be limited. Those interested in participating, either as speakers or
audience, are asked to submit a one-page summary of work in this area. A
small number of invitations will be extended to those who are interested in
the area but have not yet contributed. Those interested in such an
invitation should contact the Program Chair. A limited amount of financial
assistance will be available to graduate students invited to participate.
Review Process:
Invitation will be based on an informal review of submissions by the Program
Committee.
Workshop Information:
The conference chair is Prof. B. Chandrasekaran (Ohio State University). The
program committee consists of Prof.s R. Alterman (Brandeis), J. Carbonell
(CMU), M. Dyer (UCLA), and J. Hendler (U of Maryland, Chair).
Submission:
A one page abstract of recent work in the area should be submitted to the
Program Chair. The deadline for these submissions is April 15, 1987.
Applicants will be informed of their status soon thereafter. Send abstracts
(but please, no papers) to:
James Hendler
Computer Science Department
University of Maryland
College Park, Md. 20742.
hendler@brillig.umd.edu
hendler@maryland
------------------------------
End of AIList Digest
********************
∂02-Feb-87 0352 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #29
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 2 Feb 87 03:52:12 PST
Date: Sun 1 Feb 1987 22:39-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #29
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 2 Feb 1987 Volume 5 : Issue 29
Today's Topics:
Philosophy - Consciousness & Methodological Epiphenomenalism
----------------------------------------------------------------------
Date: Thu, 29 Jan 87 09:27 EST
From: Seth Steinberg <sas@bfly-vax.bbn.com>
Subject: Consciousness?
I always thought that a scientific theory had to undergo a number of
tests to determine how "good" it is. Needless to say, a perfect score
on one test may be balanced by a mediocre score on another test. Some
useful tests are:
- Does the theory account for the data?
- Is the theory simple? Are there unnecessary superfluousities?
- Is the theory useful? Does it provide the basis for a fruitful
program of research?
There are theories of the mind which include consciousness and those
arguing that it is secondary - a side effect of thought. It seems
quite probable that the bulk of artificial intelligence work (machine
reasoning, qualitative physics, theorem proving ... ) can be performed
without considering this thorny issue. While I frequently accuse my
computers of malice, I doubt they are consciously malicious when they
flake out on me.
While the study of consciousness is fascinating and lies at the base of
numerous religions, it doesn't seem to be scientifically useful. Do I
rewrite my code because the machine is conscious or because it is
getting the wrong answer? Is there a program of experimentation
suggested by the search for consciousness? (Don't confuse this with
using conscious introspection to build unconscious intelligence as I
would to guide a toy tank from my office to the men's room). Does
consciousness change the way artificial intelligence must be
programmed? The evidence so far says NO. [How is that for a baldfaced
assertion? Send me your code with comments showing how consciousness
is taken into account and I'll see if I can rewrite it without
consciousness].
I don't think scientific theories of consciousness are incorrect, I
think they are barren.
Seth
P.S. For an excellent example of a nifty but otherwise barren theory
read the essay Adam's Navel in Stephen Gould's book the Flamingo's
Smile.
------------------------------
Date: 28 Jan 87 17:36:10 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: More on Minsky on Mind(s)
Ken Laws <Laws@SRI-STRIPE.ARPA> wrote on mod.ai:
> I'm inclined to grant a limited amount of consciousness to corporations
> and even to ant colonies. To do so, though, requires rethinking the
> nature of pain and pleasure (to something related to homeostatis).
Unfortunately, the problem can't be resolved by mere magnanimity. Nor
by simply reinterpreting experience as something else -- at least not
without a VERY persuasive argument -- one no one in the history of the M/B
problem has managed to come up with so far. This history is just one of
hand-waving. Do you think "rethinking" pain as homeostastis does the trick?
> computer operating systems and adaptive communications networks are
> close [to conscious]. The issue is partly one of complexity, partly
> of structure, partly of function.
I'll get back to the question of whether experiencing is an
all-or-none phenomenon or a matter of degree below. For now, I just
wonder what kind and degree of structural/functional "complexity" you
believe adds up to EXPERIENCING pain as opposed to merely behaving as
if experiencing pain.
> I am assuming that neurons and other "simple" systems are C-1 but
> not C-2 -- and C-2 is the kind of consciousness that people are
> really interested in.
Yes, but do you really think that hard questions like these can be
settled by assumption? The question is: What justifies the inference
that an organism or device is experiencing ANYTHING AT ALL (C-1), and
what justifies interpreting internal functions as conscious ones?
Assumption does not seem like a very strong justification for an
inference or interpretation. What is the basis for your assumption?
I have proposed the TTT as the only justifiable basis, and I've given
arguments in support of that proposal. The default assumptions in the
AI/Cog-Sci community seem to be that sufficiently "complex" function
and performance capacity, preferably with "memory" and "learning," can be
dubbed "conscious," especially with the help of the subsidiary
assumption that consciousness admits of degrees. The thrust of my
critique is that this position is rather weak and arbitrary, and open
to telling counter-examples (like Searle's). But, more important, it
is not an issue on which the Cog-sci community even needs to take a
stand! For Cog-sci's objective goal -- of giving a causal explanation
of organisms' and devices' functional properties -- can be achieved
without embellishing any of its functional constructs with a conscious
interpretation. This is what I've called "methodological
epiphenomenalism." Moreover, the TTT (as an asymptotic goal) even
captures the intuitions about "sufficient functional complexity and
performance capacity," in a nonarbitrary way.
It is the resolution of these issues by unsupportable assumption, circularity,
arbitrary fiat and obiter dicta that I think is not doing the field
any good. And this is not at all because (1) it simply makes cog-sci look
silly to philosophers, but because, as I've repeatedly suggested, (2) the
unjustified embellishment of (otherwise trivial, toy-like) function
or performance as "conscious" can actually side-track cog-sci from its
objective, empirical goals, masking performance weaknesses by
anthropomorphically over-interpreting them. Finally (3), the
unrealizable goal of objectively capturing conscious phenomenology,
being illogical, threatens to derail cog-sci altogether, heading it in
the direction of hermeneutics (i.e., subjective interpretation of
mental states, i.e., C-2) rather than objective empirical explanation of
behavioral capacity. [If C-2 is "what people are really interested
in," then maybe they should turn to lit-crit instead of cog-sci.]
> The mystery for me is why only >>one<< subsystem in my brain
> seems to have that introspective property -- but
> multiple personalities or split-brain subjects may be examples that
> this is not a necessary condition.
Again, we'd probably be better off tackling the mystery of what the
brain can DO in the world, rather than what subjective states it can
generate. But, for the record, there is hardly agreement in clinical
psychology and neuropsychology about whether split-brain subjects or
multiple-personality patients really have more than one "mind," rather
than merely somewhat dissociated functions -- some conscious, some not --
that are not fully integrated, either temporally or experientially.
Inferring that someone has TWO minds seems to be an even trickier
problem than the usual problem ("solved" by the TTT) of inferring that
someone has ONE (a variant of the mind/body problem called the "other-minds"
problem). At least in the case of the latter we have our own, normal unitary
experience to generalize from...
> [Regarding the question of whether consciousness admits of degrees:]
> An airplane either can fly or it can't. Yet there are
> simpler forms of flight used by other entities-- kites, frisbees,
> paper airplanes, butterflies, dandelion seeds... My own opinion
> is that insects and fish feel pain, but often do so in a generalized,
> nonlocalized way that is similar to a feeling of illness in humans.
Flight is an objective, objectively definable function. Experience is
not. We can, for example, say that a massive body that stays aloft in
space for any non-zero period of time is "flying" to a degree. There
is no logical problem with this. But what does it mean to say that
something is conscious to a degree? Does the entity in question
EXPERIENCE anything AT ALL? If so, it is conscious. If not, not. What
has degree to do with it (apart from how much, or how intensely it
experiences, which is not the issue)?
I too believe that lower animals feel pain. I don't want to conjecture
what it feels like to them; but having conceded that it feels like
anything at all, you seem to have conceded that they are conscious.
Now where does the question of degree come into it?
The mind/body problem is the problem of subjectivity. When you ask
whether something is conscious, you're asking whether it has
subjective states at all, not which ones, how many, or how strong.
That is an all-or-none matter, and it concerns C-1. You can't speak of
C-2 at all until you have a principled handle on C-1.
> I assume that lower forms experience lower forms of consciousness
> along with lower levels of intelligence. Such continuua seem natural
> to me. If you wish to say that only humans and TTT-equivalents are
> conscious, you should bear the burden of establishing the existence
> and nature of the discontinuity.
I happen to share all those assumptions about consciousness in lower
forms, except that I don't see any continuum of consciousness there at
all. They're either conscious or not. I too believe they are conscious,
but that's an all-or-none matter. What's on a continuum is what they're
conscious OF, how much, to what degree, perhaps even what it's "like" for
them (although the latter is more a qualitative than a quantitative
matter). But THAT it's like SOMETHING is what it is that I am
assenting to when I agree that they are conscious at all. That's C-1.
And it's the biggest discontinuity we're ever likely to know of.
(Note that I didn't say "ever likely to experience," because of course
we DON'T experience the discontinuity: We know what it is like to
experience something, and to experience more or less things, more or less
intensely. But we don't know what it's like NOT to experience
something. [Be careful of the scope of the "not" here: I know what
it's like to see not-red, but not what it's like to not-see red, or be
unconscious, etc.] To know what it's like NOT to experience
anything at all is to experience not-experiencing, which is
a contradiction in terms. This is what I've called, in another paper,
the problem of "uncomplemented" categories. It is normally solved by
analogy. But where the categories are uncomplementable in principle,
analogy fails in principle. I think that this is what is behind our
incoherent intuition that consciousness admits of degrees: Because to
experience the conscious/unconscious discontinuity is logically
impossible, hence, a fortiori, experientially impossible.)
> [About why neurons are conscious and atoms are not:]
> When someone demonstrates that atoms can learn, I'll reconsider.
You're showing your assumptions here. What can be more evident about
the gratuitousness of mentalistic interpretation (in place of which I'm
recommending abstention or agnosticism on methodological grounds)
than that you're prepared to equate it with "learning"?
> You are questioning my choice of discontinuity, but mine is easy
> to defend (or give up) because I assume that the scale of
> consciousness tapers off into meaninglessness. Asking whether
> atoms are conscious is like asking whether aircraft bolts can fly.
So far, it's the continuum itself that seems meaningless (and the defense
a bit too easy-going). Asking questions about subjective phenomena
is not as easy as asking about objective ones, hopeful analogies
notwithstanding. The difficulty is called the mind/body problem.
> I hope you're not insisting that no entity can be conscious without
> passing the TTT. Even a rock could be conscious without our having
> any justifiable means of deciding so.
Perhaps this is a good place to point out the frequent mistake of
mixing up "ontic" questions (about what's actually TRUE of the world)
and "epistemic" ones (about what we can KNOW about what's actually true of
the world, and how). I am not claiming that no entity can be conscious
without passing the TTT. I am not even claiming that every entity that
passes the TTT must be conscious. I am simply saying that IF there is
any defensible basis for inferring that an entity is conscious, it is
the TTT. The TTT is what we use with one another, when we daily
"solve" the informal "other-minds" problem. It is also cog-sci's
natural asymptotic goal in mind-modeling, and again the only one that
seems methodologically and logically defensible.
I believe that animals are conscious; I've even spoken of
species-specific variants of the TTT; but with these variants both our
intuitions and our ecological knowledge become weaker, and with them
the usefulness of the TTT in such cases. Our inability to devise or
administer an animal TTT doesn't make animals any less conscious. It just
makes it harder to know whether they are, and to justify our inferences.
(I'll leave the case of the stone as an exercise in applying the
ontic/epistemic distinction.)
>>SH: "(To reply that synthetic substances with the same functional properties
>> must be conscious under these conditions is to beg the question.)"
>KL: I presume that a synthetic replica of myself, or any number of such
> replicas, would continue my consciousness.
I agree completely. The problem was justifying attributing consciousness
to neurons and denying it to, say, atoms. It's circular to say
neurons are conscious because they have certain functional properties
that atoms lack MERELY on the grounds that neurons are functional
parts of (obviously) conscious organisms. If synthetic components
would work just as well (as I agree they would), you need a better
justification for imputing consciousness to neurons than that they are
parts of conscious organisms. You also need a better argument for
imputing consciousness to their synthetic substitutes. The TTT is my
(epistemic) criterion for consciousness at the whole-organism level.
Its usefulness and applicability trail off drastically with lower and lower
organisms. I've criticized cog-sci's default criteria earlier in this
response. What criteria do you propose, and what is the supporting
justification, for imputing consciousness to, say, neurons?
> Perhaps professional philosophers are able to strive for a totally
> consistent world view.
The only thing at issue is logical consistency, not world view. And even
professional scientists have to strive for that.
> Why is there Being instead of Nothingness? Who cares?
These standard examples (along with the unheard sound of the tree
falling alone in the forest) are easily used to lampoon philosophical
inquiry. They tend to be based on naive misunderstandings of what
philosophers are actually doing -- which is usually as significant and
rigorous as any other area of logically constrained intellectual
inquiry (although I wouldn't vouch for all of it, in any area of
inquiry).
But in this case consider the actual ironic state of affairs:
It is cog-sci that is hopefully opening up and taking an ambitious
position on the problems that normally only concern philosophers,
such as the mind/body problem. NONphilosophers are claiming : "this is
conscious and that's not," and "this is why," and "this is what
consciousness is." So who's bringing it up, and who's the one that cares?
Moreover, I happen myself to be a nonphilosopher (although I have a
sizeable respect for that venerable discipline and its inevitable quota
of insightful exponents); yet I repeatedly find myself in the peculiar
role of having to point out the philosophically well-known howlers
that cog-sci keeps tumbling into in its self-initiated inquiry into
"Nothingness." More ironic still, in arguing for the TTT and methodological
epiphenomenalism, I am actually saying: "Why do you care? Worrying about
consciousness will get you nowhere, and there's objective empirical
work to do!"
> If I had to build an aircraft, I would not begin by refuting
> theological arguments about Man being given dominion over the
> Earth rather than the Heavens. I would start from a premise that
> flight was possible and would try to derive enabling conditions.
Building aircraft and devices that (attempt to) pass the TTT are objective,
do-able empirical tasks. Trying to model conscious phenomenology, or to
justify interpreting processes as conscious, gets you as embroiled in
"theology" as trying to justify interpreting the Communal wafer as the
body of Christ. Now who's the pragmatist and who's the theologian?
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: 30 Jan 87 07:39:00 EST
From: "CUGINI, JOHN" <cugini@icst-ecf>
Reply-to: "CUGINI, JOHN" <cugini@icst-ecf>
Subject: Why I am not a Methodological Epiphenomenalist
> > Me: Consciousness may be as superflouous (wrt evolution) as earlobes.
> > That hardly goes to show that it ain't there.
>
> Harnad: Agreed. It only goes to show that methodological epiphenomalism may
> indeed be the right research strategy.
>
> > I don't think [the existence of consciousness] does NEED to be so.
> > It just is so.
>
> Fine. Now what are you going to do about it, methodologically speaking?
>
> ... Methodological epiphenomenalism recommends we face it [the inability
> to objectively measure subjective phenomena] and live
> with it, since not that much is lost. The "incompleteness" of an
> objective account is, after all, just a subjective problem. But
> supposing away the incompleteness -- by wishful thinking, hopeful
> over-interpretation, hidden (subjective) premises or blurring of the
> objective/subjective distinction -- is a logical problem.
A few points:
1. Insofar as meth.. ep.. (ME) is simply the following kind of counsel:
"when trying to get a computer to play chess, don't worry about the
subjective feelings which accompany human chess-playing, just get the
machine to make the right moves", I have no particular quarrel with it.
2. It is the claim that the TTT is the only relevant criterion (or,
by far, the major criterion) for the presence of consciousness that
strikes me as unnecessarily provocative and, almost as bad, false.
It is not clear to me whether this claim is an integral part of ME,
or an independent thesis. At any rate, such a claim is clearly
a philosophical one, having to do mainly with the epistemology of
consciousness, and as such is fair game for philosophically-based
(rather than AI-research-based) debate. If the claim instead were
that the TTT is the major criterion for the presence of intelligence
(defined in a perhaps somewhat austere way, as the ability to
perform certain kinds of tasks...) then, again, I would have no
serious disagreement.
3. Is the incompleteness of objective accounts of the world "just
a subjective problem" ? Is it true that "not that much is lost"?
Well, I guess each of us can decide how much to be bothered by this
incompleteness. I agree it's no argument against AI, psychophysics
or anything else that they "leave consciousness out" any more than it
is that they leave astronomy out. But there are astronomers around to
cover that ground (metaphorical ground, of course). It does bother me
(more than it does you?) that consciousness, of all things,
consciousness, which may be subjective, but, we agree, is real,
consciousness, without which my day would be so boring, is simply not
addressed by any systematic rational inquiry.
John Cugini <Cugini@icst-ecf>
------------------------------
Date: 26 Jan 87 23:43:37 GMT
From: clyde!watmath!utzoo!dciem!mmt@rutgers.rutgers.edu (Martin
Taylor)
Subject: Re: Minsky on Mind(s)
> To telescope the intuitive sense
>of the rebuttals: Do you believe rooms or corporations feel pain, as
>we do?
That final comma is crucial. Of course they do not feel pain as we do,
but they might feel pain, as we do.
On what grounds do you require proof that something has consciousness,
rather than proof that it has not? Can there be grounds other than
prejudice (i.e. prior judgment that consciousness in non-humans is
overwhelmingly unlikely?). As I understand the Total Turing Test,
the objective is to find whether soemthing can be distinguished from
human, but this again prejudges the issue. I don't think one CAN use
the TTT to assess whether another entity is conscious.
As I have tried to say in a posting that may or may not get to mod.ai,
Okham's razor demands that we describe the world using the simplest
possible hypotheses, INCLUDING the boundary conditions, which involve
our prior conceptions. It seems to me simpler to ascribe consciousness
to an entity that resembles me in many ways than not to ascribe
consciousness to that entity. Humans have very many points of resemblance;
comatose humans fewer. Silicon-based entities have few overt points
of resemblance, so their behaviour has to be convincingly like mine
before I will grant them a consciousness like mine. I don't really
care whether their behaviour is like yours, if you don't have
consciousness, and as Steve Harnad has so often said, mine is the
only consciousness I can be sure of.
The problem splits in two ways: (1) Define consciousness so that it does
not involve a reference to me, or (2) Find a way of describing behaviour
that is simpler than ascribing consciousness to me alone. Only if you
can fulfil one of these conditions can there be a sensible argument about
the consciousness of some entity other than ME.
--
Martin Taylor
{allegra,linus,ihnp4,floyd,ubc-vision}!utzoo!dciem!mmt
{uw-beaver,qucis,watmath}!utcsri!dciem!mmt
------------------------------
End of AIList Digest
********************
∂02-Feb-87 0703 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #30
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 2 Feb 87 07:03:04 PST
Date: Sun 1 Feb 1987 22:42-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #30
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 2 Feb 1987 Volume 5 : Issue 30
Today's Topics:
Philosophy - Consciousness
----------------------------------------------------------------------
Date: 30 Jan 87 01:51:19 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: Minsky on Mind(s)
mmt@dciem.UUCP (Martin Taylor) of D.C.I.E.M., Toronto, Canada,
writes:
> Of course [rooms and corporations] do not feel pain as we do,
> but they might feel pain, as we do.
The solution is not in the punctuation, I'm afraid. Pain is just an
example standing in for whether the candidate experiences anything AT
ALL. It doesn't matter WHAT a candidate feels, but THAT it feels, for
it to be conscious.
> On what grounds do you require proof that something has consciousness,
> rather than proof that it has not? Can there be grounds other than
> prejudice (i.e. prior judgment that consciousness in non-humans is
> overwhelmingly unlikely?).
First, none of this has anything to do with proof. We're trying to
make empirical inferences here, not mathematical deductions. Second,
even as empirical evidence, the Total Turing Test (TTT) is not evidential
in the usual way, because of the mind/body problem (private vs. public
events; objective vs. subjective inferences). Third, the natural null
hypothesis seems to be that an object is NOT conscious, pending
evidence to the contrary, just as the natural null hypothesis is that
an object is, say, not alive, radioactive or massless until shown
otherwise. -- Yes, the grounds for the null hypothesis are that the
presence of consciousness is more likely than its absence; the
alternative is animism. But no, the complement to the set of
probably-conscious entities is not "non-human," because animals are
(at least to me) just about as likely to be conscious as other humans
are (although one's intuitions get weaker down the phylogenetic scale);
the complement is "inanimate." All of these are quite natural and
readily defensible default assumptions rather than prejudices.
> [i] Occam's razor demands that we describe the world using the simplest
> possible hypotheses.
> [ii] It seems to me simpler to ascribe consciousness to an entity that
> resembles me in many ways than not to ascribe consciousness to that
> entity.
> [iii] I don't think one CAN use the TTT to assess whether another
> entity is conscious.
> [iv] Silicon-based entities have few overt points of resemblance,
> so their behaviour has to be convincingly like mine before I will
> grant them a consciousness like mine.
{i} Why do you think animism is simpler than its alternative?
{ii} Everything resembles everything else in an infinite number of
ways; the problem is sorting out which of the similarities is relevant.
{iii} The Total Turing Test (a variant of my own devise, not to be
confused with the classical turing test -- see prior chapters in these
discussions) is the only relevant criterion that has so far been
proposed and defended. Similarities of appearance are obvious
nonstarters, including the "appearance" of the nervous system to
untutored inspection. Similarities of "function," on the other hand,
are moot, pending the empirical outcome of the investigation of what
functions will successfully generate what performances (the TTT).
{iv} [iv] seems to be in contradiction with [iii].
> The problem splits in two ways: (1) Define consciousness so that it does
> not involve a reference to me, or (2) Find a way of describing behaviour
> that is simpler than ascribing consciousness to me alone. Only if you
> can fulfil one of these conditions can there be a sensible argument
> about the consciousness of some entity other than ME.
It never ceases to amaze me how many people think this problem is one
that is to be solved by "definition." To redefine consciousness as
something non-subjective is not to solve the problem but to beg the
question.
[The TTT, by the way, I proposed as logically the strongest (objective) evidence
for inferring consciousness in entities other than oneself; it also seems to be
the only methodologically defensible evidence; it's what all other
(objective) evidence must ultimately be validated against; moreover, it's
already what we use in contending with the other-minds problem intuitively
every day. Yet the TTT remains more fallible than conventional inferential
hypotheses (let alone proof) because it is really only a pragmatic conjecture
rather than a "solution." It's only good up to turing-indistinguishability,
which is good enough for the rest of objective empirical science, but not
good enough to handle the problem of subjectivity -- otherwise known as the
mind/body problem.]
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: 30 Jan 87 23:35:23 GMT
From: clyde!watmath!utzoo!dciem!mmt@rutgers.rutgers.edu (Martin
Taylor)
Subject: Re: More on Minsky on Mind(s)
> More ironic still, in arguing for the TTT and methodological
>epiphenomenalism, I am actually saying: "Why do you care? Worrying about
>consciousness will get you nowhere, and there's objective empirical
>work to do!"
>
That's a highly prejudiced, anti-empirical point of view: "Ignore Theory A.
It'll never help you. Theory B will explain the data better, whatever
they may prove to be!"
Sure, there's all sorts of objective empirical work to do. There's lots
of experimental work to do as well. But there is also theoretical work
to be done, to find out how best to describe our world. If the descriptions
are simpler using a theory that embodies consciousness than using one that
does not, then we SHOULD assume consciousness. Whether this is the case
is itself an empirical question, which cannot be begged by asserting
(correctly) that all behaviour can be explained without resort to
consciousness.
--
Martin Taylor
{allegra,linus,ihnp4,floyd,ubc-vision}!utzoo!dciem!mmt
{uw-beaver,qucis,watmath}!utcsri!dciem!mmt
------------------------------
Date: Wed, 28 Jan 87 12:29:51 est
From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>
Subject: Laws on Consciousness
Ken Laws <Laws@SRI-STRIPE.ARPA> wrote:
> I'm inclined to grant a limited amount of consciousness to corporations
> and even to ant colonies. To do so, though, requires rethinking the
> nature of pain and pleasure (to something related to homeostatis).
Unfortunately, the problem can't be resolved by mere magnanimity. Nor
by simply reinterpreting experience as something else -- at least not
without a VERY persuasive argument -- one no one in the history of the M/B
problem has managed to come up with so far. This history is just one of
hand-waving. Do you think "rethinking" pain as homeostastis does the trick?
> computer operating systems and adaptive communications networks are
> close [to conscious]. The issue is partly one of complexity, partly
> of structure, partly of function.
I'll get back to the question of whether experiencing is an
all-or-none phenomenon or a matter of degree below. For now, I just
wonder what kind and degree of structural/functional "complexity" you
believe adds up to EXPERIENCING pain as opposed to merely behaving as
if experiencing pain.
> I am assuming that neurons and other "simple" systems are C-1 but
> not C-2 -- and C-2 is the kind of consciousness that people are
> really interested in.
Yes, but do you really think that hard questions like these can be
settled by assumption? The question is: What justifies the inference
that an organism or device is experiencing ANYTHING AT ALL (C-1), and
what justifies interpreting internal functions as conscious ones?
Assumption does not seem like a very strong justification for an
inference or interpretation. What is the basis for your assumption?
I have proposed the TTT as the only justifiable basis, and I've given
arguments in support of that proposal. The default assumptions in the
AI/Cog-Sci community seem to be that sufficiently "complex" function
and performance capacity, preferably with "memory" and "learning," can be
dubbed "conscious," especially with the help of the subsidiary
assumption that consciousness admits of degrees. The thrust of my
critique is that this position is rather weak and arbitrary, and open
to telling counter-examples (like Searle's). But, more important, it
is not an issue on which the Cog-sci community even needs to take a
stand! For Cog-sci's objective goal -- of giving a causal explanation
of organisms' and devices' functional properties -- can be achieved
without embellishing any of its functional constructs with a conscious
interpretation. This is what I've called "methodological
epiphenomenalism." Moreover, the TTT (as an asymptotic goal) even
captures the intuitions about "sufficient functional complexity and
performance capacity," in a nonarbitrary way.
It is the resolution of these issues by unsupportable assumption, circularity,
arbitrary fiat and obiter dicta that I think is not doing the field
any good. And this is not at all because (1) it simply makes cog-sci look
silly to philosophers, but because, as I've repeatedly suggested, (2) the
unjustified embellishment of (otherwise trivial, toy-like) function
or performance as "conscious" can actually side-track cog-sci from its
objective, empirical goals, masking performance weaknesses by
anthropomorphically over-interpreting them. Finally (3), the
unrealizable goal of objectively capturing conscious phenomenology,
being illogical, threatens to derail cog-sci altogether, heading it in
the direction of hermeneutics (i.e., subjective interpretation of
mental states, i.e., C-2) rather than objective empirical explanation of
behavioral capacity. [If C-2 is "what people are really interested
in," then maybe they should turn to lit-crit instead of cog-sci.]
> The mystery for me is why only >>one<< subsystem in my brain
> seems to have that introspective property -- but
> multiple personalities or split-brain subjects may be examples that
> this is not a necessary condition.
Again, we'd probably be better off tackling the mystery of what the
brain can DO in the world, rather than what subjective states it can
generate. But, for the record, there is hardly agreement in clinical
psychology and neuropsychology about whether split-brain subjects or
multiple-personality patients really have more than one "mind," rather
than merely somewhat dissociated functions -- some conscious, some not --
that are not fully integrated, either temporally or experientially.
Inferring that someone has TWO minds seems to be an even trickier
problem than the usual problem ("solved" by the TTT) of inferring that
someone has ONE (a variant of the mind/body problem called the "other-minds"
problem). At least in the case of the latter we have our own, normal unitary
experience to generalize from...
> [Regarding the question of whether consciousness admits of degrees:]
> An airplane either can fly or it can't. Yet there are
> simpler forms of flight used by other entities-- kites, frisbees,
> paper airplanes, butterflies, dandelion seeds... My own opinion
> is that insects and fish feel pain, but often do so in a generalized,
> nonlocalized way that is similar to a feeling of illness in humans.
Flight is an objective, objectively definable function. Experience is
not. We can, for example, say that a massive body that stays aloft in
space for any non-zero period of time is "flying" to a degree. There
is no logical problem with this. But what does it mean to say that
something is conscious to a degree? Does the entity in question
EXPERIENCE anything AT ALL? If so, it is conscious. If not, not. What
has degree to do with it (apart from how much, or how intensely it
experiences, which is not the issue)?
I too believe that lower animals feel pain. I don't want to conjecture
what it feels like to them; but having conceded that it feels like
anything at all, you seem to have conceded that they are conscious.
Now where does the question of degree come into it?
The mind/body problem is the problem of subjectivity. When you ask
whether something is conscious, you're asking whether it has
subjective states at all, not which ones, how many, or how strong.
That is an all-or-none matter, and it concerns C-1. You can't speak of
C-2 at all until you have a principled handle on C-1.
> I assume that lower forms experience lower forms of consciousness
> along with lower levels of intelligence. Such continuua seem natural
> to me. If you wish to say that only humans and TTT-equivalents are
> conscious, you should bear the burden of establishing the existence
> and nature of the discontinuity.
I happen to share all those assumptions about consciousness in lower
forms, except that I don't see any continuum of consciousness there at
all. They're either conscious or not. I too believe they are conscious,
but that's an all-or-none matter. What's on a continuum is what they're
conscious OF, how much, to what degree, perhaps even what it's "like" for
them (although the latter is more a qualitative than a quantitative
matter). But THAT it's like SOMETHING is what it is that I am
assenting to when I agree that they are conscious at all. That's C-1.
And it's the biggest discontinuity we're ever likely to know of.
(Note that I didn't say "ever likely to experience," because of course
we DON'T experience the discontinuity: We know what it is like to
experience something, and to experience more or less things, more or less
intensely. But we don't know what it's like NOT to experience
something. [Be careful of the scope of the "not" here: I know what
it's like to see not-red, but not what it's like to not-see red, or be
unconscious, etc.] To know what it's like NOT to experience
anything at all is to experience not-experiencing, which is
a contradiction in terms. This is what I've called, in another paper,
the problem of "uncomplemented" categories. It is normally solved by
analogy. But where the categories are uncomplementable in principle,
analogy fails in principle. I think that this is what is behind our
incoherent intuition that consciousness admits of degrees: Because to
experience the conscious/unconscious discontinuity is logically
impossible, hence, a fortiori, experientially impossible.)
> [About why neurons are conscious and atoms are not:]
> When someone demonstrates that atoms can learn, I'll reconsider.
You're showing your assumptions here. What can be more evident about
the gratuitousness of mentalistic interpretation (in place of which I'm
recommending abstention or agnosticism on methodological grounds)
than that you're prepared to equate it with "learning"?
> You are questioning my choice of discontinuity, but mine is easy
> to defend (or give up) because I assume that the scale of
> consciousness tapers off into meaninglessness. Asking whether
> atoms are conscious is like asking whether aircraft bolts can fly.
So far, it's the continuum itself that seems meaningless (and the defense
a bit too easy-going). Asking questions about subjective phenomena
is not as easy as asking about objective ones, hopeful analogies
notwithstanding. The difficulty is called the mind/body problem.
> I hope you're not insisting that no entity can be conscious without
> passing the TTT. Even a rock could be conscious without our having
> any justifiable means of deciding so.
Perhaps this is a good place to point out the frequent mistake of
mixing up "ontic" questions (about what's actually TRUE of the world)
and "epistemic" ones (about what we can KNOW about what's actually true of
the world, and how). I am not claiming that no entity can be conscious
without passing the TTT. I am not even claiming that every entity that
passes the TTT must be conscious. I am simply saying that IF there is
any defensible basis for inferring that an entity is conscious, it is
the TTT. The TTT is what we use with one another, when we daily
"solve" the informal "other-minds" problem. It is also cog-sci's
natural asymptotic goal in mind-modeling, and again the only one that
seems methodologically and logically defensible.
I believe that animals are conscious; I've even spoken of
species-specific variants of the TTT; but with these variants both our
intuitions and our ecological knowledge become weaker, and with them
the usefulness of the TTT in such cases. Our inability to devise or
administer an animal TTT doesn't make animals any less conscious. It just
makes it harder to know whether they are, and to justify our inferences.
(I'll leave the case of the stone as an exercise in applying the
ontic/epistemic distinction.)
>>SH: "(To reply that synthetic substances with the same functional properties
>> must be conscious under these conditions is to beg the question.)"
>KL: I presume that a synthetic replica of myself, or any number of such
> replicas, would continue my consciousness.
I agree completely. The problem was justifying attributing consciousness
to neurons and denying it to, say, atoms. It's circular to say
neurons are conscious because they have certain functional properties
that atoms lack MERELY on the grounds that neurons are functional
parts of (obviously) conscious organisms. If synthetic components
would work just as well (as I agree they would), you need a better
justification for imputing consciousness to neurons than that they are
parts of conscious organisms. You also need a better argument for
imputing consciousness to their synthetic substitutes. The TTT is my
(epistemic) criterion for consciousness at the whole-organism level.
Its usefulness and applicability trail off drastically with lower and lower
organisms. I've criticized cog-sci's default criteria earlier in this
response. What criteria do you propose, and what is the supporting
justification, for imputing consciousness to, say, neurons?
> Perhaps professional philosophers are able to strive for a totally
> consistent world view.
The only thing at issue is logical consistency, not world view. And even
professional scientists have to strive for that.
> Why is there Being instead of Nothingness? Who cares?
These standard examples (along with the unheard sound of the tree
falling alone in the forest) are easily used to lampoon philosophical
inquiry. They tend to be based on naive misunderstandings of what
philosophers are actually doing -- which is usual as significant and
rigorous as any other area of logically constrained intellectual
inquiry (although I wouldn't vouch for all of it, in any area of
inquiry).
But in this case consider the actual ironic state of affairs:
It is cog-sci that is hopefully opening up and taking an ambitious
position on the problems that normally only concern philosophers,
such as the mind/body problem. NONphilosophers are claiming : "this is
conscious and that's not," and "this is why," and "this is what
consciousness is." So who's bringing it up, and who's the one that cares?
Moreover, I happen myself to be a nonphilosopher (although I have a
sizeable respect for that venerable discipline and its inevitable quota
of insightful exponents); yet I repeatedly find myself in the peculiar
role of having to point out the philosophically well-known howlers
that cog-sci keeps tumbling into in its self-initiated inquiry into
"Nothingness." More ironic still, in arguing for the TTT and methodological
epiphenomenalism, I am actually saying: "Why do you care? Worrying about
consciousness will get you nowhere, and there's objective empirical
work to do!"
> If I had to build an aircraft, I would not begin by refuting
> theological arguments about Man being given dominion over the
> Earth rather than the Heavens. I would start from a premise that
> flight was possible and would try to derive enabling conditions.
Building aircraft and devices that (attempt to) pass the TTT are objective,
do-able empirical tasks. Trying to model conscious phenomenology, or to
justify interpreting processes as conscious, gets you as embroiled in
"theology" as trying to justify interpreting the Communal wafer as the
body of Christ. Now who's the pragmatist and who's the theologian?
Stevan Harnad
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
(609)-921-7771
------------------------------
End of AIList Digest
********************
∂02-Feb-87 1919 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #31
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 2 Feb 87 19:14:10 PST
Date: Sun 1 Feb 1987 22:46-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #31
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 2 Feb 1987 Volume 5 : Issue 31
Today's Topics:
Seminar - Logic Programming: The Japanese Were Right (TI) &
A Logic of Knowledge, Action, and Communication (Rutgers) &
An Intelligent Modeling Environment (Rutgers) &
Knowledge-Based Inductive Inference (Rutgers) &
Spatial Objects in Database Systems (IBM) &
Induction in Model-Based Systems (SU) &
Influence Diagrams (CMU) &
The ISIS Project (CMU)
----------------------------------------------------------------------
Date: WED, 10 oct 86 17:02:23 CDT
From: leff%smu@csnet-relay
Subject: Seminar - Logic Programming: The Japanese Were Right (TI)
TI Computer Science Center Lecture Series
LOGIC PROGRAMMING: A TOOL FOR THINKING
(OR WHY THE JAPANESE WERE RIGHT)
Dr. Leon Sterling
Case Western Reserve University
10:00 am, Friday, 6 February 1987
Semiconductor Building Main Auditorium
Logic programming, or the design, study and implementation of logic
programs, will be significant in software developments of the future.
Logic programming links the traditional uses of logic in program
specification and database query languages with newer uses of logic as
a knowledge representation language for artificial intelligence and as
a general-purpose programming language. A logic program is a set of
axioms, or truths about the world. A computation of a logic program
is the use of axioms to make logical deductions. This talk will
discuss the value of logic programming for artificial intelligence
applications. It will demonstrate how a well-written logic program
can clearly reflect the problem solving knowledge of a human expert.
Examples will be given of AI programs in Prolog, the most developed of
the languages based on logic programming.
BIOGRAPHY
Leon Sterling received his Ph.D. in computational group theory from
the Australian National University in 1981. After three years as a
research fellow in the Department of Artificial Intelligence at the
University of Edinburgh, and one year as the Dov Biegun Postdoctoral
Fellow in the Computer Science Department at the Weizmann Institute of
Science, he joined the faculty at Case Western Reserve University in
1985. In 1986 he became Associate Director of the Center for
Automation and Intelligent Systems Research at Case Western. He is
co-author, with Ehud Shapiro, of the recent textbook on Prolog,
"The Art of Prolog."
Visitors to TI should contact Dr. Bruce Flinchbaugh (214-995-0349) in
advance and meet at the north lobby of the SC Building by 9:45 am.
------------------------------
Date: 26 Jan 87 23:03:47 EST
From: KALANTARI@RED.RUTGERS.EDU
Subject: Seminar - A Logic of Knowledge, Action, and Communication
(Rutgers)
RUTGERS COMPUTER SCIENCE AND RUTCOR COLLOQUIUM SCHEDULE - SPRING 1987
Computer Science Department Colloquium :
DATE: Thursday, January 29, 1987
SPEAKER: Leora Morgenstern
AFFILIATION: New York University
TITLE: Foundations of a Logic of Knowledge, Action, and Communication
TIME: 9:50 (Coffee and Cookies will be setup at 9:30)
PLACE: Hill Center, Room 705
Most AI planners work on the assumption that they have complete knowledge
of their problem domain and situation, so that formulating a plan consists
of searching through some pre-packaged list of action operators for an
action sequence that achieves some desired goal. Real life planning rarely
works this way because we usually don't have enough information to map out
a detailed plan of action when we start out. Instead, we initially draw up
a sketchy plan and fill in details as we proceed and gain more exact
information about the world.
This talk will present a formalism that is expressive enough to describe this
flexible planning process. We begin by discussing the various requirements
that such a formalism must meet, and present a syntactic theory of knowledge
that meets these requirements. We discuss the paradoxes, such as the Knower
Paradox, that arise from syntactic treatments of knowledge, and propose a
solution to these paradoxes based on Kripke's solution to the Liar Paradox.
Next, we present a theory of action that is powerful enough to describe
partial plans and joint-effort plans. We demonstrate that we can integrate
this theory with an Austinian and Searlian theory of communicative acts.
Finally, we give solutions to the Knowledge Preconditions and Ignorant Agent
Problems as part of our integrated theory of planning.
The talk will include comparisons of our theory with other syntactic and
modal theories such as Konolige's and Moore's. We will demonstrate
that our theory is powerful enough to solve classes of problems that these
theories cannot handle.
------------------------------
Date: 26 Jan 87 23:03:47 EST
From: KALANTARI@RED.RUTGERS.EDU
Subject: Seminar - An Intelligent Modeling Environment (Rutgers)
RUTGERS COMPUTER SCIENCE AND RUTCOR COLLOQUIUM SCHEDULE - SPRING 1987
Computer Science Department Colloquium :
DATE: Friday, January 30, 1987
SPEAKER: Dr. Axel Lehmann
AFFILIATION: University of Karlsruhe, Institute fur Informatik IV,
F.R. Germany
TITLE: An Interactive, Intelligent and Integrated
Modeling Environment
TIME: 11:00 AM
PLACE: Hill Center, Room 423
This paper describes an approach for interactive assistance of users
in the different phases of modeling processes for analysis of system
dynamics, especially regarding performance, reliability or
cost-benefit predictions of computer systems. The conceptual approach
is based on the assumptions that more and more experts out of various
domains, who are not familiar in detail with modeling techniques,
require supporting tools available on their PC or their workstation
for quantitative analysis of system dynamics as a basis for making
decisions.
Considering this situation, the global objective of the INT3 project
and the research involved is to provide system experts as well as
users supporting tools for problem specification, for interactive
selection and (graphical) construction of a problem-adapted
(simulation) model, for validation, experiment planning and for
interpretation of modeling results. Beside a detailed concept, we have
already implemented some graphical supporting tools for semi-automatic
model synthesis and for result interpretation, as well as prototypes
of expert systems as advisory systems for the selection of
problem-adapted modeling methods and of efficient solution techniques.
This paper summarizes the goals and our basic concept of INT3, an
interactive and knowledge-based modelling environment, including
actual restrictions and its initial implementation on IBM PC/XT or AT.
In addition, it is focused on the description and stepwise solution of
a typical computer performance analysis problem and a manufacturing
problem by means of these supporting tools. These examples will
demonstrate the applicability of this concept and of INT3, its actual
state of realization, experience and problems, as well, and future
plans.
------------------------------
Date: 26 Jan 87 23:03:47 EST
From: KALANTARI@RED.RUTGERS.EDU
Subject: Seminar - Knowledge-Based Inductive Inference (Rutgers)
RUTGERS COMPUTER SCIENCE AND RUTCOR COLLOQUIUM SCHEDULE - SPRING 1987
Computer Science Department Colloquium :
DATE: Friday, January 30, 1987
SPEAKER: Thomas G. Dietterich
AFFILIATION: Department of Computer Science, Oregon State University
TITLE: KNOWLEDGE-BASED INDUCTIVE INFERENCE
(or EBG: The wrong view)
TIME: 2:50 (Coffee and Cookies will be setup at 2:30)
PLACE: HILL 705
Explanation-based generalization (EBG) began as a reaction to such weak
syntactic inductive inference methods as AQ11, ID3, and the version space
approach. However, in its pursuit of "justifiable generalization", EBG has
been shown to be too strong--the system already knows (in Newell's knowledge
level sense) the knowledge it is trying to "learn." Despite this
shortcoming, the methods employed in EBG suggest ways that knowledge might
be incorporated into the inductive learning process. Using examples from
Meta-DENDRAL (Buchanan, et al.), Sierra (VanLehn), and WYL (Flann), it will
be argued that the process of forming "explanations" in EBG should be viewed
as knowledge-based representation change. Each of these systems can be
viewed as shifting the learning problem to an "explanation space" where
syntactic inductive inference methods are then applied. The conclusion is
that the "knowledge revolution," which has transformed most of the rest of
AI, has finally begun to affect machine learning research.
RUTCOR Colloquium : (Discrete Mathematics Seminar)
--------------------------------------
DATE: Tuesday, January 27, 1987
SPEAKER: Professor P.P. Palfy
AFFILIATION: Dept. of Mathematics, University of Hawaii at Manoa
a
TITLE: Applications of finite simple groups in combinatorics
TIME: 1:30
PLACE: Hill Center, Room 705
------------------------------
Date: Wed, 28 Jan 87 17:30:16 PST
From: IBM Almaden Research Center Calendar <CALENDAR@IBM.COM>
Subject: Seminar - Spatial Objects in Database Systems (IBM)
IBM Almaden Research Center
650 Harry Road
San Jose, CA 95120-6099
February 2-6, 1987
ACCESS STRUCTURES FOR SPATIAL OBJECTS IN NONTRADITIONAL DATABASE SYSTEMS
H.-P. Kriegel, University Wuerzburg, West Germany
Computer Science Seminar Monday, Feb. 2 1:00 P.M. Room: B3-247
Database systems must offer storage and access structures for spatial
objects to meet the needs of nontraditional applications such as
computer-aided design and manufacturing (CAD/CAM), image processing
and geographic information processing. First, we will show that
access methods for spatial objects should be based on multidimensional
dynamic hashing schemes. However, even for uniform object
distributions, previous schemes of this type do not exhibit ideal
performance; for nonuniform object distributions which are common in
the above mentioned applications, the retrieval performance of all
known schemes is rather poor. In this talk, we will present new
schemes which exhibit practically optimal retrieval performance for
uniform and nonuniform object distributions. We will underline this
fact by the results of experimental runs with implementations of our
schemes.
Host: D. Ruland
Visitors, please arrive 15 minutes early. IBM's new Almaden Research
Center (ARC) is located adjacent to Santa Teresa County Park, between
Almaden Expressway and U.S. 101, about 10 miles south of Interstate
280. From U.S. 101, exit at Bernal Road, and follow Bernal Road west
past Santa Teresa Blvd. into the hills (ignoring the left turn for
Santa Teresa Park). Alternatively, follow Almaden Expressway to its
southern terminus, turn left onto Harry Road, then go right at the ARC
entrance (about a quarter of a mile later) and go up the hill. For
more detailed directions, please phone the ARC receptionist at (408)
927-1080.
------------------------------
Date: 29 Jan 1987 1206-PST (Thursday)
From: Valerie Ross <ross@pescadero.stanford.edu>
Subject: Seminar - Induction in Model-Based Systems (SU)
CS 500 Computer Science Colloquium
Feb. 3, 4:15 pm, Skilling Auditorium
THE PROVISION OF INDUCTION AS A PROBLEM SOLVING METHOD
IN MODEL BASED SYSTEMS
DAVID HARTZBAND, D.Sc.
Artificial Intelligence Technology Group
Digital Equipment Corporation, Hudson, MA
Much research in artificial intelligence and cognitive science has focused on
mental modeling and the mapping of mental models to machine systems. This is
especially critical in systems which provide inference capabilities in order to
enhance peoples' problem solving abilities. Such a system should present a
machine model that is homomorphic with a human perception of knowledge
representation and problem solving. An approach to the development of such a
model has allowed a model-theoretic approach to be taken toward machine
representation and problem solving. Considerable work done in psychology,
cognitive science and decision analysis in the past 20 years has indicated that
human problem solving methods are primarily comparative (that is analogic) and
proceed by successive refinement of comparisons among known and unknown
entities (e.g. Carbonell, 1985; Rummelhart and Abrahamson, 1973; Simon, 1985;
Tversky, 1977).
A series of algorithms has been developed to provide analogic (Hartzband et al.
1986) and symmetric comparative induction methods (Hartzband and Holly, in
preparation) in the context of the homomorphic machine model previously
referred to. These general methods can be combined with heuristics and
structural information in a specific domain to provide a powerful problem
solving paradigm which could enhance human problem solving capabilities.
This paper will:
a. describe the characteristics of this model-theoretic approach,
b. describe (in part) the model used in this work,
c. develop both the theory and algorithms for comparative induction in
this context, and
d. discuss the use of these inductive methods in the provision of effective
problem solving paradigms.
------------------------------
Date: 26 Jan 87 17:54:08 EST
From: Charles.Wiecha@isl1.ri.cmu.edu
Subject: Seminar - Influence Diagrams (CMU)
Influence Diagrams: Graphical Representations for Uncertainty
Ross D. Shachter
Department of Engineering-Economic Systems
Stanford University
Wednesday, January 28
2:30-4:00 PM
Porter Hall 223D
The influence diagram is a network for structuring bayesian decision analysis
problems. The nodes represent uncertain quantities, goals, and decisions, and
the arcs indicate probabilistic dependence and the observability of
information. The graphical heirarchy promotes discussion by emphasizing the
structure of a problem and the relationships among variables, while allowing
the details of assessment to be completed later. Because the components have a
basic mathematical interpretation, even a qualitative diagram has a precise
meaning. When the quantitative information is complete, the influence diagram
can be evaluated in a generalization of decision tree solving. Examples using
influence diagrams will be drawn from decision analysis, information theory,
dynamic programming, Kalman filtering, and expert systems. In the latter, we
ask the question "Why do probabilists insist on looking at everything
backwards?"
------------------------------
Date: 27 Jan 87 10:39:13 EST
From: Patty.Hodgson@isl1.ri.cmu.edu
Subject: Seminar - The ISIS Project (CMU)
AI SEMINAR
TOPIC: THE ISIS PROJECT: AN HISTORICAL PERSPECTIVE OR LESSONS LEARNED
AND RESEARCH RESULTS
SPEAKER: MARK S. FOX, CMU Robotics Institute
PLACE: Wean Hall 5409
DATE: Tuesday, January 27, 1987
TIME: 3:30 pm
ABSTRACT:
ISIS is a knowledge-based system designed to provide intelligent
support in the domain of job shop production management and control.
Job-shop scheduling is a "uncooperative" multi-agent (i.e., each
order is to be "optimized" separately) planning problem in which
activities must be selected, sequenced, and assigned resources and
time of execution. Resource contention is high, hence closely
coupling decisions. Search is combinatorially explosive; for
example, 85 orders moving through eight operations without
alternatives, with a single machine substitution for each and no
machine idle time has over 10@+[880] possible schedules. Many of
which may be discarded given knowledge of shop constraints. At
the core of ISIS is an approach to automatic scheduling that provides
a framework for incorporating the full range of real world
constraints that typically influence the decisions made by human
schedulers. This results in an ability to generate detailed schedules
for production that accurately reflect the current status of the shop
floor, and distinguishes ISIS from traditional scheduling systems
based on more restrictive management science models. ISIS is capable
of incrementally scheduling orders as they are received by the shop
as well as reactively rescheduling orders in response to unexpected
events (e.g. machine breakdowns) that might occur.
The construction of job shop schedules is a complex constraint-directed
activity influenced by such diverse factors as due date requirements, cost
restrictions, production levels, machine capabilities and substitutability,
alternative production processes, order characteristics, resource
requirements, and resource availability. The problem is a prime candidate
for application of AI technology, as human schedulers are overburdened by
its complexity and existing computer-based approaches provide little more
than a high level predictive capability. It also raises some interesting
research issues. Given the conflicting nature of the domain's constraints,
the problem differs from typical constraint satisfaction problems. One
cannot rely solely on propagation techniques to arrive at an acceptable
solution. Rather, constraints must be selectively relaxed in which case
the problem solving strategy becomes one of finding a solution that best
satisfies the constraints. This implies that constraints must serve to
discriminate among alternative hypotheses as well as to restrict the number
of hypotheses generated. Thus, the design of ISIS has focused on
o constructing a knowledge representation that captures the requisite
knowledge of the job shop environment and its constraints to support
constraint-directed search, and
o developing a search architecture capable of exploiting this
constraint knowledge to effectively control the combinatorics of
the underlying search space.
This presentation will provide an historical perspective on the development
of ISIS family of systems. It will focus on the evolution of its
representation of knowledge and search techniques. Performance data for
each version will be presented.
------------------------------
End of AIList Digest
********************
∂05-Feb-87 0240 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #32
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 5 Feb 87 02:39:57 PST
Date: Wed 4 Feb 1987 22:51-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #32
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 5 Feb 1987 Volume 5 : Issue 32
Today's Topics:
Queries - Graphics for Frames and Semantic Networks & Learning Programs,
AI Tools - Expert Shell for VAX & PCs & OPS5 for 4.2BSD,
Discussion List - Color and Vision Network,
Seminars - Dynamic Belief Revision System (CMU) &
The Synthesis of Dirty Lisp Programs (SU) &
Why Software Cannot be Property (UTexas) &
Expert Systems in Manufacturing (UCB)
----------------------------------------------------------------------
Date: 29 Jan 87 13:34:34 GMT
From: mcvax!ukc!hrc63!hughes@seismo.css.gov (Andrew C. Hughes)
Subject: Graphics for frames and semantic networks
We have some people developing a knowledge representation system who wish to
implement a graphics based user interface which will support frame
editing/displaying taxonomic hierarchy/semantic network editing/displaying etc.
The system is currently written in Franz Lisp Opus 42.16 on a Sun 2,
but we hope to port to Common Lisp on a Sun 3 in the near future. The Lisp
should have an adequate interface to other languages such as 'c'.
Does anyone know of a package (preferably in the public domain) which would
ease the writing of such a UI, in particular allowing displaying/editing
of hierarchies, networks and frames.
Andrew Hughes (GEC Research, Chelmsford, UK)
Tel: +44 245 73331 Ext. 3247
Email: ..!mcvax!ukc!a.gec-mrc.co.uk!hughes
ARPA: hughes%a.gec-mrc.co.uk@ucl-cs
------------------------------
Date: 2 Feb 87 02:34:05 GMT
From: uwslh!lishka@rsch.wisc.edu (Christopher Lishka)
Subject: Re: Learning programs wanted [Public Domain preferred]
I would also be interested in any learning programs...maybe someone (I would
be willing) could collect replies and post a listing of NAMES of good
learning programs to comp.ai after everyone has sent in their info. [By
the way, what is this Marvin program?]
--
Chris Lishka /lishka@uwslh.uucp
Wisconsin State Lab of Hygiene <-lishka%uwslh.uucp@rsch.wisc.edu
\{seismo, harvard,topaz,...}!uwvax!uwslh!lishka
------------------------------
Date: Tue, 3 Feb 87 13:07:12 EST
From: "Fred J. Shaw" (IBD) <fshaw@BRL.ARPA>
Subject: expert shell for vax & pc's
In response to your request for an expert system shell that runs
on both unix and pc's. TIMM and TIMM-PC (General Research Corp 703-893-5900,
Mclean Va.) will run on vax and pc respectively. I have used TIMM a little
and am not impressed with it's capablities. I currently use Insight 2+ on
a pc.
Fred
------------------------------
Date: 3 Feb 87 11:31 PST
From: Ghenis.pasa@Xerox.COM
Subject: Re: OPS5 for 4.2BSD?
The Franz and Common Lisp versions of the OPS-5 source code are
available on CompuServe from the AI Expert Data Library. Some sample
programs are posted there as well.
Pablo Ghenis
Xerox Artificial Intelligence Systems
Educational Services
------------------------------
Date: 29-JAN-1987
From: CVNET%YORKVM1.BITNET@WISCVM.WISC.EDU
Subject: COLOR & VISION NETWORK
Forwarded from the Neuron Digest.]
COLOR AND VISION NETWORK
The Color and Vision Network is for scientists working in color and
vision research. At present the Network has three major activities.
1. Members' E-mail addresses are maintained and sent to all
those in the Network.
2. A key word list that associates scientists and their
interests within the areas of color and vision is
maintained and distributed.
3. Any person in the Network can have a bulletin,
announcement, etc, sent to all other people in the
Network.
Scientists working in color and/or vision who wish to join should
contact Peter Kaiser at:
cvnet@yorkvm1 or
cvnet%yorkvm1.bitnet@wiscvm.wisc.edu
They will receive the list of E-mail addresses plus a request to provide
key words which represent their interests and experience in color and/or
vision research.
Scientists from Australia, Canada, Germany, Japan, Netherlands,
Sweden, U.K., and the U.S. are in the Network. They come from universities,
research institutes, national laboratories and private industry. The list
is growing daily.
Peter K. Kaiser
York University
4700 Keele St.
North York, Ontario, M3J 1P3
Canada
pkaiser@yorkvm1.bitnet
pkaiser%yorkvm1.bitnet@wiscvm.wisc.edu
------------------------------
Date: 3 Feb 1987 1647-EST
From: Lydia DeFilippo <DEFILIPPO@C.CS.CMU.EDU>
Subject: Seminar - Dynamic Belief Revision System (CMU)
LOGIC COLLOQUIUM (CMU/PITT)
Speaker: Norman Foo and Anand Rao (U. Sydney/ IBM)
Date: Thursday, February 5
Time: 3:30
Place: Wean 5409
Topic: Dynamic belief revision system
We have combined the notions of constructive negation (Gabbay & Sergot),
stratified logic programs (Apt, Blair, & Walker), and the logic of small
changes (Gardenfors, Makinson, & Alchouron) to produce a sound and complete
belief revision system. This was done by separating the object logic from
the meta logic. The object logic turns out to be paraconsistent (Routley &
Priest).
This talk will discuss this work and plans for future extensions. One
extension is to adapt the logic to conceptual graphs and use it as a
back-end for the CONGRESS system. Another extension is to attempt a
graceful merger of finite failure negation with constructive negation.
If anyone would like to have an appointment with them, please contact
me @defilippo or x3063.
------------------------------
Date: 03 Feb 87 1153 PST
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - The Synthesis of Dirty Lisp Programs (SU)
Commonsense and Nonmonotonic Reasoning Seminar
THE SYNTHESIS OF DIRTY LISP PROGRAMS
Richard Waldinger
Artificial Intelligence Center
SRI International
Thursday, February 5, 4pm
Bldg. 160, Room 161K
Most work in program synthesis has focused on the
derivation of applicative programs, which return an
output but produce no side effects. In this talk we
turn to the synthesis of imperative programs, which
may alter data structures and produce other side effects
as part of their intended behavior. We concentrate on
"dirty LISP," an imperative LISP with assignment and
destructive list operations (rplaca and rplacd).
We treat dirty LISP with the same deductive approach
we use for the relatively clean applicative programs.
For this purpose, we introduce a new situational
logic, called "dirty-LISP theory." The talk will
emphasize how to represent instructions and specifications
in this theory.
------------------------------
Date: Tue, 3 Feb 1987 15:26 CST
From: AI.KUIPERS@R20.UTEXAS.EDU
Subject: Seminar - Why Software Cannot be Property (UTexas)
"Why Software Cannot Be Property"
Richard Stallman
Free Software Foundation
Friday, February 6, TAY 3.128
tea at 10:30 am
talk at 11:00 am
Richard Stallman is the creator of the Emacs text editor, and of GNU,
a freely distributed, complete software system to replace UNIX. He
was one of the hackers at the MIT Artificial Intelligence Laboratory,
and contributed in many ways to its excellent software environment,
including major portions of the design and implementation of the MIT
Lisp Machine software. The GNU project is inspired by his observations
on the personal, societal, and technical problems that result from
the commercialization of software.
------------------------------
Date: Mon, 2 Feb 87 16:29:11 PST
From: ashutosh%euler.Berkeley.EDU@berkeley.edu (Ashutosh Rege)
Subject: Seminar - Expert Systems in Manufacturing (UCB)
CS 298 Seminar
Expert Systems for Diagnostic and Control in Manufacturing
Prof. Alice M. Agogino
Dept. of Mechanical Engineering, UC Berkeley
608-7 Evans, Tuesday Feb.3, 5 - 6 pm.
Abtract : An architecture for the hierarchical integration of sensors and
diagnostic reasoning in expert systems for automated manufacturing and
process control is described. The system architecture uses influence diagrams
to provide a symbolic representation of the knowledge obtained from experts
with varying degrees of technical proficiency and from diverse domains of
expertise. The symbolic representation also maps to a functional level of
knowledge which can be used by the knowledge acquistion system to obtain a
more detailed numerical level of information from experts , maintenance
records, statistical data bases or sensor signals. The diagnostic
implementation uses probailistic inference to answer questions concerning
possible failures in an automated manufacturing or process system based on
observable sensor readings. A search through the influence diagram network
provides the topological solution or calculation sequence to answer any
such diagnostic query. Once the topological and numerical solution to the
influence diagram has been determined, qualitative and quantitative advice
can be relayed to the controller , operator or diagnostician. A description
of an implementation of such an architecture will be provided.
------------------------------
End of AIList Digest
********************
∂09-Feb-87 0024 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #33
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 9 Feb 87 00:23:52 PST
Date: Sun 8 Feb 1987 22:21-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #33
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 9 Feb 1987 Volume 5 : Issue 33
Today's Topics:
Queries - Terminfo Entry for Symbolics 3640 &
W.D. Clinger & Representation Languages &
E. Hausen-Tropper & MICE Expert System Shell,
Availability of Wilensky's UC & Public-Domain Expert System &
ExperLogo & Expert Shell for VAX and PCs &
Coordinator Systems & Connectionism,
Bibliographies - Connectionism/Neural Nets
----------------------------------------------------------------------
Date: 3 Feb 87 21:43:30 GMT
From: cadre!pitt!darth!beaver!frankb@pt.cs.cmu.edu (Frank Berry)
Subject: Terminfo entry for Symbolics 3640
I am serching a terminfo (SysV) entry that will work for
the Release 6.1 or earlier Symbolics terminal, remote-terminal.
The docs prescribe an 'ann arbor ambassador' of unspecified type,
but my use of several 'aaa' term types yield some ugliness.
Alternatively, does anyone have modified sources for remote-terminal.lisp
that deal with the terminal attributes normally encountered in say,
a 'vi' session?
Please, no flames about regressing to 'vi';I have to be able to connect
to several SysV machines via serial links.
Franklyn Berry
{allegra, bellcore, cadre, idis, psuvax1}!pitt!darth!beaver!frankb
Stingray:"Some day I'm going to call and ask you for a favor..."
------------------------------
Date: 3 Feb 87 18:53:00 GMT
From: uiucdcsm!mccaugh@a.cs.uiuc.edu
Subject: Actor Semantics
I apologize in advance if this appears in the wrong place...I need to
communicate with W.D. Clinger re: his work "Foundations of Actor Semantics"
(AI-TR-633, MIT AI Lab, May, 1981) and so would appreciate knowing how to
obtain a copy of it or how to reach the author. Thanks very much,
scott mccaughrin (mccaugh@uiucmsl)
------------------------------
Date: 5 Feb 87 03:37:30 GMT
From: berleant@sally.utexas.edu (Dan Berleant)
Subject: representation languages: richness and flexibility
Hmm. I just attended a lecture in which frame based representation
schemes were touted on the basis of the fact that representation
languages should be rich and flexible.
Well, it sounds good, it even sounds simple, but I'm sure not sure what
it means! In the context of representation languages, what is
'rich', and what is 'flexible'?
Dan Berleant
UUCP: {gatech,ucbvax,ihnp4,seismo,kpno,ctvax}!ut-sally!berleant
ARPA: ai.berleant@r20.utexas.edu
------------------------------
Date: Fri, 6 Feb 87 11:07:21 EST
From: munnari!trlamct.oz!andrew@seismo.CSS.GOV (Andrew Jennings)
Subject: trying to locate paper/author
If anyone has knowledge of who/where the author of :
E.Hausen-Tropper "An application of learning algorithms to telecommunication
networks", presented at 6th International Workshop on Expert Systems and
their Application, Avignon France 1986
is located, I'd be grateful.
UUCP: ...!{seismo, mcvax, ucb-vision, ukc}!munnari!trlamct.trl!andrew
ARPA: andrew%trlamct.trl.oz@seismo.css.gov
Andrew Jennings Telecom Australia Research Labs
"Its not enough to know a few bright sparks ..... you have to burn."
------------------------------
Date: 5 Feb 87 18:59:36 GMT
From: decvax!mcnc!duke!ravi@ucbvax.Berkeley.EDU (Ravi Subrahmanyan)
Subject: MICE expert system shell
Has anyone ordered the "MICE" expert system tool advertized in the
Winter "AI Magazine"? At $20 it seems to be too good to be true. (even
if the software isn't any good the blank disks would almost be worth it).
I am considering sending them my $20, but thought I'd see if anyone else
had first.
Thanks
Michael Lee Gleicher (-: If it looks like I'm wandering
Duke University (-: around like I'm lost . . .
Now appearing at : duke!ravi (-:
Or P.O.B. 5899 D.S., Durham, NC 27706 (-: It's because I am!
------------------------------
Date: 6 Feb 87 04:28:28 GMT
From: nosc!humu!uhmanoa!uhccux!todd@sdcsvax.ucsd.edu (The Perplexed
Wiz)
Subject: availability of Wilensky's UC?
Does anyone know if Wilensky's UC (UNIX Consultant) program is available
anywhere? I'd like to install it on a VAX 8650 with a large population of
new UNIX users.
Please let me know if you know anything about the availability of UC...todd
References:
Wilensky, R. (1982). Talking to UNIX in English: An overview of UC.
Proceedings of the Second Annual National Conference on
Artificial Intelligence. Pittsburgh.
Wilensky, R. (1983). Planning and understanding: A computational
approach to human reasoning. New York: Addison-Wesley Pub. Co.
--
Todd Ogasawara, U. of Hawaii Computing Center
UUCP: {ihnp4,seismo,ucbvax,dcdwest}!sdcsvax!nosc!uhccux!todd
ARPA: uhccux!todd@nosc.ARPA
INTERNET: todd@UHCC.HAWAII.EDU
------------------------------
Date: 6 Feb 87 18:12:36 GMT
From: cmcl2!localhost!aecom!aecom2!lyakhovs@seismo.CSS.GOV
Subject: expert sysyem
I am looking into reserch of expert systems.
I was wondering if any body have writen a shell or an expert system itself
utilizing blackbord and many other good things.
If you wouldn't mind shring your sourses with me or the rest of the net
please post it or direct me to where i might find one.
P.S. Thankx in advence for your input.
------------------------------
Date: 8 Feb 87 23:41:59 GMT
From: princeton!puvax2!6065833%PUCC.BITNET@rutgers.rutgers.edu (Una
Smith)
Subject: ExperLogo
I have found ExperLogo for the Macintosh a very unsatisfactory product. There
are several problems with it:
The current version was written for 128 and 512K macs, and I have had various
adventures getting it to run on a mac+.
1) To work on a mac+, certain files must be together in a certain folder,
says the company.
2) The program works with System 3.1 and Finder 5.0, but not with any more
recent versions. These versions are obsolete and there are very few
around. They were in any case very buggy.
3) The company told me when I called on 2 occasions 2 different things:
a) "Finder 5.3? When did that come out?" (answer: almost a year ago)
b) "There is a bug in Finder 5.3, which Apple will have to fix. Have
you tried calling Apple?"
4) I have not, after many hours of work, managed to print to a laserwriter;
the program offers very little interfacing support for other applications,
and the documentation is incredibly deficient.
I would not recommend this application to anyone. I have found MS Logo to
be quite nice and flexible, however. Can anyone recommend another LOGO
for the macintosh? Has anyone found a way to print graphics windows on
a laserwriter? Any information would be greatly appreciated.
------------------------------
Date: Thu, 5 Feb 87 17:24:30 PST
From: Stergios Marinopoul <stergios@rocky.stanford.edu>
Reply-to: rocky!stergios@rocky.stanford.edu (Stergios Marinopoul)
Subject: Re: expert shell for vax & pc's
In article <8702031307.aa03835@IBD.BRL.ARPA> fshaw@BRL.ARPA ("Fred J.
Shaw", IBD) writes:
>
> In response to your request for an expert system shell that runs
>on both unix and pc's. TIMM and TIMM-PC (General Research Corp 703-893-5900,
>Mclean Va.) will run on vax and pc respectively. I have used TIMM a little
>and am not impressed with it's capablities. I currently use Insight 2+ on
>a pc.
> Fred
You can obtain an expert system shell that runs on most computers in use today.
It is called CLIPS ( C Language Integrated Production Systems), is available
from COSMIC, and is developed/supported by the AI section, MPAD divsion,
NASA Johnson Space Center. The cost through COSMIC is ~$200.00 including
source.
The last time I was around there it was running on Vaxens, IBM, (big&littles)
HP9000, AS9000, CYBER, Amiga, and the Atari. It was written with the purpose
of being portable, and extendable by the user.
So, check it out. If you need some help obtaining it let me know,
and I'll see what I can do.
Stergios Marinopoulos
% UUCP: { lll-crg, seismo, sun } !rocky!stergios %
% ARPA: f.flex@othello.stanford.edu %
% USnail: Crothers Memorial #690, Stanford, CA. 94305 %
% Pa Bell: (415) 326-9051 %
------------------------------
Date: Sun, 8 Feb 87 08:38:22 est
From: davidwk@tecnet-clemson
Subject: References -- Coordinator systems
In their book "Understanding Computers and Cognition", Winograd and Flores
discuss coordinator systems, which are programs that employ ideas from Searle's
speech acts and system theory to facilitate "conversations" between computer
users. Is there anything in the literature about these creatures? I would
greatly appreciate any pointers.
Thanks in advance.
David Kelley
davidwk@tecnet-clemson.ARPA
------------------------------
Date: 2 Feb 87 14:01:20 GMT
From: mcvax!enea!pesv@seismo.css.gov (Peter Svenson)
Subject: Connectionism
I wonder if anyone could give me some -> Up to date <- pointers to current
literature on the field of connectionism/neural networks. The only things
I seem to be able to dig up of our Technical libraries (in Sweden) is stuff
about moths and leeches and other equally wierd things.
Where's the computer-related stuff??? Please give some hints complete with
which company that sells them, ISBN, etc..
Thank you very, very much.
/Peter (turbo) Svenson pesv@enea (UUCP) enea!pesv@seismo.arpa (ARPA)
"Zen can make you help other people, or, failing that, at least get them off
your back."
[This really belongs on the neuron%ti-csl.csnet@csnet-relay list,
but I'll go ahead and include the replies that came in on
comp.ai. -- KIL]
------------------------------
Date: 5 Feb 87 20:52:13 GMT
From: chandros@topaz.rutgers.edu (Jonathan A. Chandross)
Subject: Connectionism/Neural Net references
>Peter (turbo) Svenson pesv@enea (UUCP) enea!pesv@seismo.arpa (ARPA)
>I wonder if anyone could give me some -> Up to date <- pointers to current
>literature on the field of connectionism/neural networks. The only things
>I seem to be able to dig up of our Technical libraries (in Sweden) is stuff
>about moths and leeches and other equally wierd things.
Enclosed is a small sampling of what is available. Hope it helps. The
format is bib, but refer should work.
(Some of the references became a little scrambled courtesy of uncompact.
Sorry if bib/refer complain).
Jonathan A. Chandross
allegra!rutgers!topaz!chandros
%A Dell, Gary S.
%T A Spreading-Activation Theory of Retrieval in Sentence Production
%J Psychological Review
%V 93
%N 3
%D 1983
%P 283-321
%A Fahlman, Scott E.
%T Representing Implicit Knowledge
%B Parallel Models of Associative Memory
%E E Geoffrey E. Hinton
%E James A. Anderson
%D 1981
%I Lawrence Erlbaum Associates
%C Hillsdale, New Jersey
%A Fanty, Mark
%T Context-Free Parsing in Connectionist Networks
%R Tech Report TR174
%I Department of Computer Science, University of Rochester
%D Nov. 1985
%A Feldman, Jerome A.
%T A Connectionist Model of Visual Memory
%B Parallel Models of Associative Memory
%E Geoffrey E. Hinton
%E James A. Anderson
%D 1981
%I Lawrence Erlbaum Associates
%C Hillsdale, New Jersey
%A Feldman, Jerome A.
%A Dana H. Ballard
%T Connectionist Models and Their Properties
%J Cognitive Science
%V 6
%P 205-254
%D 1982
%A Feldman, Jerome A.
%T Dynamic Connections in Neural Networks
%J Biological Cybernetics
%I Springer-Verlag
%V 46
%D 1982
%P 27-39
%A Fodor, Jerry A.
%T Information and Association
%O This paper is a critique of connectionism. Author is with department
of Philosophy, MIT, Cambridge Massachussetts.
%A Hopfield, John J.
%T Neural Networks and physical systems with emergent collective
computational abilities
%J Proceedings National Acadamy of Science
%V 79
%P 2554-2558
%D Apr. 1982
%A Hopfield, John J.
%A David W. Tank
%T Simple "Neural" Optimization Networks: An A/D Converter, Signal Decision
Circuit, and a Linear Programming Circuit
%J IEEE Transactions on Circuits and Systems
%V CAS-33
%N 5
%P 533-541
%D May 1986
%A Hopfield, John J.
%A David W. Tank
%T Collective Computation with Continuous Variables
%J Disordered Systems and Biological Organization
%I Springer-Verlag
%O In press, 1986
%A Hopfield, John J.
%A David W. Tank
%T "Neural" Computation of Decisions in Optimization Problems
%J Biological Cybernetics
%I Springer-Verlag
%V 52
%D 1985
%P 141-152
%A Kosslyn, Stephen M.
%A Gary Hatfield
%T Representation without Symbol Systems
%J Social Research
%V 51
%N 4
%D 1984
%P 1019-1044
%O Winter 1984
%A Matthews, Robert J.
%T Problems with Representationalism
%J Social Research
%V 51
%N 4
%D 1984
O Winter 1984
%P 1065-1097
%A McClelland, James L.
%A Jerome Feldman
%A Beth Adelson
%A Gordon Bower
%A Drew McDermott
%T Connectionist Models and Cognitive Science: Goals, Directions and
Implications
%D Jan. 1987
%O National Science Foundation Grant Proposal
%A McClelland, James L.
%A David E. Rumelhart
%A The PDP Research Group
%T Parallel Distributed Processing: Explorations in the Microstructures
of Cognition
%I MIT Press
%C Cambridge, Massachusetts
%D 1986
%O Two Volume Set
%A Plaut, David C.
%J Visual Recognition of Simple Objects by a Connection Network
%R Tech Report TR143
%I Computer Science Department, University of Rochester
%D Aug. 1984
%A Pylyshyn, Zenon W.
%T Computation and Cognition: Toward a Foundation for Cognitive Science
%I MIT Press
%D 1984
%C Cambridge, Massachusetts
%A Reiss, Richard F.
%T An Abstract Machine Based on Classical Association Psychology
%B Proceedings 1962 Joint Computer Conference
%I AFIPS
%D 1962
%V 21
%A Shastri, Lokendra
%A Jerome A. Feldman
%T Semantic Networks and Neural Nets
%R Tech Report TR131
%I Computer Science Department, University of Rochester
%D June 1984
%A Schwartz, Robert
%T "The" Problems of Representation
%J Social Research
%V 51
%N 4
%D 1984
%P 1047-1064
%O Winter 1984
%A Touretzky, David S.
%A Geoffrey E. Hinton
%T Symbols Among the Neurons: Details of a Connectionist Inference
Architecture
%J IJCAI
%D Aug. 1985
------------------------------
Date: 6 Feb 87 22:29:37 GMT
From: ihnp4!chinet!nucsrl!coray@ucbvax.Berkeley.EDU (Elizabeth Coray)
Subject: Re: Connectionism
Re: Connectionist References
Ackley, D.H., Hinton, G.E., and Sejnowski, T.J. " A learning algorithm for
Boltzmann Machines", COGNITIVE SCIENCE 9, pp. 147-149, 1985.
Ballard, D.H., Hinton, G.E., and Sejnowski, T.J. "Parallel visual computation",
NATURE (London) 306, pp.21-26, 1983
Ballard, D.H., "Cortical connections and parallel processing: structure
and function", BEHAV. BRAIN SCI., 1985.
Barto, A.G. "Learning by statistical cooperation of self-interested neuron-
like computing elements", HUMAN NEUROBIOLOGY 4, pp. 229-256, 1985.
Feldman, J.A. and Ballard, D.H., "Connectionist models and their properties",
COGNITIVE SCIENCE 6, pp. 205-254, 1982.
Hinton, G.E. "Learning in Massively Parallel Nets", an invited talk at the
AAAI 1986 confence in Philadelphia. (The talk is not published in the
proceedings but may be available from the author--don't quote me).
Hinton, G.E. and Sejnowski, T.J. "Optimal perceptual inference" in
PROCEEDINGS OF THE IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION
AND PATTERN RECOGNITION, pp. 448-453, 1983.
Hopfield, J.J. and Tank, D.W., " 'Neural' computation of decisions in
optimization problems", BIOLOGICAL CYBERNETICS 52, pp. 141-152, 1985.
Kienker, P.K, Sejnowski, T.J., Hinton, G.E., Schumacher, L.E., "Separating
figure From ground with a parallel network", PERCEPTION 15, pp. 197-216.
Kirkpatrick, S., Gelatt, S., and Vecchi, M., "Optimization by Simulated
Annealing", SCIENCE 220, pp. 672-680, 1983.
Rumelhart, D.E., MccClelland, J.L. and the PDP research group, PARALLEL
DISTRIBUTED PROCESSING: EXPLORATIONS IN THE MICROSTRUCTURE OF COGNITION,
MIT Press, Cambridge Mass., 1986.
Saund, Eric "Abstraction and Representation of Continuous Variables
in Connectionist Networks", AAAI CONFERENCE PROCEEDINGS, pp. 638-644,
1986.
Sejnowski, T.J., Kienker, P.K., and Hinton, G.E., "Learning symmetry groups
with hidden units: Beyond the perceptron", PHYSICA D 22, 1986.
These references offer a starting point.
------------------------------
End of AIList Digest
********************
∂09-Feb-87 0222 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #34
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 9 Feb 87 02:22:30 PST
Date: Sun 8 Feb 1987 23:10-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #34
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 9 Feb 1987 Volume 5 : Issue 34
Today's Topics:
Philosophy - Consciousness & Objective Measurement of Subjective Variables
----------------------------------------------------------------------
Date: 26 Jan 87 09:41:00 GMT
From: mcvax!unido!ztivax!steve@seismo.css.gov
Subject: Harnad on Consciousness - (nf)
/* Written 5:10 pm Jan 23, 1987 by harnad@mind in ztivax:comp.ai */
Everyone knows that there's no
AT&T to stick a pin into, and to correspondingly feel pain. You can do
that to the CEO, but we already know (modulo the TTT) that he's
conscious. You can speak figuratively, and even functionally, of a
corporation as if it were conscious, but that still doesn't make it so.
To telescope the intuitive sense
of the rebuttals: Do you believe rooms or corporations feel pain, as
we do?
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
/* End of text from ztivax:comp.ai */
How do you know that AT&T doesn't feel pain? How do you know that corporations
are not conscious? People have referred to "national consciousness" (and other
consciousnesses of organisations) for a long time. The analogy works quite
well, too well for me to be certain that there is no truth to them. If neurons
are conscious, what kind of picture would they have of the consciousness of
a human? In my opinion, not much. Similarly, I cannot rule out the
possibility that corporations are also conscious. Corporations appear to act
in a conscious manner, but they do not share much experience with us neurons
(I mean humans). Therefore, we cannot do much of a Total Turing Test for
Corporations.
Harnad also suggested in another posting that he has never seen a convincing
argument that conscious interpretation is necessary to understand a given
set of objective behavior. Has he ever, I wonder, tried doing that to
human behavior? (I don't think I'm being very clear here.)
My position is this: if the conscious interpretation of a given set of
behavior is useful, then by all means interpret the behavior as conscious!
As for proving that behavior is conscious, I feel that that is impossible.
(At least for a philosopher.) For to do so would require a rigorous,
testable definition of consciousness and people (especially philosophers)
have a mystique about consciousness: if someone provides a rigorous,
testable definition for consciousness, then people will not accept it
because it is not mysterious - "it is just" something.
I'm afraid I'm not being very clear again. Consider the great numbers of
people who are very impressed about a computer learning program, and then
when they hear how it works, they say "that's not learning, that's just
optimisation [or whatever the learning algorithm is]." People have an
intuition that says things like "learning" "intelligence" and "consciousness"
are things that cannot be defined, and will reject definitions of them that
can be used for anything. This mystique has been greatly reduced over the
past few years for "intelligence", and people are wasting less and less time
arguing about whether computer programs really learn.
I suggest that the problem with "consciousness" is the same, that we reject
rigorous definitions because of our desire for a mystique. In the end, I
personally feel that the issue is not particularly important - that when it
becomes really useful to think of our programs as conscious (if it ever does)
then we will, and arguing about whether they really are conscious, especially
before we talk about them (routinely) as being conscious, is an exercise in
futility. I guess, though, that someone ought to argue against Minsky just
for the sake that he not go unchallenged.
When biologists get together, they don't waste their time trying to define
"life". No one has come up with a good definition of "life" to date. There
was a pretty good one a while back (unfortunately I don't remember all of it),
and part of it was something about converting energy for its benefit. Some
clever person showed that a rock satisfied this definition of life! When
sunlight falls on a rock, the rock warms up - (I forgot too much of this
anecdote, I don't remember why that is in the rock's benefit). When biologists
do talk about the meaning of (I mean, the definition of) life, they don't
expect to get anywhere, it is more of a game or something. And I suppose
occasionally some biologist thinks he's come up with the Ultimate Definition
of Life (using the Ten Tests of Timbuktu, or TTT :-) and goes on a one-man
crusade to convince the community that that's The Definition they've all
been looking for.
Have fun trying to send mail to me, it probably is possible but don't ask
me how.
Steve Clark EUnet: unido!ztivax!steve
Usenet: topaz!princeton!siemens!steve
CSnet: something like steve@siemens.siemens-rtl.com
------------------------------
Date: 31 Jan 87 23:13:11 GMT
From: clyde!burl!codas!mtune!mtund!adam@rutgers.rutgers.edu (Adam V.
Reed)
Subject: Re: Re: Objective measurement of subjective variables
This is a reply to Stevan Harnad, who wrote:
> adam@mtund.UUCP (Adam V. Reed), of AT&T ISL Middletown NJ USA, wrote:
>
> > Stevan Harnad makes an unstated assumption... that subjective
> > variables are not amenable to objective measurement. But if by
> > "objective" Steve means, as I think he does, "observer-invariant", then
> > this assumption is demonstrably false.
>
> I do make the assumption (let me state it boldly) that subjective
> variables are not objectively measurable (nor are they objectively
> explainable) and that that's the mind/body problem. I don't know what
> "observer-invariant" means, but if it means the same thing as in
> physics -- which is that the very same physical phenomenon can
> occur independently of any particular observation, and can in
> principle be measured by any observer, then individuals' private events
> certainly are not such, since the only eligible observer is the
> subject of the experience himself (and without an observer there is no
> experience -- I'll return to this below). I can't observe yours and you
> can't observe mine.
Yes, and in Efron's analogy, A can't observe B's, and vice versa.
However, I don't buy the assumption that two must *observe the same
instance of a phenomenon* in order to perform an *observer-independent
measurement of the same (generic) phenomenon*. The two physicists can
agree that they are studying the same generic phenomenon because they
know they are doing similar things to similar equipment, and getting
similar results. But there is nothing to prevent two psychologists from
doing similar (mental) things to similar (mental) equipment and getting
similar results, even if neither engages in any overt behavior apart
from reporting the results of his measurements to the other. My point is
that this constitutes objective (observer-independent) measurement of
private (no behavior observable by others) mental processes.
> That's one of the definitive features of the
> subjective/objective distinction itself, and it's intimately related to
> the nature of experience, i.e., of subjectivity, of consciousness.
>
> > Whether or not a stimulus is experienced as belonging to some target
> > category is clearly a private event...[This is followed by an
> > interesting thought-experiment in which the signal detection parameter
> > d' could be calculated for himself by a subject after an appropriate
> > series of trials with feedback and no overt response.]... the observer
> > would be able to mentally compute d' without engaging in any externally
> > observable behavior whatever.
>
> Unfortunately, this in no way refutes the claim that subjective experience
> cannot be objectively measured or explained. Not only is there (1) no way
> of objectively testing whether the subject's covert calculations on
> that series of trials were correct,
This objection applies with equal force to the observation, recording
and calculations of externally observable behavior. So what?
> not only is there (2) no way of
> getting any data AT ALL without his overt mega-response at the end
Yes, but *this is not what is being measured*. Or is the subject matter
of physics the communication behavior of physicists?
> (unless, of course, the subject is the experimenter, which makes the
> whole exercise solipsistic), but, worst of all, (3) the very same
> performance data could be generated by presenting inputs to a
> computer's transducer, and no matter how accurately it reported its
> d', we presumably wouldn't want to conclude that it had experienced anything
> at all. So what's OBJECTIVELY different about the human case?
What is objectively different about the human case is that not only is
the other human doing similar (mental) things, he or she is doing those
things to similar (human mind implemented on a human brain) equipment.
If we obtain similar results, Occam's razor suggests that we explain
them similarly: if my results come from measurement of subjectively
experienced events, it is reasonable for me to suppose that another
human's similar results come from the same source. But a computer's
"mental" equipment is (at this point in time) sufficiently dissimilar
from a human's that the above reasoning would break down at the point
of "doing similar things to similar equipment with similar results",
even if the procedures and results somehow did turn out to be identical.
> At best, what's being objectively measured happens to correlate
> reliably with subjective experience (as we can each confirm in our own
> cases only -- privately and subjectively). What we are actually measuring
> objectively is merely behavior
Not true. As I have shown in my original posting, d' can be measured
without there *being* any behavior prior to measurement. There is
nothing in Harnad's reply to refute this.
> (and, if we know what to look for, also
> its neural substrate). By the usual objective techniques of scientific
> inference on these data we can then go on to formulate (again objective)
> hypotheses about underlying functional (causal) mechanisms. These should
> be testable and may even be valid (all likewise objectively). But the
> testability and validity of these hypotheses will always be objectively
> independent of any experiential correlations (i.e., the presence or
> absence of consciousness).
Why? And how can this be true in cases when it is the conscious
experience that is being measured?
> To put it my standard stark way: The psychophysics of a conscious
> organism (or device) will always be objectively identical to that
> of a turing-indistinguishable unconscious organism (or device) that
> merely BEHAVES EXACTLY AS IF it were conscious. (It is irrelevant whether
> there are or could be such organisms or devices; what's at issue here is
> objectivity. Moreover, the "reliability" of the correlations is of
> course objectively untestable.) This leaves subjective experience a
> mere "nomological dangler" (as the old identity theorists used to call
> it) in a lawful psychophysical account. We each (presumably) know it's
> there from our respective subjective observations. But, objectively speaking,
> psychophysics is only the study of, say, the detecting and discriminating
> capacity (i.e., behavior) of our trandsucer systems, NOT the qualities of our
> conscious experience, no matter how tight the subjective correlation.
> That's no limit on psychophysics. We can do it as if it were the study
> of our conscious experience, and the correlations may all be real,
> even causal. But the mind/body problem and the problem of objective
> measurement and explanation remain completely untouched by our findings,
> both in practise and in principle.
The above re-states Steve's position, but fails deal with my objections
to it.
> So even in psychophysics, the appropriate research strategy seems to
> be methodological epiphenomenalism. If you disagree, answer this: What
> MORE is added to our empirical mission in doing psychophysics if we
> insist that we are not "merely" trying to account for the underlying
> regularities and causal mechanisms of detection, discrimination,
> categorization (etc.) PERFORMANCE, but of the qualitative experience
> accompanying and "mediating" it? How would someone who wanted to
> undertake the latter rather than merely the former go about things any
> differently, and how would his methods and findings differ (apart from
> being embellished with a subjective interpretation)? Would there be any
> OBJECTIVE difference?
I think so - I would not accept as legitimate any psychological theory
which appeared to contradict my conscious experience, and failed to
account for the apparent contradiction. As far as I can tell, Steve's
position means that he would not disqualify a psychological theory just
because it happened to be contradicted by his own conscious experience.
> I have no lack of respect for psychophysics, and what it can tell us
> about the functional basis of categorization. (I've just edited and
> contributed to a book on it.) But I have no illusions about its being
> in any better a position to make objective inroads on the mind/body
> problem than neuroscience, cognitive psychology, artificial
> intelligence or evolutionary biology -- and they're in no position at all.
> > In principle, two investigators could perform the [above] experiment
> > ...and obtain objective (in the sense of observer-independent)
> > results as to the form of the resulting lawful relationships between,
> > for example, d' and memory retention time, *without engaging in any
> > externally observable behavior until it came time to compare results*.
>
> I'd be interested in knowing how, if I were one of the experimenters
> and Adam Reed were the other, he could get "objective
> (observer-independent) results" on my experience and I on his. Of
> course, if we make some (question-begging) assumptions about the fact
> that the experience of our respective alter egos (a) exists, (b) is
> similar to our own, and (c) is veridically reflected by the "form" of the
> overt outcome of our respective covert calculations, then we'd have some
> agreement, but I'd hardly dare to say we had objectivity.
These assumptions are not "question-begging": they are logically
necessary consequences of applying Occam's razor to this situation (see
above). And yes, I would tend to regard the resulting agreement among
different subjective observers as evidence for the objectivity of their
measurements.
> (What, by the way, is the difference in principle between overt behavior
> on every trial and overt behavior after a complex-series-of-trials?
> Whether I'm detecting individual signals or calculating cumulating d's
> or even more complex psychophysical functions, I'm just an
> organism/device that's behaving in a certain way under certain
> conditions. And you're just a theorist making inferences about the
> regularities underlying my performance. Where does "experience" come
> into it, objectively speaking? -- And you're surely not suggesting that
> psychophyics be practiced as a solipsistic science, each experimenter
> serving as his own sole subject: for from solipsistic methods you can
> only arrive at solipsistic conclusions, trivially observer-invariant,
> but hardly objective.)
For measurement to be *measurement of behavior*, the behavior must be,
in the temporal sequence, prior to measurement. But if the only overt
behavior is the communication of the results of measurement, then the
behavior occurs only after measurement has already taken place. So the
measurement in question cannot be a measurement of behavior, and must be
a measurement of something else. And the only plausible candidate for
that "something else" is conscious experience.
> > The following analogy (proposed, if I remember correctly, by Robert
> > Efron) may illuminate what is happening here. Two physicists, A and B,
> > live in countries with closed borders, so that they may never visit each
> > other's laboratories and personally observe each other's experiments.
> > Relative to each other's personal perception, their experiments are
> > as private as the conscious experiences of different observers. But, by
> > replicating each other's experiments in their respective laboratories,
> > they are capable of arriving at objective knowledge. This is also true,
> > I submit, of the psychological study of private, "subjective"
> > experience.
>
> As far as I can see, Efron's analogy casts no light at all.
See my comments at the beginning of this reply.
> It merely reminds us that even normal objectivity in science (intersubjective
> repeatability) happens to be piggy-backing on the existence of
> subjective experience. We are not, after all, unconscious automata. When we
> perform an "observation," it is not ONLY objective, in the sense that
> anyone in principle can perform the same observation and arrive at the
> same result. There is also something it is "like" to observe
> something -- observations are also conscious experiences.
>
> But apart from some voodoo in certain quantum mechanical meta-theories,
> the subjective aspect of objective observations in physics seems to be
> nothing but an innocent fellow-traveller: The outcome of the
> Michelson-Morley Experiment would presumably be the same if it were
> performed by an unconscious automaton, or even if WE were
> unconscious automata.
> This is decidely NOT true of the (untouched) subjective aspect of a
> psychophysical experiment. Observer-independent "experience" is a
> contradiction in terms.
Yes, but observer-independent *measurement of* experience is not. See
above.
> (Most scientists, by the way, do not construe repeatability to require
> travelling directly to one another's labs; rather, it's a matter of
> recreating the same objective conditions. Unfortunately, this does not
> generalize to the replication of anyone else's private events, or even
> to the EXISTENCE of any private events other than one's own.)
Yes it does: see the argument from Occam's razor earlier in this
article.
> Note that I am not denying that objective knowledge can be derived
> from psychophysics; I'm only denying that this can amount to objective
> knowledge about anything MORE than psychophysical performance and its
> underlying causal substrate. The accompanying subjective phenomenology is
> simply not part of the objective story science can tell, no matter how, and
> how tightly, it happens to be coupled to it in reality. That's the
> mind/body problem, and a fundamental limit on objective inquiry.
Steve seems to be saying that the mind-body problem constitutes "a
fundamental limit on objective inquiry", i.e. that this problem is *in
principle* incapable of ever being solved. I happen to think that human
consciousness is a fact of reality and, like all facts of reality, will
prove amenable to scientific explanation. And I like to think that
this explanation will constitute, in some scientifically relevant sense,
a solution to the "mind-body problem". So I don't see this problem as a
"fundamental limit".
> Methodological epiphenomenalism recommends we face it and live with
> it, since not that much is lost. The "incompleteness" of an objective
> account is, after all, just a subjective problem. But supposing away
> the incompleteness -- by wishful thinking, hopeful over-interpretation,
> hidden (subjective) premises or blurring of the objective/subjective
> distinction -- is a logical problem.
Yes, but need it remain one forever?
Adam Reed (mtund!adam, attmail!adamreed)
------------------------------
End of AIList Digest
********************
∂09-Feb-87 0420 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #35
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 9 Feb 87 04:20:21 PST
Date: Mon 9 Feb 1987 01:28-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #35
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 9 Feb 1987 Volume 5 : Issue 35
Today's Topics:
Philosophy - Consciousness & Nonconsciousness
----------------------------------------------------------------------
Date: Mon, 02 Feb 87 17:35:13 n
From: DAVIS@EMBL.BITNET
Subject: backtracking.....
It seems like its time on the AIList to cut around some of the
interesting but bottomless waffle that has come to fill this useful organ.
I fear that Stevan Harnad's most important point is being lost in his
endless efforts to deal with a shower of light and insubstantial blows.
At the same time, his own language and approach to the problem is
obscuring some of the issues he himself raises.
I cannot help but notice that the debates on conciousness that
we're seeing resemble the debating of the Data General engineers in
Tracy Kidder's book "The Soul of a New Machine". Its time to wake up
folks - we're not building a new Eclipse, with some giant semiconductor
supplying the new 60880 'concious' chip, and the only real task left
being the arranging of the goodies to make use of its wondrous capacities.
No, its time to wake up to the mystery of the C-1: How can ANYTHING *know*
ANYTHING at all ? We are not concerned with how we shuffle the use of
memory, illusion, perceptual inputs etc., so as to maximise efficiency and
speed - we are concerned with the most fundamental problem of all - how
can we know ? Too many contributors seem to me to be concerned with the
secondary extension of this question to a specific version of the general
one "how can we know about X ?". It may be important for AI programmers
to deal with ways of shuffling the data and the processing order so that
a system gets access to X for further data manipulation, but this has
ABSOLUTELY NOTHING to do with the primary question of how it is possible
to know anything.....
The glimpses of Dennet & Hofstadter's wise approach that we've seen
are encouraging, but still we see Harnad struggling with why's and not how's.
Being a molecular biologist by trade if not religion, I would like to
temporarily assert that conciousness is a *biological* phenomenon, and,
taking Harnad's bull by its horns once again, to assert further that because
this is so, the question of *why* conciousness is used is quite irrelevant
in this context. Haven't any of you read Armstrong and the other arguers
for the selection of conciousness as a means for social interaction ? I
agree with Harnad that to put the origin iof conciousness in the same murky
quasi-random froth as, say, that of selfsplicing introns is a backdoor exit
from the problem. However, conciousness would certianly seem to be here
-leave it to the evolutionary biologists to sort out why, while we get
on with the how.....
Not that we are getting anywhere fast though...and I would hark
back to the point I tried to raise a while back, merely to get sidetracked
into the semantics of intention vs. intension. This is the same point that
Harnad has been making somewhat obliquely in his wise call for performance
oriented development of AI systems. We have to separate the issues of
personal conciousness (subjective experience) and the notorious "problem
of other minds". When dealing with the possibilities of designing concious
machines, we can only concern ourselves with the latter issue - such devices
will *always* be "other minds" and never available for our subjective
experience. As many contributors have shown, we can only judge "other-mind"
conciousness by performance-oriented measures. So, on with the nuts, on
with the bolts, and forward to sentient silicon......
paul ("the questions were easy - I just didn't know the answers") davis
mail:EMBL,postfach 10.22.09, 6900 Heidleberg, FRG
email: davis@embl.bitnet
(and hence available from UUCP, ARPA, JANET, CSNET etc...)
------------------------------
Date: 3 Feb 87 06:01:23 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Why I Am Not A Methodological Mentalist
cugini@icst-ecf.UUCP ("CUGINI, JOHN") wrote on mod.ai:
> "Why I am not a Methodological Epiphenomenalist"
This is an ironic twist on Russell's sceptical book about religious
beliefs! I'm the one who should be writing "Why I'm Not a Methodological
Mentalist."
> Insofar as methodological epiphenomenalism (ME) is simply the
> following kind of counsel: "when trying to get a computer to
> play chess, don't worry about the subjective feelings which
> accompany human chess-playing, just get the machine to make
> the right moves", I have no particular quarrel with it.
It's a bit more than that, as indicated by the "Total" in the Total
Turing Test. The counsel is NOT to rest with toy models and modules:
That the only kind of performance which will meet our sole frail intuitive
criterion for contending with the real-world other-minds problem --
indistinguishability from a person like any other -- is the total
performance capacity of a (generic) person. Settling for less mires us
in an even deeper underdetermination than we're stuck in anyway. The
asymptotic TTT is the only way to reduce that underdetermination to
the level we're already accustomed to. Chess-playing's simple not
enough. In mind-modeling, it's all-or-nothing. And this is again a
methodological matter. [I know that this is going to trigger (not from
Cugini) another series of queries about animals, retardates, aliens,
subtotal modules. Please, first read the prior iterations on those matters...]
> It is the claim that the TTT is the only relevant criterion (or,
> by far, the major criterion) for the presence of consciousness that
> strikes me as unnecessarily provocative and, almost as bad, false.
> It is not clear to me whether this claim is an integral part of ME,
> or an independent thesis... If the claim instead were
> that the TTT is the major criterion for the presence of intelligence
> (defined in a perhaps somewhat austere way, as the ability to
> perform certain kinds of tasks...) then, again, I would have no
> serious disagreement.
The TTT is an integral part of ME, and the shorthand reminder of why it
must be is this: A complete, objective, causal theory of the mind will
always be equally true of conscious organisms like ourselves AND of
insentient automata that behave exactly as if they were conscious --
i.e., are turing-indistinguishable from ourselves. (It is irrelevant
whether there could really be such insentient perform-alikes; the point is
that there is no objective way of telling the difference. Hence the
difference, if any, cannot make a difference to the objective
theory. Ergo, methodological epiphenomenalism.)
The TTT may be false, of course; but unfortunately, it's not
falsifiable, so we cannot know whether or not it is in reality false.
[I'd also like to hold off the hordes -- again not Cugini -- who are
now poised to pounce on this "nonfalsifiability." The TTT is a
methodological criterion and not an empirical hypothesis. It's only
justification is that it's the only criterion available and it's the
one we use in real life already. It's also the best that one can hope for
from objective inquiry. And what is science, if not that?]
Nor will it do to try to duck the issue by focusing on "intelligence."
We don't know what intelligence is, except that it's something that
minds have, as demonstrated by what minds do. The issue, as I must
relentlessly keep recalling, is not one of definition. It cannot be
settled by fiat. Intelligence is as intelligence does. We know minds
are intelligent, if anything is. Hence only the capacity to pass the
TTT is so far entitled to be dubbed intelligent. Lesser performances
-- toy models and modules -- are no more than clever tricks, until we
know how (and whether) they figure functionally in a candidate that
can pass the TTT.
> It does bother me (more than it does you?) that consciousness,
> of all things, consciousness, which may be subjective, but, we
> agree, is real, consciousness, without which my day would be so
> boring, is simply not addressed by any systematic rational inquiry.
It does bother me. It used to bother me more; until I realized that
fretting about it only had two outcomes: To lure me into flawed
arguments about how consciousness can be "captured" objectively after
all, and to divert attention from ambitious performance modeling to
doing hermeneutics on trivial performances and promises of
performances. It also helps to settle my mind about it that if one
adopts an epiphenomenalist stance not only is consciousness
bracketed, but so is its vexatious cohort, "free will." I'm less
bothered in principle by the fact that (nondualistic) science has no
room for free will -- that it's just an illusion -- but that certainly
doesn't make the bothersome illusion go away in practice. (By the way,
without consciousness, your day wouldn't even be boring.)
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: 2 Feb 87 22:52:29 GMT
From: clyde!watmath!utzoo!dciem!mmt@rutgers.rutgers.edu (Martin
Taylor)
Subject: Re: Minsky on Mind(s)
>> = Martin Taylor (me) > = Steven Harnad
>
>> Of course [rooms and corporations] do not feel pain as we do,
>> but they might feel pain, as we do.
>
>The solution is not in the punctuation, I'm afraid. Pain is just an
>example standing in for whether the candidate experiences anything AT
>ALL. It doesn't matter WHAT a candidate feels, but THAT it feels, for
>it to be conscious.
Understood. Nevertheless, the punctuation IS important, for although it
is most unlikely they feel as we do, it is less unlikely that they feel.
>
>> [i] Occam's razor demands that we describe the world using the simplest
>> possible hypotheses.
>> [ii] It seems to me simpler to ascribe consciousness to an entity that
>> resembles me in many ways than not to ascribe consciousness to that
>> entity.
>> [iii] I don't think one CAN use the TTT to assess whether another
>> entity is conscious.
>> [iv] Silicon-based entities have few overt points of resemblance,
>> so their behaviour has to be convincingly like mine before I will
>> grant them a consciousness like mine.
>
>{i} Why do you think animism is simpler than its alternative?
Because of [ii].
>{ii} Everything resembles everything else in an infinite number of
>ways; the problem is sorting out which of the similarities is relevant.
Absolutely. Watanabe's Theorem of the Ugly Duckling applies. The
distinctions (and similarities) we deem important are no more or less
real than the infinity of ones that we ignore. Nevertheless, we DO see
some things as more alike than other things, because we see some similarities
(and some differences) as more important than others.
In the matter of consciousness, I KNOW (no counterargument possible) that
I am conscious, Ken Laws knows he is conscious, Steve Harnad knows he is
conscious. I don't know this of Ken or Steve, but their output on a
computer terminal is enough like mine for me to presume by that similarity
that they are human. By Occam's razor, in the absence of evidence to the
contrary, I am forced to believe that most humans work the way I do. Therefore
it is simpler to presume that Ken and Steve experience consciousness than
that they work according to one set of natural laws, and I, alone of all
the world, conform to another.
>{iii} The Total Turing Test (a variant of my own devise, not to be
>confused with the classical turing test -- see prior chapters in these
>discussions) is the only relevant criterion that has so far been
>proposed and defended. Similarities of appearance are obvious
>nonstarters, including the "appearance" of the nervous system to
>untutored inspection. Similarities of "function," on the other hand,
>are moot, pending the empirical outcome of the investigation of what
>functions will successfully generate what performances (the TTT).
All the TTT does, unless I have it very wrong, is provide a large set of
similarities which, taken together, force the conclusion that the tested
entity is LIKE ME, in the sense of [i] and [ii].
>{iv} [iv] seems to be in contradiction with [iii].
Not at all. What I meant was that the biological mechanisms of natural
life follow (by Occam's razor) the same rules in me as in dogs or fish,
and that I therefore need less information about their function than I
would for a silicon entity before I would treat one as conscious.
One of the paradoxes of AI has been that as soon as a mechanism is
described, the behaviour suddenly becomes "not intelligent." The same
is true, with more force, for consciousness. In my theory about another
entity that looks and behaves like me, Occam's razor says I should
presume consciousness as a component of their functioning. If I have
been told the principles by which an entity functions, and those principles
are adequate to describe the behaviour I observe, Occam's razor (in its
original form "Entities should not needlessly be multiplied") says that
I should NOT introduce the additional concept of consciousness. For the
time being, all silicon entities function by principles that are well
enough understood that the extra concept of consciousness is not required.
Maybe this will change.
>
>> The problem splits in two ways: (1) Define consciousness so that it does
>> not involve a reference to me, or (2) Find a way of describing behaviour
>> that is simpler than ascribing consciousness to me alone. Only if you
>> can fulfil one of these conditions can there be a sensible argument
>> about the consciousness of some entity other than ME.
>
>It never ceases to amaze me how many people think this problem is one
>that is to be solved by "definition." To redefine consciousness as
>something non-subjective is not to solve the problem but to beg the
>question.
>
I don't see how you can determine whether something is conscious without
defining what consciousness is. Usually it is done by self-reference.
"I experience, therefore I am conscious." Does he/she/it experience?
But never is it prescribed what experience means. Hence I do maintain
that the first problem is that of definition. But I never suggested that
the problem is solved by definition. Definition merely makes the subject
less slippery, so that someone who claims an answer can't be refuted by
another who says "that wasn't what I meant at all."
The second part of my split attempts to avoid the conclusion from
similarity that beings like me function like me. If a simpler description
of the world can be found, then I no longer should ascribe consciousness
to others, whether human or not. Now, I believe that better descriptions
CAN be found for beings as different from me as fish or bacteria or
computers. I do not therefore deny or affirm that they have experiences.
(In fact, despite Harnad, I rather like Ken Law's (?) proposition that
there is a graded quality of experience, rather than an all-or-none
choice). What I do argue is that I have better grounds for not treating
these entities as conscious than I do for more human-like entities.
Harnad says that we are not looking for a mathematical proof, which is
true. But most of his postings demand that we show the NEED for assuming
consciousness in an entity, which is empirically the same thing as
proving them to be conscious.
--
Martin Taylor
{allegra,linus,ihnp4,floyd,ubc-vision}!utzoo!dciem!mmt
{uw-beaver,qucis,watmath}!utcsri!dciem!mmt
------------------------------
Date: Sun 8 Feb 87 22:52:30-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Reply-to: AIList-Request@SRI-AI.ARPA
Subject: Disclaimer of Consciousness
From: clyde!watmath!utzoo!dciem!mmt@rutgers.rutgers.edu (Martin Taylor)
In the matter of consciousness, I KNOW (no counterargument possible)
that I am conscious, Ken Laws knows he is conscious, Steve Harnad
knows he is conscious.
I'm not so sure that I'm conscious. Oh, in the linguistic sense I
have the same property of consciousness that [we presume] everyone
has. But I question the "I experience a toothache" touchstone for
consciousness that Steve has been using. On the one hand, I'm not
sure I do experience the pain because I'm not sure what "I" is doing
the experiencing; on the other hand, I'm not sure that silicon systems
can't experience pain in essentially the same way. Instead of claiming
that robots can be conscious, I am just as willing to claim that
consciousness is an illusion and that I am just as unconscious as
any robot.
It is difficult to put this argument into words because the
presumption of consciousness is built into the language itself, so
let's try to examine the linguistic assumptions.
First, the word "I". The aspect of my existence that we are interested
in here is my mind, which is somehow dependent on my brain as a substrate.
My brain is system of neural circuits. The "I" is a property of the
system, and cannot be claimed by any neural subsystem (or homunculus),
although some subsystems may be more "central" to my identity than others.
Consciousness would also seem to be a property of the whole system.
But not so fast -- there is strong evidence that consciousness (in the
sense of experiencing and responding to stimuli) is primarily located
in the brain stem. Large portions of the cortex can be cut away with
little effect on consciousness, but even slight damage to the upper
brain stem cause loss of consciousness. [I am not recanting my position
that consciousness is quantitative across species. Within something
as complex as a human (or a B-52), emergent system properties can be
very fragile and thus seem to be all or nothing.] We must be careful
not to equate sensory consciousness with personality (or personal
behavioral characteristics, as in the TTT), self, or soul.
Well, I hear someone saying, that kind of consciousness hardly counts;
all birds and mammals (at least) can be comatose instead of awake --
that doesn't prove they >>experience<< pain when they are awake. Ah,
but that leads to further difficulties. The experience is real --
after all, behavior changes because of it. We need to know if the
process of experience is just the setting of bits in memory, or if
there is some awareness that goes along with the changes in the neural
substrate.
All right, then, how about self-awareness? As the bits are changed,
some other part of the brain (or the brain as a whole) is "watching"
and interprets the neural changes as a painful experience. But either
that pushes us back to a conscious homunculus (and ultimately to a
nonphysical soul) or we must accept that computers can be self-aware
in that same sense. No, self-awareness is Steve's C-2 consciousness.
What we have to get a grip on is C-1 consciousness, an awareness of
the pain itself.
One way out is to assume that neurons themselves are aware of pain,
and that our overall awareness is some sum over the individual
discomforts. But the summation requires that the neurons communicate
their pain, and we are back to the problem of how the rest of the
brain can sense and interpret that signal. A similar dead end is
to suppose that toothache signals interfere with brain functioning and
that the brain interprets its own performance degradations as pain.
What is the "I" that has the awareness of pain?
How do we know that we experience pain? (Or, following Descarte,
that we experience our own thought?) We can formulate sentences
about the experience, but it seems doubtful that our speech centers
are the subsystems that actually experience the pain. (That theory,
that all awareness is linguistic awareness, has been suggested. I am
reminded of the saying that there is no ideas so outrageous that it
has not been championed by some philosopher.) Similarly we can
rule out the motor center, the logical centers, and just about any
other centers of the brain. Either the pain is experienced by some
tiny neural subsystem, in which case "I" am not the conscious agent,
or it is experienced by the system as a whole, in which case analogous
states or processes in analogous systems should also be considered
conscious.
I propose that we bite the bullet and accept that our "experience"
or "awareness" of pain is an illusion, replicable in all relevant
respect by inorganic systems. Terms such as pain, experience,
awareness, consciousness, and self are crude linguistic analogies,
based on false models, to the true patterns of neural events.
Pain is real, as are the other concepts, but our model of how
they arise and interrelate is hopelessly animistic.
-- Ken Laws
------------------------------
End of AIList Digest
********************
∂09-Feb-87 1648 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #36
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 9 Feb 87 16:47:34 PST
Date: Mon 9 Feb 1987 09:04-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #36
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 9 Feb 1987 Volume 5 : Issue 36
Today's Topics:
Philosophy - Consciousness & Objective vs. Subjective Inquiry
----------------------------------------------------------------------
Date: 3 Feb 87 07:15:00 EST
From: "CUGINI, JOHN" <cugini@icst-ecf>
Reply-to: "CUGINI, JOHN" <cugini@icst-ecf>
Subject: pique experience
> Harnad: {iii} The Total Turing Test (a variant of my own devise, not
> to be confused with the classical turing test -- see prior chapters
> in these discussions) is the only relevant criterion that has so far
> been proposed and defended. Similarities of appearance are obvious
> nonstarters, including the "appearance" of the nervous system to
> untutored inspection.
Just a quick pout here - last December I posted a somewhat detailed
defense of the "brain-as-criterion" position, since it seemed to be a
major point of contention. (Again, the one with the labeled events
A1, B1, etc.). No one has responded directly to this posting. I'm
prepared to argue the brain-vs-TTT case on its merits, but it would be
helpful if those who assert the TTT position would acknowledge the
existence, if not the validity, of counter-arguments.
John Cugini <Cugini@icst-ecf>
------------------------------
Date: 3 Feb 87 19:51:58 GMT
From: norman@husc4.harvard.edu (John Norman)
Subject: Re: Objective vs. Subjective Inquiry
In article <462@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>Let's leave the subjective discussion of private events
>to lit-crit, where it belongs.
Could you elaborate on this smug comment, in detail?
John Norman
UUCP: {seismo,ihnp4,allegra,ut-sally}harvard!h-sc4!norman
Internet: norman%h-sc4@harvard.HARVARD.EDU
BITNET: NORMAN@HARVLAW1
------------------------------
Date: Wed, 4 Feb 87 10:44:32 pst
From: Ray Allis <ray@BOEING.COM>
Subject: Conscious Intelligence
I've been reading the discussion of consciousness with interest,
because I DO consider such philosophical inquiry to be relevant
to AI. Philosophical issues must be addressed if we are serious
about building "intelligent" systems. Lately, though, several
people, either explicitly or by expressing impatience with the
subject, have implied that they consider consciousness irrelevant
to AI. Does this reflect a belief that consciousness is irrelevant
to "natural" intelligence as well? What is the explanation for the
observation that "intelligent behavior" and consciousness seem to
occur together? Can an entity "behave intelligently" without being
conscious? Can an entity be conscious without being "intelligent"?
Is consciousness required in order to have "intelligent behavior" or
is it a side-effect? What are some examples? Counter-examples?
Even prior to some definitive answer to "The Mind-Body Problem", I
believe we should try to understand the nature of the relationship
between consciousness and "intelligent behavior", justify the
conclusion that there is no relationship, or lower our expectations
(and proclamations) considerably.
I'd like to see some forum for these discussions kept available,
whether or not it's the AILIST.
------------------------------
Date: 5 Feb 87 07:10:19 GMT
From: ptsfa!hoptoad!tim@LLL-LCC.ARPA (Tim Maroney)
Subject: Re: More on Minsky on Mind(s)
How well respected is Minsky among cognitive psychologists? I was rather
surprised to see him putting the stamp of approval on Drexler's "Engines of
Creation", since the psychology is so amazingly shallow; e.g., reducing
identity to a matter of memory, ignoring effects of the glands and digestion
on personality. Drexler had apparently read no actual psychology, only AI
literature and neuro-linguistics, and in my opinion his approach is very
anti-humanistic. (Much like that of hard sf authors.)
Is this true in general in the AI world? Is it largely incestuous, without
reference to scientific observations of psychic function? In short, does it
remain almost entirely speculative with respect to higher-order cognition?
--
Tim Maroney, Electronic Village Idiot
{ihnp4,sun,well,ptsfa,lll-crg,frog}!hoptoad!tim (uucp)
hoptoad!tim@lll-crg (arpa)
Second Coming Still Vaporware After 2,000 Years
------------------------------
Date: 3 Feb 87 16:10:05 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: Minsky on Mind(s)
mmt@dciem.UUCP (Martin Taylor) writes:
> we DO see some things as more alike than other things, because
> we see some similarities (and some differences) as more important
> than others.
The scientific version of the other-minds problem -- the one we deal
with in the lab and at the theoretical bench, as opposed to the informal
version of the other-minds problem we practice with one another every
day -- requires us to investigate what causal devices have minds, and,
in particular, what functional properties of those causal devices are
responsible for their having minds. In other words (unless you know
the answer to the theoretical problems of cognitive science and
neurosience a priori) it is an EMPIRICAL question what the relevant
underlying functional and structural similarities are. The only
defensible prior criterion of similarity we have cannot be functional
or structural, since we don't know anything about that yet; it can
only be the frail, fallible, underdetermined one we use already in
everyday life, namely, behavioral similarity.
Every other similarity is, in this state of ignorance, arbitrary,
a mere similarity of superficial appearance. (And that INCLUDES the
similarity of the nervous system, because we do not yet have the vaguest
idea what the relevant properties there are either.) Will this state of
affairs ever change? (Will we ever find similarities other than behavioral
ones on the basis of which we can infer consciousness?) I argue that it will
not change. For any other correlate of consciousness must be VALIDATED
against the behavioral criterion. Hence the relevant functional
similarities we eventually discover will always have to be grounded in
the behavioral ones. Their predictive power will always be derivative.
And finally, since the behavioral-indistinguishability criterion is itself
abundantly fallible -- incommensurably moreso than ordinary scientific
inferences and their inductive risks -- our whole objective structure
will be hanging on a skyhook, so to speak, always turing
indistinguishable from state of affairs in which everything behaves
exactly the same way, but the similarities are all deceiving, and
consciousness is not present at all. The devices merely behave exactly
as if it were.
Throughout the response, by the way, Taylor freely interchanges the
formal scientific problem of modeling mind -- inferring its substrates,
and hence trying to judge what functional conditions are validly
inferred to be conscious (what the relevant similarities are) -- with
the informal problem of judging who else in our everyday world is
conscious. Similarities of superficial appearance may be good enough
when you're just trying to get by in the world, and you don't have the
burden of inferring causal substrate, but it won't do any good with
the hard cases you have to judge in the lab. And in the end, even
real-world judgments are grounded in behavioral similarity
(indistinguishability) rather than something else.
> it is simpler to presume that Ken and Steve experience
> consciousness than that they work according to one set of
> natural laws, and I, alone of all the world, conform to another.
Here's an example of conflating the informal and the empirical
problems. Informally, we just want to make sure we're interacting with
thinking/feeling people, not insentient robots. In the lab, we have to
find out what the "natural laws" are that generate the former and not
the latter. (Your criterion for ascribing consciousness to Ken and me,
by the way, was a turing criterion...)
> All the TTT does, unless I have it very wrong, is provide a large set of
> similarities which, taken together, force the conclusion that the tested
> entity is LIKE ME
The Total Turing Test simply requires that the performance capacity of
a candidate that I infer to have a mind be indistinguishable from the
performance capacity of a real person. That's behavioral similarity
only. When a device passes that test, we are entitled to infer that
its functional substrate is also relevantly similar to our own. But
that inference is secondary and derivative, depending for its
validation entirely on the behavioral similarities.
> If a simpler description of the world can be found, then I no
> longer should ascribe consciousness to others, whether human or not.
I can't imagine a description sufficiently simple to make solipsism
convincing. Hence even the informal other-minds problem is not settled
by "Occam's Razor." Parsimony is a constraint on empirical inference,
not on our everyday, intuitive and practical judgements, which are
often not only uneconomical, but irrational, and irresistible.
> What I do argue is that I have better grounds for not treating
> these [animals and machines] as conscious than I do for more
> human-like entities.
That may be good enough for everyday practical and perhaps ethical
judgments. (I happen to think that it's extremely wrong to treat
animals inhumanely.) I agree that our intuitions about the minds of
animals are marginally weaker than about the minds of other people,
and that these intuitions get rapidly weaker still as we go down the
phylogenetic scale. I also haven't much more doubt that present-day
artificial devices lack minds than that stones lack minds. But none
of this helps in the lab, or in the principled attempt to say what
functions DO give rise to minds, and how.
> Harnad says that we are not looking for a mathematical proof, which is
> true. But most of his postings demand that we show the NEED for assuming
> consciousness in an entity, which is empirically the same thing as
> proving them to be conscious.
No. I argue for methodological epiphenomenalism for three reasons
only: (1) Wrestling with an insoluble problem is futile. (2) Gussying
up trivial performance models with conscious interpretations gives the
appearance of having accomplished more than one has; it is
self-deceptive and distracts from the real goal, which is a
performance goal. (3) Focusing on trying to capture subjective phenomenology
rather than objective performance leads to subjectively gratifying
analogy, metaphor and hermeneutics instead of to objectively stronger
performance models. Hence when I challenge a triumphant mentalist
interpretation of a process, function or performance and ask why it
wouldn't function exactly the same way without the consciousness, I am
simply trying to show up theoretical vacuity for what it is. I promise
to stop asking that question when someone designs a device that passes
the TTT, because then there's nothing objective left to do, and an
orgy of interpretation can no longer do any harm.
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: 4 Feb 87 02:46:27 GMT
From: clyde!watmath!utzoo!dciem!mmt@rutgers.rutgers.edu (Martin
Taylor)
Subject: Re: Consciousness?
(Moved from mod.ai)
> I always thought that a scientific theory had to undergo a number of
> tests to determine how "good" it is. Needless to say, a perfect score
> on one test may be balanced by a mediocre score on another test. Some
> useful tests are:
>
> - Does the theory account for the data?
> - Is the theory simple? Are there unnecessary superfluousities?
> - Is the theory useful? Does it provide the basis for a fruitful
> program of research?
All true, and probably all necessary.
> ....
> While the study of consciousness is fascinating and lies at the base of
> numerous religions, it doesn't seem to be scientifically useful. Do I
> rewrite my code because the machine is conscious or because it is
> getting the wrong answer?
If you CAN write your code without demanding your machine be conscious,
then you don't need consciousness to write your code. But if you want
to construct a system that can, for example, darn socks or write a fine
sonata, you should probably (for now) write your code with the assumption
of consciousness in the executing machine.
In other words, you are confusing the unnecessary introduction of
consciousness into a system wherein you know all the working principles
with the question of whether consciousness is required for certain
functions.
> Is there a program of experimentation
> suggested by the search for consciousness?
Consciousness need not be sought. You experience it (I presume). The
question is whether behaviour can better (by the tests you present above)
be described by including consciousness or by not including it. If, by
"the search for consciousness" you mean the search for a useful definition
of consciousness, I'll let others answer that question.
> Does consciousness change the way artificial intelligence must be
> programmed? The evidence so far says NO. [How is that for a baldfaced
> assertion?
Pretty good. But for reasons stated above, it's irrelevant if you start
with the idea that AI must be programmed in a silicon (i.e. constructed)
machine. Any such development precludes the necessity of using consciousness
in the design, although it does not preclude the possibility that the
end product might BE conscious.
>
>
> I don't think scientific theories of consciousness are incorrect, I
> think they are barren.
Now THAT's a bald assertion. Barren for what purpose? Certainly for
construction purposes, but perhaps not for understanding what evolved
organisms do. (I take no stand on whether consciousness is in fact a
useful construct. I only want to point out that it has potential for
being useful, even though not in devising artificial constructs).
>
> Seth
--
Martin Taylor
{allegra,linus,ihnp4,floyd,ubc-vision}!utzoo!dciem!mmt
{uw-beaver,qucis,watmath}!utcsri!dciem!mmt
mmt@zorac.arpa
------------------------------
End of AIList Digest
********************
∂09-Feb-87 2017 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #37
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 9 Feb 87 20:16:58 PST
Date: Mon 9 Feb 1987 09:07-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #37
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 9 Feb 1987 Volume 5 : Issue 37
Today's Topics:
Philosophy - Consciousness
----------------------------------------------------------------------
Date: 9 Feb 87 06:14:48 GMT
From: well!wcalvin@lll-lcc.arpa (William Calvin)
Subject: Re: More on Minsky on Mind(s)
In following the replies to Minsky's excerpts from SOCIETY OF MIND, I
am struck by all the attempts to use slippery word-logic. If that's all
one has to use, then one suffers with word-logic until something better
comes along. But there are some mechanistic concepts from both
neurobiology and evolutionary biology which I find quite helpful in
thinking about consciousness -- or at least one major aspect of it, namely
what the writer Peter Brooks described in READING FOR THE PLOT (1985) as
follows:
"Our lives are ceaselessly intertwined with narrative, with the
stories that we tell and hear told, those we dream or imagine or would
like to tell, all of which are reworked in that story of our own lives
that we narrate to ourselves in an episodic, sometimes semiconscious,
but virtually uninterrupted monologue. We live immersed in narrative,
recounting and reassessing the meaning of our past actions,
anticipating the outcome of our future projects, situating ourselves
at the intersection of several stories not yet completed."
Note the emphasis on both past and future, rather than the perceiving-
the-present and recalling-the-recent-past, e.g., Minsky:
> although people usually assume that consciousness is knowing
> what is happening in the minds, right at the
> present time, consciousness never is really concerned with the
> present, but with how we think about the records of our recent
> thoughts... how thinking about our short term memories changes them!
But simulation is more the issue, e.g., E.O. Wilson in ON HUMAN NATURE
1978:
"Since the mind recreates reality from abstractions of sense
impressions, it can equally well simulate reality by recall and
fantasy. The brain invents stories and runs imagined and remembered
events back and forth through time."
Rehearsing movements may be the key to appreciating the brain mechanisms,
if I may quote myself (THE RIVER THAT FLOWS UPHILL: A JOURNEY FROM THE BIG
BANG TO THE BIG BRAIN, 1986):
"We have an ability to run through a motion with our muscles detached
from the circuit, then run through it again for real, the muscles
actually carrying out the commands. We can let our simulation run
through the past and future, trying different scenarios and judging
which is most advantageous -- it allows us to respond in advance to
probable future environments, to imagine an accidental rockfall
loosened by a climber above us and to therefore stay out of his fall
line."
Though how we acquired this foresight is a bit of a mystery. Never
mind for a moment all those "surely it's useful" arguments which, using
compound interest reasoning, can justify anything (given enough
evolutionary time for compounding). As Jacob Bronowski noted in THE
ORIGINS OF KNOWLEDGE AND IMAGINATION 1967, foresight hasn't been
widespread:
"[Man's] unique ability to imagine, to make plans... are generally
included in the catchall phrase "free will." What we really mean by
free will, of course, is the visualizing of alternatives and making a
choice between them. In my view, which not everyone shares, the
central problem of human consciousness depends on this ability to
imagine..... Foresight is so obviously of great evolutionary
advantage that one would say, `Why haven't all animals used it and
come up with it?' But the fact is that obviously it is a very strange
accident. And I guess as human beings we must all pray that it will
not strike any other species."
So if other animals have not evolved very much of our fussing-about-the-
future consciousness via its usefulness, what other avenues are there for
evolution? A major one, noted by Darwin himself but forgotten by almost
everyone else, is conversion ("functional change in anatomical
continuity"), new functions from old structures. Thus one looks at brain
circuitry for some aspects of the problem -- such as planning movements --
and sees if a secondary use can be made of it to yield other aspects of
consciousness -- such as spinning scenarios about past and future.
And how do we generate a detailed PLAN A and PLAN B, and then compare
them? First we recognize that detailed plans are rarely needed: many
elaborate movements can get along fine on just a general goal and feedback
corrections, as when I pick up my cup of coffee and move it to my lips.
But feedback has a loop time (nerve conduction time, plus decision-making,
often adds up to several hundred milliseconds of reaction time). This
means the feedback arrives too late to do any good in the case of certain
rapid movements (saccadic eye flicks, hammering, throwing, swinging a golf
club). Animals who utilize such "ballistic movements" (as we call them in
motor systems neurophysiology) simply have to evolve a serial command
buffer: plan at leisure (as when we "get set" to throw) but then pump out
that whole detailed sequence of muscle commands without feedback. And get
it right the first time. Since it goes out on a series of channels (all
those muscles of arm and hand), it is something like planning a whole
fireworks display finale (carefully coordinated ignitions from a series of
launch platforms with different inherent delays, etc.).
But once a species has such a serial command buffer, it may be useful
for all sorts of things besides the actions which were originally under
natural selection during evolution (throwing for hunting is my favorite
shaper-upper --see J.Theor.Biol. 104:121-135,1983 -- but word-order-coded
language is conceivably another way of selecting for a serial command
buffer). Besides rehearsing slow movements better with the new-fangled
ballistic movement sequencer, perhaps one could also string together other
concepts-images-schemata with the same neural machinery: spin a scenario?
The other contribution from evolutionary biology is the notion that
one can randomly generate a whole family of such strings and then select
amongst them (imagine a railroad marshalling yard, a whole series of
possible trains being randomly assembled). Each train is graded against
memory for reasonableness -- Does it have an engine at one end and a
caboose at the other? -- before one is let loose on the main line. "Best"
is surely a value judgment determined by memories of the fate of similar
sequences in the past, and one presumes a series of selection steps that
shape up candidates into increasingly more realistic sequences, just as
many generations of evolution have shaped up increasingly more
sophisticated species. To quote an abstract of mine called "Designing
Darwin Machines":
This selection of stochastic sequences is more
analogous to the ways of Darwinian evolutionary biology
than to von Neumann machines. One might call it a
Darwin machine instead, but operating on a time scale
of milliseconds rather than millennia, using innocuous
virtual environments rather than noxious real-time
ones.
Is this what Darwin's "bulldog," Thomas Henry Huxley, would have
agreed was the "mechanical equivalent of consciousness" which Huxley
thought possible, almost a century ago? It would certainly be fitting.
We do not yet know how much of our mental life such stochastic
sequencers might explain. But I tend to think that this approach using
mechanical analogies from motor systems neurophysiology and evolutionary
biology might have something to recommend it, in contrast to word-logic
attempts to describe consciousness. At least it provides a different place
to start, hopefully less slippery than variants on the little person inside
the head with all their infinite regress.
William H. Calvin
Biology Program NJ-15
University of Washington
Seattle WA 98195 USA
206/328-1192
USENET: wcalvin@well.uucp
------------------------------
Date: 9 Feb 87 08:41:00 EST
From: "CUGINI, JOHN" <cugini@icst-ecf>
Reply-to: "CUGINI, JOHN" <cugini@icst-ecf>
Subject: another stab at "what are we arguing about"
> > Me: "Why I am not a Methodological Epiphenomenalist"
>
> Harnad: This is an ironic twist on Russell's sceptical book about religious
> beliefs! I'm the one who should be writing "Why I'm Not a Methodological
> Mentalist."
Yeah, but I said it first...
OK, seriously folks, I think I see this discussion starting to converge on
a central point of disagreement (don't look so skeptical). Harnad,
Reed, Taylor, and I have all mentioned this "on the side" but I think it
may be the major sticking point between Harnad and the latter three.
> Reed: ...However, I don't buy the assumption that two must *observe the same
> instance of a phenomenon* in order to perform an *observer-independent
> measurement of the same (generic) phenomenon*. The two physicists can
> agree that they are studying the same generic phenomenon because they
> know they are doing similar things to similar equipment, and getting
> similar results. But there is nothing to prevent two psychologists from
> doing similar (mental) things to similar (mental) equipment and getting
> similar results, even if neither engages in any overt behavior apart
> from reporting the results of his measurements to the other....
>
> What is objectively different about the human case is that not only is
> the other human doing similar (mental) things, he or she is doing those
> things to similar (human mind implemented on a human brain) equipment.
> If we obtain similar results, Occam's razor suggests that we explain
> them similarly: if my results come from measurement of subjectively
> experienced events, it is reasonable for me to suppose that another
> human's similar results come from the same source. But a computer's
> "mental" equipment is (at this point in time) sufficiently dissimilar
> from a human's that the above reasoning would break down at the point
> of "doing similar things to similar equipment with similar results",
> even if the procedures and results somehow did turn out to be identical.
> > Harnad: Everything resembles everything else in an infinite number of
> > ways; the problem is sorting out which of the similarities is relevant.
>
> Taylor: Absolutely. Watanabe's Theorem of the Ugly Duckling applies. The
> distinctions (and similarities) we deem important are no more or less
> real than the infinity of ones that we ignore. Nevertheless, we DO see
> some things as more alike than other things, because we see some similarities
> (and some differences) as more important than others.
>
> In the matter of consciousness, I KNOW (no counterargument possible) that
> I am conscious, Ken Laws knows he is conscious, Steve Harnad knows he is
> conscious. I don't know this of Ken or Steve, but their output on a
> computer terminal is enough like mine for me to presume by that similarity
> that they are human. By Occam's razor, in the absence of evidence to the
> contrary, I am forced to believe that most humans work the way I do.
> Therefore
> it is simpler to presume that Ken and Steve experience consciousness than
> that they work according to one set of natural laws, and I, alone of all
> the world, conform to another.
The Big Question: Is your brain more similar to mine than either is to any
plausible silicon-based device?
I (and Reed and Taylor?) been pushing the "brain-as-criterion" based
on a very simple line of reasoning:
1. my brain causes my consciousness.
2. your brain is a lot like mine.
3. therefore, by "same cause, same effect" your brain probably
causes consciousness in you.
(BTW, The above does NOT deny the relevance of similar performance in
confirming 3.)
Now, when I say simple things like this, Harnad says complicated things like:
re 1: how do you KNOW your brain causes your consciousness? How can you have
causal knowledge without a good theory of mind-brain interaction?
Re 2: How do you KNOW your brain is similar to others'? Similar wrt
what features? How do you know these are the relevant features?
For now (and with some luck, for ever) I am going to avoid a
straightforward philosophical reply. I think there may be some
reasonably satisfactory (but very long and philosophical) answers to
these questions, but I maintain the questions are really not relevant.
We are dealing with the mind-body problem. That's enough of a philosophical
problem to keep us busy. I have noticed (although I can't explain why),
that when you start discussing the mind-body problem, people (even me, once
in a while) start to use it as a hook on which to hang every other
known philosophical problem:
1. well how do we know anything at all, much less our neighbors' mental states?
(skepticism and epistemology).
2. what does it mean to say that A causes B, and what is the nature of
causal knowledge? (metaphysics and epistemology).
3. is it more moral to kill living thing X than a robot? (ethics).
All of these are perfectly legitimate philosophical questions, but
they are general problems, NOT peculiar to the mind-body problem.
When addressing the mind-body problem, we should deal with its
peculiar features (of which there are enough), and not get mired in
more general problems * unless they are truly in doubt and thus their
solution truly necessary for M-B purposes. *
I do not believe that this is so of the issues Harnad raises. I
believe people can a) have causal knowledge, both of instances and
types of events, without any articulated "deep" theory of the
mechanics going on behind the scenes (indeed the deep knowledge
comes later as an attempt to explain the already observed causal
interaction), and b) can spot relevant similarities without being
able to articulate them.
A member of an Amazon tribe could find out, truly know, that light
switches cause lights to come on, with a few minutes of
experimentation. It is no objection to his knowledge to say that he
has no causal theory within which to embed this knowledge, or to
question his knowledge of the relevance of the similarities among
various light switches, even if he is hard-pressed to say anything
beyond "they look alike." It is a commonplace example that many
people can distinguish between canines and felines without being
able to say why. I do not assert, I am quick to add, that
these rough-and-ready processes are infallible - yes, yes, are whales
more like cows than fish, how should I know?
But again, to raise the specter of certainty is again a side-issue.
Do we all not agree that the Indian's knowledge of lights and light
switches is truly knowledge, however unsophisticated?
Now, S. Harnad, upon your solemn oath, do you have any serious practical
doubt, that, in fact,
1. you have a brain?
2. that it is the primary cause of your consciousness?
3. that other people have brains?
4. that these brains are similar to your own (and if not, why do you
and everyone else use the same word to refer to them?), at least
more so than any other object with which you are familiar?
Now if you do know these utterly ordinary assertions to be true,
* even if you can't produce a high-quality philosophical defense for
them, (which inability, I argue, does not cast serious doubt on them,
or on the status of your belief in them as knowledge) * then, what
is wrong with the simple inference that others' possession of a brain
is a good reason (not necessarily the only reason) to believe that
they are conscious?
John Cugini <Cugini@icst-ecf>
------------------------------
Date: 9 Feb 87 08:59:00 EST
From: "CUGINI, JOHN" <cugini@icst-ecf>
Reply-to: "CUGINI, JOHN" <cugini@icst-ecf>
Subject: and another thing..
Yeah, while I'm at it, how do you, Harnad, know that two performances
by two entities in question (a human and a robot) are relevantly
similar? What is it precisely about the performances you intend to
measure? How do you know that these are the important aspects?
Refresh my memory if I'm wrong, but as I recall, the TTT was a kind
of gestalt you'll-know-intelligent-behavior-when-you-see-it test.
How is this different from looking at two brains and saying, yeah
they look like the same kind of thing to me?
John Cugini <Cugini@icst-ecf>
------------------------------
End of AIList Digest
********************
∂11-Feb-87 0204 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #38
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 11 Feb 87 02:04:24 PST
Date: Tue 10 Feb 1987 23:41-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #38
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 11 Feb 1987 Volume 5 : Issue 38
Today's Topics:
Seminars - High-Level Architecture for LISP (SMU) &
Combinatorics of Rule-Based Expert Systems (Rutgers) &
Optimal Histories for Default Reasoning (SU),
Conference - Extended Deadline for AAAI Uncertainty in AI Workshop &
IEEE First Annual Conference on Neural Networks &
Office Knowledge
----------------------------------------------------------------------
Date: WED, 10 oct 86 17:02:23 CDT
From: leff%smu@csnet-relay
Subject: Seminar - High-Level Architecture for LISP (SMU)
Wednesday, February 11, 1987, Computer Science and Engineering, Southern
Methodist University, Dallas, Texas 315SIC, 1:30 PM
High-Level Language Architecture for LISP
Steve Krueger (kreuger%home@TI-CSL)
Symbolic Computing Laboratory
Texas Instruments
The TI LISP Machine family utilizes a high-level language architecture
for LISP in order to gain high performance, preserve the full dynamic
behavior of LISP and support software debugging. These processors
support a complex high-level language instruction set for Common LISP (a
rich dialect of LISP) implemented in hardware and microcode. Support
for LISP and the instruction set gives high LISP performance. An
overview and motivation of the HLL instruction set will be given, as
will an overview of TI's LISP architecture.
Steven D. Krueger
S.M. Massachusetts Institute of Technology, Computer Science, 1980.
S.B. Massachusetts Institute of Technology, Electrical Engineering,
1980.
Mr Krueger is a Sr. Member of Technical Staff in TI Computer Science
Center where his research interests are in computer architecture
and hardware/software interfaces. He is responsible for the
architecture of the Explorer Lisp Machine processor and its
successors. He has been involved in Explorer since early 1983 and has
made contributions to the processor and system architecture, and was
leader of the hardware and software integration team. He also
contributed to the architecture of the single chip Lisp processor
(CLM) and is responsible for an improved instruction set architecture
for Explorer and CLM.
------------------------------
Date: 4 Feb 87 22:30:28 EST
From: KALANTARI@RED.RUTGERS.EDU
Subject: Seminar - Combinatorics of Rule-Based Expert Systems
(Rutgers)
RUTGERS COMPUTER SCIENCE AND RUTCOR COLLOQUIUM SCHEDULE - SPRING 1987
Computer Science Department Colloquium :
DATE: Friday, Feb. 6, 1987
SPEAKER: Wiktor Marek
AFFILIATION: University of Kentucky
TITLE: "On the logic and combinatorics of rule-based expert systems"
TIME: 2:50 (Coffee and Cookies will be setup at 2:30)
PLACE: Hill Center, Room 705
We discuss some basic issues of rule-based expert systems, their
logic and the main complexity issues related to the algorithms of
deciding the consistency and completeness of such systems. In
addition we study the connections to the theory of non-first
normal form relational databases and find the applications of our
theory to non-first normal form relations.
------------------------------
Date: 06 Feb 87 1028 PST
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Optimal Histories for Default Reasoning (SU)
Commonsense and Nonmonotonic Reasoning Seminar
OPTIMAL HISTORIES: A TEMPORAL APPROACH TO DEFAULT REASONING
Van Nguyen
IBM T.J.Watson Research Center
Yorktown Heights, NY 10598
Thursday, February 12, 4pm
Bldg. 160, Room 161K
A new technique in default reasoning (non-monotonic reasoning)
is presented. It is based on the notion of optimal histories.
Intuitively, an optimal history contains a sequence of sets S(n),
n = 0, 1, ..., of first-order formulae. Each S(n) is a description of
the state of the world, as seen by some computing agent, at time
(situation) n. State S(n+1) is computed from S(n) and the event
(action) E(n+1) that occurs at time n+1 by a default-inference rule,
so that facts that are true in S(n) tend to stay true in S(n+1), unless
something falsifies them. Other parameters of an optimal history are
the deductive ability of the computing agent and a set of basic axioms
and constraints. Thus an optimal history is a description of how the
world changes with new events, as time passes.
The technique is applicable to such problems in default reasoning as
belief revision, dealing with exceptions to general rules, the frame
problem of McCarthy and Hayes, the qualification problem of McCarthy,
and the temporal projection problem of Hanks and McDermott. Optimal
histories can also be formulated in the framework of temporal logic of
Manna and Pnueli.
------------------------------
Date: Sat, 7 Feb 87 21:39:25 pst
From: levitt@ads.ARPA (Tod Levitt)
Subject: Conference - Extended Deadline for AAAI Uncertainty in AI
Workshop
EXTENSION OF SUBMISSION DEADLINE
for
AAAI UNCERTAINTY IN ARTIFICIAL INTELLIGENCE WORKSHOP
Seattle, Washington
July 10-12, 1987
Due to conflicts with a number of other submission deadlines for
related conferences and workshops, the deadline for the 1987
Uncertainty in AI workshop is being extended until March 10, 1987.
Please send four copies of papers or extended abstracts to
Tod S. Levitt
c/o Advanced Decision Systems
201 San Antonio Circle, Suite 286
Mountain View, California 94040
------------------------------
Date: Fri, 6 Feb 87 17:58 EDT
From: MIKE@BUCASA.BITNET
Subject: Conference - IEEE First Annual Conference on Neural Networks
From: <grossberg@nprdc.arpa> (Stephen Grossberg)
IEEE First Annual Conference on Neural Networks, San Diego,
California, 21-24 June 1987. Requests from many scientists who
heard about the meeting only recently have led to a revised
deadline for abstracts and papers.
Extended abstracts should be submitted for conference
presentation by April 1, 1987
Abstracts received after April 1, 1987 will be returned.
Please submit abstract plus 4 clean copies. Abstracts
must be neatly typed, single spaced, and no more than four
pages.
Abstracts will be carefully refereed as they are received.
Authors of accepted abstracts will be notified as soon after
receipt as possible, and no later than the first week of May.
Authors of accepted abstracts will promptly be sent materials
for paper preparation. Papers can be up to 8 pages in length.
Final papers for publication in the book of proceedings are
due no later than June 21, 1987 at the meeting. The
proceedings will be published in the Fall of 1987.
Address all correspondence referring to abstracts and papers
to:
Maureen Caudill
IEEE - ICNN
10615G Tierrasanta Blvd.
Suite 346
San Diego, California 92124
Telephone: (619) 457-5550, ext. 221
------------------------------
Date: Mon, 9 Feb 87 07:49:30 est
From: rba@flash.bellcore.com (Robert B. Allen)
Subject: Conference - Office Knowledge
CALL FOR PARTICIPATION
IFIP WG8.4 Workshop on
Office Knowledge: Representation, Management and Utilization
17-19 August 1987
University of Toronto
Toronto, Canada
WORKSHOP CHAIRMAN PROGRAM CHAIRMAN
Prof. Dr. Alex A. Verrijn-Stuart Dr. Winfried Lamersdorf
University of Leiden IBM European Networking Center
ORGANIZING CHAIRMAN
Prof. Fred H. Lochovsky
University of Toronto
This workshop is intended as a forum and focus for research in
the representation, management and utilization of knowledge in
the office. This research area draws from and extends techniques
in the areas of artificial intelligence, data base management
systems, programming languages, and communication systems. The
workshop program will consist of one day of invited presentations
from key researchers in the area plus one and one half days of
contributed presentations. Extended abstracts, in English, of
4-8 double-spaced pages (1,000-2,000 words) are invited. Each
submission will be screened for relevance and potential to
stimulate discussion. There will be no formal workshop
proceedings. However, accepted submissions will appear as
2
submitted in a special issue of the WG8.4 newsletter and will be
made available to workshop participants.
How to submit
Four copies of double-spaced extended abstracts in English of
1,000-2,000 words (4-8 pages) should be submitted by 15 April
1987 to the Program Chairman:
Dr. Winfried Lamersdorf
IBM European Networking Center
Tiergartenstrasse 15
Postfach 10 30 68
D-6900 Heidelberg
West Germany
Important Dates
Extended abstracts due: 15 April 1987
Notification of acceptance for presentation: 1 June 1987
Workshop: 17-19 August 1987
------------------------------
End of AIList Digest
********************
∂11-Feb-87 0443 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #39
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 11 Feb 87 04:42:57 PST
Date: Tue 10 Feb 1987 23:52-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #39
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 11 Feb 1987 Volume 5 : Issue 39
Today's Topics:
Queries - LISP Conversion & Symbolics Termcap,
AI Tools - Coral Object Logo & MICE Expert System Shell,
Education - Introductory AI Books,
Representations - Richness and Flexibility
----------------------------------------------------------------------
Date: Mon, 09 Feb 87 11:00:18 -0800
From: simmons@aerospace.aero.org
Subject: LISP Conversion
I am gathering information concerning the conversion or
translation of programs written is LISP to procedural languages
(especially interested in LISP to Fortran). I would appreciate
comments from anyone who knows of work being done in this area.
I will summarize replies for the AILIST.
Thanks, Charles Simmons (simmons@aerospace.arpa)
------------------------------
Date: Tue, 10 Feb 87 09:18:16 -0800
From: Amnon Meyers <meyers@CIP.UCI.EDU>
Subject: symbolics question
I'm having trouble getting the Symbolics 3600 to behave
properly as a terminal, when logged into UNIX systems.
Editors like VI and EMACS don't work right, even though
vt100 emulation mode is set up.
If someone has a TERMCAP line that works well, or can
otherwise help, I'd appreciate it.
Thanks,
Amnon Meyers
------------------------------
Date: 9 Feb 87 15:15:09 GMT
From: mdc@EDDIE.MIT.EDU (Martin Connor)
Subject: Coral Object Logo
In article <1725@PUCC.BITNET> 6065833@PUCC.BITNET writes:
> Can anyone recommend another LOGO for the macintosh? Has anyone found
> a way to print graphics windows on >a laserwriter? Any information
> would be greatly appreciated.
Object Logo from Coral Software in Cambridge, Mass is a good value.
It is about $80 and has loads of features, Comes with Finder 5.3 and
system 3.2, lots of examples, a good reference manual, and is
supported by a solid bunch of hackers (I know some of them).
They have an ad in this month's MACWORLD, with ordering info.
I've used it, and I recommend it highly. I hope some schools pick up
on it and use it.
------------------------------
Date: Mon 9 Feb 87 18:08:06-PST
From: Matt Heffron <BEC.HEFFRON@USC-ECL.ARPA>
Subject: MICE Expert System Shell
We ordered the $20 MICE system. I haven't used it yet, as I haven't had time
to really sit down and read and understand the manuals. From the various
features referred to in the Table of Contents of the 3 manuals (yes, 3. User
Reference, Technical Reference, and Graphic System User Manual (total: approx
140 pgs) it looks very impressive. The knowledge representation appears to be
primarily Semantic Net based, and there is support for graphically perusing
the network and building custom graphic objects for use with the system.
HOWEVER, after reading some of the User Reference manual, it quickly begins to
look like "you get what you pay for". E.g. the definitions of FORWARD
CHAINING and BACKWARD CHAINING in the User Reference are *REVERSED* (from what
I understand them to be):
"In general, facts make up evidence; in the process of determining the
validity of a fact, further evidence may be required. This propagation of
the thought process continues until a fundamental fact is encountered
which requires no further evidence. This fundamental fact is called an
ATOMIC FACT. And, this thought process is called FORWARD CHAINING.
Forward chaining is often used by human experts to validate assumptions.
On the other hand, if a given fact is being used to support the validity
of more than one fact, validating the other fact will often cause the
human expert to consider the other alternatives which it supports. This
thought process is called BACKWARD CHAINING."
Also, it becomes clear from the included price list that this is really only
designed to be a DEMO system. The KB is limited to 12K. For versions that
support larger KB's the price goes WAY up (e.g. 20K is $200, 100K is $1750,
1M is $9000). I also recently received a letter asking if I wanted to
subscribe to the monthly users newsletter and/or program updates (at $60/year
for the newsletter, $80/year for the updates, or $120/year for both).
For $20 (without the support) it will probably be OK for simple
prototypes.
Matt Heffron BEC.HEFFRON@USC-ECL.ARPA
Standard Disclaimer about these being my opinions, not those of my employer.
------------------------------
Date: 9 Feb 87 14:32:36 GMT
From: atux01!jlc@rutgers.rutgers.edu (J. Collymore)
Subject: A List of AI Books (for beginners)
I have received a number of requests for a posting any of my replies on my
query regarding good books on Artificial Intelligence for the beginner.
Well, here are those replies.
Thank you to all who responded to my query.
Jim Collymore
*******************************************************************************
Re: Need References to VERY BASIC Concepts of AI & Preferred Comp. Langs.
Artificial Intelligence, by Patrick Winston
===============================================================================
Re: Need References to VERY BASIC Concepts of AI & Preferred Comp. Langs.
Newsgroups: comp.ai,comp.misc
Organization: MIT Media Lab, Cambridge MA
The following two books are the most recommended ones I have seen and
are coordinated to introduce (1) concepts and (2) techniques of AI.
(1) Artificial Intelligence
Patrick Henry Winston
Addison Wesley
(2) Lisp
Patrick Henry Winston and Berthold Klaus Horn
Addison Wesley
As for good languages for AI, Lisp is good because with it you think
more about the solution than about the implementation and because it
allows you to develop the language you would have like to have to
solve the problem with in the first place. This latter requirement
seems to be important for the kind of approach used for AI these days.
There are two compilations of papers available which are of interest.
Titles are:
Readings in Artificial Intelligence
Readings in Knowledge Representation
I will try to get the publisher's name for you.
--Mario
===============================================================================
Subject: AI
Learn LISP and PROLOG.
Winston's or Steele's book on COMMON LISP are good. Steele is more of
a reference book.
Clocksin and Mellish is the default standard of PROLOG. However, Bratko
is easier to learn from. Bratko also provides a good intro to AI. I
highly recommend reading Bratko.
Winston's book on AI is TERRIBLE for a beginning book. For some history
MIT puts out some collected papers.
--------
LISP, Winston.
COMMON LISP, Steele.
Programming in Prolog, Clocksin and Mellish.
Programming in Prolog for Artificial Intelligence, Bratko.
===============================================================================
Subject: AI programming languages
Have you thought about trying Logo? This Department used it for years, though
we have now moved to Edinburgh Prolog.
Try reading Alan Bundy's book "Artificial Intelligence, an introductory
course", paperback published by Edinburgh University Press
------------------------------
Date: 10 Feb 87 17:40:17 GMT
From: jennifer!lyang@sun.com (Larry Yang)
Subject: Learing about AI (was Re: A List of AI Books (for beginners))
>Learn LISP and PROLOG.
When I took a class on Artificial Intelligence at Stanford (CS223, for
those who care), I figured I was ready. I knew PROLOG and LISP.
And I was all set to learn about this great thing called 'AI', at
the place where big names made it happen.
I was in for a surprise. Based on my experience, if you want
to learn about hard-core, theoretical artificial intelligence,
then you must have a strong (I mean STRONG) background in formal
logic. My understanding of PROLOG (which resembles predicate logic)
was very helpful, but it wasn't enough.
If you want to go out and build expert systems, or perform some other
intelligence engineering task, then PROLOG and LISP and a basic
grasp of logic are probably enough. But if you want to follow the
latest research (and maybe eventually do some of it), then a formal
training in logic is a must.
================================================================================
Whydoesn'titsnowintherightplaces?
--Larry Yang | *A REAL signature* _|> /\ |
lyang@sun.com,{backbone}!sun!lyang | "Limit? We don't | | | /-\ |-\ /-\
Sun Microsystems, Inc. | need no stinkin' <|_/ \_| \_/\_| |_\_|
Mountain View, California | 4-line limit! " _/ _/
------------------------------
Date: 9 Feb 87 11:06:42 est
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: representation languages: richness and flexibility
Date: 5 Feb 87 03:37:30 GMT
From: berleant@sally.utexas.edu (Dan Berleant)
Hmm. I just attended a lecture in which frame based representation
schemes were touted on the basis of the fact that representation
languages should be rich and flexible.
Well, it sounds good, it even sounds simple, but I'm sure not sure what
it means! In the context of representation languages, what is
'rich', and what is 'flexible'?
Good question.
Flame on...
The term ``representation language'' is redundant. What other kind of
language could there be? Just think about languages, period, and the
terms make more sense. Languages are symbol structures that have an
interpreter. And since the terms are relative, it makes more sense to
ask ``what makes language A richer than language B'' and ``what makes
language X more flexible than language Y.''
Here's one way to characterize richness: A is richer than B if symbol
structures in A can finitely denote facts (i.e., the interpreter can
interpret as) that B can't. E.g., 1st order predicate calculus is
richer than propositional calculus because it has quantification,
which allows you to express infinitely large propositional
conjunctions and disjunctions. Frame languages, semantic nets, etc,
differ as to whether they correspond to first-, second-, or
omega-order logics, and that's probably the best way to characterize
its richness in a technical sense. If you replace finiteness with
compactness, it becomes more a matter of taste: frame languages print
nicely because they supress some redundancies, but does the computer
really care about that?
Here's one way to characterize flexibility: X is more flexible than Y
if a local incremental change to the denotation of a symbol structure
in X can be done by changing fewer symbols and relations. This
actually turns out to go along with richness sometimes. For example,
a frame based language with inheritance and cancellation is more
flexible than 1st order predicate calculus because (to beat on a tired
example) you can say that birds fly and then later say that penguins,
which are birds, don't fly, without having to go back and change the
original statement about how birds fly. You make a local addition and
you don't have to go around the whole symbol structure fixing a lot of
things up. What this goes to show is that a frame language with these
features has second order properties; if you go to 2nd order predicate
calculus via circumscription, you get this locality property back.
Now you get to the real question: what are the properties of the
interpreter that come packaged with the language? Does it give you
some kind of guarantee about completeness, about variant queries,
about constant time complexity for query answering, or what? Does the
language come with a basic set of facts about the world that you can
build on (like a subroutine library in a programming language)? Or
does it just stuff things into a database and let you figure out what
to do with them later? The richness and flexibility of the language
itself are not very interesting properties, it's the interpreter that
matters. What people usually mean when they say ``representation
language'' is ``belief language'', since they're talking about a
language whose purpose is to denote the beliefs of an agent. But if
you expect the interpreter of your belief language to do a lot of
automatic inferences that solve a significant part of the software
engineering problem for you, then you're probably expecting too much
from it: that's the job of a programming language and environment.
Flame off...
Walter Hamscher
------------------------------
End of AIList Digest
********************
∂12-Feb-87 0325 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #40
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 12 Feb 87 03:25:31 PST
Date: Thu 12 Feb 1987 00:16-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #40
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 12 Feb 1987 Volume 5 : Issue 40
Today's Topics:
Queries - Pattern Recognition/Graphs & Mac PD Prolog &
Print Driver Extension & DEC AI Workstation & J.M. Spivey,
Representation - Language Comparisons,
AI Tools - Against the Tide of Common LISP
----------------------------------------------------------------------
Date: Wed, 11 Feb 87 10:42:08 n
From: DAVIS@EMBL.BITNET
Subject: pattern recognition/graphs
Does anyone out there in the electronic village have any familiarity or
knowledge of pattern recognition algorithms which are or may be of
particular use in the identification of fuzzy predefined graph features ?
Whilst I have a couple of approaches of my own, I'd be very interested to
hear about any other methods. I guess that 'template matching' with
arbitrary match coefficients is the most obvious, but any other offers ?
netmail: davis@embl.bitnet (from uucp thats psuvax1!embl.bitnet!davis)
wetmail: embl, postfach 10.2209, 6900 Heidleberg, west germany
paul davis
------------------------------
Date: 10 Feb 87 22:51:12 GMT
From: mendozag@ee.ecn.purdue.edu (Grado)
Subject: Mac PD Prolog wanted
Does anyone have the sources for a PD Prolog for the Mac+?
How about any other PD Prolog, so I can port it to the Mac?
Please, let me know by e-mail.
Thanks in advance,
Victor M Grado
School of EE
Purdue University
West Lafayette, IN 47907
(317) 494-3494
mendozag@ecn.purdue.edu
pur-ee!mendozag
------------------------------
Date: Wed, 11 Feb 87 15:53 EST
From: DON%atc.bendix.com@RELAY.CS.NET
Subject: Print driver extension for HP Laser printers on LMI
Does anyone have a print driver adapted for the HP Laser printer
written for LMI, Symbolics, or TI explorer? I'm looking for
the ability to set tab stops and use multiple fonts.
[I like to be as helpful as possible, but several readers have
pointed out that termcap entries and other hardware queries
have nothing to do with AI. There are lists (SLUG@UTEXAS-20,
INFO-TI-EXPLORER@SUMEX-AIM, INFO-1100@SUMEX-AIM, WORKS@RUTGERS,
etc.) devoted to specific hardware and operating systems. -- KIL]
------------------------------
Date: Wed, 11 Feb 87 08:42 EST
From: DON%atc.bendix.com@RELAY.CS.NET
Subject: DEC AI Workstation
One of my colleagues is thinking of buying an AI workstation from
DEC. I have heard nothing good about them. However, the negative
remarks have not come from people who have actually used them. In
order to better advise my colleague, I would like to hear from people
who have used the workstations. Of particular interest to me are
remarks from people who have used the DEC workstation and one of the
standard Lisp workstations (XEROX, Symbolics, LMI, TI, Sun, Apollo).
What about the Lisp Sensitive Editor. Is that worth anything? How
does it compare to ZMACS?
Thank you,
Don Mitchell
------------------------------
Date: Wed, 11 Feb 87 09:35 EDT
From: Peter Heitman <HEITMAN%cs.umass.edu@RELAY.CS.NET>
Subject: Looking for J.M. Spivey, the author of Portable Prolog
Can anyone help me locate J.M. Spivey, the author of Portable Prolog?
He was at the University of York years ago and then went to Edinburgh
for a while after that. Any help tracking him down will be appreciated.
Peter Heitman
heitman@cs.umass.edu
------------------------------
Date: Wed, 11 Feb 87 12:35:50 pst
From: ladkin@kestrel.ARPA (Peter Ladkin)
Subject: language comparisons
Walter Hamscher writes:
> Here's one way to characterize richness: A is richer than B if symbol
> structures in A can finitely denote facts (i.e., the interpreter can
> interpret as) that B can't.
I suppose the intention of `richer than' is to be an
aymmetric comparative. Thus, he needs to add some condition
such as:
A can also finitely denote all facts that B can't
to rule out cases where both A is richer than B and
B is richer than A. A case of this would be first-order logic
and modal logic. Each may express conditions that are
inexpressible in the other (e.g. irreflexivity for modal logic,
well-cappedness for first-order logic).
peter ladkin
ladkin@kestrel.arpa
------------------------------
Date: Tue, 10 Feb 87 19:24:09 pst
From: well!jjacobs@lll-lcc.ARPA (Jeffrey Jacobs)
Reply-to: well!jjacobs@lll-lcc.ARPA (Jeffrey Jacobs)
Subject: Against the Tide of Common LISP
"Against the Tide of Common LISP"
Copyright (c) 1986, Jeffrey M. Jacobs, CONSART Systems Inc.,
P.O. Box 3016, Manhattan Beach, CA 90266 (213)376-3802
Bix ID: jeffjacobs, CIS Userid 75076,2603
Reproduction by electronic means is permitted, provided that it is not
for commercial gain, and that this copyright notice remains intact."
The following are from various correspondences and notes on Common LISP:
Since you were brave enough to ask about Common Lisp, sit down for my answer:
I think CL is the WORST thing that could possibly happen to LISP. In fact, I
consider it a language different from "true" LISP. CL has everything in the
world in it, usually in 3 different forms and 4 different flavors, with 6
different options. I think the only thing they left out was FEXPRs...
It is obviously intended to be a "compiled" language, not an interpreted
language. By nature it will be very slow; somebody would have to spend quite a
bit of time and $ to make a "fast" interpreted version (say for a VAX). The
grotesque complexity and plethora of data types presents incredible problems to
the developer; it was several years before Golden Hill had lexical scoping,
and NIL from MIT DOES NOT HAVE A GARBAGE COLLECTOR!!!!
It just eventually eats up it's entire VAX/VMS virtual memory and dies...
Further, there are inconsistencies and flat out errors in the book. So many
things are left vague, poorly defined and "to the developer".
The entire INTERLISP arena is left out of the range of compatability.
As a last shot; most of the fancy Expert Systems (KEE, ART) are implemented in
Common LISP. Once again we hear that LISP is "too slow" for such things, when
a large part of it is the use of Common LISP as opposed to a "faster" form
(i.e. such as with shallow dynamic binding and simpler LAMBDA variables; they
should have left the &aux, etc as macros). Every operation in CL is very
expensive in terms of CPU...
______________________________________________________________
I forgot to leave out the fact that I do NOT like lexical scoping in LISP; to
allow both dynamic and lexical makes the performance even worse. To me,
lexical scoping was and should be a compiler OPTIMIZATION, not an inherent
part of the language semantics. I can accept SCHEME, where you always know
that it's lexical, but CL could drive you crazy (especially if you were
testing/debugging other people's code).
This whole phenomenon is called "Techno-dazzle"; i.e. look at what a super
duper complex system that will do everything I can build. Who cares if it's
incredibly difficult and costly to build and understand, and that most of the
features will only get used because "they are there", driving up the cpu useage
and making the whole development process more costly...
BTW, I think the book is poorly written and assume a great deal of knowledge
about LISP and MACLISP in particular. I wouldn't give it to ANYBODY to learn
LISP
...Not only does he assume you know a lot about LISP, he assume you know a LOT
about half the other existing implementations to boot.
I am inclined to doubt that it is possible to write a good introductory text on
Common LISP; you d**n near need to understand ALL of it before you can start
to use it. There is nowhere near the basic underlying set of primitives (or
philosophy) to start with, as there is in Real LISP (RL vs CL). You'll notice
that there is almost NO defining of functions using LISP in the Steele book.
Yet one of the best things about Real LISP is the precise definition of a
function!
Even when using Common LISP (NIL), I deliberately use a subset. I'm always
amazed when I pick up the book; I always find something that makes me curse.
Friday I was in a bookstore and saw a new LISP book ("Looking at LISP", I
think, the author's name escapes me). The author uses SETF instead of SETQ,
stating that SETF will eventually replace SETQ and SET (!!). Thinking that
this was an error, I checked in Steel; lo and behold, tis true (sort of).
In 2 2/3 pages devoted to SETF, there is >> 1 << line at the very bottom
of page 94! And it isn't even clear; if the variable is lexically bound AND
dynamically bound, which gets changed (or is it BOTH)? Who knows?
Where is the definitive reference?
"For consistency, it is legal to write (SETF)"; (a) in my book, that should be
an error, (b) if it's not an error, why isn't there a definition using the
approprate & keywords? Consistency? Generating an "insufficient args"
error seems more consistent to me...
Care to explain this to a "beginner"? Not to mention that SETF is a
MACRO, by definition, which will always take longer to evaluate.
Then try explaining why SET only affects dynamic bindings (a most glaring
error, in my opinion). Again, how many years of training, understanding
and textbooks are suddenly rendered obsolete? How many books say
(SETQ X Y) is a convenient form of (SET (QUOTE X) Y)? Probably all
but two...
Then try to introduce them to DEFVAR, which may or may not get
evaluated who knows when! (And which aren't implemented correctly
very often, e.g. Franz Common and Golden Hill).
I don't think you can get 40% of the points in 4 readings! I'm constantly
amazed at what I find in there, and it's always the opposite of Real LISP!
MEMBER is a perfect example. I complained to David Betz (XLISP) that MEMBER
used EQ instead of EQUAL. I only checked about 4 books and manuals (UCILSP,
INTERLISP, IQLISP and a couple of others). David correctly pointed out that
CL defaults to EQ unless you use the keyword syntax. So years of training,
learning and ingrained habit go out the window. How many bugs
will this introduce. MEMQ wasn't good enough?
MEMBER isn't the only case...
While I'm at it, let me pick on the book itself a little. Even though CL
translates lower case to upper case, every instance of LISP names, code,
examples, etc are in **>> lower <<** case and lighter type. In fact,
everything that is not descriptive text is in lighter or smaller type.
It's VERY difficult to read just from the point of eye strain; instead of
the names and definitions leaping out to embed themselves in your brain,
you have to squint and strain, producing a nice avoidance response.
Not to mention that you can't skim it worth beans.
Although it's probably hopeless, I wish more implementors would take a stand
against COMMON LISP; I'm afraid that the challenge of "doing a COMMON LISP"
is more than most would-be implementors can resist. Even I occasionally find
myself thinking "how would I implement that"; fortunately I then ask myself
WHY?
Jeffrey M. Jacobs <UCILSP>
CONSART Systems Inc.
Technical and Managerial Consultants
P.O. Box 3016, Manhattan Beach, CA 90266
(213)376-3802
CIS:75076,2603
BIX:jeffjacobs
USENET: jjacobs@well.UUCP
(originally written in late 1985 and early 1986; more to come RSN)
------------------------------
Date: Wed, 11 Feb 87 23:04:46 pst
From: well!jjacobs@lll-lcc.ARPA (Jeffrey Jacobs)
Reply-to: well!jjacobs@lll-lcc.ARPA (Jeffrey Jacobs)
Subject: Re: Against the Tide of Common LISP
Some comments on "Against the Tide of Common LISP".
First, let me point out that this is a repeat of material that appeared
here last June. There are several reasons that I have repeated it:
1) To gauge the ongoing change in reaction over the past two years.
The first time parts of it appeared in 1985, the reaction was
uniformly pro-CL.
When it appeared last year, the results were 3:1 *against* CL, mostly
via Mail.
Now, being "Against the Tide..." is almost fashionable...
2) To lay the groundwork for some new material that is in progress
and will be ready RSN.
I did not edit it since it last appeared, so let me briefly repeat some
of the comments made last summer:
I. My complaint that "both dynamic and lexical makes the
performance" even worse refers *mainly* to interpreted code.
I have already pointed out that in compiled code the difference in
performance is insignificant.
2. The same thing applies to macros. In interpreted code, a
macro takes significantly more time to evaluate.
I do not believe that it
is acceptable for a macro in interpreted code to by destructively
exanded, except under user control.
3. SET has always been a nasty problem; CL didn't fix the problem,
it only changed it. Getting rid of it and using a new name would
have been better.
After all, maybe somebody *wants* SET to set a lexical variable if that's
what it gets...
I will, however, concede that CL's SET is indeed generally the desired
result.
4. CL did not fix the problems associated with dynamic vs lexical
scoping and compilation, it only compounded them. My comment
that
>"lexical scoping was and should be a compiler OPTIMIZATION"
is a *historical* viewpoint. In the 'early' days, it was recognized
that most well written code was written in such a manner that
it was an easy and effective optimization to treat variables as
being lexical/local in scope. The interpreter/compiler dichotomy
is effectively a *historical accident* rather than design or intent of the
early builders of LISP.
UCI LISP should have been released with the compiler default as
SPECIAL. If it had been, would everybody now have a different
perspective?
BTW, it is trivial for a compiler to default to dynamic scoping...
5. >I checked in Steel; lo and behold, tis true (sort of).
>In 2 2/3 pages devoted to SETF, there is >> 1 << line at the very bottom
>of page 94!
I was picking on the book, not the language. But thanks for all
the explanations anyway...
6. >"For consistency, it is legal to write (SETF)"
I have so much heartburn with SETF as a "primitive" that I'll save it
for another day.
7. >MEMBER used EQ instead of EQUAL.
Mea culpa, it uses EQL!
8. I only refer to Common LISP as defined in the Steele Book, and
to the Common LISP community's subsequent inability to make
any meaningful changes or create a subset. (Excluding current
ANSI efforts).
Some additional points:
1. Interpreter Performance
I believe that development under an interpreter provides
a substantially better development environment, and that
compiling should be a final step in development.
It is also one of LISP's major features that anonymous functions
get generated as non-compiled functions and must be interpreted.
As such, interpreter performance is important.
3. "Against the Tide of Common LISP"
The title expresses my 'agenda'. Common LISP is not a practical,
real world language.
It will result in the ongoing rejection of LISP by the real world; it is
too big and too expensive. To be accepted, LISP must be able to run
on general purpose, multi-user computers.
It is choking off acceptance of other avenues and paths of
development in the United States.
There must be a greater understanding of the problems, and benefits
of Common LISP, particularly by the 'naive' would be user.
Selling it as the 'ultimate' LISP standard is dangerous and
self-defeating!
Jeffrey M. Jacobs
CONSART Systems Inc.
Technical and Managerial Consultants
P.O. Box 3016, Manhattan Beach, CA 90266
(213)376-3802
CIS:75076,2603
BIX:jeffjacobs
USENET: jjacobs@well.UUCP
------------------------------
End of AIList Digest
********************
∂14-Feb-87 0030 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #41
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 14 Feb 87 00:30:25 PST
Date: Thu 12 Feb 1987 21:21-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #41
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 13 Feb 1987 Volume 5 : Issue 41
Today's Topics:
Seminars - Large Optical Expert Systems (CMU) &
Knowledge Acquisition in Magnetic Resonance Imaging (CMU) &
Methods for treating Uncertainty in AI (CMU) &
The PRL Mathematics Environment (CMU),
Conference - IEEE Conference on Neural Nets: Student Special &
2nd Conference on Artificial Intelligence and Sea &
European Conference on AI in Medicine
----------------------------------------------------------------------
Date: 10 Feb 87 16:49:48 EST
From: Patty.Hodgson@isl1.ri.cmu.edu
Subject: Seminar - Large Optical Expert Systems (CMU)
SPECIAL SEMINAR
TOPIC: Large Optical Expert Systems
SPEAKER: Dr. Alastair D. McAulay
Wright State University
Department of Computer Science
DATE: Thursday, February 12
TIME: 10:30 am
PLACE: Doherty Hall 3313, CMU
ABSTRACT:
Fast expert systems are required in such areas as plant diagnosis, and
robotics. The advantages of optics over electronics for such systems are
discussed and include: massively parallel logic and pattern matching,
and global communications and search. New computer architectures are required
to efficiently utilize fast 2-D optical spatial light modulators in
development.
A proposed real-time optical recursive probabilistic expert system is
described. Conventionally, matching in optics is performed in an
analog manner. An alternative digital symbolic substitution approach
is described for matching and variable instantiation in logic programming
languages.
*************************************************************************
Alastair holds a PhD from Carnegie Mellon University, and M.A. and
B.A. degrees with honors from Cambridge University.
He is NCR Distinguished Professor in the Department of Computer Science at
Wright State University. He has numerous publications involving optical
computing, scientific computation, signal processing, and parallel
computation.
Previously, for the past eight years, he was Program Manager and Principal
Investigator in the Corporate Computer Science Laboratory at Texas
Instruments for a DARPA/ONR optical computing contract. He is a Senior
member of IEEE and a member of SPIE and SEG. He founded the Dallas IEEE
Computer Society and was Chairman of the Dallas Section.
*****************************************************************************
If you are interested in an appointment with Dr. McAulay contact
Patty at 8818 or send mail pah@d.
------------------------------
Date: 10 Feb 87 18:58:05 EST
From: Steven.Minton@k.cs.cmu.edu
Subject: Seminar - Knowledge Acquisition in Magnetic Resonance
Imaging (CMU)
This week's speaker in the Grad AI Seminar is Mark Perlin.
(The seminar is held weekly in 7220 Wean, at 3:15 on Fridays.)
Mark is going to be describing work that he recently wrote up
for a AAAI paper. Here's the title and abstract from the paper:
Title: Knowledge Acquisition in Magnetic Resonance Imaging
We have been observing and analyzing expert problem solving behavior
in the magnetic resonance imaging (MRI) domain for over a year.
Our methodology has included the collection and analysis of
verbal transcripts and computer-assisted protocols. Our version of
protocol analysis, which incorporates detailed followup interviewing,
proved useful in the formulation of an effective computer procedure
for the domain task. We will outline the approach, with numerous
domain examples, and discuss what we learned. The key points are:
-- the effectiveness of protocol analysis
-- the usefulness of our expert's mental pictures
-- the elucidation of domain independent heuristics.
------------------------------
Date: 10 Feb 1987 2020-EST
From: David A. Evans <DAE@C.CS.CMU.EDU>
Subject: Seminar - Methods for treating Uncertainty in AI (CMU)
Artificial Intelligence in Medicine (AIM) Seminar
Friday, February 13, 1987
1:30-4:00 PM
Wean 8220
"Comparing Methods for Treating Uncertainty in AI"
Max Henrion
Engineering and Public Policy
Carnegie Mellon University
As schemes for representing uncertainty in expert systems proliferate, the
debate about their relative merits and drawbacks is heating up. Current
contenders include Mycin's Certainty Factors, the Prospector scheme, Fuzzy
Logic, Dempster-Shafer Theory, qualitative/verbal approaches, and a variety
of coherent probabilistic schemes, including Bayesian belief nets, influence
diagrams, and Maximum Entropy approaches. I will discuss various criteria
for comparing them, including epistemological (do they represent what we mean
by "uncertainty"?), heuristic (Are they computationally practical? Are they
"good enough"?), and transductional (Can you easily encode human judgment and
can you explain the results?). I will examine treatment of dependent
evidence, causal and diagnostic reasoning, with simple medical examples. I
will also describe a recent experiment comparing knowledge engineering for a
rule-based expert system with a decision analysis/Bayes' net approach to the
same task.
Papers available from Max Henrion (maxh@Andrew)
------------------------------
Date: 11 Feb 87 10:30:03 EST
From: Theona.Stefanis@g.cs.cmu.edu
Subject: Seminar - The PRL Mathematics Environment (CMU)
PS SEMINAR
MONDAY, 16 February
WeH 5409
3:30
The PRL Mathematics Environment:
A Knowledge Based Medium
Joseph Bates
Cornell University
A computer system, NuPRL, has been developed at Cornell over the last
six years to serve as a dynamic electronic medium for mathematicians.
Users of the system interactively create libraries of terminology,
proofs, and ways of reasoning that constitute particular areas of
mathematics. The system assists in creating these libraries, validates
them, and extracts executable programs from proofs that implicitly
describe computation methods. This behavior is not lost as the
mathematics becomes increasingly abstract.
NuPRL libraries have been developed for parts of number theory, real
analysis, a theory of concurrency, automata theory, and several other
areas. The system has been distributed to a dozen research groups and
is being used at the University of Edinburgh as the foundation for
their next generation mathematics environment.
Much of the NuPRL architecture does not depend on the domain being
mathematics. This observation together with experience using NuPRL has
led us to begin designing a framework for providing active media in a
variety of domains. After presenting the NuPRL architecture we
will discuss what we have learned and then describe MetaPrl, our new
framework for "knowledge based media".
-------
To schedule an appointment with Joseph Bates, contact Becky Alden
at X3772 or send mail to alden@gnome.
------------------------------
Date: Wed, 11 Feb 87 16:27 EDT
From: MIKE%BUCASA.BITNET@wiscvm.wisc.edu
Subject: Conference - IEEE Conference on Neural Nets: Student Special
Student Special!
IEEE First Annual Conference on Neural Networks, San Diego,
June 21-24, 1987
San Diego, California
Undergraduate and graduate student registration fee is $50.00.
This includes attendance at all scientific sessions and social
occasions. A valid university ID and picture ID must be
presented at the meeting.
Send registration fee to:
Maureen Caudill
IEEE - ICNN
10615G Tierrasanta Blvd.
Suite 346
San Diego, California 92124
For further information call her at the telephone number listed
below.
Telephone: (619) 457-5550, ext. 221
------------------------------
Date: 12 Feb 1987 18:17:44 EST
From: Herve.Lambert@PS3.CS.CMU.EDU
Subject: Conference - 2nd Conference on Artificial Intelligence and
Sea
Please POST
2nd INTERNATIONAL CONFERENCE ON
ARTIFICIAL INTELLLIGENCE AND SEA
___________
Marseilles (France), June 18-19, 1987
Sponsored by: International Institute of Robotics and Artificial Intelligence
Organization:
Viviane Bernadac Phone: 33 91 91 36 72
IIRIAM/CMCI Telefax:33 91 91 70 24
2 rue Henri Barbusse Telex: MISTEL 440 860 F
13241 Marseille Cedex 1
FRANCE
Objectives:
The objectives of this second ORIA conference are to show, through real
applications, that actual developments in Artificial Intelligence and
especially in the area of expert systems are out of laboratories. They are now
in the industrial world, particularly in the sea linked business, such as:
offshore, shipbuilding, fishing, harbours installations,...
Communications on the state of the art and different tools available will be
followed by conferences on the present applications.
An exhibition of industrial products and prototypes involved in hardware and
software will be at hand.
CALL FOR PAPERS
Authors are invited to contribute papers on applications in:
- Offshore Process Control (platforms, ships, drilling semi-subs,
harbour installations, ...)
- Underwater Robotics (mobile robots, UMC, subsea stations,...)
- CAD and naval building (ships, platforms, piping,...)
Deadline: February 28th
Instructions to authors: Send 4 copies of the paper (up to 15 pages) to
Viviane Bernadac, IIRIAM/CMCI (address mentionned above) :
1st page:
Title of the paper
Name of Authors
Addresses
Telephone, telex and telefax numbers
Abstract (15 lines)
------------------------------
Date: 12 Feb 1987 20:17:29 EST
From: Herve.Lambert@PS3.CS.CMU.EDU
Subject: Conference - European Conference on AI in medicine
Please POST
EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE IN MEDICINE
_______________
Marseilles (France), August 31st - September 3rd 1987
Following proposals at the International Conference on Artificial
Intelligence in Medicine, Pavia, November 1985 the European Society for
Artificial Intelligence in Medicine (AIME) has been established to foster
fundamental and applied research in artificial intelligence and symbolic
information processing techniques for medical care and medical research.
AIME also wishes to assist industry in identifying high quality medical
products which exploit these techniques.
A major AIME activity will be a biannual series of intenational conferences,
the next of which will be in Marseilles, France, following the International
Conference on Artificial Intelligence in Milan, August 1987.
CALL FOR PAPERS
______
Papers are invited on any aspect of the theory, design or application of
medical AI systems. Submissions will be refereed by an international panel on
the basis of complete but succinct papers. These should be in English, length
2000 - 4000 words. Criteria for acceptance will include originality,
practical significance, contribution to theory of bmethodology and clarity of
presentation. Submissions for a poster session are also invited; these should
be a maximum of 500 words or one A4 page. The conference proceedings of
papers and poster summaries will be available at the conference.
DEADLINES
- April 1st, 1987 Final date for receipt of full short paper camera
ready.
- May 15th, 1987 Notifications of acceptance of papers distribution of
the Preliminary Program.
- July 1st, 1987 Register for reduced registration fee until now.
ADDRESS
Viviane Bernadac - AIME 87
IIRIAM
2 rue Henri Barbusse
13241 Marseille Cedex 1
FRANCE
------------------------------
End of AIList Digest
********************
∂14-Feb-87 0313 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #42
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 14 Feb 87 03:13:36 PST
Date: Fri 13 Feb 1987 21:40-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #42
To: AIList@SRI-STRIPE.ARPA
AIList Digest Saturday, 14 Feb 1987 Volume 5 : Issue 42
Today's Topics:
Philosophy - Emotions & Consciousness & Methodology
----------------------------------------------------------------------
Date: Mon, 9 Feb 1987 18:52 EST
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: Glands and Psychic Function
In asking about my qualifications for endorsing Eric Drexler's book about
nanotechnology, Tim Maroney says
> The psychology {in Eric Drexler's "Engines of Creation"} is so
> amazingly shallow; e.g., reducing identity to a matter of memory,
> ignoring effects of the glands and digestion on personality.
> ...in my opinion his approach is very anti-humanistic.
It is not a matter of reducing identity to memory alone, but, if he
will read what Drexler said, a matter of replacing each minute section
of the brain by some machinery that is functionally the same.
Naturally, many of those functions will be affected by chemicals that,
in turn, are partially controlled by other brain activities. A
functional duplicate of the brain will have to be embedded in a system
that duplicates enough of those non-neurological functions.
However, in the view of many thinkers concerned with what is sometimes
called the "downloading" enterprise, the functions of glands,
digestion, and the rest are much simpler than those embodied in the
brain; furthermore, they are common to all of us - and to all mammals
as well, with presumably minor variations; in this sense they are not
particularly involved in what we think of as individual identity.
I should add that it is in order to avoid falling prey to such
conventional superstitions, as this one - that emotions are much
harder to comprehend and duplicate than are intellectual functions -
that it is the requisite if sometimes unpleasant obligation of the
good psychologist to try to be as anti-humanistic as possible; that
is, in the sense of assuming that our oldest beliefs must be
preserved, no matter what the scientific cost.
------------------------------
Date: 10 Feb 87 06:19:58 GMT
From: well!wcalvin@lll-lcc.arpa (William Calvin)
Subject: Re: More on Minsky on Mind(s)
Sender:
Reply-To: wcalvin@well.UUCP (William Calvin)
Followup-To:
Distribution:
Organization: Whole Earth 'Lectronic Link, Sausalito, CA
Keywords: Consciousness, throwing, command buffer, evolution, foresight
Reply to Peter O. Mikes <lll-lcc!mordor!pom> email remarks:
> The ability to form 'the model of reality' and to exercise that model is
> (I believe) a necessary attribute of 'sentient' being and the richness
> of such model may one-day point a way to 'something better' then
> word-logic. Certainly, the machines which exist so far, do not indeed
> have any model of universe 'to speak off' and are not conscious.
A model of reality is not uniquely human; I'd ascribe it to a spider
as well as my pet cat. Similarly, rehearsing with peripherals switched off
is probably not very different from the "get set" behavior of said cat when
about to pounce. Choosing between behaviors isn't unique either, as when
the cat chooses between taking an interest in my shoe-laces vs. washing a
little more. What is, I suspect, different about humans is the wide range
of simulations and scenario-spinning. To use the railroad analogy again,
it isn't having two short candidate trains to choose between, but having
many strings of a half-dozen each, being shaped up into more realistic
scenarios all the time by testing against memory -- and being able to
select the best of that lot as one's next act.
I'd agree that present machines aren't conscious, but that's because
they aren't Darwin machines with this random element, followed by
successive selection steps. Granted, they don't have even a spider's model
of the (spider's limited) universe; improve that all you like, and you
still won't have human-like forecasting-the-future worry-fretting-joy. It
takes that touch of the random, as W. Ross Ashby noted back in 1956 in his
cybernetics book, to create anything really new -- and I'd bet on a Darwin-
machine-like process such as multitrack stochastic sequencing as the source
of both our continuing production of novelty and our uniquely-human aspects
of consciousness.
William H. Calvin
University of Washington 206/328-1192 or 206/543-1648
Biology Program NJ-15 BITNET: wcalvin@uwalocke
Seattle WA 98195 USA USENET: wcalvin@well.uucp
------------------------------
Date: Tue, 10 Feb 87 13:32:05 n
From: DAVIS@EMBL.BITNET
Subject: oh no, not more philosophy!
From: "CUGINI, JOHN" <cugini@icst-ecf>
> I (and Reed and Taylor?) been pushing the "brain-as-criterion" based
> on a very simple line of reasoning:
> 1. my brain causes my consciousness.
> .......
> Now, when I say simple things like this, Harnad says complicated things like:
> re 1: how do you KNOW your brain causes your consciousness? How can you have
> causal knowledge without a good theory of mind-brain interaction?
> Re 2: How do you KNOW your brain is similar to others'? Similar wrt
> what features? How do you know these are the relevant features?
> .....
> We are dealing with the mind-body problem. That's enough of a philosophical
> problem to keep us busy. I have noticed (although I can't explain why),
> that when you start discussing the mind-body problem, people (even me, once
> in a while) start to use it as a hook on which to hang every other
> known philosophical problem:
> 1. well how do we know anything at all, much less our neighbors' mental states
?
(skepticism and epistemology).
> ........
> All of these are perfectly legitimate philosophical questions, but
> they are general problems, NOT peculiar to the mind-body problem.
> When addressing the mind-body problem, we should deal with its
> peculiar features (of which there are enough), and not get mired in
> more general problems * unless they are truly in doubt and thus their
> solution truly necessary for M-B purposes. *
> I do not believe that this is so of the issues Harnad raises.
Sorry John, but you can't get away with this sort of 'simple' stuff. Dressing
up complex issues in straightforward clothing is not an answer.
Firstly, as Ken Laws recently indicated with considerable flair (though
to my mind, insufficient force), we have to deal with your assertion that
'my brain causes my conciousness'. Harnad's question may or may not be
relevant, but *IF* we are going to get bogged down in subjective conciousness
(which is of little relevance to AI for the next 30 years AT LEAST), then
we must begin by questioning even this most basic assumption. I don't think
its necessary to take you through the argument, only to note that we end
up with Nagel in asserting that "it is like something to be me/us". Its
not difficult to assert and to cogently argue that conciousness is an
illusion, but what is not so easily got around is that *something* could
be having an illusion. The mere fact that we are aware (yes, I know, that's
what conciousness *used* to mean!) immediately propels us to question how
"anything can know anything at all".
This question is absolutely central to the M-B problem, and there is no
getting around by arguing for ways in which we might organise concious
experience. The simple fact that we either *are* or even just *seem to be*
concious immediately forces to deal with this issue. Of course, you can
avoid it if you want to return to pre-computational philosophy, and
put the M-B problem simply as the issue as the localisation of concious
activity, but that seems to me to be as enourmous a bypass of the *real*
issue as you can get.
Speaking personally, I must say that it seems initially easier to suppose
that we only suffer an illusion of conciousness - by which I mean we only
suffer the illusion of being aware of possessing motivation, desire, intention,
(maybe even intension !!!!) and emotion. In a superficial sense this clears
everything up quite nicely, since it tends to be sort of things that have
been referred to (implicitly or not) during the Minsky Meanderings. However,
it DOES NOT get around the fact that there still seems to be a 'we' being
the subject of these (magnificent) illusions.
And that, my friends, must surely be the central issue. It makes not an
iota of difference what our 'concious experiences' actually consist of,
it makes no difference how our neural networks are linked to allow us to
access previous events, to formulate reasons, to plan, to rehearse (re:
Calvin). The problem at the heart of all this is simply that as individuals
we are aware of *something*, and that is the biggest problem of all.
Buts its irrelevant for ai. We will never be the computers we have designed,
and hence they will always be 'other minds'. Hence, the issue for practical
ai is simply one of nomenclature, and can never (?) be one of design.C'est
ca.
I don't think I explained this too well - maybe a prod will help me rearrange
my thoughts.....
so, robot cow -bolts or electronic battering rams to:
paul ("the answers come easy - you have any questions ?") davis
netmail: davis@embl.bitnet
wetmail: embl, postfach 10.2209, 6900 Heidelberg, FRG.
"conciousness is as a butterfly,
which, chased after with great fervour,
will never be yours.
but if you will only sit down quietly,
to admire the view,
may alight gently upon your arm."
with apologies to Nathaniel Hawthorne (I think)
------------------------------
Date: 9 Feb 87 14:48:28 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: More on Minsky on Mind(s)
wcalvin@well.UUCP (William Calvin), Whole Earth 'Lectronic Link, Sausalito, CA
writes:
> Rehearsing movements may be the key to appreciating the brain
> mechanisms [of consciousness and free will]
But WHY do the functional mechanisms of planning have to be conscious?
What does experience, awareness, etc., have to do with the causal
processes involved in the fanciest plan you may care to describe? This
is not a teleological why-question I'm asking (as other contributors
have mistakenly suggested); it is a purely causal and functional one:
Every one of the internal functions described for a planning,
past/future-oriented device of the kind Minsky describes (and we too
could conceivably be) would be physically, causally and functionally EXACTLY
THE SAME -- i.e., would accomplish the EXACT same things, by EXACTLY the same
means -- WITHOUT being interpreted as being conscious. So what functional
work is the consciousness doing? And if none, what is the justification
for the conscious interpretation of any such processes (except in
my own private case -- and of course that can't be claimed to the credit of
Minsky's hypothetical processes)? [As to "free will" -- apart from the aspect
that is redundant with the consciousness-problem [namely, the experience,
surely illusory, of free will], I sure wouldn't want to have to defend a
functional blueprint for that...]
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: 9 Feb 87 19:28:40 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: More on Minsky on Mind(s) (Reply to Davis)
Causality
Summary: On the "how" vs. the "why" of consciousness
References: <460@mind.UUCP> <1032@cuuxb.UUCP> <465@mind.UUCP>
<2556@well.UUCP> <491@mind.UUCP>
Paul Davis (davis@embl.bitnet) EMBL,postfach 10.22.09, 6900 Heidleberg, FRG
wrote on mod.ai:
> we see Harnad struggling with why's and not how's...
> conciousness is a *biological* phenomenon... because
> this is so, the question of *why* conciousness is used
> is quite irrelevant in this context...[Davis cites Armstrong,
> etc., on "conciousness as a means for social interaction"]...
> conciousness would certainly seem to be here -- leave it to
> the evolutionary biologists to sort out why, while we get on
> with the how...
I'm concerned ONLY with "how," not "why." That's what the TTT and
methodological epiphenomenalism are about. When I ask pointedly about
"why," I am not asking a teleological question or even an evolutionary one.
[In prior iterations I explained why evolutionary accounts of the origins
and "survival value" of consciousness are doomed: because they're
turing-indistinguishable from the IDENTICAL selective-advantage scenario,
minus consciousness.] My "why" is a logical and methodological challenge
to inadequate, overinterpreted "how" stories (including evolutionary
"just-so" stories, e.g., "social" ones): Why couldn't the objectively
identical "how" features stand alone, without being conscious? What
functional work is the consciousness itself doing, as opposed to
piggy-backing on the real functional work? If there's no answer to that,
then there is no justification for the conscious interpretation of the "how."
[If we're not causal dualists, it's not even clear whether we would
WANT consciousness to be doing any independent work. But if we
wouldn't, then why does it figure in our functional accounts? -- Just
give me the objective "how," without the frills.]
> the mystery of the C-1: How can ANYTHING *know* ANYTHING at all?
The problem of consciousness is not really the same as the problem of
knowledge (although they're linked, since, until shown otherwise, only
conscious devices have knowledge). To know X is not the same as to
experience X. In fact, I don't think knowledge is a C-1-level
phenomenon. [I know (C-2) THAT I experience pain, but does the cow know
THAT she experiences pain? Yet she presumably does experience pain (C-1).]
Moreover, "knowledge" is mired in epistemological and even
ontological issues that cog-sci would do well to steer clear of (such
as the difference between knowing X and merely believing X, with
justification, when X is true).
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: 9 Feb 87 18:33:49 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: More on Minsky on Mind(s) (Reply to Laws)
Ken Laws <Laws@SRI-STRIPE.ARPA> wrote on mod.ai:
> I'm not so sure that I'm conscious... I'm not sure I do experience
> the pain because I'm not sure what "I" is doing the experiencing
This is a tough condition to remedy. How about this for a start: The
inferential story, involving "I" and objects, etc. (i.e., C-2) may
have the details wrong. Never mind who or what seems to be doing the
experiencing of what. The question of C-1 is whether there is any
experience going on at all. That's not a linguistic matter. And it's
something we presumably share with speechless, unreflective cows.
> on the other hand, I'm not sure that silicon systems
> can't experience pain in essentially the same way.
Neither am I. But there's been a critical inversion of the null hypothesis
here. From the certainty that there's experience going on in one privileged
case (the first one), one cannot be too triumphant about the ordinary inductive
uncertainty attending all other cases. That's called the other-minds
problem, and the validity of that ineference is what's at issue here.
The substantive problem is characterizing the functional capacities of
artificial and natural systems that warrant inferring they're conscious.
> Instead of claiming that robots can be conscious, I am just as
> willing to claim that consciousness is an illusion and that I am
> just as unconscious as any robot.
If what you're saying is that you feel nothing (or, if you prefer, "no
feeling is going on") when I pinch you, then I must of course defer to
your higher authority on whether or not you are really an unconscious robot.
If you're simply saying that some features of the experience of pain and
how we describe it are inferential (or "linguistic," if you prefer)
and may be wrong, I agree, but that's beside the point (and a C-2
matter, not a C-1 matter). If you're saying that the contents of
experience, even its form of presentation, may be illusory -- i.e.,
the way things seem may not be the way things are -- I again agree,
and again remind you that that's not the issue. But if you're saying
that the fact THAT there's an experience going on is an illusion, then
it would seem that you're either saying something (1) incoherent or (in
MY case, in any event) (2) false. It's incoherent to say that it's
illusory that there is experience because the experience is illusory.
If it's an experience, it's an experience (rather than something else,
say, an inert event), irrespective of its relation to reality or to any
interpretations and inferences we may wrap it in. And it's false (of me,
at any rate) that there's no experience going on at all when I say (and
feel) I have a toothache. As for the case of the robot, well, that's
what's at issue here.
[Cartesian exercise: Try to apply Descartes' method of doubt -- which
so easily undermines "I have a toothache" -- to "It feels as if I have
a toothache." This, by the way, is to extend the "cogito" (validly) even
further than its author saw it as leading. You can doubt that things
ARE as they seem, but you can't doubt that things SEEM as they seem.
And that's the problem of experience (of appearances, if you will).
Calling them "illusions" just doesn't help.]
> One way out is to assume that neurons themselves are aware of pain
Out of what? The other-minds problem? This sounds more like an
instance of it than a way out. (And assumption hardly seems to amount
to solution.)
> How do we know that we experience pain?
I'm not sure about the "I," and the specifics of the pain and its
characterization are negotiable, but THAT there is SOME experience
going on when "I" feel "pain" is something that anyone but an
unconscious robot can experience for himself. And that's how one
"knows" it.
> I propose that... our "experience" or "awareness" of pain is
> an illusion, replicable in all relevant respects by inorganic systems.
Replicate that "illusion" -- design devices that can experience the
illusion of pain -- and you've won the battle. [One little question:
How are you going to know whether the device really experiences that
illusion, rather than your merely being under the illusion that it
does?]
As to inorganic systems: As ever, I think I have no more (or less)
reason to deny that an inorganic system that can pass the TTT has a
mind than I do to deny that anyone else other than myself has a mind.
That really is a "way out" of the other-minds problem. But inorganic
systems that can't pass the TTT...
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
End of AIList Digest
********************
∂14-Feb-87 0633 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #43
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 14 Feb 87 06:33:02 PST
Date: Fri 13 Feb 1987 22:00-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #43
To: AIList@SRI-STRIPE.ARPA
AIList Digest Saturday, 14 Feb 1987 Volume 5 : Issue 43
Today's Topics:
Philosophy - Consciousness & Methodology & Zen
----------------------------------------------------------------------
Date: 10 Feb 87 19:41:21 GMT
From: Diamond!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Harnad's epiphenomenalism
In defending his thesis of "methodological epiphenomenalism", one of Harnad's
favorite strategies is apparently a variant of G.E. Moore's "naturalistic
fallacy" argument: For any proposed definition of consciousness, he will
ask: "You say consciousness is X, but why couldn't you just as well have X
WITHOUT consciousness?" If we concede the meaningfulness of this question in
all cases, obviously this objection will be decisive.
But, I think this argument is as question-begging now as it was when Moore
used it in ethical philosophy. The definer is proposing that X is just what
consciousness IS. Accordingly, he does *not* grant that you could have X
without consciousness since, on his view, X and consciousness are one and the
same.
Put another way, the materialist is not trying to ADD anything to the
objective, causal story of X by calling it consciousness. Rather, he is
attempting to illuminate the problematic common-sense notion of consciousness
by showing how it is interpretable in naturalistic terms. Obviously the
adequacy of any proposed definition of consciousness will need to be
established; the issues to be considered will pertain to whether or not the
definition does reasonable justice to the pre-analytic application of the
term, etc. But these issues are just the usual ones for inter-theoretical
identification, and don't present any special problem in the case of mind and
brain.
Another point that Harnad has often stated is that behavior is in practice
our only criterion for the ascription of consciousness. While this is
currently true, it does not at all preclude the revision of our theory in the
direction of a more refined criterion. Compare, say, the definition of
"gold." At one time, this substance was identifiable solely on the basis of
its superficial properties such as color, hardness, and specific gravity.
With the growth of scientific knowledge, a new definition of gold in terms of
atomic structure has come to be accepted, and this criterion now supersedes
the earlier ones. If you like, you might say that atomic theory came to
reveal the "essence" of gold. I see no reason to suppose an analagous shift
couldn't arise out of the study of the mind and brain.
Harnad's "methodological epiphenomenalism" is a apparently an unavoidable
consequence of his philosophy of mind, which seems to be epiphenomenalism
simpliciter. I am surprised to find many of Harnad's interlocutors
essentially granting him this controversial premise. Whatever happened to
materialism? As I understood it, the whole field of cognitive science -- the
rehabilitation of mentalistic theorizing in psychology -- was inspired by the
philosophical insight that the functional states of computers seemed to have
just the right sorts of features we would want for psycho-physical
identification. Harnad must believe that this philosophy has failed, dooming
us to return to an uneasy and unappealling view: ontological dualism coupled
with methodological behaviorism -- the worst of both worlds.
Well, I don't think we ought to give this up so easily. I would urge that
cognitivists *not* buy into the premise of so many of Harnad's replies: the
existence of some weird parallel universe of subjective experience.
(Actually, *multiple* such universes, one per conscious subject, though of
course the existence of more than my own is always open to doubt.) We should
recognize no such private worlds. The most promising prospect we have is that
conscious experiences are either to be identified with functional states of
the brain or eliminated from our ultimate picture of the world. How this
reduction is to be carried out in detail is naturally a matter for
empirical study to reveal, but this should remain one (distant) goal of
mind/brain inquiry.
Anders Weinstein aweinste@DIAMOND.BBN.COM
BBN Labs, Cambridge MA
------------------------------
Date: 10 Feb 87 20:09:44 GMT
From: ihnp4!houxm!houem!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: More on Minsky on Mind(s)
In article <490@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> wcalvin@well.UUCP (William Calvin), Whole Earth 'Lectronic Link, Sausalito, CA
> writes:
> > Rehearsing movements may be the key to appreciating the brain
> > mechanisms [of consciousness and free will]
>
> But WHY do the functional mechanisms of planning have to be conscious?
> What does experience, awareness, etc., have to do with the causal
> processes involved in the fanciest plan you may care to describe?...
I have the gall to answer an answer to an answer without having read
Minsky. But then, my interest in AI is untutored and practical.
Here goes:
My notion is that a being that thinks is not necessarily conscious,
but a being that thinks about thinking, and knows when it is just
thinking and when it is actually doing, must be called conscious.
In UNIX(tm) there is a program called "make" that reads a script of
instructions, compares the ages of various files named in the
instructions, and follows the instructions by updating only the files
that need to be updated. It can be said to be acting with some sort of
rudimentary intelligence.
If you invoke the "make" command with the "-n" flag, it doesn't do any
updating, it just tells you what it would do. It is rehearsing a
potential future action. In a sense, it's thinking about what it would
do. But it doesn't have to know that it's only thinking and not
doing. It could simply have its actuators cut off from its rudimentary
intelligence, so that it thinks it's acting but really isn't.
Now suppose the "make" command could, under its own internal program,
run through its instructions with a simulated "-n" flag, varying some
conditions until the result of the "thinking without doing" satisfied
some objective, and then could remove the "-n" flag and actually do
what it had just thought about.
This "make" would appear to know when it is thinking and when it is
acting, because it decided when to think and when to act. In fact, in
its diagnostic output it could say first "I am thinking about the
following alternative," and then finally say, "The last run looked
good, so this time I'm really going to do it." Not only would it
appear to be conscious, but it would be accomplishing a practical
purpose in a manner that requires it to distinguish internally between
introspection and action.
I think that version of "make" would be within the current state of the
art of programming, and I would call it conscious. So we're not far
from artificial consciousness.
Marty
M. B. Brilliant (201)-949-1858
AT&T-BL HO 3D-520 houem!marty1
------------------------------
Date: 11 Feb 87 19:44:14 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: Harnad's epiphenomenalism
aweinste@Diamond.BBN.COM (Anders Weinstein) of BBN Labs, Cambridge, MA,
writes:
> For any proposed definition of consciousness, [Harnad] will
> ask: "You say consciousness is X, but why couldn't you just as
> well have X WITHOUT consciousness?"
> I think this argument is as question-begging now as it was when Moore
> used it in ethical philosophy. The definer is proposing that X is
> just what consciousness IS. Accordingly, he does *not* grant that
> you could have X without consciousness since, on his view, X and
> consciousness are one and the same.
It unfortunately has to be relentlessly reiterated that these matters
are not settled by definitions or obiter dicta. It simply won't do to
say "On my view, consciousness and X [say, memory, learning,
self-referential capacity, linguistic capacity, or what have you] are
one and the same." It is perfectly legitimate -- indeed, mandatory, if
SOMEONE is going to exercise some self-critical constraints on mentalistic
interpretation -- to ask WHY a candidate process should be interpreted as
conscious. If all the functional answers to that question -- "it's so it
can accomplish X," or "it's so it can accomplish Y this way rather than that
way" -- would be the SAME for an unconscious process, then there are indeed
strong grounds for supposing that the mentalistic interpretation is
methodologically (I might even say, to bait the functionalists more
pointedly, "functionally") superfluous. (It's not the skepticism
that's question-begging, but the mentalistic interpretation that's
supererogatory.)
I have no idea how or why Moore used a similar argument in ethics.
My own argument is purely methodological (and functional -- I am a
kind of functionalist too): I am concerned with how to get devices we
build (and hence understand) to DO what minds can do. These devices may
also turn out to BE what minds are (namely conscious), but I do not
believe that there is any objective, scientific way to ascertain that.
Nor do I think it is methodologically possible or relevant (or, a
fortiori, necessary) to do so. My pointed "why" questions are intended to
pare off the unjustified and distracting mentalistic hype and leave a clearer
image of just how far we really have or haven't gotten in answering the
"how" questions, which are the only scientifically tractable ones in the
area of theoretical bioengineering that mind-modeling occupies.
> the materialist is attempting to illuminate the problematic
> common-sense notion of consciousness by showing how it is
> interpretable in naturalistic terms. Obviously the adequacy of
> any proposed definition of consciousness will need to be established;
> the issues to be considered will pertain to whether or not the
> definition does reasonable justice to the pre-analytic application
> of the term, etc. But these issues are just the usual ones for
> inter-theoretical identification, and don't present any special
> problem in the case of mind and brain.
But it is just the question of whether these issues are indeed the
"usual" ones in the mind/brain case that is at issue. I've given lots of
logical and methodological reasons why they're not. Wishful thinking, hopeful
overinterpretation and scientistic dogma seem to be the only rejoinders
I'm hearing. (I'm a materialist too; methodological constraints on
theoretical inference and its deliverances are what's at issue here.)
> Compare, say, the definition of "gold."...
> growth of scientific knowledge...new definition of gold
> I see no reason to suppose an analogous shift
> couldn't arise out of the study of the mind and brain.
I like the way Nagel handled this old reductionist chesnut: In
a chesnut-shell, he pointed out that all of the standard
reduction/revision scenarios of science have always consisted of one
objective account of an objective phenomenon being superseded or
subsumed by another objective account of an objective phenomenon (heat
--> mean molecular motion, etc.). There's nothing in this standard
revision-scenario that applies to -- much less can handle --
redefining subjective phenomena objectively. That prominent disanalogy
is yet another of the faces of the mind/body problem (that
functionalist euphoria sometimes overlooks). As it stands, the faith
in an eventual successful "redefinition" is just that: a faith. One
wonders why it does not founder in the sea of counter-examples and
disanalogies rightly generated by Moore's (if it's really his) method
of pointed "why" challenges. But there's no accounting for faith.
> Harnad's "methodological epiphenomenalism" is apparently an
> unavoidable consequence of his philosophy of mind, which seems to
> be epiphenomenalism simpliciter.
No, I'm not an ontological epiphenomenalist (which I suppose is a kind
of dualism), just a methodological one. I don't think consciousness
can enter into scientific theory-building and theory-testing, for the
reasons I've stated. In fact, I think it retards theory-building to
try to account for consciousness or to dress theory up with conscious
interpretations. (Among other things, it masks the performance work
that still remains to be done, and lionizes possible nonstarters.)
However, I have no doubt that consciousness exists, and no serious
doubts that organisms are conscious. Moreover, I'm quite prepared to believe
the same of devices that pass the TTT, and on exactly the same grounds. These
devices may well have "captured" consciousness functionally. Yet not only
is there no way of knowing whether or not they really have; it even makes no
methodological difference to their functioning or to our theoretical
understanding of it whether or not they have really captured
consciousness. This is not an ontological issue. The mind/body problem
simply represents a methodological constraint on what can be known objectively,
i.e., scientifically. (Note that this constraint is not just the ordinary
underdetermination of scientific inferences about unobservables; it's
much worse. For, as I've pointed out several times before, although
hypthesized entities such as quarks or superstrings are no more
observable or "verifiable" than consciousness, it is a methodological
fact that the respective theories from which they come cannot account for the
objective phenomena without positing their existence, whereas any
theory of the objective phenomena of mind -- i.e., I/O performance
capacity, perhaps supplemented by structure and function -- will work
just as well with or without a mentalistic interpretation.)
> the whole field of cognitive science -- the rehabilitation of
> mentalistic theorizing in psychology -- was inspired by the
> philosophical insight that the functional states of computers
> seemed to have just the right sorts of features we would want for
> psycho-physical identification. Harnad must believe that this
> philosophy has failed, dooming us to return to an uneasy and
> unappealling view: ontological dualism coupled with methodological
> behaviorism -- the worst of both worlds.
I certainly believe that the view has failed methodologically. But I
don't think the consequence is ontological dualism (for the reasons
I've stated) and it's not clear what "methodological behaviorism" is
(or was, I'll return to this important point). Nor do I consider
cognitive science to be synonymous with mentalistic theorizing; nor
do I consider the field to be inspired by the the psycho-physical
identificatory hopes aroused by the computer. If you want to know what
I think, it's this:
Behaviorism, in a reaction against the sterility of introspectionism,
rejected reflecting and theorizing on what went on in the mind,
suggesting instead that psychology's task was to study observable
behavior. But in its animus against mentalistic theory, behaviorism
managed to do in or trivialize theory altogether. Put another way, not
only was behaviorism opposed to (observing or) theorizing about what went
on in the MIND, it also opposed theorizing about what went on in the HEAD.
As a consequence, behavioristic psychology effectively became a
"science" without a theoretical or inferential branch to speak of.
Now what I think happened with the advent of cognitive science was
that, again, just as unobservable mental processes and unobservable
(shall we call them) "inernal" processes had been jointly banned from
the citadel, they were, with the rise of computer modeling (and
neural modeling), jointly readmitted. The mistake, as I see it,
was to embrace indiscriminately BOTH the legitimate right (and need) to
make theoretical inferences about the unobservable functional subtrates of
behavior AND the temptation to make mentalistic interpretations of
them. In my view, the first advances empirical progress (in fact is
essential for it), the second beclouds and retards it. Cognitive
science is (or should be) behaviorism-with-a-theory (or theories) at
last. If that's "methodological behaviorism," then it took the computer
era to make it so.
> Well, I don't think we ought to give this up so easily.
> I would urge that cognitivists *not* buy into the premise of
> so many of Harnad's replies: the existence of some weird parallel
> universe of subjective experience... conscious experiences are
> either to be identified with functional states of the brain or
> eliminated from our ultimate picture of the world. How this
> reduction is to be carried out in detail is naturally a matter for
> empirical study to reveal, but this should remain one (distant)
> goal of mind/brain inquiry.
Identify it with the functional states if you like. But then FORGET
about it until you've GOT the functional states that deliver the
performance (TTT) goods. When you've got those -- i.e., when all the
objective questions there are to be answered are answered -- then no
harm whatever will be done by an orgy of mentalistic interpretation of
the objective story.
No "weird parallel universe." Just the familiar subjective one we all
know at first hand. Plus the methodological constraint that the
complete scientific picture is doomed to fail to account to our satisfaction
for the existence, nature, and utility of subjectivity.
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: 11 Feb 87 17:39:14 GMT
From: mcvax!ukc!cheviot!rosa@seismo.css.gov (Rosa Michaelson - U of
Dundee)
Subject: Re: More on Minsky on Mind(s) (Reply to Davis)
This is really afollow up to Cuigini but I do not have the moderators address.
Please refer to McCarthy's seminal work "The conciousness of Thermostats".
All good AI believers emphasize with thermostats rather than other humans.
Thank goodness I do computer science...(:-)
Has Zen and the art of Programming not gone far enough??? Please no more
philosophy, I admit it I do Not care about conciousness/minsky/the mind
brain identity problem....
Is it the cursor that moves, the computer that thinks or the human
that controls?
None of these, grasshopper, only a small data error on the tape of life.
------------------------------
End of AIList Digest
********************
∂14-Feb-87 0853 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #44
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 14 Feb 87 08:53:41 PST
Date: Fri 13 Feb 1987 22:04-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #44
To: AIList@SRI-STRIPE.ARPA
AIList Digest Saturday, 14 Feb 1987 Volume 5 : Issue 44
Today's Topics:
AI Methodology - Symbolic Logic vs. Analog Representation &
Pragmatic Definitions of AI/Cognitive Terms
----------------------------------------------------------------------
Date: 12 Feb 87 17:52:55 GMT
From: vax1!czhj@cu-arpa.cs.cornell.edu (Ted )
Subject: Re: Learing about AI
In article <12992@sun.uucp> lyang%jennifer@Sun.COM (Larry Yang) writes:
>....
>I was in for a surprise. Based on my experience, if you want
>to learn about hard-core, theoretical artificial intelligence,
>then you must have a strong (I mean STRONG) background in formal
>logic.
This is EXACTLY the problem with AI research as it is commonly done today.
(and perhaps yesterday as well). The problem is that mathematicians, logicians
and computer scientists, with their background in formal logic have no other
recourse than to attack the AI problem using these tools that are available
to them. Perhaps this is why the field makes such slow progress?
AI is an ENORMOUS problem, to say the least and research into it should not
be bound by the conventional thinking that is going on. We have to look at
the problem in NEW ways in order to make progress. I am strongly under the
impression that people with a strict theoretical training will actually HINDER
the field rather than advance it because of the constraints on the ideas that
they come up with just because of their background.
Now, I'm NOT saying that nobody in CS, MATH, or LOGIC is capable of original
thought, however, from much of the research that is being done, and from the
scope of the discussions on the NET, it seems safe to say that many people of
these disciplines discount less formal accounts as frivolous.
But look at the approach that LOGIC gives AI. It is a purely reductionist
view, akin to studying global plate motion at the level of sub-atomic
particles. It is simply the wrong level at which to approach the problem.
A far more RATIONAL approach would be to integrate a number of disciplines
towards the goal of understanding intelligence. COMPUTER SCIENCE has a major
role because of the power of computer modeling, efficient data structures and
models of efficient parallel computation. Beyond that, it seems that
computer science should take a back seat. LOGIC, well, where would that fit
in? Maybe at the very lowest level, but most of that is taken for granted by
computer science. PHILOSOPHY tends to be a DEAD END, as can clearly be noted
by the arguments going on on the NET :) Honestly, the philosophy arguments
tend to get so jumbled (though logical), that they really add little to the
field. COGNITIVE PSYCHOLOGY is a quickly emerging field that is producing some
interesting findings, however, at this stage, it is more descriptive than
anything else. There is some interesting speculation into the processes that
are going on behind thought in this field, and they should be looked at
carefully. However, there is simply so much fluff and pointless experiments
that it takes quite a while to wade through and get anything significant.
LINGUISTICS is a similar field. The work of Chomsky and others has given us
some fascinating ideas and may get somewhere in terms of biological constraints
on knowledge and such. Even NEUROBIOLOGY should get involved. Reasearch in
this field gives us more insight into internal constraints. Furthermore,
by studying people with brain disorders (both congenital and through accident)
we can gain some insight into what types of structures are innate or have a
SPECIFIC locus of control.
In sum, I call for using many different disciplines to solve the basic problems
in knowledge, learning and perception. No single approach will do.
---Ted Inoue
------------------------------
Date: 13 Feb 87 14:17:24 GMT
From: sher@CS.ROCHESTER.EDU (David Sher)
Subject: Re: Learing about AI
If I didn't respond to this I'd have to work on my thesis so here
goes:
I think there seems to be something of a misconception regarding the
place of logic wrt AI and computer science in general. To start with
I will declare this:
Logic is a language for expressing mathematical constructs.
It is not a science and as far as artificial intelligence is concerned
the mathematics of logic are not very relevant. Its main feature
is that it can be used for precise expression.
So why use logic rather than a more familiar language, like english.
One can be precise in english, writers like Edgar Allen Poe, Issac
Asimov, and George Gamov all have written very precise english on a
variety of topics. However the problem is that few of us knowledge
engineers have the talent to be precise in our everyday language.
There are few great, or even very good writers among AI practitioners.
Thus for decades engineers, scientists, and statisticians have used
logic to express their ideas since even an incompetent speaker can be
clear and precise using logical formalisms. However like any language
with expressive power one can be totally incomprehensible using logic.
I have seen logical expressions that even the author did not
understand. Thus logic is not a panacea, it is merely a tool. But it
is a very useful and important tool (you can chop down trees with a
boy scout knife but I'll take an axe any day and a chain saw is even
better). Also like english or any other language the more logic you
know the more clearly and compactly you can state your ideas (if you
can avoid the temptation to use false erudition and use your document
to demonstrate your formal facility rather than what you are trying to
say). Thus if you know modal or second order logics you can express
more than you can with simple 1st order predicate calculus and you can
express it better.
Of course, not everyones goals are to express themselves clearly.
Some people's business is to confuse and obfuscate. While logic can
be put to this purpose it is easier to use english for this task. It
takes an uncommon level of expertise to be really confusing without
appearing incompetant with logic.
Note: I am not a logician but I use a lot of logic in my everyday
work which is probabilistic analysis of computer vision problems
(anyone got a job?).
--
-David Sher
sher@rochester
{allegra,seismo}!rochester!sher
------------------------------
Date: Fri, 13 Feb 87 14:02:51 pst
From: Ray Allis <ray@BOEING.COM>
Subject: Other Minds
Some of you may be after the fame and great wealth associated with AI
research, but MY goal all along has been to BUILD an "other mind"; a
machine who thinks *at least* as well as I do. If current "expert
systems" are good enough for you, please skip this. Homo Sap.'s
distinguished success among inhabitants of this planet is primarily due
to our ability to think. We will continue to exist only if we act
intelligently, and we can use all the help we can get. I am not
convinced that Mutual Assured Destruction is the most intelligent
behavior we can come up with. It's clear the planetary population can
benefit from help in the management of complexity, and it is difficult
for me to imagine a goal more relevant than improving the chances for
survival by increasing our ability to act intelligently.
However, no machine yet thinks nearly as well as a human, let alone
better. I wouldn't trust any computer I know to babysit my child, or
my country. Why? Machines don't understand! Anything! The reason
for this poor performance is an inadequate paradigm of human intelligence.
The Physical Symbol System Hypothesis does not in fact account for human
intelligent behavior.
Parenthetically, there's no more excitement in symbol-processing computers;
that's what digital computers have been doing right along, taking the
symbol for two and the symbol for two, performing the defined operation
"ADD" and producing the symbol for four. We may have lost interest in
analog systems prematurely.
Manipulation of symbols is insufficient by itself to duplicate human
performance; it is necessary to treat the perceptions and experiences the
symbols *symbolize*. Put a symbol for red and a symbol for blue in a pot,
and stir as you will, there will be no trace of magenta.
I have developed a large suite of ideas concerning symbols and
representations, analog and digital "computing", induction and
deduction, natural language, consciousness and related concepts which
are inextricably intertwined and somewhat radical, and the following
is necessarily a too-brief introduction. But maybe it will supply
some fuel for discussion.
Definition of terms: By intelligence, I mean intelligent behavior;
intelligent is an adjective describing behavior, and intelligence is a name
for the ability of an organism to behave in a way we can call intelligent.
Symbols and representations: There are two quite distinct notions denoted
by *symbolize* and *represent*. Here is an illustration by example:
Voodoo dolls are intended as symbols, not necessarily as faithful images
of a person. A photo of your family is representative, not symbolic. A
picture of Old Glory *represents* a flag, which in turn *symbolizes* some
concepts we have concerning our nation. An evoked potential in the visual
cortex *represents* some event or condition in the environment, but does
not *symbolize* it.
The essence of this notion of symbolism is that humans can associate
phenomena "arbitrarily"; we are not limited to representations. Any
phenomenon can "stand for" any other. That which any symbol symbolizes
is a human experience. Human, because we appear to be the only symbol
users on the planet. Experience, because that is symbolism's ultimate
referent, not other symbols. Sensory experience stops any recursion.
Noises and marks "symbolize" phenomenological experience, independent of
whether those noises and marks are "representative".
Consciousness: Consciousness is self-consciousness; you aren't conscious
of your environment, you are conscious of your perceptions of your
environment. Sensory neurons synapse in the thalamus. From there,
neurons project to the cortex, and from the cortex, other neurons project
back to the thalamus, so there, in associative contiguity, lie the input
lines and reflections of the results of the perceptive mechanisms. The
brain has information as to the effects of its own actions. Whether it is
resident in thalamic neurons or distributed throughout the brain mass, that
loop is where YOU are, and life experience builds your identity; that hand
is part of YOU, that hammer is not. One benefit of consciousness is that
it extends an organism's time horizon into the past and the future,
improving its chance for survival. Consciousness may be necessary for
symbol use.
Natural language: Words, spoken or written, are *symbols*. But human
natural language is not a symbol system; there are no useful interactions
among the symbols themselves. Human language is evocative; its function
is to evoke experiences in minds, including the originating mind. Words
do not interact with each other; their connotations, the evoked responses
in human minds interact with each other. Responses are based on human
experience; touch, smell, vision, sound, emotional effects. Communication
between two minds requires some "common ground"; if we humans are to
communicate with the minds we create, we and they must have some
experiential "common ground". That's why no machine will "really
understand" human natural language until that machine can possess the
experiences the symbols evoke in humans.
Induction and deduction: Induction, as defined here, consists in the
cumulative effect of experience on our behavior, as implemented by neural
structures and components. Induction is the effect on an organism's
behavior; not a procedure effected by the organism. That is to say, the
"act" of induction is only detectable through its effects. All living
organisms' behavior is modified by experience, though only humans seem
to be self-aware of the phenomenon. Induction treats *representations*,
rather than *symbols*; the operation is on *representation* of experience,
quite different from symbolic deduction.
Deduction treats the *relationships among symbols*, that which Hume
described as "Relations of Ideas". There is absolute certainty concerning
all valid operations, and hence the resulting statements. The intent is
to manipulate a specific set of symbols using a specific set of operations
in a mechanical way, having made the process sufficiently explicit that we
can believe in the results. But deduction is an operation on the *form*
of a symbol system; a "formal" operation, and deliberately says nothing at
all concerning the content. Deductive, symbolic reasoning may be the
highest ability of humans, but there's more to minds than that.
Analogy: One definition of analogy is as the belief that if two objects or
events are alike in some observed attributes they are alike in other,
unobserved, attributes. It follows that the prime requisite for analogy
is the perception of "similarity". It could be argued that the detection
of similarity is one of the most basic abilities an organism must have to
survive. Similarity and analogy are relationships among *representations*,
not among *symbols*. Significant similarities, (i.e. analogy and metaphor)
are not to be found among the symbols representing mental perceptions, but
among the perceptions themselves. Similarity is perceived among
experiences, as recorded in the central nervous system. The mechanism is
that symbols evoke, through association, the identical effects in the
nervous system as are evoked by the environmental senses. Associative
memory operates using sensory phenomena; that is, not symbols, but *that
which is symbolized* and evoked by the symbols. We don't perceive
analogies between symbols, but between the experiences the symbols evoke
in our minds.
Analog and digital: The physical substrate supporting intelligent behavior
in humans is the central nervous system. The model for understanding the
CNS is the analog "gadget" which "solves problems", as in A. K. Dewdney's
Scientific American articles, not Von Neumann computers; nor symbol
systems of any kind. The "neural net" approaches look promising, if they
are considered to be modifiable analog devices, rather than alternative
designs for algorithmic digital computers.
Learning and knowledge: Learning is inductive; by definition the addition
of knowledge. "Deductive logic is tautological"; i.e. implications of
present knowledge can be made explicit, but no new knowledge is introduced
by deductive operations. There is no certainty with induction, though:
"And this kind of association is not confined to men; in
animals also it is very strong. A horse which has been
often driven along a certain road resists the attempt to
drive him in a different direction. Domestic animals
expect food when they see the person who usually feeds them.
We know that all these rather crude expectations of
uniformity are liable to be misleading. The man who has
fed the chicken every day throughout its life at last
wrings its neck instead, showing that more refined views
as to the uniformity of nature would have been useful to
the chicken."
[Bertrand Russell. 1912. "On Induction", Problems of Philosophy.]
Thinking systems will be far too complex for us to construct in "mature"
form; artificial minds must learn. Our most reasonable approach is to
specify the initial conditions is terms of the physical implementation
(e.g., sensory equipment and pre-wired associations) and influence the
experience to which a mind is exposed, as with our children.
What is meant by "learning"? One operational definition is this: can you
apply your knowledge in appropriate ways? Some behavior must be modified.
All through your childhood, all through life, your parents and teachers
are checking whether you have learned something by asking you to apply it.
As a generalization of applying, a teacher will ask if you can re-phrase
or restate your knowledge. This demonstrates that you have internalized
it, and can "translate" from internal to external, in symbols or in modified
behavior. Language to internalized, and back to language... if you can
do this, you "understand".
Knowledge is the state of the central nervous system, either built in or
acquired through experience. Experience is recorded in the CNS paths which
"process" it. Recording experience essentially in the same lines which
sense it saves space and totally eliminates access time. There is no
retrieval problem; re-evocation, re-stimulation of the sensory path is
retrieval, and that can be done by association with other experience, or
with symbols.
That's probably enough for one shot. Except to say I think the time
is ripe for trying some of these ideas out on real machines. A few years
ago there was no real possibility of building anything so complex as a
Connection Machine or a million-node "neural net", and there's still no
chance at constructing something as complex as a baby, but maybe there's
enough technology to build something pretty interesting, anyway.
Ray
------------------------------
End of AIList Digest
********************
∂18-Feb-87 0052 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #45
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 18 Feb 87 00:51:57 PST
Date: Tue 17 Feb 1987 21:52-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #45
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 18 Feb 1987 Volume 5 : Issue 45
Today's Topics:
Queries - Window System & And/Or Graphs & Organic Microchips &
OPS5 in Standard/Cambridge Lisp & Lisp Sources for OPS5 &
Legal Reasoning & Parallel Functional Programming Languages,
AI Tools - DEC AI Workstation & Common LISP
----------------------------------------------------------------------
Date: Thu, 12 Feb 87 12:15:49 MEZ
From: ZZZO%DHVRRZN1.BITNET@wiscvm.wisc.edu
Subject: Window System
Date: 12 February 1987, 12:07:58 MEZ
From: Wolfgang Zocher (0511) 762-3684 ZZZO at DHVRRZN1
To: AILIST at SRI-STRIPE
I'm looking for an powerful window-system written in LISP (pref. Commonlisp)
to support an object-oriented KR-System (TLC-LISP on IBM PC/AT). My major
task is the devellopment of KR; windows are only needed for better demon-
stration... So, I would like public domain sources.
Wolfgang Zocher
zzzo@dhvrrzn1.bitnet
------------------------------
Date: Thursday, 12 February 1987 17:10:44 EST
From: Kenneth.Goldberg@a.gp.cs.cmu.edu
Subject: And/Or graphs
Two queries concerning And/Or graphs (as opposed to trees):
1) Has anyone published a thorough survey of And/Or graph search algorithms?
2) What is the convention regarding And-nodes? Nilsson (Prob. Solving
Methods in AI, pp. 87-88) labels those with incoming And-links
as And-nodes. Winston (AI, p. 148) and Pearl (Heuristics, p. 25)
labels those with outgoing And-links as And-nodes. More importantly,
is there a convincing argument for either one?
------------------------------
Date: 12 Feb 87 22:26:26 GMT
From: gorin@MEDIA-LAB.MIT.EDU (Amy Gorin)
Subject: organic microchips
if anybody has any information regarding organic systems for use in ai and
computers in general,and especially the work of :
Arieh Aviram and Philip Seiden of IBM
Mark ratner of Northwestern
Robert Metzger and Charless Panetta of U of Miss.
Forest L. Carter, Naval Research Lab
Pichart Potember , John's Hopkins
Tim Posten and F. Eugene Yates, UCLA
Please let me know (recent papers and articles, etc.)
Thanks,
* ARPA: gorin@media-lab.media.mit.edu * It's not who you know, *
* UUCP: mit-eddie!mit-amt!gorin * it's whom you know *
------------------------------
Date: 15 Feb 87 19:58:50 GMT
From: husc2!chabris@husc6.harvard.edu (chabris)
Subject: OPS5 in Standard/Cambridge Lisp?
I have the OPS5 source code in Franz Lisp and Common Lisp (as posted in the
AI Forum on Compuserve) and am interested in porting it to Cambridge Lisp.
Does anyone know if this has already been done, or if there is any OPS5 source
in either Standard Lisp or Portable Standard Lisp, the ancestor dialects of
Cambridge Lisp? Thank you very much.
--
===============================================================================
Christopher F. Chabris Contributing Editor, START Magazine, Antic Publishing
[Dunster F-61, Harvard University, Cambridge, MA, 02138 (617) 498-2239]
[Permanent: 15 Sterling Road, Armonk, NY, 10504 (914) 273-8828]
ARPAnet: chabris@husc4.harvard.edu Compuserve: 73277,305
UUCP: ...harvard!husc4!chabris Bitnet: chabris@harvunxu
===============================================================================
------------------------------
Date: 17 Feb 87 20:12 AST
From: AXDRW%ALASKA.BITNET@wiscvm.wisc.edu
Subject: Lisp Sources for OPS5
Hello, I have been asked to look for the Lisp source to OPS5.
Does anyone out there know of where I might get this? I would
perfer a net address if possible. Please EMAIL your responses
directly to me. Thank you
Don R Withey BITNET: AXDRW@ALASKA.BITNET
University of Alaska BIX: dwithey
3221 UAA Drive
Anchorage, Alaska 99508
907-786-4851 (work) 907-277-9063 (home) 907-274-6378 (other home)
Any expressed opinion is my own, and in no way represent those of my employer,
the University of Alaska.
------------------------------
Date: Sun, 15 Feb 87 22:44:17 est
From: mayerk@eniac.seas.upenn.edu (Kenneth Mayer)
Subject: Legal reasoning
Could someone give some pointers into the literature about legal
reasoning. Or better yet, someone you know whom I could contact.
Ken
/|---------------------------------------------------------------|\
/ | ARPA: mayerk@eniac.upenn.seas.EDU | \
| | USnail: Kenneth Mayer | |
| | University of Pennsylvania, Moore School of Eng.| |
- | 305 S. 41st St | -
| | Philadelphia, PA 19104 | |
| | GENIE: MAYERK | |
\ | CIS: [73537,3411] | /
\|---------------------------------------------------------------|/
"It's a sky-blue sky, "The future is a place,
Satellites are out tonite, About 70 miles east of here,
Let X = X..." Where it's lighter..."
------------------------------
Date: 17 FEB 87 18:53 GMT
From: U06Q%CBEBDA3T.BITNET@wiscvm.wisc.edu
Subject: Parallel Functional Programming Languages
Hello out there,
I'm looking for books, papers news etc. about parallel functional
programming languages and especially about possibilities to
parallelize LISP (garbage collection, memory management etc). Is there
anyone out there, who has some experience with that subject or who
knows someone, who has experiences. I would be glad to receive book
titles or to receive addresses of people, who are interested in that
subject.
My network address: U06Q@CBEBDA3T.BITNET
thanks a lot Rene Rehmann
Dep. of computer science
University of Berne
Switzerland
------------------------------
Date: Thu, 12 Feb 87 08:49:03 EST
From: yerazuws@csv.rpi.edu (Crah)
Subject: Re: DEC AI Workstation
In article <8702120856.AA22369@ucbvax.Berkeley.EDU>, DON@atc.bendix.com writes:
> .... Of particular interest to me are
> remarks from people who have used the DEC workstation and one of the
> standard Lisp workstations (XEROX, Symbolics, LMI, TI, Sun, Apollo).
>
First the disclaimer - I've worked for DEC over two summers now, and am
hoping to work there permanently. However, the opinions below are
(I believe) not significantly influenced by that- and I'm also a
stockholder in Symbolics, so *there* :-)
I've worked with 3600's, SUNs and AI VAXstations.
The Symbolics used to be unquestionably superior- now I'm not
so sure. Release 7 of Symbolics not only has proprietary code (and new
microcode _again_), but now there are two different LISPS (Zeta and Common)
and you have to be careful which LISP window you're typing at. The
Symbolics also carry hefty price tags. The color display is a separate
monitor- which takes up a good chunk of space. The tools are great, however.
Window Debugger (c-m-W) is still unmatched elsewhere.
I wouldn't bother with the SUN, especially in a diskless
configuration. I wasted (yes, wasted) nine months trying to develop
an architecture simulator on Sun 2's. Little things like a server
being slow can completely hang your LISP and your editor - so you sit.
And sit. And forget what you were doing...
The problem is that when you page on a diskless SUN, you generate I/O
requests at a HUGE rate compared to normal file I/O. Hence, a server
which is only mildly busy as seen by fileio users is essentially locked
up as far as the LISP user is concerned. I don't know if adding huge
amounts of memory would help the SUN or not... but see the comments
under "memory" below.
Just so you understand HOW bad diskless SUN's are- We switched
from the SUN workstations to a heavily loaded 4.2 BSD /780 and found
that we were getting about ten times as much work done- even though
we were sharing the machine with twenty other people.
Now, the AI VAXstation. I like it a lot. I've got the simulator
running (in LISP), the compiler for it (a LISP compiler, in LISP, with chunks
migrating into OPS5), and most of my thesis written (in TeX). I've got
C when I want to do C-like things, and FORTRAN when that's appropriate.
I only have the black and white scope- but the color scope is usable
without needing a b/w scope also.
The LISP on VAXstations can do graphics, too. Very cleanly.
I don't bother with the LISP Language Sensitive Editor, having
been addicted to EMACS for so long. Sorry, can't help you there.
Suggestion- if you buy the VAXstation, get lots of memory.
Five megs is not enough if you have a LISP, three EMACSes and a DCL and are
using them all- the LISP will thrash when you gc. Get nine megs (the
one meg that comes on the CPU card, plus an eight-meg card) and you'll
GC in about six seconds- which is much better than the Symbolics'
time of ONE HOUR or more. I don't know if going to 16 megs (max addressable
in a MicroVAX II) would improve anything- my system rarely pages at
all in the above LISP/EMACS/DCL load configuration.
I had Ultrix and Xwindows up for a while instead of DCL; I liked
UIS better than X, so I accepted the DCL as part of the package. Besides
there's a shell around somewhere....
Disclaimer repeated: I have been and hope again to be an employee of
DEC. I am a stockholder of record in Symbolics, Inc. My best drinkin'
buddy works for SUN Microsystems.
-Bill Yerazunis
------------------------------
Date: 13 Feb 87 22:01:14 GMT
From: brothers@topaz.rutgers.edu (Laurence R. Brothers)
Subject: Re: Against the Tide of Common LISP
The fun thing about common lisp, though, is that any given little
utility function you care to write probably already exists.... I was
working on a project last year that caused me to want to resize an
array - I wrote the little routine, then something caused me to look
in the arrays section of Steele, and -- lo and behold -- resize-array
(or something like that).
--
Laurence R. Brothers
brothers@topaz.rutgers.edu
{harvard,seismo,ut-sally,sri-iu,ihnp4!packard}!topaz!brothers
"I can't control my fingers -- I can't control my brain -- Oh nooooo!"
------------------------------
End of AIList Digest
********************
∂19-Feb-87 0222 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #46
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 19 Feb 87 02:22:41 PST
Date: Wed 18 Feb 1987 21:51-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #46
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 19 Feb 1987 Volume 5 : Issue 46
Today's Topics:
Seminars - A Juggling Robot (SU) &
Evaluating Data-Intensive Logic Programs (Rutgers),
Meetings - Mid-Atlantic Universities Regional AI Meeting &
Midwest AI and CogSci Society,
Conferences - Workshops on Database Programming Languages&
Change in Cognitive Science Conference,
Course - 2nd European Advanced Course in Artificial Intelligence
----------------------------------------------------------------------
Date: 12 Feb 1987 1354-PST (Thursday)
From: Grace Schmidt <schmidt@pescadero.stanford.edu>
Subject: Seminar - A Juggling Robot (SU)
CS 500 Computer Science Colloquium
Feb. 17, 4:15 pm, Skilling Auditorium
A Juggling Robot - Adventures in Real Time Control
by
Marc D. Donner
IBM, T.J. Watson Research Center
The computer community has generally addressed real-time control
problems in an ad-hoc fashion using tools designed for information
processing. In information processing the important issue is
ensuring that the correct calculations are carried out in the correct
order. In real-time problems there are deadlines that require that
the calculations be completed before a certain time to be correct.
This class of problems is interesting and is becoming more and more
important as we increasingly use computers to control things and not
just for information processing. In this talk I will describe work
in real-time control at the Thomas J. Watson Research Center in
Yorktown Heights and in particular, the juggling machine that we are
constructing as a testbed for our ideas. This talk will cover the
engineering of the machine, the design and construction of
programming languages and operating systems for real-time control,
and interesting problems in the mathematics of juggling.
------------------------------
Date: 16 Feb 87 02:38:15 EST
From: KALANTARI@RED.RUTGERS.EDU
Subject: Seminar - Evaluating Data-Intensive Logic Programs (Rutgers)
RUTGERS COMPUTER SCIENCE AND RUTCOR COLLOQUIUM SCHEDULE - SPRING 1987
Computer Science Department Colloquium :
Here is summary of speakers:
Date(Feb), Time, Place(Hill), Speaker Title
18, 9:50 ,705, Raghu Ramakrishnan,EVALUATING DATA INTENSIVE LOGIC PROGRAMS
18, 4:30, 525, Allan Borodin,Parallel Complexity of Algebraic Problems
19, 2:50, 705, Victor Pan, Parallel Nested Dissection for Path Algebra
Computations
20, 2:50, 705, Ben Cohen, "Knowledge-Based CAD-CAM Software Integration."
DATE : Wednesday, February 18
SPEAKER: Raghu Ramakrishnan
AFFILIATION: University of Texas at Austin
TITLE: EVALUATING DATA INTENSIVE LOGIC PROGRAMS
TIME: 9:50
PLACE: Hill 705
ABSTRACT
There has been considerable interest recently in the problem of
evaluating @u[logic queries] against relational databases. The
evaluation methods that we consider rely upon @i[bottom-up fixpoint
computation], which, unlike Prolog's depth-first strategy, is
@i[complete]. These methods also take advantage of efficient database
join techniques. The major criticism of such methods is that they do
not fully utilize the constants in the query to restrict the search
space, and thus perform unnecessary computation. Such constants are
used by Prolog through a process of @i[sideways information passing],
since variable bindings generated in solving a goal restrict the
search space in solving subsequent goals.
We define @i[sideways information passing] formally. Given a program,
we show that any sideways information passing strategy may be
implemented by rewriting the program and evaluating the rewritten
program bottom-up, thus answering the above criticism. We describe
several rewriting algorithms, generalizing some of the bottom-up
methods described in the literature - Magic Sets, Counting, and their
variants - to work with arbitrary logic programs. We also present the
results of a performance analysis which provides some insight about
the relative cost of these methods.
------------------------------
Date: Fri, 13-FEB-1987 13:11 EST
From: MILLER%VTCS1.BITNET@wiscvm.wisc.edu
Subject: Meeting - Mid-Atlantic Universities Regional AI Meeting
********************Mid-Atlantic Regional AI Meeting********************
The first annual meeting of AISMAS (the AI Society of the Mid-Atlantic
States) will be held at Virginia Tech in Blacksburg, Virginia on March 6
and 7. The meeting will include a keynote speech by Prof. Gerry Dejong
of the University of Illinois, panels on the value and capabilities of
expert systems and AI architectures, and graduate student presentations
of current research. As a special inducement towards graduate student
attendance/participation, there will be free doughnuts and coffee, and
no registration fee.
Below is a preliminary schedule of the AISMAS meeting:
Friday, March 6 Saturday, March 7
8:00pm Keynote speech: 8:30am Grad Student presentations
Prof Gerry Dejong, U. of Ill. 10:00am Coffee Break
9:30pm Reception 10:15am Panel
"What Expert Systems Can't Do"
11:15am Grad Student presentations
12:00 Lunch & program demos
1:30pm Grad Student presentations
3:00pm Coffee Break
3:15pm Panel
"Special AI Architectures"
4:15pm Grad Student presentations
5:00pm AISMAS Business Meeting
If you are doing AI research and in the Mid-Atlantic region (or near the
Mid-Atlantic region and don't mind a longish trip) then your attendance
and/or participation is encouraged. For more information about AISMAS
contact your local AISMAS coordinator or
Prof. David Miller
Dept of Computer Science, Virginia Tech
(703) 961-5605
miller%vtcs1@bitnet-relay.arpa
This year's meeting is sponsored by the Automation and Robotics Project
at the Jet Propulsion Laboratories and the Virginia Tech Department of
Computer Science.
------------------------------
Date: Mon, 16 Feb 87 10:44:51 CST
From: Kris Hammond <kris%gargoyle.uchicago.csnet@RELAY.CS.NET>
Subject: Meeting - Midwest AI and CogSci Society
The First Annual Meeting
of
The Midwest Artificial Intelligence
and
Cognitive Science Society
April 24th and 25th
University of Chicago
Department of Computer Science
Call for Abstracts
Deadline: March 20th.
MAICSS is a new organization designed to promote interaction between
AI and Cognitive Science groups in the Midwest. Its activity is
centered around an annual meeting including talks by both faculty and
students. The first meeting is scheduled for April 24th and 25th at
the University of Chicago.
The emphasis in student talks is work in progress. The idea is to air
new work at a time when feedback will be most helpful. Submissions
for these talks will take the form of short abstracts (about 3 pages).
Each submission should include three copies of the abstract, each with
a title page including name, address and affiliation. The deadline
for abstracts is March 20th, 1987.
There is no registration fee, but we ask that anyone interested in
attending please contact us so we can get a correct head count.
Send submissions and inquires to:
Kristian Hammond
Department of Computer Science
University of Chicago
1100 East 58th Street
Chicago, IL 60637
Any questions can be sent to me via E-mail addressed to:
kris@uchicago.csnet --- for CSnet mail.
kris%uchicago.csnet-relay.arpa --- for ARPA mail.
------------------------------
Date: Sun, 15 Feb 87 15:57:49 EST
From: Peter Buneman <Peter@cis.upenn.edu>
Subject: Conference - Workshops on Database Programming Languages
Workshops on Persistent Object Systems and
Formal Aspects of Database Programming Languages.
Two workshops on these topics are to take place this summer in Europe
immediately before and after VLDB.
The first, to be held on the West coast of Scotland, August 25-28, will
focus on the design and implementation of persistent object systems.
The second, in Finistere, France, Sept 7-10, will discuss the relationship
between the semantics of databases an programming languages as it appears in
data types and data models, object oriented programming, logic programming,
higher-order relations etc.
The purpose of both workshops is to encourage informal discussions among
researchers in these areas and presentations of current research.
Attendance at these workshops is limited and will be decided on the basis
of abstracts.
For more information, send mail to one of the following addresses.
In the US:
Peter Buneman Rishiyur Nikhil
CIS, Moore School/D2 Labporatory for Computer Science
University of Pennsylvania Massachusetts Institute of Technology
Philadelphia, PA 19104 545 Technology Square
(Peter@cis.upenn.edu) Cambridge MA 02139
(Nikhil@xx.lcs.mit.edu)
In Europe:
Francois Bancilhon Malcolm Atkinson
INRIA Department of Computing Science
BP 105 University of Glasgow
78153 Le Chesnay Cedex Glasgow, G12 8QQ
France Scotland
(bancilhon@inria.uucp) (mpa@cs.glasgow.ac.uk)
------------------------------
Date: Sun, 15 Feb 87 22:52:48 PST
From: levin@CS.UCLA.EDU
Reply-to: levin@CS.UCLA.EDU (Stuart Levine)
Subject: Conference - Change in Cognitive Science Conference
I have been asked to post this by Prof. Earl Hunt.
Note that there are two changes to the original: a new
submission deadline, and info on camera-ready papers.
Cognitive Science Society
Announcement of Meeting and Preliminary call for Papers
The Ninth Annual Conference of the Cognitive Science Society will be held
on July 16-18, 1987 at the University of Washington. The dates have been
chosen to allow people to attend this conference and the conference
of the American Association for Artificial Intelligence, which meets in
Seattle earlier in the week. The conference will feature symposia and
invited speakers on the topics of mental models, educational and indus-
trial applications of cognitive science, discourse comprehension, the
relation between cognitive and neural sciences, and the use of connec-
tionist models in the cognitive sciences. The conference schedule will
include paper sessions and a poster session, covering the full range
of the cognitive sciences. The proceedings of the conference will be
published by L Erlbaum Associates.
Submitted papers are invited. These should cover original, unreported
work, research or analysis related to cognition. All submissions for
paper and poster sessions will be refereed.
All submitted papers and posters must include the following:
Author's name, address, and telephone number.
Set of four or fewer topic area keywords.
Four copies of the full paper (4000 words maximum) or poster
(2000 words maximum). Each copy should include a 100-250
word abstract.
Indication of preference for paper or poster session.
All papers MUST adhere to the following rules for preparation of
camera-ready copy. NOTE: Papers will NOT be sent back after
acceptance for modification. The accepted paper will be sent
directly to the publisher.
1 inch margins on both sides, top, and bottom.
Single spaced text. Figures centered on type page at
top or bottom.
Titles and author's names and institutions centered at
top of first page.
One line between title heading and text.
Use American Psychological Association publication format.
Authors are responsible for obtaining permission to reprint
published material.
Send submissions to Earl Hunt, Department of Psychology,
University of Washington, Seattle, Wa 98195
Submissions are due by MARCH 16, 1987. NOTE NEW DATE
All members of the Cognitive Science society will receive a further
mailing discussing registration, accommodation, and travel.
------------------------------
Date: Mon, 16 Feb 87 18:58:56 +0100
From: aamodt%vax.runit.unit.uninett@NTA-VAX.ARPA
Subject: Course - 2nd European Advanced Course in Artificial
Intelligence
ACAI-87
ECCAI's 2nd Advanced Course in Artificial Intelligence
July 28 to August 7, 1987
Oslo, Norway
Organizer: NAIS - Norwegian Artificial Intelligence Society
Chairman : Rolf Nossum, Computas Expert Systems, N-1322 Hovik
The European Coordinating Committee for Artificial Intelligence (ECCAI)
organizes biannual Avanced Courses in Artificial Intelligence. This
years course is the second of its kind, following the one held in
Vignieu, France, 1985.
Despite the spectrum of scientific activities in Artificial Intelligence
research, covering such diverse domains as Knowledge Representation,
Learning, Natural Language, Robotics, Vision, Program Synthesis, Automated
Reasoning, AI-oriented Programming, there exists a common core of methods
and techniques for Symbolic Information Processing.
This common formal basis will be treated in depth during the course, and
the use of general as well as special techniques in some selected subfields
of AI will be the main emphasis.
ACAI-87 will not be an introductory course in AI, but is intended to meet
the needs of researchers and practitioners in the field.
TOPICS LECTURERS
Inference methods WOLFGANG BIBEL , Germany
Machine Learning ALAN BIERMAN , USA
Expert Systems Methodology WILLIAM CLANCEY , USA
Qualitative Reasoning TONY COHN , England
Natural Language JENS-ERIK FENSTAD, Norway
Parallell and Rewriting Systems PHILLIPPE JORRAND, France
AI Planning SAM STEEL , England
Knowledge Acquisition BOB WIELINGA , Holland
Fee: Appx. $900 (900 ECU). This covers accomodation, meals and course
material.
Interested? For more information, please write to:
ACAI-87
P.O. Box 5030 Majorstua
N-0301 OSLO 2
N o r w a y
Specific questions may be sent to the network address below.
DEADLINE FOR APPLICATION IS MARCH 1, 1987 !
Sent by: <aamodt%vax.runit.unit.uninett@nta-vax.arpa>
Agnar Aamodt, Knowledge Engineering Laboratory
SINTEF-RUNIT, University of Trondheim, N-7034 Trondheim-NTH
------------------------------
End of AIList Digest
********************
∂19-Feb-87 1553 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #47
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 19 Feb 87 15:53:05 PST
Date: Wed 18 Feb 1987 21:56-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #47
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 19 Feb 1987 Volume 5 : Issue 47
Today's Topics:
Queries - ISTEL's See Why & Quintus Computer Systems,
Cognitive Science - Re: Learing about AI,
Games - GO Program on PC (MAC),
AI Tools - Rochester Connectionist Simulator,
Book - Knowledge Systems and Prolog
----------------------------------------------------------------------
Date: Wed, 18 Feb 87 19:12 EST
From: Troy Shinbrot <900380%UMDD.BITNET@wiscvm.wisc.edu>
Subject: ISTEL, see why
I am interested in comments from anyone who has experience with or
information regarding ISTEL corporation's "See Why" system. It is apparently
a Fortran (!) based simulation system with somewhat vague specifications.
Thanks in advance.
- Troy Shinbrot (aka 900380@umdd.bitnet)
------------------------------
Date: 18 Feb 87 09:47:29 +1000 (Wed)
From: "ERIC Y.H. TSUI" <decvax!mulga!aragorn.oz!eric@decwrl.DEC.COM>
Subject: Query - Quintus Computer Systems
Has anyone has experience in using Quintus Prolog in Xerox (or other AI)
workstation ?
Does anyone have information about whether Quintus Computer Systems
has a node on the network or not ?
Appreciate any useful information on the above questions.
Eric Tsui eric@aragorn.oz
------------------------------
Date: 16 Feb 87 16:52:00 GMT
From: necntc!adelie!mirror!gabriel!inmet!sebes@husc6.harvard.edu
Subject: Re: Learing about AI
Ted Inoue's description of an interdisciplinary effort is
essentially a description of cognitive science. I have two
points to add to what he said:
1) such an interdisciplinary effort is not new, and has
been going on for decades in some circles; it is only
now that a broader awareness of the field as a field
is developing
2) Ted's assessments of the various fields that can contribute
to cognitve science is rather simplistic and harsh. I think,
as many would agree, that each feild has importamt thigns to offer.
Also, there can be varying combinations of the fields for various
subjects of inquiry. For example, Stanford's Center for the Study
of Language and Information is composed mostly of linguists,
computer scientists (both academic and professional), and
philosophers; in fact, the philosophers run the show.
For further elaboration of these points, I recommend the
introduction and first chapter of Martin Gardners's _The Mind's
New Science_.
-John Sebes
------------------------------
Date: 18 Feb 87 08:31:00 EST
From: "CLSTR1::BECK" <beck@clstr1.decnet>
Reply-to: "CLSTR1::BECK" <beck@clstr1.decnet>
Subject: GO PROGRAM ON PC (MAC)
I BELIEVE THERE WAS AN INQUIRY AS TO GO PROGRAMS ON PCS.
I HAVE NOT USED THIS PROGRAM BUT PLAN TO SOMETIME THIS SPRING.
Date: Sat, 7 Feb 87 01:23:36 PST
From: <LOGANJ@byuvax.bitnet>
Reply-to: LOGANJ%BYUVAX.BITNET@forsythe.stanford.edu
Subject: Go program, v1.0b2
This is version 1.0B2 of the Go program for the Macintosh. This
file is about 137,XXX bytes long. When unhexed it is 98.5K bytes.
Recent improvements to the program are as follows:
- You can now set the baud rate and other modem port characteristics
from within the program, for playing games between two Macs. If
you play through modems over telephone lines, for example, you can
communicate by typing on the keyboard - a line of text is sent to
the opponent when you hit the return key.
- The program will give a short analysis of a board position, showing
the number of primary liberties (max about 8), number of secondary
liberties (max 8), and the result of a simple ladder.
- The program will now display the "Reasons for Computer Moves".
Other recent improvements include more reasonable end of game scoring
and the ability to add symbols to handicap stones.
I have tested the communications between two Macs and it seems to work
okay.
This is public domain, so you may give it to friends and post to
bulletin boards.
Regards,
Jim
[
archived as [SUMEX-AIM.Stanford.EDU]<INFO-MAC>GAME-GO.HQX
DoD
]
..............................
POSTED TO AI BY <BECK@ARDEC-LCSS>
..............................
------------------------------
Date: Tue, 17 Feb 87 22:27:57 -0500
From: goddard@rochester.arpa
Subject: Rochester Connectionist Simulator release in April
In mid-April we will be releasing a much improved version of the simulator.
The Rochester simulator allows construction and simulation of arbitrary
networks with arbitrary unit functions. It is designed to be easily
extensible both in unit structures and user interface, and includes a facility
for interactive debugging during network construction. The simulator is
written in C and currently runs here on Suns, Vaxen and the BBN Butterfly
multiprocessor (and should run on any UNIX machine). There is a graphics
interface package which runs on a Sun under suntools, and is primarily
designed for interactive display of the flow of activation during network
simulation. The simulator is easy to use for novices, and highly flexible
for those with expertise.
We are now collecting names and addresses of people and sites interested
in receiving a copy of the simulator when released in April. The preferred
method for dissemination is via electronic mail, but we will also send tape
and possibly disk copies. To get on the distribution list, send mail to
costanzo@cs.rochester.edu giving your name and addresses (both physical
and electronic). This address is for the distribution list ONLY, for other
questions see below. It is possible that there will be some kind of minimal
licensing agreement required, for a nominal fee.
There are many papers, journal articles and technical reports which give
an idea of the connectionist research and philosophy here at Rochester.
A complete list of these is in "Rochester Connectionist Papers: 1979-1985",
by Feldman, Ballard, Brown and Dell, Computer Science TR 172. For this or
any other technical report, write to:
Peggy Meeker
Department of Computer Science
University of Rochester
Rochester, NY 14627
The previous version of the simulator with some documentation is availible
immediately via electronic mail from me (see addresses below). However
you are advised to wait for the April release, as the documentation will be
much better. Any other questions about the simulator should also be addressed
to me.
Nigel Goddard
goddard@cs.rochester.edu
...!seismo!rochester!goddard
------------------------------
Date: 13 February 1987, 17:50:57 EST
From: Adrian Walker <ADRIAN@ibm.com>
Subject: book announcement - Knowledge Systems and Prolog
A new book which may be of interest to readers of AILIST--
KNOWLEDGE SYSTEMS AND PROLOG
A LOGICAL APPROACH TO EXPERT SYSTEMS
and
NATURAL LANGUAGE PROCESSING
Adrian Walker (Ed.), Michael McCord,
John F. Sowa, Walter G. Wilson
Addison-Wesley, 1987
This book introduces Prolog and two important areas of Pro-
log use-- expert systems and natural language processing
systems (together known as knowledge systems.) The book
covers basic and more advanced Prolog programming, describes
practical expert systems and natural language processing in
depth, and provides an introduction to the formal basis in
mathematical logic for the meaning of Prolog programs.
HIGHLIGHTS
y Presents significant examples of knowledge systems, with
useful parts of actual programs included.
y Describes important research results in expert systems,
natural language processing, and logic programming.
y Integrates many trends in knowledge systems by bringing
diverse representations of knowledge together in one
practical framework.
y Though useful with any Prolog implementation, provides
an introductory tutorial followed by advanced program-
ming techniques for IBM Prolog.
TABLE OF CONTENTS
Chapter 1. Knowledge Systems: Principles and Practice (Adrian Walker )
1.1 What is a Knowledge System?
1.2 From General to Specific, and Back Again
1.3 Prolog and Logic Programming
1.4 Knowledge Representation
1.5 Getting the Computer to Understand English
1.6 Some Trends in Knowledge Acquisition
1.6.1 Learning by Being Told
1.6.2 Learning by Induction from Examples
1.6.3 Learning by Observation and Discovery
1.7 Summary
Chapter 2. A Prolog to Prolog (John Sowa)
2.1 Features of Prolog
2.1.1 Nonprocedural Programming
2.1.2 Facts and Predicates
2.1.3 Variables and Rules
2.1.4 Goals
2.1.5 Prolog Structures
2.1.6 Built-in Predicates
2.1.7 The Inference Engine
2.2 Pure Prolog
2.2.1 Solving Problems Stated in English
2.2.2 Subtle Properties of English
2.2.3 Representing Quantifiers
2.2.4 Choosing a Data Structure
2.2.5 Unification: Binding Values to Variables
2.2.6 List-Handling Predicates
2.2.7 Reversible Predicates
2.3 Procedural Prolog
2.3.1 Backtracking and Cuts
2.3.2 Saving Computed Values
2.3.3 Searching a State Space
2.3.4 Input/Output
2.3.5 String Handling
2.3.6 Changing Syntax
2.4 Performance and Optimization
2.4.1 Choosing an Algorithm
2.4.2 Generate and Test
2.4.3 Reordering the Generate and Test
2.4.4 Observations on the Method
Exercises
Chapter 3. Programming Techniques in Prolog (Walter Wilson)
3.1 How to Structure Prolog Programs
3.1.1 Logic Programming Development Process
3.1.2 Declarative Style
3.1.3 Data Representation
3.1.4 Structuring and Verifying Recursive Programs
3.1.5 Control Structures
3.2 Techniques and Examples
3.2.1 Meta-level Programming
3.2.2 Graph Searching
3.2.3 Balanced Trees
3.2.4 Playing Games and Alpha-beta Pruning
3.2.5 Most-Specific Generalizations
3.3 Summary of Prolog Programming Principles
Exercises
Chapter 4. Expert Systems in Prolog (Adrian Walker)
4.1 Knowledge Representation and Use
4.1.1 Rules
4.1.2 Frames
4.1.3 Logic
4.1.4 Summary
4.2 Syllog: an Expert and Data System Shell
4.2.1 Introduction to Syllog
4.2.2 A Manufacturing Knowledge Base in Syllog
4.2.3 Inside the Syllog Shell
4.2.4 Summary of Syllog
4.3 Plantdoc
4.3.1 Using Plantdoc
4.3.2 The Plantdoc Inference Engine
4.3.3 Weighing the Evidence
4.3.4 Summary of Plantdoc
4.4 Generating Useful Explanations
4.4.1 Explaining Yes Answers, Stopping at a Negation
4.4.2 Explaining Yes and No Answers, Stopping at a Negation
4.4.3 Full Explanations of Both Yes and No Answers
4.5 Checking Incoming Knowledge
4.5.1 Subject-Independent Checking of Individual Rules
4.5.2 Subject-Independent Checking of the Knowledge Base
4.5.3 Subject-Dependent Checking of the Knowledge Base
4.6 Summary
Exercises
Chapter 5. Natural Language Processing in Prolog (Michael McCord)
5.1 The Logical Form Language
5.1.1 The Formation Rules for LFL
5.1.2 Verbs
5.1.3 Nouns
5.1.4 Determiners
5.1.5 Pronouns
5.1.6 Adverbs and the Notion of Focalizer
5.1.7 Adjectives
5.1.8 Prepositions
5.1.9 Conjunctions
5.1.10 Nonlexical Predicates in LFL
5.1.11 The Indexing Operator
5.2 Logic Grammars
5.2.1 Definite Clause Grammars
5.2.2 Modular Logic Grammars
5.3 Words
5.3.1 Tokenizing
5.3.2 Inflections
5.3.3 Slot Frames
5.3.4 Semantic Types
5.3.5 Lexical Look-up
5.4 Syntactic Constructions
5.4.1 Verb Phrases, Complements, and Adjuncts
5.4.2 Left Extraposition
5.4.3 Noun Phrases
5.4.4 Left-Recursive Constructions
5.5 Semantic Interpretation
5.5.1 The Top Level
5.5.2 Modification
5.5.3 Reshaping
5.5.4 A One-Pass Approach
5.6 Application to Question Answering
5.6.1 A Sample Database
5.6.2 Setting up the Lexicon
5.6.3 Translation to Executable Form
5.6.4 A Driver for Question Answering
Exercises
Chapter 6. Conclusions (Adrian Walker)
Appendix A. How to Use IBM Prolog (Adrian Walker & Walter Wilson)
A.1 A Simple Example
A.2 Detailed Programming of a Metainterpeter
A.3 Testing the Metainterpreter at the Terminal
A.4 VM/Prolog Input and Output
A.5 VM/Prolog and the VM Operating System
A.6 Tailoring VM/prolog
A.7 Clause Names and Modules
A.8 Types, Expressions, and Sets
A.9 MVS/Prolog
Appendix B. Logical Basis for Prolog and Syllog (Adrian Walker)
B.1 Model Theory Provides the Declarative View
B.2 Logical Basis for Prolog without Negation
B.3 Logical Basis for Prolog with Negation
B.4 Further Techniques for Interpreting Knowledge
Bibliography
Author Index
Subject Index
The book can be ordered direct from Addison-Wesley. In the
USA, phone 617-944-3700, ask for the Order Department, and
quote title, authors, and Order Number ISBN 09044.
Adrian Walker
IBM T.J. Watson Research Center
PO Box 704
Yorktown Heights
NY 10598
Tel: 914-789-7806
Adrian @ IBM.COM
------------------------------
End of AIList Digest
********************
∂22-Feb-87 0214 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #48
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 22 Feb 87 02:13:52 PST
Date: Sat 21 Feb 1987 23:06-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #48
To: AIList@SRI-STRIPE.ARPA
AIList Digest Sunday, 22 Feb 1987 Volume 5 : Issue 48
Today's Topics:
Scientific Method - Psycho-Physical Measurement
----------------------------------------------------------------------
Date: 15 Feb 87 05:40:19 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Psycho-Physical Measurement: Reply to Adam Reed
Adam V. Reed (adam@mtund.UUCP) at AT&T ISL, Middletown NJ USA, wrote
in support of the following position: Psychophysicists measure
conscious experience in the same sense that physicists measure
ordinary physical properties. Our senses and central nervous systems
are analogous to the physicist's measuring equipment. If we can assume
that this "mental" equipment is similar in all of us, then reports of
psychophysical "measurements" of private, conscious experiences are just
as objective as reports of physical measurements of physical phenomena,
and objective in the same sense (observer-independence).
I will attempt to show why this is incorrect. But first let me say
that there is really no reason for a psychophysicist to get embroiled
in the mind/body problem (or its "other-minds" variant). In cog-sci
there is a real empirical question about what processes and
performances are justifiably and relevantly mind-like, because it is
mental capacity (or at least its performance manifestations) that one
is attempting to capture and model. It MATTERS in cognitive modeling
whether you've really captured intelligence, or just a clever toy
(partial) look-alike. There is no corresponding problem in
psychophysics. The input/output charactersitics, detection
sensitivities, etc., of human observers have face validity as
displayed in their performance data. There is no empirical question
affecting the validity (as opposed to the interpretation) of the
data that depends on their being a measure of conscious experience
rather than merely human receiver I/O characteristics.
For simplicity I will focus on detection performance only, although the
same arguments could be applied to discrimination, magnitude judgment,
identification, etc.
If a subject reports when he detects the presence of a signal, and this
relation (signal/detection-report) displays interesting I/O regularities
(thresholds, detectabilities, criterial biases, etc.), those regularities
are indisputably objective in the same sense that the physicist's
(or engineer's) regularities are. The sticky part comes when one wants
to interpret the measurements and their regularities, not as they are
objectively -- namely input/output performance regularities of human subjects
under certain experimental conditions -- but as measurements of and
regularities in conscious experience.
Adam has an "intuition pump" in support of the latter interpretation:
He suggests that a subject can compute his own (say) detection
thresholds if he receives detection trials plus feedback as to whether
or not a stimulus was present. His only performance would be to
report, after a long series of trials and private calculations, what
his detection threshold was. Since everyone can in principle do this
for himself, it is observer-independent, and hence objective. Yet it
involves no overt behavior other than the final threshold report;
otherwise, it is exactly like a physicist performing an experiment in
the privacy of his lab, and then reporting the results, which anyone
else can then replicate in the privacy of his own lab. So surely the
measurement is not merely of behavioral regularities, but of conscious
experience.
There are many directions from which one can attack this argument:
(i) One could call into question the "lab" analogy, pointing out
that, in principle, two physicists could check each other's
measurements in the same "lab," whereas this is not possible in
one-man psychophysics.
(ii) One could question the objectivity of being both subject and
experimenter.
(iii) One could question whether the subject is performing a
"measurement" at all, in the objective sense of measurement;
only the psychophysicist is measuring, with the subject's receiver
characteristics under various input conditions being the object of
measurement. The subject is detecting and reporting.
(iv) One could point out that one subject's report of his
threshold is not subject-independently tested by another
subject's report of his own threshold.
(v) One could point out that intersubjective consensus hardly
amounts to objectivity, since all subjects could simply share the same
subjective bias.
(and so on)
These objections would all trade (validly) on what we really MEAN by the
objective/subjective distinction, which is considerably more than consensus
among observers. I will focus my rebuttal, however, on Adam's argument,
taken more or less on its own terms; I will try to show that it cannot lead
to the interpretation he believes it supports.
First, what work are the "covert calculations" really doing in Adam's
thought-experiment? What (other than the time taken and the complexity
of the task) differentiates a simple, one-trial detection-response from
the complex report of a threshold after a series of trials with feedback
and internal calculations? My reply is: nothing. Objectively speaking,
the normal trial-by-trial method and the long-calculation-with-feedback
method are just two different ways of making the same measurement of a
given subject's threshold. (And the only one doing the measuring in both
cases is the psychophysicist, with the data being the subject's input and
output. Not even the subject himself can wear both hats -- objective
and subjective -- at one time.)
So let's just talk about a simple one-trial detection, because it shares all
the critical features at issue, and is not complicated by irrelevant
ones. The question then becomes "What is the objectivity-status of
reports of single stimulus-detections from individual subjects?" rather
than "How observer-independent is the calculation of detection
thresholds after a series of trials with feedback?" The two questions
are equivalent in the relevant respects, and they share the same
weaknesses.
When a subject reports that he has detected a stimulus, and there was in
fact a stimulus presented, that's ALL there is, by way of data: Input
was the stimulus, output was a positive detection report. (When I say
"behavioral" or "performance" data, I am always referring to such
input/output regularities.) Of course, if I'm the subject, I know that
there's something it's "like" to detect a stimulus, and that the
presence of that sensation is what I'm really reporting. But that's
not part of the psychophysical data, at least not an objective part.
Because whereas someone else can certainly look at the same stimulus,
and experience the sensation for himself, he's not experiencing MY
sensation. I believe that he's experiencing the same KIND of
sensation. The belief is surely right. But there's certainly no
objective basis for it. Consider that no matter how many times the
same stimulus is presented to different subjects, and all report
detecting it, there is still no objective evidence that they're having
the same sensation -- or even that they're having any sensation at all.
It is the everyday, informal solution to this "other-minds" problem --
based on the similarity of other subjects' behavior to our
own -- that confers on us the conviction that they're experiencing
similar things with "similar equipment." But that's no objective basis
either.
Contrast this psychophysical detection experiment with a PHYSICAL
detection experiment. Suppose we're trying to detect an astronomic
effect (say, an "alpha") through a telescope. If an astronomer reports
detecting an alpha, there is the presumption -- and it can be tested,
and confirmed -- that another astronomer could, with similar equipment
and under similar conditions, detect an alpha. Not his OWN alpha, but
an objective, observer-independent alpha. This would not necessarily
be the self-same alpha -- only a token of the same type. Even
establishing that it was indeed an instance of the same generic type
could be done objectively.
But none of this carries over to the case of psychophysical detection,
where all the weight of our confidence that the sensation exists and is
of the same type is borne by our individual, subjective, intuitive solutions
to the every-day other-minds problem -- the "common"-sense-experience we all
share, if you will. I'm not, of course, claiming that this "common sense" is
likely to be wrong; just that it's unique to subjective phenomena and
does not amount to objectivity. Nor can it be used as a basis for
claiming that psychophysics "measures" conscious experience. Yes, we
all have subjective experience of the same kind. Yes, that's what
we're reporting when we are subjects in a psychophysical experiment.
But, no, that does not make psychophysical data into objective measures of
conscious experience. (In fact, "an objective measure of a subjective
phenomenon" is probably a contradiction in terms. Think about it.)
A third case is worth considering, because it's midway between the
physical and the psychophysical detection situation, and more like the
latter in the relevant respects: Unlike cognitive science, which is
concerned with active information-processing -- learning, memory,
language, etc. -- psychophysics is in many ways a calibration science:
It's concerned with determining our sensitivities for detection,
discrimination, etc. As such, it is really considering us in our
capacity as sensory devices -- measuring instruments. So the best
analogy would probably be the equivalent kind of investigation on
physical measuring devices. If what was at issue was not the
astronomer's objectivity in alpha detection but the telescope's, then
once again observer-independent conclusions could be drawn.
Comparisons between the telescope's sensitivity and that of other
alpha-detection devices could be made, etc. Here it would clearly be
the device's input/output behavior that was at issue, nothing more.
The same seems true of psychophysical detection. For although we all
know we're having sensations in a detection experiment, the only thing
that is being, or can be, objectively measured under such conditions
is our sensitivity as detection devices. Nor is more AT ISSUE in
psychophysics. In cog-sci, one can say of an input/output device that
purports to model our behavior: "But how do you know that's really
how I did it? After all, I can do much more (and I do it all consciously),
whereas all you have there is a few dumb processes and performances."
This is a real issue in cognitive modeling. (The buck stops at the TTT,
however, according to my account.) In psychophysics, on the other hand,
nobody is going to question the validity of a detection threshold because
there's no way to show that it's based on measuring consciousness rather
than mere input/output performance characteristics.
Before turning to Adam Reed's specific comments, let me reiterate that
this analysis is just as applicable, mutatis mutandis, to the more
complicated case of threshold calculation after a series of trials
with feedback. It's still a matter of input/output characteristics -- this
time with a long series of inputs, with instructions -- rather than
any "direct, objective measurement of experience." There's just no such
thing as the latter, according to the arguments I'm making.
[And I haven't even brought up the vexed issue of psycho-physical
"incommensurability," namely, that no matter how reliable our
psychophysical judgments, and how strong our conviction that they're
veridical in our own case, there is no OBJECTIVE measure on which to
equate and check the validity of the relation between physical stimulation
and sensation. Correlations between input and output are one thing -- but
between physical intensity and "experiential intensity"...?]
Adam writes:
> I don't buy the assumption that two must *observe the same
> instance of a phenomenon* in order to perform an *observer-independent
> measurement of the same (generic) phenomenon*. The two physicists can
> agree that they are studying the same generic phenomenon because they
> know they are doing similar things to similar equipment, and getting
> similar results. But there is nothing to prevent two psychologists from
> doing similar (mental) things to similar (mental) equipment and getting
> similar results, even if neither engages in any overt behavior apart
> from reporting the results of his measurements to the other. My point is
> that this constitutes objective (observer-independent) measurement of
> private (no behavior observable by others) mental processes.
Apart from the objections I've already made about the "similar
equipment" argument [what, by the way, is "mental equipment"? sounds
figurative], about the experimenter as subject, about detection as
"measurement," and about the irrelevance of the behavioral covertness
to the basic input/output issue, the "generic" question seems problematic.
With the alphas, above, we didn't have to oberve the same alpha, but
we did have to observe the same kind of alpha. Now the "alpha" in the
private case is MY sensations, not sensations simpliciter. So you
needn't verify, for objectivity's sake, the specific detection
sensation I had on trial N, or on any of my trials when I was subject,
if you like -- just as long as the generic sensation you do check on
is MINE not YOURS. Because otherwise, you see, there's this
observer-dependence...
> This objection [that there's no way of checking the correctness of a
> subject's covert calculations] applies with equal force to the
> observation, recording and calculations of externally observable
> behavior. So what?
What I meant here was that, after a long series of detection trials
with feedback and covert calculations, there's no way you can check
that I calculated MY threshold right except by running the trials on
yourself and checking YOUR threshold. But what has that to do with the
validity of MY threshold, or its status as a measure of my experience,
rather than just my input/output sensitivity after a series of trials
with complex instructions?
I agree that there is validity-problem with all behavior, by the way,
but I think that favors my argument rather than yours. One way to
check the covert calculation is to have a subject do both -- overt
detecting AND covert calculations on subsequent feedback. The two
thresholds -- one calculated covertly by the subject, the other by the
experimenter -- may well agree, but all that shows is that they get
the same result when wearing their respctive (objective) psychophysicist's
hats. What the agreement does not -- and cannot -- show is that the
subject was "measuring experience" when he was detecting. It can't
even show he was HAVING experience when he was detecting. But that's
the whole point about behavioral measures and objectivity. If we're
lucky, they'll swing together with conscious experience, but there's
no objective basis for counting on it, or checking it. (And, equally
important: It makes no methodological difference at all.)
> Yes [there {is} no way of getting any data AT ALL without the subject's
> overt mega-response at the end], but *this is not what is being
> measured*. Or is the subject matter of physics the communication
> behavior of physicists?
The subject may be silent till trial N, but the input/output
performance that is being measured is the presentation of N trials
followed by a report that stands in a certain relation to the inputs.
This is no different from the case of a simple trial, with a single
stimulus input, and the simple report "I saw it." That's not
scientific testimony, that's subjective report. The only one who can
ever see THAT kind of "it" (namely, yours), is you. (And, as I
mentioned, the subject is really switching hats here too.)
> What is objectively different about the human case is that not only is
> the other human doing similar (mental) things, he is doing those
> things to similar (human mind implemented on a human brain) equipment.
> If we obtain similar results, Occam's razor suggests that we explain
> them similarly: if my results come from measurement of subjectively
> experienced events, it is reasonable for me to suppose that another
> human's similar results come from the same source. But a computer's
> "mental" equipment is (at this point in time) sufficiently dissimilar
> [to] a human's that the above reasoning would break down at the point
> of "doing similar things to similar equipment with similar results",
> even if the procedures and results somehow did turn out to be identical.
First, I of course agree that people have similar experiences and
similar brains, and that computers differ in both respects. But I
don't consider an experience, or the report of an experience, to be a
"measurement." If anything, all of me -- rather than part of me, used and
experimented on by another part -- is the measuring device when I'm
detecting a stimulus. After all, what's happening when I'm detecting
an (astronomic) alpha: a measurement of a measurement? (The point
about the computer was just meant to remind you that psychophysicists
are just doing input/output sensitivity measurements, and that the
same data could be generated by a computer-plus-transducer. But the
difference between current computer and ourselves touches on more
complex issues related to the TTT that needn't be raised here.)
The relevant factors are all there in simple one-trial detection: If I
report a detection, there's absolutely no objective test of whether
(1) I had a sensation at all, (2) I "measured" it accurately, or even
(3) whether it's measurable at all (i.e., whether experience and
phsyical magnitude are commensurable). My detection sensitivity in the
face of inputs, on the other hand, is indeed objectively testable. No
number of private experiments by experimenter/subjects can make a dent
in this epistemic barrier (called the mind/body problem).
> Not true [that what we are actually measuring objectively is merely
> behavior]. As I have shown in my original posting, d' can be measured
> without there *being* any behavior prior to measurement. There is
> nothing in Harnad's reply to refute this.
It can't be done without presenting stimuli and feedback. And
"behavior" refers to input/output relations. So there's a long string
of real-time input involved in the covert experiment, followed by the
report of a d' value. From that we can formulate the following
behavioral description: That after so-and-so-many trials of
such-and-such stimuli with such-and-such instructions, the subject
reports X. Even when I'm myself the subject in such an experiment,
that's how I would describe my findings, and those data are
behavioral. This is no different, as I suggested, from a single
detection trial. And the subject, of course, is switching hats during
such an experiment; there's nothing magic about his behavioral silence
during the covert calculations, any more than there is in the
astronomer's, after he's gotten his telescope reading and performs
calculations on them.
> Why [will the testability and validity of these hypotheses always be
> objectively independent of any experiential correlations (i.e., the
> presence or absence of consciousness)]? And how can this be true in
> cases when it is the conscious experience that is being measured?
These input/output sensitivity characteristics of human observers
would look the same whether or not human subjects were conscious. They
ARE conscious, and they ARE having experiences during the
measurements, but it's not their experiences we (or they) are measuring, it's
their sensitivity to stimuli. It feels, when I'm the subject, as if there's a
close coupling between the two. But who am I to say? That's just a feeling
And feelings also seem, objectively speaking, incommensurable with
physical intensities. The astronomer's detection has no such liability
(except, of course, its subjective side -- "What it's like to detect
an alpha," or what have you). Rather than forcing us to conclude that
it's conscious experience that we're measuring in psychophysics, as
Adam suggests, I think Occam's Razor (a methodological principle,
after all) is dictating precisely the opposite.
> I would not accept as legitimate any psychological theory
> which appeared to contradict my conscious experience, and failed to
> account for the apparent contradiction. As far as I can tell, Steve's
> position means that he would not disqualify a psychological theory just
> because it happened to be contradicted by his own conscious experience.
That depends on what you mean by "contradicted conscious experience."
I assume we're both willing to concede on hallucinations and illusions.
I also reject radical behaviorism, which says that consciousness is just
behavior. (I know that's not true.) I'd reject any theory that said I
wasn't conscious, or that there was no such thing, or that it's
"really" just something else that I know perfectly well it isn't. I'd
also reject a theory that couldn't account for everything I can
detect, discriminate, report and describe. But if a theory simply
couldn't account for the fact that I have subjective experience at
all, it wouldn't be contradicting my experience, it would just be
missing it, bypassing it. That's just what the methodological
solipsism I recommend does. It is, in a sense, epistemologically
incomplete -- it can't explain everything. Whether it's also
ontologically incomplete depends on the (objectively untestable)
question of whether the asymptotic model that passes the TTT is or is
not really conscious. If it is, then the model has "captured"
conscious, even though the coupling cannot be demonstrated or
explicated. If it has not, it is ontologically incomplete. But, short
of BEING that model, there's no way we can ever know. (I also think
that turing-indistinguishability is an EXPLANATION of why there's
this incompleteness.)
>>[SH:] If I were one of the [psychophysical] experimenters
>>and Adam Reed were the other, how would he could get "objective
>>(observer-independent) results" on my experience and I on his? Of
>>course, if we make some (question-begging) assumptions about the fact
>>that the experience of our respective alter egos (a) exists, (b) is
>>similar to our own, and (c) is veridically reflected by the "form" of the
>>overt outcome of our respective covert calculations, then we'd have some
>>agreement, but I'd hardly dare to say we had objectivity.
> [AR:] These assumptions are not "question-begging": they are logically
> necessary consequences of applying Occam's razor to this situation (see
> above). And yes, I would tend to regard the resulting agreement among
> different subjective observers as evidence for the objectivity of their
> measurements.
I guess it'll have to be a standoff then. We disagree on what counts
as objective -- perhaps even on what objective means. Also on which
way Occam's Razor cuts.
> For measurement to be *measurement of behavior*, the behavior must be,
> in the temporal sequence, prior to measurement. But if the only overt
> behavior is the communication of the results of measurement, then the
> behavior occurs only after measurement has already taken place. So the
> measurement in question cannot be a measurement of behavior, and must be
> a measurement of something else. And the only plausible candidate for
> that "something else" is conscious experience.
If you're measuring, say, detection sensitivity, you're measuring
input/output characteristics. It doesn't matter if these are
trial-to-trial I/O/I/O etc., or just III...I/O. Only the behaviorists
have made a fetish of overt performance. These days, it's safe to say
that performance CAPACITY is what we're measuring, and that includes
the capacity to do things covertly, as revealed in the final output,
and inferrable therefrom. (Suppose you were checking a seismograph by
looking at it's monthly cumulations only: Would the long behavioral
silence make the end-result any less overt and "behavioral"?) As I suggested
in another module, cognitive science is just behaviorism-with-a-theory,
at last. The theory includes attributing covert, unobservable processes to
the head -- but not conscious experiences to the mind. We know that's there
those too, but for the (Occamian) reasons I've been discussing endlessly,
they can't figure in our theories.
> Steve seems to be saying that the mind-body problem constitutes "a
> fundamental limit on objective inquiry", i.e. that this problem is *in
> principle* incapable of ever being solved. I happen to think that human
> consciousness is a fact of reality and, like all facts of reality, will
> prove amenable to scientific explanation. And I like to think that
> this explanation will constitute, in some scientifically relevant sense,
> a solution to the "mind-body problem". So I don't see this problem as a
> "fundamental limit".
I used to have that fond hope too. Now I've seen there's a deep problem
inherent in all the existing candidates, and I've gotten an idea of what
the problem is in principle (that turing-indistinguishability IS
objectivity), so I don't see any basis for hope in the future (unless
there is a flaw in my reasoning). And, as Nagel has shown, the
inductive scenario based on our long successful history in explaining
objective phenomena simply fails to be generalizable to subjective
ones. So I don't see the rational basis for Adam Reed's optimism. On
the other hand, methodological epiphenomenalism is not all that bad --
after all, nothing OBJECTIVE is left out.
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
End of AIList Digest
********************
∂22-Feb-87 0412 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #49
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 22 Feb 87 04:12:18 PST
Date: Sat 21 Feb 1987 23:16-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
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Subject: AIList Digest V5 #49
To: AIList@SRI-STRIPE.ARPA
AIList Digest Sunday, 22 Feb 1987 Volume 5 : Issue 49
Today's Topics:
Philosophy - Consciousness & Other Minds
Scientific Method - Formalization in AI
----------------------------------------------------------------------
Date: 14 Feb 87 03:33:12 GMT
From: well!wcalvin@LLL-LCC.ARPA (William Calvin)
Subject: Re: More on Minsky on Mind(s)
Stevan Harnad replies to my Darwin Machine proposal for consciousness
(2256@well.uucp) as follows:
> Summary: No objective account of planning for the future can give an
independent causal role to consciousness, so why bother?
> wcalvin@well.UUCP writes:
>
>> Rehearsing movements may be the key to appreciating the brain
>> mechanisms [of consciousness and free will]
>
> But WHY do the functional mechanisms of planning have to be conscious?
> ...Every one of the internal functions described for a planning,
> past/future-oriented device of the kind Minsky describes (and we too
> could conceivably be) would be physically, causally and functionally EXACTL
Y
> THE SAME--i.e., would accomplish the EXACT same things, by EXACTLY the same
> means -- WITHOUT being interpreted as being conscious. So what functional
> work is the consciousness doing? And if none, what is the justification
> for the conscious interpretation of any such processes...?
>
Why bother? Why bother to talk about the subject at all? Because one
hopes to understand the subject, maybe extend our capabilities a little by
appreciating the mechanistic underpinning a little better. I am describing a
stochastic-plus-selective process that, I suggest, accounts for many of the
things which are ordinarily subsumed under the topic of consciousness. I'd
like the reactions of people who've argued consciousness more than I have,
who could perhaps improve on my characterization or point out what it can't
subsume.
I don't claim that these functional aspects of planning (I prefer to
just say "scenario-spinning" rather than something as purposeful-sounding as
planning) are ALL of consciousness -- they seem a good bet to me, worthy of
careful examination, so as to better delineate what's left over after such
stochastic-plus-selective processes are accounted for. But to talk about
consciousness as being purely personal and subjective and hence beyond
research -- that's just a turn-off to developing better approaches that are
less dependent on slippery words.
That's why one bothers. We tend to think that humans have something
special going for them in this area. It is often confused with mere
appreciation of one's world (perceiving pain, etc.) but there's nothing
uniquely human about that. The world we perceive is probably a lot more
detailed than that of a spider -- and even of a chimp, thanks to our constant
creation of new schemata via word combinations. But if there is something
more than that, I tend to think that it is in the area of scenario-spinning:
foresight, "free will" as we choose between candidate scenarios, self-
consciousness as we see ourselves poised at the intersection of several
scenarios leading to alternative futures. I have proposed a mechanistic
neurophysiological model to get us started thinking about this aspect of
human experience; I expect it to pare away one aspect of "consciousness" so
as to better define, if anything, what remains. Maybe there really is a
little person inside the head, but I am working on the assumption that such
distributed properties of stochastic neural networks will account for the
whole thing, including how we shift our attention from one thing to another.
Even William James in 1890 saw attention as a matter of competing scenarios:
[Attention] is the taking possession by the mind, in
clear and vivid form, of one out of what seem several
simultaneously possible objects or trains of thought."
To those offended by the notion that "chance rules," I would point out
that it doesn't: like mutations and permutations of genes, neural stochastic
events serve as the generators of novelty -- but it is selection by one's
memories (often incorporated as values, ethics, and such) that determine what
survives. Those values rule. We choose between the options we generate, and
often without overt action -- we just form a new memory, a judgement on file
to guide future choices and actions.
And apropos chance, I cannot resist quoting Halifax:
"He that leavth nothing to chance
will do few things ill,
but he will do very few things."
He probably wasn't using "chance" in quite the sense that I am, but it's
still appropriate when said using my stochastic sense too.
William H. Calvin BITNET: wcalvin@uwalocke
University of Washington USENET: wcalvin@well.uucp
Biology Program NJ-15 206/328-1192 or 543-1648
Seattle WA 98195
------------------------------
Date: 12 Feb 87 19:12:48 GMT
From: mcvax!ukc!reading!onion!minster!adt@seismo.css.gov
Subject: Re: Harnad's epiphenomenalism
In article <4021@quartz.Diamond.BBN.COM> aweinste@Diamond.BBN.COM
(Anders Weinstein) writes:
>Well, I don't think we ought to give this up so easily. I would urge that
>cognitivists *not* buy into the premise of so many of Harnad's replies: the
>existence of some weird parallel universe of subjective experience.
>(Actually, *multiple* such universes, one per conscious subject, though of
>course the existence of more than my own is always open to doubt.) We should
>recognize no such private worlds. The most promising prospect we have is that
>conscious experiences are either to be identified with functional states of
>the brain or eliminated from our ultimate picture of the world. How this
>reduction is to be carried out in detail is naturally a matter for
>empirical study to reveal, but this should remain one (distant) goal of
>mind/brain inquiry.
>
>Anders Weinstein aweinste@DIAMOND.BBN.COM
>BBN Labs, Cambridge MA
Why is it necessary to assert that there are no subjective universes, all that
is necessary is that everyone in their own subjective universe agrees the
definition of consciousness as they perceive it. Eliminating conscious
experiences from our ultimate picture of the world sounds like throwing away
half the results so that the theory fits. The analogy of our understanding of
gold in terms of its atomic structure is a useful one but does not require
the rejection of subjective universes. If objectivism is taken to its limit
as above then surely it must be possible to define "beautiful" in terms of
physical states of mind, or "beautiful" should be eliminated from our
ultimate picture of the world. OR "beautiful" is not a conscious experience.
I would be interested to know which of these possibilities you support.
------------------------------
Date: 14 Feb 87 21:57:45 GMT
From: brothers@topaz.rutgers.edu (Laurence R. Brothers)
Subject: Submission for mod-ai
Path: topaz!brothers
From: brothers@topaz.RUTGERS.EDU (Laurence R. Brothers)
Newsgroups: mod.ai
Subject: Re: Other Minds
Message-ID: <9245@topaz.RUTGERS.EDU>
Date: 14 Feb 87 21:57:45 GMT
References: <8702132202.AA01947@BOEING.COM>
Organization: Rutgers Univ., New Brunswick, N.J.
Lines: 49
So...? I think you've basically restated a number of properties of
intelligence which AI researchers have been exploring for some time,
with varying degrees of success.
There are two REAL reasons why you can't build an "intelligent"
machine today:
1) Since no one really knows how people think, we can't build machines
which accurately model ourselves.
2) Current machines do not have anything like the kind of computing
power necessary for intelligence.
Ray@Boeing says:
>Manipulation of symbols is insufficient by itself to duplicate human
>performance; it is necessary to treat the perceptions and experiences the
>symbols *symbolize*. Put a symbol for red and a symbol for blue in a pot,
>and stir as you will, there will be no trace of magenta.
Look, manipulation of symbols by a program is analogical with
manipulation of neural impulses by a brain. When you reduce far
enough, EVERYTHING is typographical/syntactical. The neat thing about
brains is that they manipulate so MANY symbols at once.
General arguments against standard AI techniques are all well and good
(viz. Hofstadter's position), but keep in mind that while mainstream
AI has not produced so much wonderful stuff, the old neural-net
research was even less impressive.
My own view regarding true machine intelligence is that there is no
particular reason why it's not theoretically possible, but given
an "intelligent" machine, one should not expect it to be able to
do anything weird like passing a Turing Test. The hypothetical
intelligent machine won't be anything like a human -- different
architecture, different i/o bandwidths, different physical
manifestation, so it is philosophically deviant to expect it
to emulate a human.
Anyhow, as a putative AI researcher (so I'm only 1st year, so sue me),
it seems to me that decades of work have to be done on both hardware
and cognitive modeling before we can even set our sights on
HAL-9000.... Give me another ring when those terabyte RAM, femtosecond
CAML cycle optical computers come out -- until then the entire
discussion is numinous....
--
Laurence R. Brothers
brothers@topaz.rutgers.edu
{harvard,seismo,ut-sally,sri-iu,ihnp4!packard}!topaz!brothers
"The future's so bright, I gotta wear shades!"
------------------------------
Date: Mon, 16 Feb 87 18:50:21 n
From: DAVIS%EMBL.BITNET@wiscvm.wisc.edu
Subject: reply to harnad
I'm afraid that Stevan Harnad has still appeared not to grasp the irrelevance
of asking 'WHY' questions about consciousness.
> ...I am not asking a teleological question or even an evolutionary one.
> [In prior iterations I explained why evolutionary accounts of the origins
> and "survival value" of consciousness are doomed: because they're turing-
> indistinguishable from the IDENTICAL selective-advantage scenario minus
> conciousness.]
Oh dear. In my assertion that there is a *biological* dimension to the
current existence (or illusion of) consciousness, I had hoped that Harnad
would understand the idea of evolutionary events being 'frozen-in'.
Sure - there is no advantage in a conscious system doing what can be done
unconciously. BUT, and its a big but, if the system that gets to do
trick X first *just happens* to be conscious, then all future systems
evolving from that one will also be conscious. This is true of all aspects
of biological selection, and would be true in any context of natural
selection operating on an essentially randomn feature generator.
There need be NO 'why' as to the fact that consciousness is with us now
- there is every reason to suppose that we are looking at a historical
accident that is frozen-in by the irreversibility of a system evolving in
a biological context. In fact, it may not even be an accident - when you
consider the sort of complexity involved in building a'turing-
indistinguishable' automaton, versus the slow, steady progress possible
with an evolving, concious system, it may very well be that the ONLY
reason for the existence of conscious systems is that they are *easier* to build
within an evolutionary, biochemical context.
Hence, we have no real reason to suppose that there is a 'why' to be
answered, unless you have an interest in asking 'why did my random number
generator give me 4.5672 ?'. Consciousness appears to be with us today -
the > justification for the conscious interpretation of the "how" < (Harnad)
is simply this:
- as individuals we experience self-consciousness,
- other system's behaviour is so similar to our own that we may
reasonably make the assumption of conscioussness there too,
- the *a priori* existence of conciousness is supported by
(i) our own belief in our own experience
and hence
(ii) the evolutionary parrallels with other biological features
such as the pentadactyl limb, globin and histone
structures and the use of DNA.
Voila - Occam's razor meets the blind watchmaker, and gives us conscious
machines, not because there is any reason 'why' this should be so, but just
because it worked out like that.
Like it - or lump it!
As for the question of knowledge & consciousness: I did not intend the
word 'know' to be used in its epistemological sense, merely to point out
that our VAXcluster has access to information, but (appears not to) KNOW
anything. The mystery of the 'C-1' is that we can be aware, that it is
'like something to be us', period.
We don't know how yet,and we will probably never know why beyond the likelihood
of our ancestral soup bowl being pretty good at coming up with bright ideas,
like us! (no immodesty intended here.....)
regards,
Paul Davis
netmail: davis@embl.bitnet
wetmail: embl, postfach 10.2209, 6900 heidelberg, west germany
petmail: homing pigeons to ......
------------------------------
Date: Sun, 15 Feb 87 17:50:00 EST
From: Raul.Valdes-Perez@B.GP.CS.CMU.EDU
Subject: Formalization in AI (Not Philosophy)
I believe it is wrong to say that the importance of formalization to AI
is overstated; formalization is our secret weapon. Let's say that AI is
the science of codifying human knowledge in an effective manner, where by
effective is meant able to effect a result, rather than, say, listing on
paper and hanging in a museum.
Our secret weapon is formalization by embedding knowledge in a computer
program, in accordance with our theories of how best to organize the
embedding. We then run the program to test our theories. This embedding
is a formalization; we are able to discover qualitative properties of the
knowledge and organization by syntactic manipulation i.e. execution of
the computer program. These qualitative properties would not otherwise
be discovered by us because of our limited capacity to sustain complex
thought.
Programming may not seem formal, because few theorems follow from its
exercise. This difficulty is due to our programming languages that lack
useful mathematical properties. Our resulting insights are qualitative;
nevertheless they are achieved by formalization.
My conclusion is that everyone in AI believes in formalization, whether he
knows it or not.
-- Raul E. Valdes-Perez --
-- CMU CS --
------------------------------
Date: Mon, 16 Feb 87 07:41:29 PST
From: ames!styx!lll-lcc!ihnp4!hounx!kort@cad.Berkeley.EDU
Subject: Re: Other Minds
Ray Allis has brought up one of my favorite subjects: the creation
of an artificial mind.
I agree with Ray that symbol manipulation is insufficient. In last
year's discussion of the Chinese Room, we identified one of the
shortcomings of the Room: it was unable to learn from experience
and tell the stories of its own adventures.
The cognitive maps of an artificial mind are the maps and models of
the external world. It is one thing to download a map created by
an external mapmaker. It is quite another thing to explore one's
surroundings with one's senses and construct an internal representation
which is analogically similar to the external world.
An Artificial Sentient Being would be equipped with sensors (vision,
audition, olfaction, tactition), and would be given the goal of
exploring its environment, constructing an internal map or model
of the that environment, and then using that map to navigate safely.
Finally, like Marco Polo, the Artificial Sentient Being would describe
to others, in symbolic language, the contents of its internal map:
it would tell its life story.
I personally would like to see us build an Artificial Sentient Being
who was able to do Science. That is, it would observe reality and
construct accurate theories (mental models) of the dynamics which
governed external reality.
Suppose we had two such machines, and we set them to explore each
other. Would each build an accurate internal representation of the
other? (That is, could a Turing Machine construct a mathematical
model of (another) Turing Machine?) Would the Sentient Being
recognize the similarity between itself and the Other? And in seeing
its soul-mate, would it come to know itself for the first time?
Barry Kort
---
-- Barry Kort
...ihnp4!houxm!hounx!kort
A door opens. You are entering another dementia.
The dementia of the mind.
------------------------------
End of AIList Digest
********************
∂22-Feb-87 0620 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #50
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 22 Feb 87 06:20:21 PST
Date: Sat 21 Feb 1987 23:20-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #50
To: AIList@SRI-STRIPE.ARPA
AIList Digest Sunday, 22 Feb 1987 Volume 5 : Issue 50
Today's Topics:
Philosophy - Consciousness & Other Minds
----------------------------------------------------------------------
Date: 17 Feb 87 20:15:29 GMT
From: "Col. G. L. Sicherman"
<colonel%sunybcs%math.waterloo.edu@RELAY.CS.NET>
Subject: Re: artificial minds
In article <8702132202.AA01947@BOEING.COM>, ray@BOEING.COM (Ray Allis) writes:
> ... Homo Sap.'s
> distinguished success among inhabitants of this planet is primarily due
> to our ability to think. ...
Success is relative! Cockroaches are successful too, for quite
different reasons. And our own success is questionable, considering
how many of us starve to death. Try explaining _that_ to a cockroach.
Biologically, our chief advantages over other species are erect
posture and prehensile hands. Abstract thought is only ancillary;
other species lack it mainly because they cannot use it.
> and it is difficult
> for me to imagine a goal more relevant than improving the chances for
> survival by increasing our ability to act intelligently.
Well said. But this is an argument for using computers as tools, and
it is seldom true that tools ought to be designed to resemble the human
components that they extend. Would you use a hammer that looks like
a fist? Or wear a shoe with toes?
Why try to endow a lump of inorganic matter with the soul of a human
being? You don't yet know what your own mind is capable of. Besides,
if you do produce an intelligent computer, it may not like you!
--
Col. G. L. Sicherman
UU: ...{rocksvax|decvax}!sunybcs!colonel
CS: colonel@buffalo-cs
BI: colonel@sunybcs, csdsiche@ubvms
------------------------------
Date: 19 Feb 87 17:13:11 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: More on the functional irrelevance of the brain to
mind-modeling
"CUGINI, JOHN" <cugini@icst-ecf> wrote on mod.ai:
> The Big Question: Is your brain more similar to mine than either
> is to any plausible silicon-based device?
That's not the big question, at least not mine. Mine is "How does the
mind work?" To answer that, you need a functional theory of how the
mind works, you need a way of testing whether the theory works, and
you need a way of deciding whether a device implemented according to
the theory has a mind. That's what I proposed the formal and informal
TTT for: testing and implementing a functional theory of mind.
Cugini keeps focusing on the usefulness of "presence of `brain'"
as evidence for the possession of a mind. But in the absence of a
functional theory of the brain, its superficial appearance hardly
helps in constructing and testing a functional theory of the mind.
Another way of putting it is that I'm concerned with a specific
scientific (bioengineering) problem, not an exobiological one ("Does this
alien have a mind?"), nor a sci-fi one ("Does this fictitious robot
have a mind?"), nor a clinical one ("Does this comatose patient or
anencephalic have a mind?"), nor even the informal, daily folk-psychological
one ("Does this thing I'm interacting with have a mind?"). I'm only
concerned with functional theories about how the mind works.
> A member of an Amazon tribe could find out, truly know, that light
> switches cause lights to come on, with a few minutes of
> experimentation. It is no objection to his knowledge to say that he
> has no causal theory within which to embed this knowledge, or to
> question his knowledge of the relevance of the similarities among
> various light switches, even if he is hard-pressed to say anything
> beyond "they look alike."
Again, I'm not concerned with informal, practical, folk heuristics but
with functional, scientific theory.
> Now, S. Harnad, upon your solemn oath, do you have any serious
> practical doubt, that, in fact,
> 1. you have a brain?
> 2. that it is the primary cause of your consciousness?
> 3. that other people have brains?
> 4. that these brains are similar to your own
My question is not a "practical" one, but a functional, scientific
one, and none of these correlations among superficial appearances help.
> how do you know that two performances
> by two entities in question (a human and a robot) are relevantly
> similar? What is it precisely about the performances you intend to
> measure? How do you know that these are the important aspects?
> ...as I recall, the TTT was a kind
> of gestalt you'll-know-intelligent-behavior-when-you-see-it test.
> How is this different from looking at two brains and saying, yeah
> they look like the same kind of thing to me?
Making a brain look-alike is a trivial task (they do it in Hollywood
all the time). Making a (TTT-strength) behavioral look-alike is not. My
claim is that a successful construction of the latter is as close as we
can hope to get to a functional understanding of the mind.
There's no "measurement" problem. The data are in. Build a robot that
can detect, discriminate, identify, manipulate and describe objects
and events and can interact linguistically indistinguishably from the
way we do (as ultimately tested informally by laymen) and you'll have
the problem licked.
As to "relevant" similarities: Perhaps the TTT is too exacting. TOTAL
human performance capacity may be more than what's necessary to capture mind
(for example, nonhuman species and retarded humans also have minds).
Let's say it's to play it safe; to make sure we haven't left anything
relevant out; in any case, there will no doubt be many subtotal
way-stations on the long road to the asymptotic TTT.
The brain's another matter, though. Its structural appearance is
certainly not good enough to go on. And its function is an ambiguous
matter. On the one hand, its behavioral capacities are among its functional
capacities, so behavioral function is a subset of brain function. But,
over and above that we do not know what implementational details are
relevant. The TTT could in principle be beefed up to demand not only
behavioral indistinguishability, but anatomical, physiological and
pharmacologcal indistinguishability. I'd go for the behavioral
asymptote first though, as the most likely criterion of relevance,
before adding on implementational constraints too -- especially because
those implementational details will play no role in our intuitive
judgments about whether the device in question has a mind like us, any
more than they do now. Nor will they significantly increase the
objective validity of the (frail) TTT criterion itself, since brain
correlates are ultimately validated against behavioral correlates.
My own guess, though, is that our total performance capacity will be
as strong a hardware constraint as is needed to capture all the relevant
functional similarities.
> Just a quick pout here - last December I posted a somewhat detailed
> defense of the "brain-as-criterion" position...
> No one has responded directly to this posting.
I didn't reply because, as I indicated above, you're not addressing the same
question I am (and because our exchanges have become somewhat repetitive).
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: Fri, 20 Feb 87 15:23:32 pst
From: Ray Allis <ray@BOEING.COM>
Subject: Other Minds
Hello? Where'd everyone go? Was it something I said? I have
a couple of things to say, yet. But fear not, this is part 2 of 2,
so you won't have me cluttering up your mail again in the near future.
This is a continuation of my 2/13/87 posting, in which I am proposing
a radical paradigm shift in AI.
[The silence on the Arpanet AIList is due to my saving the
philosophical messages for a weekly batch mailing. This gives
other topics a chance and reduces the annoyance of those who
don't care for these discussions. -- KIL]
Our common sense thought is based on and determined by those things
which are "sensible" (i.e. that we can sense). "The fog comes in on
little cat feet" [Sandberg]. Ladies and gentlemen of the AI
community, you are not even close! Let me relax the criteria a little,
take this phrase, "a political litmus test". How do you expect a
machine to understand that without experience? Nor can you ever
*specify* enough "knowledge" to allow understanding in any useful
sense. The current computer science approach to intelligence is as
futile as the machine translation projects of the 60's, and for the
same reason; both require understanding on the part of the machine,
and of that there isn't a trace.
Obviously symbolic thinking is significant; look at the success of our
species. There are two world-changing advantages to symbolic thought.
One advantage is the ability to think about the relationships among
things and events without the confusing details of real things and
events; "content-free" or "context-independent" "reasoning" leading to
mathematics and logic and giving us a measure of control over our
environment, and our destiny. Symbol systems are tools which assist
and enhance human minds, not replacements for those minds. Production
rules are an externalization of knowledge. They are how we explain our
behavior to other people.
The other advantage lies in the fundamental difference between
"symbolize" and "represent". Consider how natural language works.
Through training, you come to associate "words" with experiences.
The immediate motive for this accomplishment is communication; when
you can say "wawa" or "no!", the use of language becomes your best
tool for satisfying your desires and needs. But a more subtle and
significant thing happens. The association between any symbol and
that which it symbolizes is arbitrary, and imprecise. Also, in any
human experience, there is *so much* context that it is practically
the case that every experience is associated with every other, even
if somewhat indirectly.
So please imagine a brain, in some instantaneous state of excitation
due to external stimuli. Part of the "context" (or experience) will
be (representations of) symbols previously associated. Now imagine
the internal loop which presents internal events to the brain as if
they were external events, presenting those symbols as if you "saw"
or "heard" them. But, since the association is imprecise, the
experience evoked by those symbols will very likely not be identical
to that which evoked the symbols. A changed pattern of activity in
the nervous system will result, possibly with different associated
symbols, in which case the cycle repeats.
The function of all this activity is to "converge" on the "appropriate"
behavior for the organism, which is to say to continue the organism's
existence. There is extreme "parallelism"; immense numbers of events
are occurring simultaneously, and all associations are stimulated
"at once". Also, none of this is "computation" in the traditional
sense; it is the operation of an analog "device", which is the central
nervous system, in its function of producing "appropriate" behavior.
Imagine an experience represented in hundreds of millions of CNS
connections. Another experience, whatever the source, (that is from
external sensors, from memory or wholly created) will be represented
in the same (identical) neurons, in point-for-point registration, all
half-billion points at once. Any variation in correspondence will be
immediately conspicuous. The field (composite) is available for the
same contrast enhancement and figure/ground "processing" as in visual
(or any) input.
Multiple experiences will reinforce at points of correspondence, and
cancel elsewhere. Tiny children are shown instances of things; dogs,
kittens, cows, fruits, and expected to generalize and to demonstrate
their generalization, so adults can correct them if necessary.
Generalization is the shift in figure / ground percentage which comes
from "thresholding" out the weaker sensations. The resultant is the
"intersection" of qualities of two or more experiences. This whole
operation, comparing millions of sensation details with corresponding
sensation details in another experience can happen in parallel in a
very few cycles or steps.
Informed by Maturana's ideas of autopoeic systems, mind can be
considered as an emergent phenomenon of the complexity which has
evolved in the central nervous systems of Terrestrial organisms
(that's us). This view has fundamental philosophical implications
concerning whether minds are likely to exist elsewhere in the Universe
due to "natural causes", and whether we can aspire to create minds.
Much "thinking" is of the sort described by the Nobel Prize winner
in "The Search for Solutions" who thinks of DNA as a rope which, when
stretched will break at certain "weak" points. That "tool", the
visualization, is guided by physical experience, his personal
experience of ropes and their behavior. Einstein said he often
thought in images; certainly his thought was guided, and perhaps
the results judged, by his personal experience with the things
represented. We also need "... the ability to generalize, the
ability to strip to the essential attributes of some actor in the
process..." "We are not ready to write equations, for the most part,
and we still rely on mechanical and chemical or other physical models."
Josua Lederberg - Nobel Prize geneticist - President of Rockefeller U.
"The Search for Solutions".
The internal loop can use motor action (intents) to re-stimulate
associated sensory input (results) and entire sequences of sensory
input to motor output to sensory input can occur without interacting
with the external environment. Here is the basis for imagination and
planning. Experiences need not be original; they may be created
entirely from abstractions. And this is called *imagination*.
The ability to construct internal imaginary events and situations is
fundamental to symbolic communication: where symbols evoke and are
derived from internal state. Planning is the process of reviewing a
set of experiences, which may be recalled, or may be constructed
imaginary experiences. Planning requires imagination (see above) of
actions and consequences. The success and effectiveness of the
resulting plan depends on the quality and quantity of experiences
available to the planner. He benefits from a rich repertoire of
experience from which to choreograph his dance of events. The novelty
in the present theory is that most of the planning process is
essentially and necessarily analog in nature, and symbol processing
is only part of it. Symbols are critical to make the process
explicit, but the planning process itself is not only, or even
primarily, symbol processing.
If we agree that our minds are an effect of our CNS, then we must
accept that the structure of our mind is determined by the structure
of our CNS. Sure there's a "deep structure" in linguistic ability;
it's our physical implementation (embodiment). The "meaning" of
language is that state which it evokes in us.
"A new meaning is born whenever the mind uses a word or other symbol
in a new way. If you think of a key as something to open a lock and
then speak of hard work as the key to success, you are using the word
key in a new way. It no longer means simply a metal implement for
opening a lock; it has acquired a much richer sense in your mind:
"necessary prerequisite for attaining a desired goal." If the word
key were not free to shift its sense, the new concept probably could
not emerge. All thinkers, whether artists, philosophers, scientists,
businessmen, or laborers, can create new thoughts if they use words
in new ways." ["The Mind Builder", Richard W. Samson, 1965.]
Samson identified seven mental "faculties" which make an interesting
list of target capabilities for "intelligent machines". These are:
1. Words: We let words (together with numbers and other symbols)
mean things.
2. Thing Making: We make mental pictures of things when we
interpret sensations.
3. Qualification: We notice the qualities of things: how things
are alike and how they differ.
4. Classification: We mentally sort things into classes, types or
families.
5. Structure Analysis: We observe how things are made: break
structural wholes into component parts.
6. Operation Analysis: We notice how things happen: in what
successive stages.
7. Analogy: We see how seemingly unconnected situations are
alike, forming parallel relations in different "worlds of
thought".
When you are ready, try your system on the SAT test:
Which word (a, b, c, or d) best completes the sentence,
in your opinion? There is no "right" answer; pick the
word which seems best to you.
Poverty and hatred are ---------- of war.
(a) roots (b) leaves (c) seeds (d) fruits
We might be well advised to imitate a real example intelligence
(ours). Later we can improve on the implementation, and possibly
the performance.
Certainly we will use mathematics to analyze and predict the system's
behavior; or rather subsets and abstractions, models of the system.
But we may not be able to construct any model less complex than the
system itself, which will produce the desired behavior; its behavior
must be understood through simulation.
"Computational irreducibility is a phenemenon that seems to arise in
many physical and mathematical systems. The behavior of any system
can be found by explicit simulation of the steps in its evolution.
When the system is simple enough, however, it is always possible to
find a short cut to the procedure: once the initial state of the system
is given, its state at any subsequent step can be found directly from
a mathematical formula." "For a system such as (illus.), however, the
behavior is so complicated that in general no short-cut description of
the evolution can be given. Such a system is computationally
irreducible, and its evolution can effectively be determined only by
the explicit simulation of each step. It seems likely that many
physical and mathematical systems for which no simple description is
now known are in fact computationally irreducible. Experiment, either
physical or computational, is effectively the only way to study such
systems."
[Stephen Wolfram, Computer Software in Science and Mathematics,
Scientific American, Sept., 1984]
A mind is an effect which probably cannot be sustained at a lesser
level of complexity than in our own case; any abstraction which
simplifies will also destroy the very capabilities we wish to
understand. There are trillions of components and connections in the
human brain. No reasonable person can expect to model a mind in any
significant way using a few tens or hundreds of components. Since
there is a threshold of complexity below which the behavior of
interest will not occur, and the complexity of models is generally
deliberately reduced below this level, models will not produce the
phenomena of interest.
"Yet recall John von Neumann's warning that a complete description of
how we perceive may be far more complicated than this complicated
process itself - that the only way to explain pattern recognition
may be to build a device capable of recognizing pattern, and then,
mutely, point to it.
How we think is still harder, and almost certainly we are not yet
breaking this problem down in solvable form."
Horace Freeland Judson, "The Search for Solutions", 1980.
In spite of the tone of that last quote, I believe we can and should
build, now, things which will prove or disprove these ideas, so we
can either quit wasting energy or get going on building other minds.
I'm not going to be at this mail address after March 1, but probably
someone will forward my mail. The Boeing Advanced Technology Center
just closed down all its robotics projects, including mobility and
stereo vision, my work in induction, and all other work not "directly
supporting Boeing programs". So twenty-plus of us are scrambling to
find other places to work. I don't know what access to any networks
I might have next month.
Ray
------------------------------
End of AIList Digest
********************
∂22-Feb-87 2313 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #51
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 22 Feb 87 23:12:52 PST
Date: Sun 22 Feb 1987 21:20-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #51
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 23 Feb 1987 Volume 5 : Issue 51
Today's Topics:
News - Impact of Artificial Intelligence,
Philosophy - Design Stance on Consciousness,
Review - Society of Mind
----------------------------------------------------------------------
Date: Sat, 21 Feb 1987 09:59 CST
From: Laurence L. Leff <E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Impact of Artificial Intelligence
"Artificial Intelligence" is the computer journal with the highest
impact factor according to the latest issue of the Journal Citation
Reports put out by the Institute for Scientific Information. It beats
by a good factor the second runner up, IEEE Transactions on Pattern
Analysis.
The Impact Factor is a measure of how often people cite the journal and is
proportional to the number of citations per article published. I. E. we
are looking at how often someone deems an article in "Artificial Intelligence"
of sufficient significance to cite it in their article.
To put this in perspective, here are the numbers for some familiar computer
journals.
Artificial Intelligence 3.914
IEEE T Pattern Anal 2.374
IEEE T Computers 1.654
Comput Surv 1.545
Commun ACM 1.528
SIAM J Comput 1.349
INT J Robot Res 1.314
J Assoc Comput Mach 1.282
Comput Vision Graph 1.170
IEEE T Syst Man Cyb 1.168
Computer 1.161
Pattern Recogn 1.092
IBJ J Res Dev 1.087
IEEE T Software Eng 0.963
Acta Inform 0.627
J Comput Syst Sci 0.613
J Robotic System 0.600
Int J. Syst Sci 0.428
Software Pract Experience 0.253
Kybernetika 0.171
AT&T Tech Journal 0.080
So who is citing "Artificial Intelligence" you might ask.
Of a total of 924 citations in 1985 to Artificial Intelligence, here is
a break down of some of the frequent and interesting citing journals
Artificial Intelligence 103
IEEE T Pattern Analysis 62
Comput Vision Graph 50
Int J Man Mach Stud 37
Comput Aided Design 29
P. Soc. Photo-Opt Inst 25
TSI-Tech Science Inf 23
Comput Math Appl 20
IEEE T Syst Man Cybern 19
Lect Notes Comput Sc 18
Comput Surv 15
J Assoc Comput Mach 12
J Symb Comput 7
Environ Plann B 6
It is also interesting to note who authors publishing in "Artificial
Intelligence" cite. When you compare the list
of items cited within "Artificial Intelligence" and compare it to that
in other fields, one is impressed by the importance of the conference
literature to artificial intelligence.
Of a total of 997 citations by "Artificial Intelligence" articles, here
are the numbers for some of the more noteworthy sources of these
citations
Artificial Intelligence 103
IJCAI and AAAI conferences 76
P Int S Robotics Res 33
Mach Intell 23
Commun ACM 16
Cognitive Science 15
Comput Surv 7
Handbook of Artifical Int. 6
.
------------------------------
Date: 22 Feb 87 1150 PST
From: John McCarthy <JMC@SAIL.STANFORD.EDU>
Subject: consciousness
This discussion of consciousness considers AI as a branch of
computer science rather than as a branch of biology or philosophy.
Therefore, it concerns why it is necessary to provide AI programs
with something like human consciousness in order that they should
behave intelligently in certain situations important for their
utility. Of course, human consciousness presumably has accidental
features that there would be no reason to imitate and other features
that are perhaps necessary consequences of its having evolved that
aren't necessary in programs designed from scratch. However, since
we don't yet understand AI very well, we shouldn't jump to conclusions
about what features of consciousness are unnecessary in order to
have the intellectual capabilities humans have and that we want our
programs to have.
Consciousness has many aspects and here are some.
1. We think about our bodies as physical objects to which
the same physical laws apply as apply to other physical objects.
This permits us to predict the behavior of our bodies in certain
situations, e.g. what might break them, and also permits us to
predict the behavior of other physical objects, e.g. we expect
them to have similar inertia. AI systems should apply physics
to their own bodies to the extent that they have them. Whether
they will need to use the analogy may depend on what knowledge
we choose to build in and what we will expect them to learn from
experience.
2. We can observe in a general way what we have been thinking
about and draw conclusions. For example, I have been thinking
about what to say about consciousness in this forum, and at present
it seems to be going rather well, so I'll continue composing
my comment rather than think about some specific aspect of
consciousness. I am, however, concerned that when I finish this
list I may have left our important aspects of consciousness that
we shall want in our programs. This kind of general observation
of the mental situation is important for making intellectual
plans, i.e. deciding what to think about. Very intelligent computer
programs will also need to examine what they have been thinking
about and reason about this information in order to decide whether
their intellectual goals are achievable. Unfortunately, AI isn't
ready for this yet, because we must solve some conceptual problems
first.
3. We compare ourselves intellectually with other people.
The concepts we use to think about our own minds are mainly learned
from other people. As with information about our bodies, we infer
from what we observe about ourselves to the mental qualities of
other people, and we also learn about ourselves from what we
learn about others. In so far as programs are made similar to
people or other programs, they may also have to learn from interaction.
4. We have goals about our own mental functioning. We would
like to be smarter, nicer and more content. It seems to me that
programs should also have such meta-goals, but I don't see that
we need to make them the same as people's. Consider that many
people have the goal of being more rational, e.g. less driven
by impulses. When we find ourselves with circular preferences,
e.g preferring A to B, B to C and C to A, we chide ourselves and
try to change. A computer program might well discover that its
heuristics give rise to circular preferences and try to modify
them in service of its grand goals. However, while people are
originally not fully rational, because our heritage provides
direct connections between our disparate drives and the actions
that achieve the goals they generate, it seems likely that
there is no reason to imitate all these features in computer programs.
Thus our programs should be able to compare the desirability
of future scenarios more readily than people do.
5. Besides our direct observations of our own mental
states, we have a lot of general information about them. We
can predict whether problems will be easy or difficult for us
and whether hypothetical events will be pleasing or not.
Programs will require similar capabilities.
Finally, it seems to me that the discussion of consciousness
in this digest has been too much an outgrowth of the ordinary
traditional philosophical discussions of the subject. It hasn't
sufficiently been influenced by Dennett's "design stance". I'm
sure that more aspects of human consciousness than I have been
able to list will require analogs in robotic systems. We should
also be alert to provide forms of self-observation and reasoning
about the programs own mental state that go beyond those evolution
has given us.
------------------------------
Date: Sun, 22 Feb 87 20:21 EST
From: ANK%CUNYVMS1.BITNET@wiscvm.wisc.edu
Subject: N.Y.Times review of SOCIETY OF MIND
Today's (22 Feb. 87) New York Times Book review section carried
a full page review of Minsky's "Society of Mind" {pp 339 Simon &
Schuster $19.95} by James W Lance, a professor in neurology from
Australia.
Since the beginning of this year, over a score of people have
devoted a cumulative of 100 + hours debating over Marvin's comments on
Consciousness. With that as a backdrop I wanted to see what Dr. Lance
had to say ! Well nothing much that readers of AI-Digest do not
already know.
In all fairness to the reviewer I must say he did a good job of
filling a page with bits and pieces from the book. But what he did not
accomplish is to critique the book as a scholarly (I am right ?...Well
many may think not..) work. New York Times, I must complain, has not been
very serious in the past two years, when it comes to reviews relating
to such topics, in comparision to other scientific books that pass through
their tables.
What then is my gripe ? I think "consciousness" is a very
serious matter. Furthermore the classical Mind-Body question will
always re-occur every few decades in the light of a new philosophical
construct. Therefore to attribute the onus of assigning the
*definitation of "consciousness" to Minsky's posting in AI Digest, is
wrong. I did not see much debate when PDP was published by M.I.T.Press
? Listen folks ! I think there is more mileage to be got from the two
Volumes of Parallel Distributed Processing than in "Society....".
I rather suspect that we in the academia expect great architecture
every monday morning. Similarly Minsky's book is *not* supposed to be
taken as the final word or *official* pronouncement of "mind-brain debate".
The purpose, as I understood it from reading the book, was
to generate idea's and reflect on the homely's and aphorisms that
the book is so full of. It is true that many common-day phenomena
relating to memory is outside many models of memory. Let me illustrate
" I forgot the my telephone number of two years ago in
Cambridge.... and last week right in the middle of
Fifth Ave. and 42nd. it came as a flash.."
I do not think many theories of memory either explain one
or the other problems, but none that in the classical sense address
all the issues. (Yes ! not even the latest theories. That's the
complexity of studying Man and his mind using expirical tools)
The point I wish to make is simple. Many of us (graduate-level students)
could get many germ-of-an-idea from his book. Lets keep it at that.
All many of us need is a metaphor or a notion, and off we go. His
book does that rather neatly. It should be a required reading along
with Drefus's, if we have to go beyond satisfying our Ph.D. requirements.
The last paragraph of Lance's review was, and let me paraphrase it:
"This is a disturbing book for a neurologist to read
because of the summation of mathematics + psychology
+ philosophy still does not approach the complexities
of neurology. And yet the text pursues an exciting
trail to the elusive goal"
Sure enough, I guess Minsky did not expect to give one either (or so I
presume..) I'm sure it is easy for Harnad to reduce all "books in
Psychology, Philosophy, Biology....theatre, music..." to the MIND-BODY
problems. Not that I personally mind, but it is better that we limit
the domain.
Finally I wonder if *intensional-realist* like Harnad (maybe I'm wrong)
really have a plausible model of the mind ?
Anil Khullar
{Ph.D. Program in Psychology
C.U.N.Y. Graduate Center.
New York NY 100036 }
ank%cunyvms1.BITNET@wiscvm.edu
BITNET: ank@cunyvms1
PS: I personally think Harnad
has given me enough insights
for my term-paper.......
------------------------------
End of AIList Digest
********************
∂23-Feb-87 0044 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #52
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 23 Feb 87 00:44:20 PST
Date: Sun 22 Feb 1987 21:37-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #52
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 23 Feb 1987 Volume 5 : Issue 52
Today's Topics:
Seminars - Boolean Concept Learning (CMU) &
Knowledge-Based CAD-CAM Software Integration (Rutgers) &
Parallel Techniques in Computer Algebra (SMU) &
A Picture Theory of Mental Images (SUNY) &
Minds, Machines, and Searle (Rutgers)
----------------------------------------------------------------------
Date: 20 Feb 87 11:41:42 EST
From: Marcella.Zaragoza@isl1.ri.cmu.edu
Subject: Seminar - Boolean Concept Learning (CMU)
THEORY SEMINAR
Lenny Pitt
Wednesday, 25 Feb.
3:30
WeH 5409
Recent results on Boolean concept learning.
Lenny Pitt
U. Illinois at Urbana-Champaign
In "A Theory of the Learnable" (Valiant, 1984), a new formal definition
for concept learning from examples was proposed. Since then a number
of interesting results have been obtained giving learnable classes of
concepts. After motivating and explaining Valiant's definition of
probabilistic and approximate learning, we show that even some
apparently simple types of concepts (e.g. Boolean trees, disjuncts
of two conjuncts) cannot be learned (assuming P not equal NP).
The reductions used suggest an interesting relationship between
learnability problems and the approximation of combinatorial optimization
problems.
This is joint work with Leslie G. Valiant.
This talk will be of interest to both Theory and AI people. To schedule
an appointment to meet with him on Wednesday, send mail to stefanis@g.
------------------------------
Date: 18 Feb 87 13:01:42 EST
From: KALANTARI@RED.RUTGERS.EDU
Subject: Seminar - Knowledge-Based CAD-CAM Software Integration
(Rutgers)
RUTGERS COMPUTER SCIENCE AND RUTCOR COLLOQUIUM SCHEDULE - SPRING 1987
Computer Science Department Colloquium :
This talk has already been announced without an abstract which is
given bellow
---------------------------------------
DATE: Friday February 20, 1987
SPEAKER: Dr. Benjamin Cohen
AFFILIATION: RCA Princeton Labs.
TITLE: "Knowledge-Based CAD-CAM Software Integration."
TIME: 2:50 (Coffee and Cookies will be setup at 2:30)
PLACE: Hill Center, Room 705
ABSTRACT
How to integrate large, distributed, heterogeneous CAD/CAM applications
to support data sharing and data integrity is a major software engineering
challenge. One of the key elements in a solution to the integration problem is
the use of knowledge-based techniques and AI languages. A tutorial overview
of the potential role of knowledge-based techniques in integrating distributed,
heterogeneous databases will be presented. We also illustrate the use of
knowledge-based techniques for process and data integration with a case study
of the CAPTEN [Computer Assisted Picture Tube Engineering] Project underway
at the David Sarnoff Research Center.
------------------------------
Date: Sat, 21 Feb 1987 12:49 CST
From: Laurence L. Leff <E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Seminar - Parallel Techniques in Computer Algebra (SMU)
Seminar Announcement, Friday February 27, 1987, 315 SIC,
1:30 PM, Southern Methodist University
Stephen Watt
ABSTRACT: PARALLEL TECHNIQUES IN COMPUTER ALGEBRA
This talk presents techniques for exploiting parallel proc-
essing in symbolic mathematical computation. We examine the
use of high-level parallelism when the number of processors
is fixed and independent of the problem size, as in existing
multiprocessors.
Since seemingly small changes to the inputs can cause dra-
matic changes in the execution times of many algorithms in
computer algebra, it is not generally useful to use static
scheduling. We find it is possible, however, to exploit the
high-level parallelism in many computer algebra problems us-
ing dynamic scheduling methods in which subproblems are
treated homogeneously. An OR-parallel algorithm for integer
factorization will be presented along with AND-parallel al-
gorithms for the computation of multivariate polynomial GCDs
and the computation of Groebner bases.
A portion of the talk will be used to present the design of
a system for running computer algebra programs on a multi-
processor. The system is a version of Maple able to dis-
tribute processes over a local area network. The fact that
the multiprocessor is a local area network need not be con-
sidered by the programmer.
------------------------------
Date: Thu, 19 Feb 87 09:57:35 EST
From: "William J. Rapaport" <rapaport%buffalo.csnet@RELAY.CS.NET>
Subject: Seminar - A Picture Theory of Mental Images (SUNY)
STATE UNIVERSITY OF NEW YORK AT BUFFALO
GRADUATE GROUP IN COGNITIVE SCIENCE
MICHAEL J. TYE
Department of Philosophy
Northern Illinois University
A PICTURE THEORY OF MENTAL IMAGES
The picture theory of mental images has become a subject of hot debate
in recent cognitive psychology. Some psychologists, notably Stephen
Kosslyn, have argued that the best explanation of a variety of experi-
ments on imagery is that mental images are pictorial. Although Kosslyn
has valiantly tried to explain just what the basic thesis of the pic-
torial approach (as he accepts it) amounts to, his position remains dif-
ficult to grasp. As a result, I believe, it has been badly misunder-
stood, both by prominent philosophers and by prominent cognitive scien-
tists.
My aims in this paper are to present a clear statement of the picture
theory as it is understood by Kosslyn, to show that this theory presents
no threat to the dominant digital-computer model of the mind (contrary
to the claims of some well-known commentators), and to argue that the
issue of imagistic indeterminacy is more problematic for the opposing
linguistic or descriptional view of mental images than it is for the
picture theory.
Monday, March 9, 1987
3:30 P.M.
Park 280, Amherst Campus
Co-sponsored by: Department of Philosophy
Informal discussion at 8:00 P.M. at a place to be announced. Call Bill
Rapaport (Dept. of Computer Science, 636-3193 or 3181) or Gail Bruder
(Dept. of Psychology, 636-3676) for further information.
William J. Rapaport
Assistant Professor
Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260
(716) 636-3193, 3180
uucp:
..!{allegra,boulder,decvax,mit-ems,nike,rocksanne,sbcs,watmath}!sunybcs!rapaport
csnet: rapaport@buffalo.csnet
bitnet: rapaport@sunybcs.bitnet
------------------------------
Date: 20 Feb 87 02:01:33 GMT
From: chandros@topaz.RUTGERS.EDU (Jonathan A. Chandross)
Subject: Seminar - Minds, Machines, and Searle (Rutgers)
USACS
is pleased to announce
a talk by Stevan Harnad on
Minds, Machines, and Searle
Tuesday, February 24th
Hill Center Room 705
at 5:30 PM
For those of you who aren't familiar with Stevan Harnad, he is the
editor of the Brain and Behaviorial Sciences journal (where Searle's
Chinese Room argument first appeared), as well as a regular poster
to mod.ai.
If you would like to come to dinner with us please send mail to:
rutgers!topaz!chandross. I need to know by Monday (2/23) at the
latest to make reservations. For further information, or a transcript
of the talk, send email.
SUMMARY AND CONCLUSIONS:
Searle's provocative "Chinese Room Argument" attempted to show that the
goals of "Strong AI" are unrealizable. Proponents of Strong AI are supposed
to believe that (i) the mind is a computer program, (ii) the brain is
irrelevant, and (iii) the Turing Test is decisive. Searle's point is that
since the programmed symbol-manipulating instructions of a computer capable of
passing the Turing Test for understanding Chinese could always be performed
instead by a person who could not understand Chinese, the computer can hardly
be said to understand Chinese. Such "simulated" understanding, Searle argues,
is not the same as real understanding, which can only be accomplished by
something that "duplicates" the "causal powers" of the brain. In the present
paper the following points have been made:
1. Simulation versus Implementation:
Searle fails to distinguish between the simulation of a mechanism, which is
only the formal testing of a theory, and the implementation of a mechanism,
which does duplicate causal powers. Searle's "simulation" only simulates
simulation rather than implementation. It can no more be expected to understand
than a simulated airplane can be expected to fly. Nevertheless, a successful
simulation must capture formally all the relevant functional properties of a
successful implementation.
2. Theory-Testing versus Turing-Testing:
Searle's argument conflates theory-testing and Turing-Testing. Computer
simulations formally encode and test models for human perceptuomotor and
cognitive performance capacities; they are the medium in which the empirical
and theoretical work is done. The Turing Test is an informal and open-ended
test of whether or not people can discriminate the performance of the
implemented simulation from that of a real human being. In a sense, we are
Turing-Testing one another all the time, in our everyday solutions to the
"other minds" problem.
3. The Convergence Argument:
Searle fails to take underdetermination into account. All scientific theories
are underdetermined by their data; i.e., the data are compatible with more
than one theory. But as the data domain grows, the degrees of freedom for
alternative (equiparametric) theories shrink. This "convergence" constraint
applies to AI's "toy" linguistic and robotic models as well, as they approach
the capacity to pass the Total (asympototic) Turing Test. Toy models are not
modules.
4. Brain Modeling versus Mind Modeling:
Searle also fails to note that the brain itself can be understood only through
theoretical modeling, and that the boundary between brain performance and body
performance becomes arbitrary as one converges on an asymptotic model of total
human performance capacity.
5. The Modularity Assumption:
Searle implicitly adopts a strong, untested "modularity" assumption to the
effect that certain functional parts of human cognitive performance capacity
(such as language) can be be successfully modeled independently of the rest
(such as perceptuomotor or "robotic" capacity). This assumption may be false
for models approaching the power and generality needed to pass the Total
Turing Test.
6. The Teletype versus the Robot Turing Test:
Foundational issues in cognitive science depend critically on the truth or
falsity of such modularity assumptions. For example, the "teletype"
(linguistic) version of the Turing Test could in principle (though not
necessarily in practice) be implemented by formal symbol-manipulation alone
(symbols in, symbols out), whereas the robot version necessarily calls for
full causal powers of interaction with the outside world (seeing, doing
AND linguistic understanding).
7. The Transducer/Effector Argument:
Prior "robot" replies to Searle have not been principled ones. They have added
on robotic requirements as an arbitrary extra constraint. A principled
"transducer/effector" counterargument, however, can be based on the logical
fact that transduction is necessarily nonsymbolic, drawing on analog and
analog-to-digital functions that can only be simulated, but not implemented,
symbolically.
8. Robotics and Causality:
Searle's argument hence fails logically for the robot version of the Turing
Test, for in simulating it he would either have to USE its transducers and
effectors (in which case he would not be simulating all of its functions) or
he would have to BE its transducers and effectors, in which case he would
indeed be duplicating their causal powers (of seeing and doing).
9. Symbolic Functionalism versus Robotic Functionalism:
If symbol-manipulation ("symbolic functionalism") cannot in principle
accomplish the functions of the transducer and effector surfaces, then there
is no reason why every function in between has to be symbolic either.
Nonsymbolic function may be essential to implementing minds and may be a
crucial constituent of the functional substrate of mental states ("robotic
functionalism"): In order to work as hypothesized, the functionalist's
"brain-in-a-vat" may have to be more than just an isolated symbolic
"understanding" module -- perhaps even hybrid analog/symbolic all the way
through, as the real brain is.
10. "Strong" versus "Weak" AI:
Finally, it is not at all clear that Searle's "Strong AI"/"Weak AI"
distinction captures all the possibilities, or is even representative of the
views of most cognitive scientists.
Hence, most of Searle's argument turns out to rest on unanswered questions
about the modularity of language and the scope of the symbolic approach to
modeling cognition. If the modularity assumption turns out to be false, then
a top-down symbol-manipulative approach to explaining the mind may be
completely misguided because its symbols (and their interpretations) remain
ungrounded -- not for Searle's reasons (since Searle's argument shares the
cognitive modularity assumption with "Strong AI"), but because of the
transdsucer/effector argument (and its ramifications for the kind of hybrid,
bottom-up processing that may then turn out to be optimal, or even essential,
in between transducers and effectors). What is undeniable is that a successful
theory of cognition will have to be computable (simulable), if not exclusively
computational (symbol-manipulative). Perhaps this is what Searle means (or
ought to mean) by "Weak AI."
------------------------------
End of AIList Digest
********************
∂23-Feb-87 0216 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #53
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 23 Feb 87 02:16:34 PST
Date: Sun 22 Feb 1987 21:59-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #53
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 23 Feb 1987 Volume 5 : Issue 53
Today's Topics:
Conferences - Possible Workshop on Real-Time at AAAI-87 &
12th IMACS, 2nd-Generation Expert Systems &
Workshop on Computer Architecture for PAMI
----------------------------------------------------------------------
Date: 16 Feb 1987 19:40-EST
From: cross@wpafb-afita
Subject: Conference - Possible Workshop on Real-Time at AAAI-87
I am proposing a workshop on real-time processing in knowledge-based
systems to be held at AAAI-87. At the present time I am looking for
suggestions about the workshop content and format (draft announcement
follows). Pending approval from the AAAI-87 Workshop Committee, I'll
place a formal announcement on AILIST and solicit participation. Thanks
in advance for your input. Steve Cross
************************************************************************
Workshop on Real-Time Processing in Knowledge-Based Systems
AI techniques are maturing to the point where application
in knowledge intensive, but time constrained situations is
desired. Examples include monitoring large dynamic systems such
as nuclear power plants; providing timely advice based on time
varying data bases such as in stock market analysis; sensor
interpretation and management in hospital intensive care units,
or in military command and control environments; and diagnoses
of malfunctions in airborne aircraft. The goal of the workshop
is to gain a better understanding of the fundamental issues that
now preclude real-time processing and to provide a focus for
future research. Specific issues that will be discussed include:
Pragmatic Issues: What is real-time performance? What
metrics are available for evaluating performance?
Parallel Computation: How can parallel computation be
exploited to achieve real-time performance? What performance
improvements can be gained by maximizing and integrating the
inherent parallelism at all levels in a knowledge-based system
(e.g., application through the hardware levels).
Meta-Level Problem Solving: How can intelligent problem
solving agents reason about and react to varying time-to-solution
resources? What general purpose or domain specific examples
exist of problem solving strategies employed under different
time-to-solution constraints? What are the tradeoffs in terms of
space, quality of solution, and completeness of solution.
Complexity Issues: How can an intelligent agent reason
about the inherent complexity of a problem?
Algorithm Issues: What novel problem solving methods can be
exploited? How can specialized hardware (for example , content
addressable memories) be exploited?
To encourage vigorous interaction and exchange of ideas
between those attending, the workshop will be limited to
approximately 30 participants (and only two from any one
organization). The workshop is scheduled for July xx, 1987, as a
parallel activity during AAAI 87, and will last for a day.
[Because of planning conflicts, we may meet on one evening and
lay plans for a more involved workshop in August or September].
All participants are required to submit an abstract (up to
1000 words) and a proposed list of discussion questions. Five
copies should be submitted to the workshop chairman by May 1,
1987. The discussion questions will help the workshop
participant's focus on the fundamental issues in real-time AI
processing.
Because of the brief time involved for the workshop,
participants will be divided into several discussion groups. A
group chairman will present a 30 minute summary of his group's
abstracts during the first session. In addition, the committee
reserves the right to arrange for invited presentations. Each
group will be assigned several questions for discussion. Each
group will provide a summary of their groups discussion. The
intent of the workshop is to promote creative discussion which
will spawn some exciting ideas for research.
Workshop Chairman:
Stephen E. Cross, AFWAL/AAX, Wright-Patterson AFB OH 45433-
6583, (513) 255-5800. arpanet: cross@wpafb-afitab.arpa
------------------------------
Date: Thu, 19 Feb 87 17:59:19
From: mcvax!crcge1!david@seismo.CSS.GOV (Jean-Marc David)
Subject: Conference - 12th IMACS, 2nd-Generation Expert Systems
12th IMACS WORLD CONGRESS' 88
PARIS - July 18 - 22, 1988
CALL FOR PAPERS
=================
********************************************************
* *
* SECOND GENERATION EXPERT SYSTEMS *
* *
* Reasoning with Heuristic and Deep Knowledge *
* *
********************************************************
The 12th IMACS WORLD CONGRESS' 88 on Scientific Computation
will be hold in Paris, France (July 18-22, 1988).
A one-day session of the Congress will be devoted to
SECOND GENERATION EXPERT SYSTEMS.
Authors are invited to submit papers describing Expert
Systems reasoning with Deep Knowledge, or any aspect of deep
reasoning ; the covered topics include:
- Model-Based Reasoning
- Qualitative Physics
- Multi-Level / Multi-Model Reasoning
- Reasoning from Structure, Behavior and Function
- Causal Reasoning
Papers can deal with both theoretical aspects of deep
reasoning and applications (diagnosis, process control,
simulation ...).
Emphasis will be put on work describing cooperation between
Heuristic and Deep Reasoning.
Submission Information :
========================
Submit three copies of a 1000 words abstract by August 1,
1987 to the Session Chairman. Papers will be accepted on
the basis of submitted abstracts. Notifications of
acceptance will be mailed by December 1, 1987.
Accepted papers will be either original contributions or
important survey papers.
Timetable :
===========
- abstracts submission: August 1, 1987
- notifications of acceptance: December 1, 1987
- full papers submission: February 15, 1988
Submissions and inquiries about the Second Generation Expert
System Session should be sent to the Session Chairman:
Jean-Marc DAVID
IMACS '88
Laboratoires de Marcoussis
Computer Science Division
Route de Nozay
91460 - Marcoussis
FRANCE
Other inquiries should be directed to the Congress
Secretariat :
Secretariat IMACS WORLD CONGRESS '88
I.D.N. BP 48
59651 - Villeneuve d'Ascq Cedex
FRANCE
------------------------------
Date: Thu, 19 Feb 87 16:45:36 CST
From: dyer@stilton.wisc.edu (Chuck Dyer)
Subject: Conference - Workshop on Computer Architecture for PAMI
CALL FOR PAPERS
1987 WORKSHOP ON COMPUTER ARCHITECTURE FOR
PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Seattle, Washington
October 5 - 7, 1987
CAPAMI-87 will focus on new architectures and associated
algorithms designed for artificial intelligence
applications. This workshop is a successor of the Computer
Architecture for Pattern Analysis and Image Database
Management workshops which were held in '81, '83, and '85.
The emphasis of the program will be the presentation of
significant new contributions plus panel and discussion
sessions in which attendees can actively compare and
contrast their methods. Papers will be reviewed by the
Program Committee. No parallel sessions are planned.
TOPICS
* Computer Vision and Image Processing Architectures
* Architectures for Inference Engines and Rule-Based Systems
* Knowledge-Based Machines and Systems
* Neural Network based Architectures
* VLSI and Systolic Implementations
* Parallel Algorithms for AI Problems on these Architectures
* Parallel Matching and Reasoning Algorithms
PAPER SUBMISSION INSTRUCTIONS
Authors should submit four (4) copies of a complete paper by
APRIL 15, 1987 to:
Charles R. Dyer
Department of Computer Science
University of Wisconsin
1210 W. Dayton St.
Madison, WI 53706
Authors will be notified of the acceptance of their papers
by June 1, 1987. Final camera-ready papers are due by July
15, 1987.
WORKSHOP ORGANIZATION
Workshop Chair: Steven L. Tanimoto
Program Chair: Charles R. Dyer
Program Committee: Christopher M. Brown James J. Little
Michael J. B. Duff Azriel Rosenfeld
Robert M. Haralick Jorge L. C. Sanz
Ramesh Jain Leonard M. Uhr
John R. Kender Jon A. Webb
H. T. Kung
------------------------------
End of AIList Digest
********************
∂24-Feb-87 0013 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #54
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 24 Feb 87 00:13:15 PST
Date: Mon 23 Feb 1987 22:28-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #54
To: AIList@SRI-STRIPE.ARPA
AIList Digest Tuesday, 24 Feb 1987 Volume 5 : Issue 54
Today's Topics:
Administrivia - Problem with Issue 51,
Queries - Financial Expert Systems & Real-Time AI &
Recognition of Text Written by Hand & Automatic Theorem Proving &
Network Complexity & DBMS Issues in KBs
----------------------------------------------------------------------
Date: Mon 23 Feb 87 10:46:16-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Reply-to: AIList-Request@SRI-AI.ARPA
Subject: Problem with Issue 51
Some of you may have found only a single message in Volume 5, No. 51,
the analysis of Artificial Intelligence citations (by Lawrence Leff).
That issue also contained a discussion by John McCarthy on taking
a "design stance" towards the cognition problem and a review of a
review of Minsky's new book.
Unfortunately, the first message ended with a line containing a single
period. This is take as an end-of-message flag by some mailers, and
so the second and third messages were lost or hidden.
If you need a remailing of the issue, with the offending line removed,
just send a request to AIList-Request@SRI-STRIPE.ARPA.
-- Ken Laws
------------------------------
Date: Mon 23 Feb 87 09:28:41-PST
From: Frances Borison <BORISON@SRI-KL.ARPA>
Subject: Financial Expert Systems
Does anyone know of any financial expert systems that are commercially
available for purchase and that run on either general purpose computers or AI
workstations? I am aware of Planpower by Applied Expert Systems
(APEX) and Financial Advisor by Palladian Software. Any assistance
would be appreciated.
Frances Borison.
------------------------------
Date: 23 Feb 87 18:35:44 GMT
From: teknowledge-vaxc!rburns@SRI-UNIX.ARPA (Randy Burns)
Subject: Wanted speaker familiar with financial applications of AI
A friend of mine is involved with an IEEE group which is sponsoring a
seminar on financial applications of Artificial Intelligence. I would
appreciate anyone with experience in this area to contact me so I can
forward your name to him.
Randy Burns
Teknowledge Inc.
415-424-0500 x543
------------------------------
Date: 17 Feb 87 12:26:52 GMT
From: mcvax!ukc!tcom!idec!camcon!ijd@seismo.css.gov (Ian Dickinson)
Subject: Research in Real-Time A.I.
I'm currently engaged in a small research project looking at the problems
of updating AI databases in real time. [By database, I mean that collection
of information that I am currently reasoning against - not the large
commercial variety.]
A typical problem in the domain is that you have N (where large(N)) sensors
attached to a process plant all throwing lots of data with low information
content at an intelligent fault diagnosis system. The system has to cope
with contradictory data, have good coverage of the incoming signals, but
still be able to respond quickly to high-priority situations.
The particular issues that I am concerned with are:
(1) what are the representational inadequacies of current AI notations
that are suited to doing real time problems and/or handling noisy and
contradictory data?
(2) what are the computational costs of using such notations?
Primary choices for handling mucky, changing data are the RMS family
(Doyle, de Kleer etc) and other non-monotonic logics, so these are typical
of the notations that I am referring to. So the issues become: what can't
you do with them, and what would it cost anyway?
The questions I would like to submit to net.land are:
o anybody doing any work on extending non-monotonic notations in wierd
directions (eg integrating them with uncertain inference techniques)?
o anybody got any pet real-time AI problems?
o anyone else working in the real-time field?
Please mail responses directly to me, and I will post a summary for
discussion later.
Thanks in advance,
Ian.
--
!! Ian Dickinson Cambridge Consultants Ltd, AI group !!
!! Voice: (0223) 358855 [U.K.] Email: ijd%camcon.co.uk !!
!! uucp: ...!seismo!mcvax!ukc!camcon!ijd or: ijd%camcon.uucp !!
>> Disclaimer: All opinions expressed are my own (surprise!). <<
------------------------------
Date: Thu, 19 Feb 87 22:45:18 +0100
From: Hakon Styri <styri%vax.runit.unit.uninett@NTA-VAX.ARPA>
Subject: Recognition of text written by hand
Is there anybody with knowledge about work going on in the field of
machine recognition of text written by hand. I'm not interested in
"understanding" the text, just converting it into machine readable
form. And, the text is already written so special pen and paper is
no good.
------------------------------
Date: 20 Feb 87 04:32:09 GMT
From: cartan!brahms.Berkeley.EDU!cotner@ucbvax.Berkeley.EDU (Carl
Cotner)
Subject: automatic theorem proving
Can anyone on the net recommend any books or articles about
automatic theorem proving? I am interested (I think) in the subject,
but know almost anything about it. Any reference would be very
welcomed. Thanks.
ucbvax!brahms!cotner Carl Cotner/UCB Math Dept/Berkeley CA 94720
------------------------------
Date: 19 Feb 87 22:47:52 GMT
From: ihnp4!ihnp3!mth@ucbvax.Berkeley.EDU (Mark Horbal)
Subject: Network Complexity
(sorry if this is a duplicate posting, but my machine burped)
I am in the process of putting together a paper which attempts to
motivate planning and development of software based Network Management tools.
In general, such tools would be both STRATEGIC, eg. network topology planning,
from the perspective of capacity, security, fault tolerance, etc, and
TACTICAL, such as visualization of network activity, dynamic routing, fault
recovery, congestion avoidance, etc. Clearly, this fields is ready for
and in desperate need of AI, which is why I'm addressing it to this group.
Now, my intuition tells me that as these networks become more complicated,
we'll realize that the seat-of-the-pants network management we're used to is
inadequate, and we'll wish that we had spent time developing the right tools
to do the job. I envision the complexity of our computer networks to be
exploding at some exponential rate, while our ability to understand and
control them is falling behind, growing relatively slowly. This brings
me to my QUESTION:
If we define the "complexity" of a computer network as a
measure of difficulty in observing, understanding, and
excercising a modicum of control over it, how is this
"complexity" estimated?
If we further choose a simple but intuitive way of representing
a computer network by a graph, how do we quantify this "complexity"
with respect to the graph's topology?
Clearly metrics such as the number of nodes, edges circuits etc have intuitive
appeal, but do not individually seem to convey the underlying combinatorial
explosion that, I believe, lurks underneath.
Are you aware of any analytic, graph-theoretical, heuristic, empirical,
or otherwise useful metrics of such "complexity"? I am not necessarily
looking for some absolute measure of the thing, but general concepts.
Any facts, comments, opinions and thoughts will be most appreciated.
M. Horbal
@ Bell Labs
ihnp4!ihnp3!mth
(312) 979-6496
------------------------------
Date: Mon, 23 Feb 87 13:01:35 EST
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: DBMS issues in KBs
A colleague is interested in what work has been done involving the
traditional concerns of a DBMS for Knowledge Bases (e.g. concurrency,
security, query optimization, etc). I don't think that these issues
have been addressed in any systematic way. Can anyone offer any
references to work regarding such things?
From: Susan Davidson <Susan@cis.upenn.edu>
Date: Thu, 19 Feb 87 15:00 EST
Can you point me to any papers that speak to the exact problems of updating,
concurrency, optmization, etc. in knowledge bases?
sbd
------------------------------
End of AIList Digest
********************
∂24-Feb-87 0141 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #55
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 24 Feb 87 01:41:04 PST
Date: Mon 23 Feb 1987 22:35-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #55
To: AIList@SRI-STRIPE.ARPA
AIList Digest Tuesday, 24 Feb 1987 Volume 5 : Issue 55
Today's Topics:
AI Tools - Language Comparisons & Prolog & DEC AI Workstation,
Application - Legal Reasoning,
Literature - Learing about AI & Automatic Theorem Proving
----------------------------------------------------------------------
Date: 19 Feb 87 12:31:00 EST
From: "CUGINI, JOHN" <cugini@icst-ecf>
Reply-to: "CUGINI, JOHN" <cugini@icst-ecf>
Subject: speaking of language comparisons
I just finished up a report, published by the Institute for Computer
Sciences and Technology / National Bureau of Standards, comparing
Common Lisp, C-Prolog, and OPS5. This is a nitty-gritty comparison-
of-features type of paper, 70 pages. It's targeted at programmers
who are just entering the wonderful world of knowledge-based systems.
The grizzled AI veteran will probably not find a wealth of new
insights.
Anyway, for those interested, it's:
NBS Special Publication 500-145
Programming Languages for Knowledge-Based Systems
order from:
Superintendent of Documents
US Government Printing Office
Washington DC 20402
GPO stock number: 003-003-02783-9
price: $4.00
John Cugini <Cugini@icst-ecf>
------------------------------
Date: 11 Feb 87 12:30:00 GMT
From: mcvax!unido!ztivax!steve@seismo.css.gov
Subject: Re: prolog information wanted - (nf)
>I am looking for a good book or two about frame based systems implemented
>in Prolog. I am especially interested in examples of code and data
>structures. If you know of any such books, please send the name, etc.,
>to this login. Thanks in advance.
>
> Lance
> ihnp4!ihuxj!lance
I thought Prolog didn't have any data structures :-)
------------------------------
Date: 18 Feb 87 21:29:42 PST (Wed)
From: spar!malcolm@decwrl.DEC.COM
Subject: Re: DEC AI Workstation
In article <8702121349.AA14488@csv.rpi.edu> yerazuws@CSV.RPI.EDU (Crah) writes:
> I wouldn't bother with the SUN, especially in a diskless
>configuration. I wasted (yes, wasted) nine months trying to develop
>an architecture simulator on Sun 2's. Little things like a server
>being slow can completely hang your LISP and your editor - so you sit.
>And sit. And forget what you were doing...
You're right....don't even think about running Lisp on a Sun-2. On the
other hand Sun-3's (which are three times faster in general than Sun-2's)
make a fast lisp workstation.
BUT, you must have enough memory on the system to make sure that you
don't page when you garbage collect. I work with both Franz and Lucid
Common Lisp and they both copy the workspace to garbage collect. When you
have to go to the disk (or network) every time you want to garbage collect
then you lose big. And then you finish GC and start doing real work again
and all the pages you want have already been flushed.
I suspect that the reason the limited memory isn't as much a factor with
Symbolics workstations is because they do incremental garbage collection.
When you are working normally everything works fast.....but go away for
a while and come back and watch the swap bar turn solid black for a few
seconds.
Franz Common Lisp can run quite nicely in 9M of memory. Memory is real
cheap these days. I have 16M on my desk and I almost never page while
switching back and forth between Lisp and other windows I am using.
As far as performance goes, I have seen a Sun3/160 running anywhere between
.5 and 4 times a Symbolics 3600. Moving to a Sun3/260 gives you another
factor of two performance improvement. Sun's can match the speed of a
Symbolics workstation....now if they can just make the environment as nice.
Cheers.
Malcolm
------------------------------
Date: Thu, 19 Feb 87 09:50:27 est
From: mnetor!lsuc!dave@seismo.CSS.GOV
Subject: Re: Legal reasoning
To: watmath!clyde!cbatt!ucbvax!ENIAC.SEAS.UPENN.EDU!mayerk
Subject: Re: Legal reasoning
Newsgroups: mod.ai
In-Reply-To: <8702160344.AA01571@eniac.seas.upenn.edu>
Organization: Law Society of Upper Canada, Toronto
Cc: mnetor!seismo!sri-stripe.arpa!ailist
In article <8702160344.AA01571@eniac.seas.upenn.edu> you write:
>
>Could someone give some pointers into the literature about legal
>reasoning. Or better yet, someone you know whom I could contact.
There's a conference coming up in May at Northeastern University
in Boston, the First International Conference on Artificial
Intelligence and Law. Contact Carole Hafner at Northeastern
or Thorne McCarty at Rutgers (mccarty@rutgers.edu).
Major projects which have been undertaken include McCarty's
TAXMAN system, Kowalski & Sergot's work in Prolog at
Imperial College (Univ. of London), Jim Sprowl's ABF
Processor, Layman Allen & Charles Saxon's work at U of
Michigan, and many others. Check the Rutgers Journal of
Computers, Technology & the Law; also law periodical
indexes under "automation".
There have been two conferences on Law & Computers at the
Univ of Houston, organized by Charles Walter. The 1984 conference
papers were published as a book, "Computing Power and Legal
Reasoning", published by West Publishing Co (St. Paul, MN),
ISBN 0-314-96670-4. The 1985 papers haven't yet been published
that I know of. Both had papers from just about everyone working
in this field in North America, as well as a few from Europe.
I recently completed an LL.M. thesis, "Blueprint for a Computer-Based
Model of the Income Tax Act of Canada", at Osgoode Hall Law School
(York University, Toronto), which contains an implementation of
tax law in Prolog and surveys previous work. (I've also submitted
a condensed version as a paper to the AI & Law conference.)
I can send you a copy if you like.
David Sherman
The Law Society of Upper Canada
Osgoode Hall
Toronto, Canada M5B 2N6
(416) 947-3466
dave@lsuc.UUCP
{ seismo!mnetor cbosgd!utgpu watmath decvax!utcsri ihnp4!utzoo } !lsuc!dave
------------------------------
Date: 17 Feb 87 17:27:59 GMT
From: ubc-vision!ubc-cs!andrews@BEAVER.CS.WASHINGTON.EDU (Jamie Andrews)
Subject: Re: Learing about AI
In article <278@vax1.ccs.cornell.edu> czhj@vax1.UUCP (Ted Inoue) writes:
>But look at the approach that LOGIC gives AI. It is a purely reductionist
>view, akin to studying global plate motion at the level of sub-atomic
>particles. It is simply the wrong level at which to approach the problem.
This is too generalized. There are good applications of logic
to AI, and there are bad ones. Only by knowing a lot about logic *and*
the structure of the problem domain can you tell which is which.
I would agree that predicate logic techniques have often been
applied to problems in a way that leaves out inordinately large chunks
of the domain. However, the same could be said about most AI techniques.
--Jamie.
...!seismo!ubc-vision!ubc-cs!andrews
"Take my shoes off & throw them in the lake"
------------------------------
Date: 21 Feb 87 22:07:01 GMT
From: ihnp4!chinet!nucsrl!ragerj@ucbvax.Berkeley.EDU (John Rager)
Subject: Re: Learing about AI (was Re: A List of AI Books (for
beginners))
from: / sher@rochester.ARPA (David Sher) / 8:17 am Feb 13, 1987 /
>I think there seems to be something of a misconception regarding the
>place of logic wrt AI and computer science in general. To start with
>I will declare this:
> Logic is a language for expressing mathematical constructs.
>It is not a science and as far as artificial intelligence is concerned
>the mathematics of logic are not very relevant. Its main feature
>is that it can be used for precise expression.
Logic is a branch of mathematics. The last time I checked mathematics
was a science. Its relevancy to AI is a matter of opinion.
> So why use logic rather than a more familiar language, like english.
> ...
> However the problem is that few of us knowledge
> engineers have the talent to be precise in our everyday language.
>Thus for decades engineers, scientists, and statisticians have used
>logic to express their ideas since even an incompetent speaker can be
>clear and precise using logical formalisms. However like any language
>with expressive power one can be totally incomprehensible using logic.
First, you aren't talking about Logic, you are talking
about mathematical notation. Second, the reason that mathematicians use
this notation has nothing to do with their inability to express concepts in
English. It has to do with the inexpressibliity of the concepts in 'ordinary
English'. Mathematical notation is the specialized language of the
mathematical disciplines. All disciplines have a specialized language, a set
of terms with precise meanings in that field. A good philosopher, writing
a good paper, writes in what seems to be ordinary English. It is not. It is
English augmented by the argot of the field. This is true even though the
difference may not be obvious to an outsider, since it looks like English.
The language of mathematics doesn't look like English.
So where does this leave English? It is a wonderful language and I love it.
It is not a specialized tool for working in a particular discipline. It
is a means of everyday communication, an amazing miracle of generality.
It does not have the expressive power of logic. Do not try to use it for what
it is not suited for. (Before anyone says anything, when the first English
grammars were devised they were modeled on these of Latin, in which
language one does not end sentences with prepositions. It has always been
common practice to use propositions as sentence-ending particles in English.)
>Note: I am not a logician but I use a lot of logic in my everyday
>work which is probabilistic analysis of computer vision problems
>-David Sher
When you say you use a lot of logic, do you really mean it? Recursive
function theory? Saturated model theory? Or do you mean you use the
vernacular of the mathematician?
John Rager
sher@rochester
{allegra,seismo}!rochester!sher
------------------------------
Date: 23 Feb 87 16:56:02 GMT
From: jbn@glacier.stanford.edu (John B. Nagle)
Subject: Re: automatic theorem proving
The best thinking on the subject is in "A Computational Logic", by
Robert Boyer and Jay Moore (Academic Press, 1979, ISBN 0-12-122950-5).
The field has regressed somewhat since then.
John Nagle
------------------------------
End of AIList Digest
********************
∂24-Feb-87 2322 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #56
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 24 Feb 87 23:22:21 PST
Date: Tue 24 Feb 1987 20:48-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #56
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 25 Feb 1987 Volume 5 : Issue 56
Today's Topics:
Query - Parallel Alpha-Beta Search,
Logic - Automated Deduction References,
News - IJCAI-87 Computers and Thought Award,
Discussion - Programming Metaphors & Logic in AI & Intelligence
----------------------------------------------------------------------
Date: Tue, 24 Feb 87 17:11:03 EST
From: "Neil B. Cohen" <ncohen@cc-washington.bbn.com>
Subject: Parallel alpha-beta search
I was told to contact you about a paper that has been recently written
in the subject of parallel alpha-beta tree searching. Can you tell me
if such a paper was recently published, and if so, where I can get
a copy of it? I am very interested in trying to apply such a technique
on the BBN Butterfly computer.
Thanks in advance for any help you can give me.
Neil B. Cohen (nbc@bbn.com)
------------------------------
Date: Tue, 24 Feb 87 13:16:45 pst
From: ladkin@kestrel.ARPA (Peter Ladkin)
Subject: automated deduction references
Some of the best sources for Automated Theorem Proving are
conference proceedings and journal articles.
Springer publishes the proceedings of the Conference on
Automated Deduction, held in even years. The last is
Lecture Notes in Computer Science 230, CADE-8 (ed. Siekmann).
Also LNCS 232, Fundamentals of Artificial Intelligence, (ed. Bibel
and Jorrand) has good material on Automated Deduction.
LNCS 202 is Rewriting Techniques and Applications (ed. Jouannaud),
another European conference on theorem proving by algebraic
term rewriting systems.
The Journal of Automated Reasoning and the Journal of Symbolic
Computation have been started in the last couple of years.
This is by no means a complete list. Taking the transitive closure
of the `referenced' relation on this material will probably lead
to a complete list.
peter ladkin
ladkin@kestrel.arpa
------------------------------
Date: Tue, 24 Feb 87 10:29:40 GMT
From: Alan Bundy <bundy%aiva.edinburgh.ac.uk@Cs.Ucl.AC.UK>
Subject: IJCAI-87 Computers and Thought Award
THE 1987 COMPUTERS AND THOUGHT AWARD
It is my great pleasure to announce that the winner of the
1987 Computers and Thought Award is Johan de Kleer of Xerox Palo Alto
Research Center. The Award is in recognition of his fundamental
contributions to artificial intelligence research in the areas of:
qualitative reasoning, truth maintenance, constraint propagation and
explicit control of reasoning.
The Computers and Thought Lecture is given at each
International Joint Conference on Artificial Intelligence by an
outstanding young scientist in the field of artificial intelligence.
The Award carries with it a certificate and the sum of $2,000 plus
travel and subsistence expenses for the IJCAI. The Lecture is one
evening during the Conference, and the public is invited to attend.
The Lecturer is invited to publish the Lecture in the conference
proceedings. The Lectureship was established with royalties received
from the book Computers and Thought, edited by Feigenbaum and Feldman;
it is currently supported by income from IJCAI funds.
Nominations for The 1987 Computers and Thought Award were invited
from all in the artificial intelligence international community. The
award selection committee was the union of the Programme, Conference
and Advisory Committees of IJCAI-87 and the Board of Trustees of
IJCAII, with nominees excluded.
Past recipients of this honour have been Terry Winograd
(1971), Patrick Winston (1973), Chuck Rieger (1975), Douglas Lenat
(1977), David Marr (1979), Gerald Sussman (1981), Tom Mitchell (1983)
and Hector Levesque (1985).
Alan Bundy
IJCAI-87 Conference Chair
------------------------------
Date: 23 Feb 87 20:00:41 EST
From: Raul.Valdes-Perez@b.gp.cs.cmu.edu
Subject: Prog. Lang. Metaphors
[Forwarded from the CMU bboard by Laws@SRI-STRIPE.]
This posting is the result of the query for metaphors that underlie
programming languages. Everything onward from (14) was compiled from
suggestions. The items upto (13) were the original ideas.
METAPHOR LANGUAGE
1. function application (lambda calculus) Pure Lisp
2. variable assignment Fortran
3. message-passing Smalltalk
4. set manipulation SETL, relational databases
5. modus ponens Prolog
6. array manipulation APL
7. constraints spreadsheets
8. rewriting production systems
9. window manipulation window managers
10. algorithm manipulation (?!) Lenat's dissertation (AI)
11. resolution resolution theorem provers
12. string manipulation SNOBOL
13. states (and transitions)? graphs?
14. List processing is a metaphor for Lisp & IPL-V
15. Does LOGO have a metaphor? [A metaphor for the graphical part of LOGO
is a moving turtle. - RVP]
16. "... metaphors involved in user interactions and the influence they
have on system design. (There is a session on metaphors at the
SIGCHI in April)"
Desktop metaphor
Electronic Book metaphor
Rooms metaphor (a method of organizing windows dealing with a
particular application into a class of windows. e.g. mailroom)
Overlay or transparency metaphor
Hierarchical metaphor
Network metaphor (Zog or Notecards are systems that use this
metaphor)
17. File [stream?] manipulation is a metaphor in UNIX.
18. Patterns in Snobol-4.
19. Type inference ML
Dataflow ID (Arvind)
Concurrent programming CSP, Linda, Multilisp
Structured programming (iffy) Pascal
20. Couple of relevant papers: "The Scientific Community Metaphor" by
Kornfeld & Hewitt, IEEE Trans. on Systems, Man, & Cybernetics Jan 81;
"Metaphor and the Cognitive Representation of Computing Systems" by
Carroll & Thomas, same journal, Mar/Apr 82.
------------------------------
Date: Tue, 24 Feb 87 13:47:23 pst
From: ladkin@kestrel.ARPA (Peter Ladkin)
Subject: logic in ai
david sher said:
>Note: I am not a logician but I use a lot of logic in my everyday
>work which is probabilistic analysis of computer vision problems
john rager replied:
>When you say you use a lot of logic, do you really mean it? Recursive
>function theory? Saturated model theory?
Rager asks whether Sher uses infinitary methods in what seems to
be a finitary context. The answer is obviously no, and I wonder
why he would ask the question? Maybe he thinks that all logic
is infinitary? Meanwhile, he seems to have forgotten that inference
is the basis of logic, and most of us use that in one form or another.
peter ladkin
ladkin@kestrel.arpa
------------------------------
Date: Tue, 24 Feb 87 10:19 EST
From: Seth Steinberg <sas@bfly-vax.bbn.com>
Subject: A defense of the vulgar tongue.
I am going to ignore the "Is mathematics a science?" argument and get
right down to why I think mathematical and logical notation are
overused in computer science presentations. The problem has very
little to do with precision and a lot to do with class, clarity, and
vulgarity. By class, I am refering to a set of societal distinctions
which have been handed down in our society and are quite extant in our
modern academic community. By clarity, I am refering to the ability to
communicate ideas both within and outside the community. By vulgarity,
I am refering to the use of the vulgar tongue - which in this case is
not English but the programming language of choice.
Class: Much as a restaurant will have a menu written in French to
impress the diner, many authors feel obligated to use logical notation
to make their paper seem more "scientific". Walt Kelley once had a
character ask "I wonder what language the Romans used for the old 24
karat bamboozle." They used Greek, and a lot of our prejudices come
from the Greeks. Somehow or another, arguing at a high level of
abstraction makes the argument more precise, general, cogent, powerful
or what not. Sometimes this is true, sometimes it isn't. Abstraction
is often a major obstacle in the search for the truth.
Clarity: Chemists use chemical notation and scratchy looking stereo
diagrams. Philologists use cryptic phonetic notation. Geneticists use
long lists of upper case letters and funny three letter combinations.
Vintners use a full set of common adjectives with very precise but not
always obvious meanings. It is quite possible to be clear, precise and
understood without resorting to mathematical or logical notation.
Each of these notations was chosen because it concisely describes
commonly discussed phenomena. Architects do not express buildings in
mathematical notation when they talk to contractors but the latter can
usually come up with a cost estimate anyway.
Vulgarity: Programmers spend a lot of time discussing the behavior of
computers. Specialized terms like "barf" and "lossage", while
evocative, are not particularly precise. Whenever two programmers get
into an argument about what a program does, they don't sit down and
write up a proof, they look at the code. They might prove something
about the problem domain. What they usually do is "desk check" the
code, or maybe even go into the debugger and make the stupid computer
"desk check" the code for them. Programs are the common language of
programmers. They are precise; they can be used as a reasoning aid;
they are widely understood.
I have read too many papers in which mathematical notation is
gratuitously introduced. I have seen this reaching for abstraction
hide obvious inferences from the author. With certain notable
exceptions, too many authors reach for the wrong tools too soon.
Seth Steinberg
------------------------------
Date: 23 Feb 87 12:12:02 GMT
From: mcvax!ukc!warwick!gordon@seismo.css.gov (Gordon Joly)
Subject: What is this "INtelliGenT"?
"Intelligent" and "intelligence" are somewhat overused I fell. Consider
the browser which was described as "semi-intelligent" and the "intelligent
terminal". No wonder there is some confusion as to the possible meaning of
the term A.I.
Gordon Joly -- {seismo,ucbvax,decvax}!mcvax!ukc!warwick!gordon
------------------------------
End of AIList Digest
********************
∂26-Feb-87 1432 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #57
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 26 Feb 87 14:32:22 PST
Date: Thu 26 Feb 1987 09:19-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #57
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 26 Feb 1987 Volume 5 : Issue 57
Today's Topics:
Seminars - Planning Robotic Manipulation Strategies (UPenn) &
Reasoning and Planning in Dynamic Domains (CSLI) &
Expert Systems in Manufacturing (SU) &
Representing Defaults with Epistemic Concepts (SU),
Journal Issue - Financial Applications, IEEE Expert,
Conference - SUNY Buffalo Comp. Sci. Grad. Student Conference
----------------------------------------------------------------------
Date: Mon, 23 Feb 87 11:22:20 EST
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Planning Robotic Manipulation Strategies (UPenn)
Computer and Information Science
University of Pennsylvania
307 Towne Building
10:30 February 25, 1987
Planning Robotic Manipulation Strategies
Michael A. Peshkin
Carnegie Mellon University
Automated planning of grasping or manipulation requires an understanding
of the physics and the geometry of objects in contact. Sliding figures
prominently, but since the pressure distribution between the surfaces in
contact is unknown, deterministic solution for the motion is impossible.
I have found the locus of motions over all distributions. Strategies based
on these results succeed despite unknown pressure distribution.
We also desire strategies which succeed despite uncertain initial position
of a workpiece. Configuration maps are introduced, mapping all configurations
of a part before an elementary operation onto all possible outcomes. Products
of configuration maps are used to synthesize complex strategies which succeed
for a wide range of initial positions of the workpiece.
------------------------------
Date: Wed 25 Feb 87 17:18:14-PST
From: Emma Pease <Emma@CSLI.Stanford.EDU>
Subject: Seminar - Reasoning and Planning in Dynamic Domains (CSLI)
Reading: "Reasoning and Planning in Dynamic Domains:
An Experiment with a Mobile Robot"
by Michael Georgeff, Amy Lansky, and Marcel Schoppers
discussion led by Amy Lansky
Ventura Hall, March 5, 12:00 noon
Both Georgeff and Lansky will be present to discuss their recent paper
on using their Procedural Reasoning System (PRS) to control SRI's
robot, Flakey. The PRS architecture has been one of the focuses of
RATAG group discussions.
This paper describes progress made toward having the mobile robot
reason and plan complex tasks in real-world environments. To cope
with the dynamic and uncertain world, they use a highly reactive
system to which is attributed the attitudes of belief, desire, and
intention. Because these attitudes are explicitly represented, they
can be manipulated and reasoned about, resulting in complex
goal-directed and reflective behaviors. Unlike most planning systems,
the plans or intentions formed by the system need only be partly
elaborated before it decides to act. This allows the system to avoid
overly strong expectations about the environment, overly constrained
plans of action, and other forms of over-commitment common to previous
planners. In addition, the system is continuously reactive and has
the ability to change its goals and intentions as situations warrant.
Thus, while the system architecture allows for reasoning about means
and ends in much the same way as traditional planners, it also
possesses the reactivity required for survival in complex, dynamic
domains.
------------------------------
Date: Wed 25 Feb 87 15:49:35-PST
From: Automation & Manufacturing <SECAM@Sierra.Stanford.EDU>
Subject: Seminar - Expert Systems in Manufacturing (SU)
Jane Frederick Friday 27 February
G.E. Industrial Automation Systems Terman 556
1:30-3:00pm
"Expert Systems in Electronic Manufacturing"
Manufacturing appears to be one of the fertile fields for expert system
applications. The tasks are bounded and repetitive in nature. There
exists a set of experts which regularly perform the tasks. These tasks
can be defined in process steps and last but not least, manufacturing is a
direct pay point. The payback for quality and productivity improvements
can be specifically determined. This last issue is very important and
often overlooked, but expert systems development and implementation is an
expensive and ongoing process. Therefore, one of the challenges for expert
systems in manufacturing is selecting the correct application and the one
with the greatest payback.
Refreshments will be served.
------------------------------
Date: 23 Feb 87 1047 PST
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Representing Defaults with Epistemic Concepts (SU)
Commonsense and Nonmonotonic Reasoning Seminar
REPRESENTING DEFAULTS WITH EPISTEMIC CONCEPTS
Kurt Konolige, SRI International
Karen Myers, Stanford
Thursday, February 26, 4pm
Bldg. 160, Room 161K
Reasoning about defaults --- implications that typically hold,
but which may have exceptions --- is an important part of
commonsense reasoning. We present some parts of a theory of
defaults, concentrating on distinctions between various subtle
ways in which defaults can be defeated, and on the adjudication
of conflicting defaults under hierarchic inheritance. In order
to represent this theory in a formal system, it seems necessary
to use the epistemic concept of self-belief. We show how to
express the theory by an almost-local translation into
autoepistemic logic, which contains the requisite epistemic
operators. Just to be controversial, we also argue that
circumscription (pointwise, schematic, prioritized, or otherwise)
is insufficient for this task.
------------------------------
Date: 24 February 1987, 11:34:26 EST
From: "Chidanand V. Apte" <APTE@ibm.com>
Subject: Journal Issue - Financial Applications, IEEE Expert
CALL FOR PAPERS
---------------
IEEE EXPERT
Special Issue - Fall 1987
AI Applications in Financial Expert Systems
The Fall 1987 issue of IEEE EXPERT will be devoted to papers that
discuss the technical requirements imposed upon AI techniques for
building intelligent systems for financial applications and the
methodologies employed for the construction of such systems.
Requirements for submission of papers
-------------------------------------
Authors should submit their papers to the guest editors no later than
APRIL 1, 1987. Each submission should include one cover page and five
copies of the complete manuscript. The one cover page should include
Name(s), affiliation(s), complete address(es), identification of
principal author and telephone number. The five copies of the complete
manuscript should each include: Title and abstract page: title of paper,
100 word abstract indicating significance of contribution, and The
complete text of the paper in English, including illustrations and
references, not exceeding 5000 words.
Topics of interest
------------------
Authors are invited to submit papers describing recent and novel
applications of AI techniques in the research and development of
financial expert systems. Topics (in the context of the domain) include,
but are not limited to: Automated Reasoning, Knowledge Representations,
Inference Techniques, Problem Solving Control Mechanisms, Natural
Language Front Ends, User Modeling, Explanation Methodologies, Knowledge
Base Debugging, Validation, and Maintenance, and System Issues in
Development and Deployment.
Guest Editors
--------------
Chidanand Apte (914-945-1024, Arpa: apte@ibm.com)
John Kastner (914-945-3821, Arpa: kastner@ibm.com)
IBM Thomas J. Watson Research Center
P.O. Box 218
Yorktown Heights, New York 10598
------------------------------
Date: Tue, 24 Feb 87 09:37:46 EST
From: "William J. Rapaport" <rapaport%buffalo.csnet@RELAY.CS.NET>
Subject: Conference - SUNY Buffalo Comp. Sci. Grad. Student Conference
STATE UNIVERSITY OF NEW YORK AT BUFFALO
DEPARTMENT OF COMPUTER SCIENCE
UBGCCS-87
SECOND ANNUAL
GRADUATE CONFERENCE ON COMPUTER SCIENCE
Topics:
Artificial Intelligence--Parallel Program Debugging
Visual Knowledge Representation--Hypercube Algorithms--Naive Physics
Model-Based Diagnosis--Computer Vision--Natural Language Understanding
Tuesday, March 10, 1987
8:00 A.M. - 5:00 P.M.
Center For Tomorrow
Amherst Campus, SUNY Buffalo
Program:
Ted F. Pawlicki
SUNY Buffalo
"The Representation of Visual Knowledge"
John M. Mellor-Crummey
University of Rochester
"Parallel Program Debugging with Partial Orders"
Susan J. Wroblewski
SUNY Buffalo
"Efficient Trouble Shooting in an Industrial Environment"
Ching-Huei Wang
SUNY Buffalo
"ABLS: An Object Recognition System for Locating
Address Blocks on Mail Pieces"
Diane Horton
University of Toronto
"Presuppositions as Beliefs: A New Approach"
Norman D. Wahl
SUNY Buffalo
"Hypercube Algorithms to Determine Geometric Properties of Digitized Images"
Ganapathy Krishnan
SUNY Buffalo
"Bottom-Up Image Analysis for Color Separation"
Bart Selman
University of Toronto
"Vivid Representations and Analogues"
Soteria Svorou
SUNY Buffalo
"The Semantics of Spatial Extension Terms in Modern Greek"
Hing Kai Hung
SUNY Buffalo
"Semantics of a Recursive Procedure with Parameters and Aliasing"
Josh D. Tenenberg
University of Rochester
"Naive Physics and the Control of Inference"
Zhigang Xiang
SUNY Buffalo
"Multi-Level Model-Based Diagnostic Reasoning"
Registration begins at 8 A.M. (free)
First talk starts at 8:45 A.M.
Optional Buffet Luncheon ($5)
For program and registration information, please contact:
Lynda Spahr (716) 636-2464
ubg-ccs%buffalo
UBGCCS-87
226 Bell Hall
SUNY at Buffalo
Buffalo, New York 14260
Sponsored by:
SUNY Buffalo Computer Science Graduate Student Association
SUNY Buffalo Department of Computer Science
SUNY Buffalo Graduate Student Association
------------------------------
End of AIList Digest
********************
∂01-Mar-87 0032 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #58
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 1 Mar 87 00:32:01 PST
Date: Sat 28 Feb 1987 22:18-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #58
To: AIList@SRI-STRIPE.ARPA
AIList Digest Sunday, 1 Mar 1987 Volume 5 : Issue 58
Today's Topics:
Philosophy & AI Methodology - Consciousness
----------------------------------------------------------------------
Date: 23 Feb 87 04:14:52 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Evolution of consciousness
DAVIS%EMBL.BITNET@wiscvm.wisc.edu wrote on mod.ai:
> Sure - there is no advantage in a conscious system doing what can
> be done unconciously. BUT, and its a big but, if the system that
> gets to do trick X first *just happens* to be conscious, then all
> future systems evolving from that one will also be conscious.
I couldn't ask for a stronger concession to methodological epiphenomenalism.
> In fact, it may not even be an accident - when you
> consider the sort of complexity involved in building a `turing-
> indistinguishable' automaton, versus the slow, steady progress possible
> with an evolving, concious system, it may very well be that the ONLY
> reason for the existence of conscious systems is that they are
> *easier* to build within an evolutionary, biochemical context.
Now it sounds like you're taking it back.
> Hence, we have no real reason to suppose that there is a 'why' to be
> answered.
You'll have to make up your mind. But as long as anyone proposes a
conscious interpretation of a functional "how" story, I must challenge
the interpretation by asking a functional "why?", and Occam's razor
will be cutting with me, not with my opponent. It is not the existence
of consciousness that's at issue (of course it exists) but its
functional explanation and the criteria for inferring that it is
present in cases other than one's own.
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
Date: 24 Feb 87 08:41:00 EST
From: "CUGINI, JOHN" <cugini@icst-ecf>
Reply-to: "CUGINI, JOHN" <cugini@icst-ecf>
Subject: epistemology vs. functional theory of mind
> > Me: The Big Question: Is your brain more similar to mine than either
> > is to any plausible silicon-based device?
>
> SH: that's not the big question, at least not mine. Mine is "How does the
> mind work?" To answer that, you need a functional theory of how the
> mind works, you need a way of testing whether the theory works, and
> you need a way of deciding whether a device implemented according to
> the theory has a mind.
> Cugini keeps focusing on the usefulness of "presence of `brain'"
> as evidence for the possession of a mind. But in the absence of a
> functional theory of the brain, its superficial appearance hardly
> helps in constructing and testing a functional theory of the mind.
>
> Another way of putting it is that I'm concerned with a specific
> scientific (bioengineering) problem, not an exobiological one ("Does this
> alien have a mind?"), nor a sci-fi one ("Does this fictitious robot
> have a mind?"), nor a clinical one ("Does this comatose patient or
> anencephalic have a mind?"), nor even the informal, daily folk-psychological
> one ("Does this thing I'm interacting with have a mind?"). I'm only
> concerned with functional theories about how the mind works.
How about the epistemological one (philosophical words sound so, so...
*dignified*): Are we justified in believing that others have
minds/consciousness, and if so, on what rational basis?
I thought that was the issue we (you and I) were mostly talking
about. (I have the feeling you're switching the issue.) Whether
detailed brain knowledge will be terribily relevant to building a
functional theory of the mind, I don't know. As you say, it's a
question of the level of simulation. My hunch is that the chemistry
and low-level structure of the brain are tied very closely to
consciousness, simpliciter. I suspect that the ability to see red,
etc (good ole C-1) will require neurons. (I take this to be the
point of Searle's remark somewhere or other that consciousness
without a brain is as likely as lactation without mammary glands). On
the other hand, integer addition clearly is implementable without
wetware.
But even if a brain isn't necessary for consciousness, it's still good
strong evidence for it, as long as one accepts the notion that brains
form a "natural kind" (like stars, gold, electrons, light switches).
As I'm sure you know, there's a big philosophical problem with
natural kinds, struggled with by philosophers from Plato to
Goodman. My point was that it's no objection to brain-as-evidence
to drag in the natural-kinds problem, because that is not unique
to the issue of other minds. And it seems to me that's what you
are (were?) guilty of when you challenge the premise that our brains
are relevantly similar, the point being that if they are similar,
then the my-brain-causes-consciousness-therefore-so-does-yours
reasoning goes through.
John Cugini <Cugini@icst-ecf>
------------------------------
Date: 24 Feb 87 16:28:46 GMT
From: clyde!burl!codas!mtune!mtuxo!houxm!houem!marty1@rutgers.rutgers.
edu (M.BRILLIANT)
Subject: Re: Evolution of consciousness
I'm sorry if it's necessary to know the technical terminology of
philosophy to participate in discussions of engineering and artifice.
I admit my ignorance and proceed to make my point anyway.
In article <552@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes
(I condense and paraphrase):
> DAVIS%EMBL.BITNET@wiscvm.wisc.edu wrote on mod.ai:
> > ... if the system that [does] X first [is] conscious, then all
> > future systems evolving from that one will also be conscious.
> I couldn't ask for a stronger concession to methodological epiphenomenalism.
In 25 words or less, what's methodological epiphenomenalism?
> > In fact ... [maybe] conscious systems ... are
> > *easier* to build within an evolutionary, biochemical context.
> Now it sounds like you're taking it back.
I think DAVIS is just suggesting an alternative hypothesis.
> > Hence, we have no real reason to suppose that there is a 'why' to be
> > answered.
Then why did DAVIS propose that "easier" is "why"?
Let me propose another "why." Not long ago I suggested that a simple
unix(tm) command like "make" could be made to know when it was acting,
and when it was merely contemplating action. It would then not only
appear to be conscious, but would thereby work more effectively.
Let us go further. IBM's infamous PL/I Checkout Compiler has many
states, in each of which it can accept only a limited set of commands
and will do only a limited set of things. As user, you can ask it what
state it's in, and it can even tell you what it can do in that state,
though it doesn't know what it could do in other states. But you can
ask it what it's doing now, and it will tell you. It answers questions
as though it were very stupid, but dimly conscious.
Of course, the "actuality" of consciousness is private, in that the
question of whether X "is conscious" can be answered only by X. An
observer of X can only tell whether X "acts as though it were
conscious." If the observer empathizes with X, that is, observes
him/her/it-self as the "same type of being" as X, the "appearance" of
consciousness becomes evidence of "actuality." I propose that we pay
less attention to whether we are the "same type of being" as X and more
attention to the (inter)action.
If expert systems can be written to tell you an answer, and also tell
you how they got the answer, it should not be hard to write a system
like the Checkout Compiler, but with a little more knowledge of its own
capabilities. That would make it a lot easier for an inexpert user to
interact with it.
Consider also the infamous "Eliza" as a system that is not conscious.
At first it appears to interact much as a psychotherapist would, but
you can test it by pulling its leg, and it won't know you're pulling
its leg; a therapist would notice and shift to another state. You can
also make a therapist speak to you non-professionally by a verbal
time-out signal, and then go back to professional mode. But Eliza has
only one functional state, and hence neither need nor capacity for
consciousness.
Thus, the evolutionary advantage of consciousness in primates (the
actuality as well as the appearance) is that it facilitates such social
interactions as communication and cooperation. The advantage of
building consciousness into computer programs (now I refer to the
appearance, since I can't empathize with a computer program) is the
same: to facilitate communication and cooperation.
I propose that we ignore the philosophy and get on with the
engineering. We already know how to build systems that interact as
though they were conscious. Even if a criterion could be devised to
tell whether X is "actually" conscious, not just "seemingly" conscious,
we don't need it to build functionally conscious systems.
Marty
M. B. Brilliant (201)-949-1858
AT&T-BL HO 3D-520 houem!marty1
------------------------------
Date: 25 Feb 87 14:32:04 GMT
From: princeton!mind!harnad@rutgers.rutgers.edu (Stevan Harnad)
Subject: Re: Evolution of consciousness
M. B. Brilliant (marty1@houem.UUCP) of AT&T-BL HO 3D-520 asks:
> In 25 words or less, what's methodological epiphenomenalism?
Your own reply (less a few words) defines it well enough:
> I propose that we ignore [the philosophy] and get on with the
> engineering. [We already know how] to build systems that interact as
> though they were conscious. Even if a criterion could be devised to
> tell whether X is "actually" conscious, not just "seemingly" conscious,
> we don't need it to build [functionally] conscious systems.
Except that we DON'T already know how. This ought to read: "We should get
down to trying" to build systems that can pass the Total Turing Test (TTT)
-- i.e., are completely performance-indistinguishable from conscious
creatures like ourselves. Also, there is (and can be) no other functional
criterion than the TTT, so "seemingly" conscious is as close as we will
ever get. Hence there's nothing gained (and a lot masked and even lost)
from focusing on interpreting trivial performance as conscious instead
of on strengthening it. What we should ignore is conscious interpretation:
That's a good philosophy. And I've dubbed it "methodological epiphenomenalism."
> Thus, the evolutionary advantage of consciousness in primates (the
> actuality as well as the appearance) is that it facilitates such social
> interactions as communication and cooperation. The advantage of
> building consciousness into computer programs (now I refer to the
> appearance, since I can't empathize with a computer program) is the
> same: to facilitate communication and cooperation.
This simply does not follow from the foregoing (in fact, it's at odds
with it). Not even a hint is given about the FUNCTIONAL advantage (or even
the functional role) of either actually being conscious or even of appearing
conscious. "Communication-and-cooperation" -- be it ever as "seemingly
conscious" as you wish -- does not answer the question about what functional
role consciousness plays, it simply presupposes it. Why aren't communication
and cooperation accomplished unconsciously? What is the FUNCTIONAL
advantage of conscious communication and cooperation? How we feel about one
another and about the devices we build is beside the point (except for
the informal TTT). It concerns the phenomenological and ontological
fact of consciousness, not its functional role, which (if there were
any) would be all that was relevant to mind engineering. That's
methodological epiphenomenalism.
--
Stevan Harnad (609) - 921 7771
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
------------------------------
End of AIList Digest
********************
∂01-Mar-87 0210 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #59
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 1 Mar 87 02:10:30 PST
Date: Sat 28 Feb 1987 22:32-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #59
To: AIList@SRI-STRIPE.ARPA
AIList Digest Sunday, 1 Mar 1987 Volume 5 : Issue 59
Today's Topics:
Policy - Hardware vs. AI,
Queries - AI in Network Protocols & Best LISPM/WorkStation &
Legal Reasoning and AI & Completeness and Consistency of Rule Bases,
Application - Network Complexity
----------------------------------------------------------------------
Date: Wed, 25 Feb 87 10:41:16 -0800
From: Amnon Meyers <meyers@CIP.UCI.EDU>
Subject: Hardware vs. AI
I would like to suggest that the AILIST be more open to hardware topics
that are related to WORKING in Artificial Intelligence, for several reasons:
This would be a valuable service to people working in AI who are having
hardware problems. They can draw upon the solutions of others who have
solved the same problems, and upon knowledge of AI facilities with hardware
experts.
Even though there are bulletin boards for specific hardware, it would be
useful to to organize the AI community's hardware and environment problems
as a single list. If this is too much for AILIST then perhaps an
AI-HARDWARE list is called for.
I disagree with the notion that hardware problems have 'nothing to do with
AI'. While discussions of LISP and PROLOG dialects are interesting, they
appear to me to have no more relevance to 'AI' than do hardware issues.
Likewise discussion of the operation and environment provided by LISP
machines and other workstations. Likewise philosophical discussions of
the mind. My point is that it is not useful to try to define AI too
narrowly. There is a theory and practice of AI, and AILIST seems to stress
the theory. It would be nice if the 'practice' were taken up somewhere
as well.
I can certainly understand that the AILIST is already overburdened, and
that the moderator already does too much work (and a fine job as well).
THOSE should be the reasons for excluding hardware issues, not arbitration
about what is and is not relevant to AI.
Amnon Meyers
meyers@ics.uci.edu
P.S. I often wonder where people are writing from, so...
Irvine Computational Intelligence Project
ICS Department
University of California
Irvine, California 92717
(714) 856-4840
------------------------------
Date: 28 Feb 87 08:10:06 GMT
From: ramarao@umn-cs.UUCP
Subject: AI in Network Protocols.
topic : EXPERT SYSTEMS OR AI IN NETWORKS AND PROTOCOLS
I am trying to find out if there has been any attempt at
applying AI techniques, AI languages to the field of network protocols.
Can anyone give me some references. I would like to know why it is
not feasible to implement network protocols, etc. in a non-procedure
based approach.
I am trying to find out if it is feasible to design network protocols
in LISP or Prolog or any AI languages.
-Bindu Rama Rao (ramarao@umn-cs.arpa)
(612)-625-9637
**** Keep smilin (-:
------------------------------
Date: Thu, 26 Feb 87 14:27:51 PST
From: TAYLOR%PLU@ames-io.ARPA
Subject: Best LISPM/WorkStation?
NOTE: This posting is being sent to the AILIST, SLUG, TI, XEROX, SUN
and WorkStation bulletin boards
Here at the AI Research & Applications Branch - NASA Ames Research Center,
we are planning to buy several Lisp or possibly non-Lisp workstations in
the near future and want to look at alternatives to Symbolics, of which
we have 7 + a 3600 file server at the present time.
Possible alternatives are (in no particular order):
Explorer
Xerox 1186
Sun
Vax station
LMI
Apollo
Several things that concern us are:
Are we maximizing productivity and minimizing cost in our
current environment ? How can we accomplish these goals
in the future ?
Is our current environment of Lisp Machine workstations going
to continue to offer us the best development environment ?
General purpose workstations offering Lisp, Prolog, Pascal,
FORTRAN, C, etc, are coming on strong.
We will be supporting outside users who have non-Symbolics
equipment; what is the most portable development/delivery
environment that we could have, consistent with our software
requirements ? (see below)
If we move to a non-Symbolics environment, what environment
will minimize the portability costs ?
Our software requirements are object oriented Lisp, Prolog, two-way
calling interface between Lisp & Prolog, rich window system/graphics
(monochrome and color) facilities and a productive development environment.
We would appreciate any comments, experiences and recommendations of people
who have used two or more of the above Lispms/work stations. We are
familiar with two Lispm comparisions which have appeared on bboards:
Dandelion vs Symbolics, 17 Sep 86, steve@siemens.UUCP
Explorer vs Symbolics, 23 Oct 86, miller@ur-acorn.ARPA
In order to liven up this discussion, we thought the repetition of
some previous bboard claims about Lispm/workstation capabilities would
elicit honest, deeply-held opinions ! Here goes:
1. The Symbolics window debugger is unmatched anywhere.
2. Symbolics' on-line documentation is much better than TI's
BUT
TI's suggestion system is much better than Symbolics'.
3. Symbolics' networking is much better than TI and better in general.
4. With Symbolics GC, must boot ea. 14 day.
With TI GC (no ephemeral exists) must boot ea 0.5 day
5. Symbolics and TI are so similar that it is easy to carry skills back
and forth.
6. Xerox's window system is easy to use but less powerful than Symbolics.
7. Xerox's GC is really a 'reference counter' and therefore CAN'T
reclaim circular lists. Other than that, however, Xerox's GC is much
better than Symbolics.
8. VAX's GC takes 6 sec (with 9 meg) while Symbolics' takes 1 hr.
9. VAX must have >5 Meg to be useful.
10. VAX's LISP Language Sensitive Editor is about as useful as EMACS.
11. A SUN without disks is useless.
Furthermore, here are a few issues to flame on -
- hardware - failure rates, ease of fault analysis
- window systems
- networking
- namespace
- garbage collection
- Initial ease of use / overall user interface.
- Power for highly trained user
- editors
- online documentation - completeness, clarity
- performance metering
- debuging tools
- maximum paging space
- speed
To try to keep this discussion in one central place and since I do not
subscribe to all the bboards to which this is being posted, I would
suggest (subject to Ken Laws veto) that all responses be posted to the
AIList (AIList@sri-stripe.ARPA). However e-mail to me if you have any
problems with that proposal.
--------------------------------------------------------------------------
Will Taylor - Sterling Software, MS 244-17,
NASA-Ames Research Center, Moffett Field, CA 94035
arpanet: taylor@ames-pluto.ARPA
usenet: ..!ames!plu.decnet!taylor
phone : (415)694-6525
------------------------------
Date: 26 Feb 87 17:28:16 GMT
From: Jim Stewart
<jims%milo%cvedc%ogcvax%tektronix.tek.com@RELAY.CS.NET>
Subject: Re: Legal Reasoning and AI
I came across an announcement regarding A.I. applications for legal
reasoning and a conference in May. This interests me as I am (one
of the few) who happens to be a law student and a software engineer/
technical writer. (Engineer/writer by day, student by night).
I have a strong interest in legal research and A.I.. Here at Lewis
& Clark's Northwestern School of Law (Portland, Oregon USA) a small
group of students is forming with support of administration to continue
research in the areas of computer applications for legal research and
reasoning. Unfortunately, notwithstanding our proximity to the "Silicon
Forest" here in Oregon, we are somewhat disconnected from the mainstream
activities in this area.
I am interested in learning who else is out there with net access, and
happens to be a law student as well as a technical professional. Is there
a sub news-group of A.I., or is this news-group appropriate for such an
exchange?
Thanks
Gregory Miller
Technical Staff
Computervision Electronics CAE Development Center (cvedc)
P.O. Box 959
Hillsboro, Oregon 97123
(503) 645-2410
Northwestern School of Law @ Lewis & Clark College
------------------------------
Date: Wed, 25 Feb 87 16:59 N
From: MFMISTAL%HMARL5.BITNET@wiscvm.wisc.edu
Subject: Completeness and consistency of rule bases
I'm interested in computer (assisted) completeness and consistency
checking of rule bases. Is there someone on the net who could provide
me with some references to the literature on these subjects.
Both references on theoretical and practical issues are welcomed.
Please, send them to me directly, I will compile a complete list for
posting on the net.
Jan L. Talmon
Department of Medical Informatics and Statistics
University of Limburg
PO Box616
6200 MD Maastricht
The Netherlands
EARN/BITNET: MFMISTAL@HMARL5
------------------------------
Date: 25 Feb 87 03:56:45 GMT
From: belmonte@svax.cs.cornell.edu (Matthew Belmonte)
Subject: Re: Network Complexity
In article <292@ihnp3.UUCP> mth@ihnp3.UUCP (Mark Horbal) writes:
> If we define the "complexity" of a computer network as a
> measure of difficulty in observing, understanding, and
> excercising a modicum of control over it, how is this
> "complexity" estimated?
>
> If we further choose a simple but intuitive way of representing
> a computer network by a graph, how do we quantify this "complexity"
> with respect to the graph's topology?
I believe there might be another area which is relevant to the problem you
mention in the second statement above, but not the first. A year ago I was
doing an internship at NRL implementing a transition-network parser for some
context-free grammars which mimicked *small* subsets of English. The
question occurred to me, "how does one quantify the complexity of the
transition networks we generate?" (By "complexity" here I mean topics such as:
Do we have a lot of long paths consisting of nonterminals which will result in
many failed parses? Do we have many null transitions that we can't squeeze out
by munging adjacent states together? etc.) The answer I got was, well, we
don't really know of any method of completely characterising such complexities.
Is this the same sort of problem as mentioned above, or am I completely
off-base?
Disclaimer: Yes, I know I'm extraordinarily weak on theory, but I'm a lowly,
simple-minded freshman, so I have an excuse.
--
"When you've got them by the balls, their hearts and minds will follow."
-- a member of the Nixon administration
Matthew Belmonte
Internet: <belmonte@svax.cs.cornell.edu>
BITNET: <d25y@cornella> <d25y@crnlvax5>
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End of AIList Digest
********************
∂01-Mar-87 0412 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #60
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 1 Mar 87 04:11:50 PST
Date: Sat 28 Feb 1987 22:39-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #60
To: AIList@SRI-STRIPE.ARPA
AIList Digest Sunday, 1 Mar 1987 Volume 5 : Issue 60
Today's Topics:
Bibliography - Leff ai.bib44C
----------------------------------------------------------------------
Date: Sat, 28 Feb 1987 13:19 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: ai.bib44C
%A S. V. Shil'man
%T Adaptive-Optimal Filtering in Random Processes
%J MAG95
%P 249-261
%K O06 AI06
%A O. Yu. Pershin
%T A Class of Extremal Combinatorial Problems for Multicomponent Network
Design
%J MAG95
%P 262-269
%K AI03 O06
%A V. I. Borzenko
%T Extrapolation of a System of Classifications
%J MAG95
%P 270-275
%K O06
%A V. V. Mottl
%A I. B. Muchnik
%T Algorithm for Recognition of a Stream of Random Events
%J MAG95
%P 276-278
%K AI06 O06
%A Dominique Perrin
%A Jean-Erric Pin
%T First-Order Logic and Star-Free Sets
%J Journal of Computer and System Sciences
%V 32
%N 3
%D JUN 1986
%P 393-406
%K AI11
%A J. A. Bergstra
%A J. W. Klop
%T Conditional Rewrite Rules: Confluence and Termination
%J Journal of Computer and System Sciences
%V 32
%N 3
%D JUN 1986
%P 323-362
%K AI14
%A M. S. Esparz
%T High-Priced Lisp Hardware Obsolete in Near Future, Says Study
%J InfoSystems
%V 33
%N 9
%D SEP 1986
%P 16
%K H02
%A D. H. Feedman
%T Expert Systems Moving from Glamour Technology to Workhorse
%J InfoSystems
%V 33
%N 9
%D SEP 1986
%P 14-15
%K AI01
%A Ewa Orlowska
%T Semantic Analysis of Inductive Reasoning
%J Theoret. Comput. Sci
%V 43
%D 1986
%N 1
%P 81-89
%K AI16
%A Francoise Bellegarde
%T Convergent Term Rewriting Systems can be Used for Program Transformation
%B Programs as Data Objects
%P 24-41
%S Lecture Notes in Computer Science
%V 217
%I Springer-Verlag
%C Berlin-New York
%D 1986
%K AA08 AI14
%A Adolfo Lagomasino
%A Andrew P. Sage
%T Imprecise Knowledge Representation in Inferential Activities
%B BOOK57
%P 473-497
%K O04
%A Murray Eden
%A Michael Unser
%A Riccardo Leonardi
%T Polynomial Representation of Pictures
%J Signal Process.
%V 10
%D 1986
%N 4
%P 385-393
%K AI06
%A Christian Ronse
%T Definitions of Convexity and Convex Hulls in Digital Images
%J Bull. Soc. Math. Belg. Ser. B
%V 37
%D 1986
%N 2
%P 71-85
%K AI06
%A David C. Rine
%T Some Applications of Multiple-Valued Logic and Fuzzy Logic to Expert Systems
%B BOOK57
%P 407-434
%K O04 AI01
%A Hung T. Nguyen
%A Irwin R. Goodman
%T On Foundations of Approximate Reasoning
%B BOOK57
%P 47-59
%K AI16 O04 AI01
%A S. T. Wierzchon
%T Mathematical Tools for Knowledge Representation
%B BOOK57
%P 61-69
%K AI16 O04 AI01
%A A. Lananer
%T Associate Processing in Brain Theory and Artificial Intelligence
%B Brain Theory
%P 193-210
%I Springer-Verlag
%C Berlin-New York
%D 1986
%P 193-210
%K AI08 AI16
%A Lawrence R. Baniner
%A Jay G. Wilpon
%A Biing-Hwang Juang
%T A Segmental k-Means Training Procedure for Connected Word Recognition
%J AT&T Technical Journal
%V 65
%N 3
%D MAY-JUN 1986
%P 21-40
%K AI04 AI05
%A A. A. Natan
%A A. I. Samylovskiy
%T Recognition of Gaussian Random Processes by Local Analysis of Their
Properties
%J MAG95
%P 128-135
%K AI06
%A M. V. Fomina
%T Methods for Successive Construction of a Hierarchical Representation of
the States of a Complex Object
%J MAG95
%P 136-145
%K AI16
%A L. B. Groysberg
%T Planning of Component Tests for Confirmation of System Reliability
%J MAG95
%P 146-153
%K AI16 AA05
%A E. Vidal Ruiz
%T An Algorithm for Finding Nearest Neighbors in (Approximately) Constant
Average Time
%J MAG96
%P 145-158
%K AI06 O06
%A S. K. Pal
%A P. K. Pramanik
%T Fuzzy Measures in Determining Seed Points in Clustering
%J MAG96
%P 159-164
%K O06
%A G. T. Toussaint
%T Interactive Curve Drawing by Segmented Bezier Approximation with a
Control Parameter
%J MAG96
%P 171-176
%K O06
%A A. Rosenfeld
%T Continuous Functions on Digital Pictures
%J MAG96
%P 177-184
%K AI06
%A E. R. Davies
%T Image Space Transforms for Detecting Straight Edges in Industrial Images
%J MAG96
%P 185-192
%K AI06
%A S. K. Parui
%A S. Eswara Sarma
%A D. Dutta Majumder
%T How to Discriminate Shapes Using Shape Vector
%J MAG96
%P 201-204
%K AI06
%A A. Schening
%A H. Nieman
%T Computing Depth from Stereo Images by Using Optical Flow
%J MAG96
%P 205-212
%K AI06
%A T. H. Phillips
%A A. Rosenfeld
%T A Simplified Method of Detecting Structure in Glass Patterns
%J MAG96
%P 213
%K AI06
%A J. K. Mattila
%T On Some Logical Points of Fuzzy Conditional Decision Making
%J MAG97
%P 137-146
%K O04
%A K. Nakamura
%T Preference Relations on a Set of Fuzzy Utilities as
a Basis for Decision Making
%J MAG97
%P 147-162
%K AI13 O04
%A M. R. Casals
%A M. A. Gil
%A P. Gil
%T On the Use of Zadeh's Probabilistic Definition for
Testing Statistical Hypothesis from Fuzzy Information
%J MAG97
%P 175-190
%K O04
%A P. Dallant
%A A. Meunier
%A P. S. Christel
%A L. Sedel
%T Semi-automatic Image-Analysis Applied to the Quantification
of Bone Microstructure
%J Journal of Biomedical Engineering
%V 8
%N 4
%D OCT 1986
%P 320-328
%K AA01 AI06
%A C. E. Riese
%A S. M. Zubrick
%T Using Rule Induction to Combine Declarative and Procedural Knowledge
Representations
%J MAG94
%P 603-606
%K AI16 AI04
%A D. S. Prerau
%A A. S.Gunderson
%A R. E. Reinke
%A S. K. Goyal
%T The COMPASS Expert System: Verification, Technology Transfer, and
Expansion
%J MAG94
%P 597-602
%K AI01
%A B. Pinkowski
%T A Lisp-based System for Generating Diagnostic Keys
%J MAG94
%P 592-596
%K T01
%A S. R. Mukherjee
%A M. Sloan
%T Positional Representation of English Words
%J MAG94
%P 587-591
%K AI02
%A J. H. Martin
%T Knowledge Acquisition Through Natural Language Dialogue
%J MAG94
%P 582-586
%K AI02
%A D. M. Mark
%T Finding Simple Routes: 'Ease of Description' as an Objective Function
in Automated Route Selection
%J MAG94
%P 577-581
%A S. Mahalingam
%A D. D. Sharma
%T WELDEX - An Expert System for Nondestructive Testing of Welds
%J MAG94
%P 572-576
%K AA05 AI01
%A J. Liebowitz
%T Evaluation of Expert Systems: An Approach and Case Study
%J MAG94
%P 564-571
%K AI01
%A S. J. Laskowski
%A H. J. Antonisse
%A R. P. Bonasso
%T Analyst II: A Knowledge-Based Intelligence Support System
%J MAG94
%P 558-563
%K AA18
%A D. A. Krawczak
%A P. J. Smith
%A S. J. Shute
%A M. Chignell
%T EP-X: A Knowledge-Based System to Aid in Search of the Environmental
Pollution Literature
%J MAG94
%P 552-557
%K AA14 AI01 AA10
%A E. Y. Kandrashina
%A O. N. Ochakovskaja
%A Y. A. Zagorulko
%T Time-1: Semantic System for Dynamic Object Domain
%J MAG94
%P 548-551
%K AI16
%A C. I. Kalme
%T A General Purpose Language for Coupled Expert Systems
%J MAG94
%P 539-547
%K T03 H03 AI01
%A J. R. James
%A P. P. Bonissone
%A D. K. Frederick
%A J. H. Taylor
%T A Retrospective View of CACE-III: Considerations in Coordinating Symbolic
and Numeric Computation in a Rule-Based Expert System
%J MAG94
%P 532-538
%K T03 AI14 AI01
%A R. T. Hartley
%T Representation of Procedural Knowledge for Expert Systems
%J MAG94
%P 526-531
%K AI16 AI01
%A J. J. Hannan
%A P. Politakis
%T ESSA: An Approach to Acquiring Decision Rules for Diagnostic Expert
Systems
%J MAG94
%P 520-525
%K AA21
%A K. Hammer
%A J. Hardin
%A D. Rudisill
%A A. Goldfein
%T Using a Predictive Parse to Create a Modeless Editor
%J MAG94
%P 514-519
%K AA15
%A R. L. Constable
%T Implementing Mathematics with the Nupri Proof Development System
%I Prentice-Hall
%C Englewood Cliffs, NJ
%D 1986
%K AI11 AA13
%X 299 pages $21.95
%A L. O. Hall
%A W. Bandler
%T Relational Knowledge Acquisition
%J MAG94
%P 509-513
%K AI16
%A W. D. Hagament
%A M. Gardy
%T MEDCAT/CATS: Two Contrasting Artificial Intelligence Applications in
Medical Education
%J MAG94
%P 503-508
%K AA07 AA01
%A J. F. Gilmore
%A K. Pulaski
%T A Survey of Expert System Tools
%J MAG94
%P 498-502
%K T03
%A A. Garcia-Ortiz
%T Computer Algebra Applied to the Design of Optical Sensor Platforms
%J MAG94
%P 493-497
%K AI14 AA16
%A B. R. Fox
%A K. G. Kempf
%T Complexity, Uncertainty, and Opportunistic Scheduling
%J MAG94
%P 487-492
%K O04 AA05 AI16 O06 AI03
%A M. E. Cohen
%A D. L. Hudson
%A N. Gitlin
%A L. T. Mann
%A J. Van den Bogaerde
%A L. Leal
%T Knowledge Representation and Classification of Chromatographic Data for
Diagnostic Medical Decison Making
%J MAG94
%P 481-486
%K AA02 AA01
%A F. Brundick
%A J. Dumer
%A T. Hanratty
%A P. Tanenbaum
%T GENIE: An Inference Engine with Diverse Applications
%J MAG94
%P 473-480
%K T03
%A H. Winter
%T Artificial Intelligence in Man-Machine Systems
%B BOOK59
%P 1-22
%K AA15
%A J. Mylopoulos
%A A. Borgida
%A S. Greenspan
%A C. Meghini
%A B. Nixon
%T Knowledge Representation in the Software Development Process - A Case Study
%B BOOK59
%P 23-44
%K AA08
%A B. Radig
%T Design and Applications of Expert Systems
%B BOOK59
%P 45-61
%K AA08
%A W. Wahlster
%T The Role of Natural Language in Advanced Knowledge Based Systems
%B BOOK59
%P 62-83
%K AI02 AA15
%A G. Fischer
%T Cognitive Science - Information Processing in Humans and Computers
%B BOOK59
%P 84-111
%K AI08
%A A. Meystel
%T Knowledge-Based Controller for Intelligent Mobile Robots
%B BOOK59
%P 112-140
%K AI07 AA19
%A S. E. Cross
%A R. B. Bahnij
%A D. O. Norman
%T Knowledge-Based Pilot Aids - A Case Study in Mission Planning
%B BOOK59
%P 141-174
%K AA19
%A U. Volckers
%T Dynamic Planning and Time-Conflict Resolution in Air Traffic Control
%B BOOK59
%P 175-197
%K AI09 O03
%A L. A. Zadeh
%T Outline of a Computational Approach to Meaning and Knowledge Representation B
ased on
the Concept of a Generalized Assignment Statement
%B BOOK59
%P 198
%K O04 AI16
%A J. K. Kastner
%T Continuous Real-Time Expert System for Computer Operations
%J Data Processing
%V 28
%N 8
%D OCT 1986
%P 411-425
%K O03 AA08 AI01
%A Keith Clark
%A Steve Gregory
%T PARLOG: Parallel Programming in Logic
%J ACM Transactions on Programming Languages and Systems
%V 8
%N 1
%D JAN 1986
%P 1-49
%K AI10 H03
%A G. I. Janbykh
%T Optimization of the Structure of Computer Networks Using Branch and Bound
%J Avtomatika I. vychisletenlnaya Teknika
%N 5
%D SEP-OCT 1986
%P 3-13
%K AA08 AI03
%A W. Rauchhindin
%T Software Integrates AI, Standard Systems
%J Mini-Micro Systems
%V 19
%N 12
%D OCT 1986
%P 69-86
%A Dragan Kolar
%A Vojislav Stojkovic
%T The Implementation of CF Grammars by PROLOG Language
%J Univ. u Novm Sadu Zb. Rad. Prirod. Mat Fak. Ser. Mat
%V 15
%N 1
%P 245-252
%K T02
%A Krzysztof R. Apt
%A Dexter C. Kozen
%T Limits for Automatic Verification of Finite-tate Concurrent Systems
%J Inform. Process. Lett
%V 22
%D 1986
%N 6
%P 307-309
%K AA08
%A Robert L. Constable
%T Constructive Mathematics as a Programming Logic I. Some Principles of Theory
%B BOOK60
%P 21-37
%K AI10 AA13
%A H. Langmaack
%T A New Transformational Approach to Partial Correctness Proof Calculi for ALGO
L
68-Like Programs with Finite Modes and Simple Side Effects
%B BOOK60
%P 73-102
%D 1985
%A Philippe Devienne
%A Patrick Lebegue
%T Weighted Graphs: A Tool for Logic Programming
%B BOOK61
%P 100-111
%K AI10
%A James S. Royer
%T Inductive Inferences of Approximations
%J Information and Control
%V 70
%N 2-3
%D AUG-SEP 1986
%P 156-178
%K AI03
%A Sergiu Hart
%A Micha Sharir
%T Probabilistic Propositional Temporal Logics
%J Information and Control
%V 70
%N 2-3
%D AUG-SEP 1986
%P AI10 AI16 O04 AI11
%A K. Yalumov
%T KET: A Knowledge Engineering Tool
%J Computers in Industry
%V 7
%N 5
%D OCT 1986
%P 417-426
%K T03
%A S. F. Bocklisch
%T A Diagnosis Sytem Based on Fuzzy Classification
%J Computers and Industry
%V 7
%N 1
%D FEB 1986
%P 73-82
%K AI01 O04
%A Justin R. Smith
%T Parallel Algorithms for Depth-first Searches I. Planar Graphs
%J SIAM J. Comput.
%V 15
%D 1986
%N 3
%P 814-830
%K AI03 O06
%A N. N. Nepievoda
%T Deductions in the Form of Graphs
%J Semiotics and Information Science
%N 26
%P 52-82
%D 1985
%X Akad. Nauk SSSR, Vsesoyuz. Inst. Nauchn. i Tekhn. Inform., Moscow
(in Russian)
%A Yu. I. Petunin
%A G. A. Shuldeshov
%T Calculation of a Plane Figure from its Discretized Image
%J Kibernetika (Kiev)
%D 1986
%N 2
%P 1-7
%K AI06
%X Russian with English Summary
%A Shuro Nagata
%A Takeshi Oshiba
%A Sakae Funahashi
%T An Implementation of a Validity Checking Program by Using N-set Partitions
%J Bull. Nagoya Inst. Tech
%V 37
%D 1985
%P 111-116
%D 1986
%K AA08
%X Japanese with English Summary
%A Alex Pelin
%A Jean H. Gallier
%T Exact Computation Sequences
%B BOOK61
%P 45-59
%A Henri Prade
%T corrections to: "A Simple Inference Techique for Dealign with Uncertain
Facts in terms of possibility" (Kybernetes 15 (1986) no. 1 19-24
%J Kybernetes
%15
%N 3
%P 214
%K O04 AT13
%A Ronald R. Yager
%T A Note on Projections of Conditional Possibility Distributions in Approximate
Reasoning
%J Kybernetes
%V 15
%N 3
%P 185-187
%K O04
%A R. I Podlovchenko
%T Investigation of s-models of programs from the standpoint of
constructing canonization algorithms for them.
%J Programmirovanie
%D 1986
%N 2
%P 3-13
%K AA08
%X Russian
%A Manfred Broy
%A Bernhard Moller
%A Peter Pepper
%A Martin Wirsing
%T Algebraic Implementations Preserve Program Correctness
%J Sci Comput. Programming
%V 7
%D 1986
%N 1
%P 35-53
%K AA08
%A Yu Qi Guo
%A Lian Li
%A Gang Wu Xu
%T On the Disjunctive Structure of Dense Languages
%J Sci. Sinica Ser. A
%V 28
%D 1985
%N 12
%P 1233-1238
%A Thomas A. Joseph
%A Thomas Rauchle
%A Sam Toueg
%T State Machines and Assertions: An Integrated Approach to Modeling
and Verification of Distributed Systems
%J Sci. Comput. Programming
%V 7
%D 1986
%N 1
%P 1-22
%A Takeshi Shinohara
%T Inductive Inference of Formal Systems From Positive Data
%J Bull Inform. Cybernet.
%V 22
%D 1986
%N 1-2
%P 9-18
%K AI04
%A Moshe Y. Vardi
%T Automata-Theoretic Techniques for Modal Logics of Programs
%J J. Comput. System Sci.
%V 32
%D 1986
%N 2
%P 183-221
%A John N. Martin
%T Some Formal Properties of Indirect Semantics
%J Theoret. Linguist
%V 12
%D 1985
%N 1
%P 1-32
%K AI02 AI16
%A Makoto Haraguchi
%T Analogical Reasoning Using Transformation of Rules
%J Bull. Inform. Cybernet.
%V 22
%D 1986
%N 1-2
%P 1-8
%K AI16
%A Takahashi Yokomori
%T Representation Theorems and Primitive Predicates for Logic Programs
%J Bull. Inform. Cybernet.
%V 22
%D 1986
%N 1-2
%P 19-37
%K AI11
%A Matthias Baaz
%A Alexander Leitsch
%T The Application of Strong Reduction Rules in Automatic Proofs
%J Osterreich Akad. Wiss. Math.-Natur. KL Sitzungsber. II
%V 194
%D 1985
%N 4-10
%P 287-307
%K AA08
%A Michael Leyton
%T A Theory of Information I. General Principles
%J J. Math. Psych.
%V 30
%D 1986
%N 2
%P 103-160
%K AI16 AI08
%A J. J. Harvey
%T Expert Systems: An Introduction
%J MAG98
%P 100-108
%K AI01 AT08
%A J. J. Harvey
%T ESSAI Expert Systems Toolkit
%J MAG98
%P 109-114
%K AI01 T03
%A M. A. Newstead
%A R. Pettipher
%T Knowledge Acquisition for Expert Systems
%J MAG98
%P 115-121
%K AI01
%A G. Jones
%A R. Nuttall
%A K. Stone
%T Integrating Multiple Control Schemes
%J MAG98
%P 122-127
%K AI01
%A R. Gunhold
%A J. Zettel
%T System 12 In-Factory Testing
%J MAG98
%P 128-134
%K AA04 AI01
%A H. Schelfhout
%T Customer Application Engineering for System 12 Hardware
%J MAG98
%P 135-140
%K AA04 AI01
%A N. Theuretzbacher
%T Expert System Technology for Safety-Critical Real-Time Systems
%J MAG98
%P 147-153
%K AI01 O03
%A M. Thandasseri
%T Expert Systems Application for TXE4A Exchanges
%J MAG98
%P 154-161
%K AI01 AA04
%A P. Benson
%T Artificial Intelligence Assisted Packet Radio Connectivity
%J MAG98
%P 162-167
%K AI01 AA04
%A E. Gaudry
%T Electronic Warfare Application for Expert Systems
%J MAG98
%P 168-173
%K AA18
%A M. E. Atwood
%A E. R. Radlinski
%T Diagnostic System Architecture
%J MAG98
%P 174-179
%K AA21
%A M. E. Atwood
%A R. Brooks
%A E. R. Radlinski
%T Causal Models: The Next Generation of Expert Systems
%J MAG98
%P 180-184
%K AI01 AI16
%A D. Neiman
%T Technological Considerations for Industrial Expert Systems Applications
%J MAG98
%P 185
%K AI01
%A M. Chester
%T The Military Reconnoiters Neural Systems
%J Electronics Product Magazine
%V 29
%N 10
%D OCT 15 1986
%P 78-82
%K AI12 AA18
%A Dennis de Champeaux
%T Subproblem Finder and Instance Checker, Two Cooperating Modules for Theorem
Provers
%J JACM
%V 33
%N 4
%D OCT 1986
%P 633-657
%K AI11
%A W. Eric L. Grimson
%T The Combinatorics of Local Constraints in Model-Based Recognition and Localiz
ation
from Sparse Data
%J JACM
%V 33
%N 4
%D OCT 1986
%P 658-686
%K AI06
%A B. Ramamurthi
%A A. Gersho
%T Classified Vector Quantization of Images
%J IEEE Transactions on Communications
%V 34
%N 11
%D NOV 1986
%P 1105-1115
%K AI06
%A R. Buhr
%T Front-face Analysis and Classification
%J ntzArchiv
%V 8
%N 10
%D OCT 1986
%P 245-256
%K AI06
%A E. M. Clarke
%A E. A. Emerson
%A A. P. Sistla
%T Automatic Verification of Finite-State Concurrent Systems Using Temporal
Logic Specifications
%J ACM TRANS on Programming Languages and Systems
%V 8
%N 2
%D APR 1986
%P 244-265
%K AA08
%A R. Narasimhan
%T Artificial Intelligence in 5th-Generation Computers
%J MAG99
%P 71-84
%K AI16
%A P. V. S. Rao
%A K. K. Paliwal
%T Automatic Speech Recognition
%J MAG99
%P 85-120
%K AI05
%A D. D. Majumder
%T Pattern Recognition, Image Processing and Computer Vision in 5th Generation
Computer Systems
%J MAG99
%P 139
%K AI06
%A A. Victor Cabot
%A S. Selcuk Erenguc
%T A Branch and Bound Algorithm for Solving a Class of Nonlinear Integer
Programming Problems
%J Naval Research Logistics Quarterly
%P 559-568
%K AI03
%A Terry Winograd
%A Fernando Flores
%T Understanding Computers and Cognition
%I Ablex Publishing Corporation
%C Norwood, NJ
%D 1986
%K AT15 AI08 AI16
%X 224 pages ISBN 0-89391-050-3 $24.95
%A Tsuyoshi Yamamoto
%T An Application of List Processing Artificial Intelligence to Computer
Graphics and CAD
%J Pixel
%N 40
%P 80-85
%D 1986
%K AA04 UNIX graphics T01
%A R. Hauser
%T NewCAT: Parsing Natural Language Using Left-Associative Grammar
%S Lecture Notes in Computer Science
%I Springer-Verlag
%V 231
%D 1986
%K AT15 AI02
%X 540 pages Figures, $34.80 ISBN 3-540-16781-1
%A T. Samad
%T Natural Language Interface for Computer-Aided Design
%S Kluwer International Series in Engineering and Computer Science
%V 14
%D 1986
%I Kluwer Academic Publishers
%X 188 pages, $38.95, ISBN 0-89838-222-X
%A P. E. Utgoff
%T Machine Learning of Inductive Bias
%S Kluwer INternational Series in Engineering and Computer Science
%V 15
%D 1986
%I Kluwer Academic Publishers
%X 165 pages, $37.50, ISBN 0-89838-223-8
%A S. P. Dutta
%A R. S. Lashkari
%A G. Nadoli
%A T. Ravi
%T A Heuristic Procedure for Determining Manufacturing Families
from Design-Based Grouping for Flexible Manufacturing Systems
%J Computers and Industrial Engineering
%V 10
%N 3
%D 1986
%P 193-202
%K AA26
%A Efraim Turban
%T Expert Systems- Another Frontier for Industrial Engineering
%J Computers and Industrial Engineering
%V 10
%N 3
%D 1986
%P 227-236
%K AI01
%A Michael M. Skolnick
%T Application of Morphological Transformation to the Analysis of
Two-Dimensional Electrophoretic Gels of Biological Materials
%J MAG100
%P 306-332
%K AA10 AI06
%A Stanely R. Sternberg
%T Grayscale Morphology
%J MAG100
%P 333-354
%K AI06
%A Fernand Meyer
%T Automatic Screening of Cytological Specimens
%J MAG100
%P 356-369
%K AA10 AI06
%A Xinhua Zhuang
%A Robert M. Haralick
%T Morphological Structuring Element Decomposition
%J MAG100
%P 370-382
%K AI06
%A Leonardo C. Topa
%A Robert J. Schalkoff
%T An Analytical App[roach to the Determination of Planar Surface Orientation
Using Active-Passive Image Pairs
%J MAG100
%P 404
%K AI06
%A Akira Shiozaki
%T Edge Extraction Using Entropy Operator
%J MAG101
%P 1-9
%K AI06
%A Son Pham
%T Digital Straight Segments
%J MAG101
%P 10-30
%K AI06
%A Hussein A. H. Ibraham
%A John R. Kender
%A David Elliot Shaw
%T On the Application of Massively Parallel SIMD Tree Machines to Certain
Intermediate Level Vision Tasks
%J MAG101
%P 42-52
%K H03 AI06
%A Marijke F. Augusteijn
%A Charles R. Dyer
%T Recognition and Recovery of the Three-Dimensional Planar Point Patterns
%J MAG101
%P 76-99
%K AI06
%A John Tyler
%T Sppec Recognition System Using Walsh Analysis and Dynamic Programming
%J Microprocessors and Microsystems
%V 10
%N 8
%D OCT 1986
%P 427-433
%K AI05 H01
%A N. Rushby
%T A Knowledge-Engineering Approach to Instructional Design
%J MAG102
%P 385-389
%K AA07
%A H. Barringer
%A I. Mearns
%T A Proof System for ADA Tasks
%J MAG102
%P 404-415
%K AA08 AI11
%A J. M. Hoc
%T Review of Introduction Expert Systems by M. Gondran
%J MAG103
%P 278
%K AT15 AI01
%A J. M. Hoc
%T Review of Man Faced with Artificial Intelligence by J. D. Warnier
%J MAG103
%P 280
%K AT15
%A E. Schuster
%A P. Knoflach
%A K. Huber
%A G. Grabner
%T An Interactive Processing System for Ultrasonic Compound Imaging,
Real-Time Image Processing and Texture Analysis
%J Ultrasonic Imaging
%D 1986
%V 8
%N 2
%P 131
%K AA01 AI06
%A R. Opie
%T Expert Systems Developing Applications
%J Control and Instrumentation
%V 18
%N 10
%D 1986
%P 57-60
%K AI01
------------------------------
End of AIList Digest
********************
∂01-Mar-87 2055 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #62
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 1 Mar 87 20:55:41 PST
Date: Sun 1 Mar 1987 19:01-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #62
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 2 Mar 1987 Volume 5 : Issue 62
Today's Topics:
Query - Expert System Definition,
Discussion - Expert System Definition & Intelligence &
Logic in AI & A Defence of Vulgar Tongue,
News - AI Software Revenues,
Review - Spang Robinson Report 3.2
----------------------------------------------------------------------
Date: 28 Feb 87 00:15:36 GMT
From: ihnp4!alberta!calgary!arcsun!roy@ucbvax.Berkeley.EDU (Roy Masrani)
Subject: dear abby....
Dear Abby. My friends are shunning me because I think that to call
a program an "expert system" it must be able to explain its decisions.
"The system must be able to show its line of reasoning", I cry. They
say "Forget it, Roy... an expert system need only make decisions that
equal human experts. An explanation facility is optional". Who's
right?
Signed,
Un*justifiably* Compromised
Roy Masrani, Alberta Research Council
3rd Floor, 6815 8 Street N.E.
Calgary, Alberta CANADA T2E 7H7
(403) 297-2676
UUCP: ...!{ubc-vision, alberta}!calgary!arcsun!roy
CSNET: masrani%noah.arc.cdn@ubc.csnet
--
Roy Masrani, Alberta Research Council
3rd Floor, 6815 8 Street N.E.
Calgary, Alberta CANADA T2E 7H7
(403) 297-2676
UUCP: ...!{ubc-vision, alberta}!calgary!arcsun!roy
CSNET: masrani%noah.arc.cdn@ubc.csnet
------------------------------
Date: Sun 1 Mar 87 10:48:43-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Subject: Definition of Expert System (Re: Dear Abby)
Why must an expert system explain its reasoning? 1) To aid system
building and debugging; 2) to convince users that the reasoning is
correct; and 3) to force conformance to a particular model of
human reasoning.
Reason 1 is hardly a sine qua non. It is necessary that the line
of reasoning be debuggable, of course, but that can be done with
checkpoints, execution traces, and other debugging tools. Forcing
the system to "explain" its own reasoning adds to the complexity of
the system without directly improving performance. An explanation
capability may reduce the time, effort, and expertise required to
build and maintain or modify the system -- particularly if domain
experts instead of programmers are doing the work -- but the real
issue is what knowledge is encoded and how it is used. We have been
guilty of defining the field by the things that happened to be easy
to implement in a few early programs, just as we sometimes define AI
as that which is easy to do in LISP.
Reason 2, convincing the user, is a worthy goal and perhaps necessary
in consulting applications, but contains some traps. The real test of
a system is its performance. If adequate (or exceptional) performance
can be documented, many customers will have no interest about what
goes on in the black box. If performance is documentably poor, adding
an explanatory mechanism is just a marketing gimick: an expert con.
The explanations are really only needed if some of the decisions are
faulty and it is possible to recognize which ones from the explanation.
Further, there are different types of explanation that should be
considered. The traditional form is basically a trace of how a
particular diagnosis was reached. This is only appropriate when
the reasoning is sequential and depends strongly on a few key facts,
the kind of reasoning that humans are able to follow and "desk check".
Reasoning that is strongly parallel, non-deterministic, or depends
on subtle data distinctions (without linguistic names) are not amenable
to such explanations. This sort of problem often arises in pattern
recognition. In image segmentation, for instance, it is typically
unreasonable (for anyone but a programmer) to ask the system "By what
sequence of operations did you extract this region?". It is reasonable,
however, to ask how the target region differs from each of its neighbors,
and how it might now be extracted easily given that one knows its
distinguishing characteristics. In other words, the system should
answer questions in light of its current knowledge instead of trying
to backtrack to its knowledge at the time it was making decisions.
The system's job is to extract structure from chaos, and explanations
in terms of half-analyzed chaos are not helpful.
Reason 3, adherence to a particular knowledge engineering methodology
is really the sticking point. Some would claim that rule-based
reasoning and its attendant explanatory capability is fundamentally
different from other paradigms and perhaps even fundamental to human
reasoning; it therefore deserves a special name ("expert system").
Others would claim that rule-based systems are only one model of
expert reasoning and that the name should apply to any attempt at
a psychologically based or knowledge-based program. A third group,
mostly those selling software, claim performance alone as the criterion.
I believe that explanatory capability, as currently feasible, is a
correlate of the rule-based approach and is not central in theory; it
may, however, be the key ingredient to making a particular application
feasible or marketable. I don't believe that every optimal algorithm
is AI, so I reject the pure performance criterion for expert systems.
As to whether expert systems include only rule-based systems or all
knowledge-based system, I can't say -- that is a matter of convention
and has to be settled by those in the expert system field.
-- Ken Laws
------------------------------
Date: 24 Feb 87 12:57:37 GMT
From: mcvax!ukc!warwick!gordon@seismo.css.gov (Gordon Joly)
Subject: Re: What is this "INtelliGenT"?
For a working definition of A.I., how about "that which is
yet to be done" or perhaps "that which is yet to be understood"?
Gordon Joly -- {seismo,ucbvax,decvax}!mcvax!ukc!warwick!gordon
------------------------------
Date: Fri, 27 Feb 87 12:46:54 GMT
From: Jerry Harper <mcvax!euroies!jharper@seismo.CSS.GOV>
Reply-to: jharper@euroies.UUCP (Jerry Harper)
Subject: Re: logic in ai
I think some useful distinction can be made between the use of _formalisms_
in AI and the use of logic(s). The function of the latter with respect to a
series of inference rules and a particular domain of discourse is the
characterization of truth and logical consequence. The function of the
former on my own reading of AI literature concerned with NLP systems
seems to merely crystallize certain _intuitions_ a researcher may have
about the description and solution to a various problem. In some cases
these may conform to a logical calculus, in other cases they merely
appear to do so. This is quite reasonable in a research context such as
AI provided one accepts that computational tractability and formal
rigour are different objectives served by methodological demands.
For instance, it would be impossible to build the model theory of
many logics used for semantic investigations of natural language into
a computational system. Yet _doing_ semantics entails the use of
infinitary methodology once the model theory is based on possible
worlds. Reinterpreting a semantic theory computationally is not
equivalent. More fundamentally, it is the usage of the word _logic_
which is at issue. With the plethora of logical calculi it makes
little sense to claim one uses _a lot of logic_ in ones work. Indeed
if anyone has an uncontentious definition of modern logic please
forward it.
------------------------------
Date: Thu, 26 Feb 87 14:53 N
From: MFMISTAL%HMARL5.BITNET@wiscvm.wisc.edu
Subject: RE: A defence of vulgar tongue.
Seth Steinberg proposes to use less formal notations in computer science
presentations. I disagree completely!
His argument about clarity is wrong.
Although architects do not use mathematical notations, they do use
a symbolic language (DRAWINGS or even better the lines that constitue
a drawing) to express their ideas. These drawings,
together with a description in specific "jargon" are necessary for
the contractor to make a proper cost estimate and to make the necessary
calculations for the strength of the constructions. So even for them
it is necessary to use a formal language. I believe a formal language
is useful to communicate ideas in a certain domain also in CS. Since the
basic operations of computers are indeed logical/mathematical ones, there
is no objection against using their symbolic notations.
Computer programs are inplementations of the stuff, computer science is
made of. Unfortunately, we have to check program code to check what the
program is doing. Just for that reason, debugging and software maintenance
is expensive. When we can better formalize the "art of programming" we
might come up with better understood, and more easy to maintain programs.
Discussions about program performance might then just as well be done in
the formal language for that formalization. I just remembered that a language
like APL is closely related with mathematics, specifically in matrixalgebra.
It is probably possible to formaly proof (at least to some extent) the
correctness of such a program.
Looking forward to more CS presentations using formal (mathematical and
logical notations) in order to increase the understanding what is really
ment.
Jan L. Talmon (not a computer scientist)
MFMISTAL@HMARL5.BITNET
------------------------------
Date: Sat, 28 Feb 1987 13:18 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: AI Software Revenues
Artificial intelligence software generated $200 million dollars in
revenue in 1986. Expert system tools generated 18.6 million.
To put these numbers in perspective, the total software market is
12.3 billion and CAD/CAE software is 665 million.
Also sold in 1986, was
464 million dollars worth of robot systems and 100 million dollars
worth of vision equipment.
------------------------------
Date: Sat, 28 Feb 1987 13:19 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Review - Spang Robinson Report 3.2
Summary of the Spang Robinson Report
February 1987, Vol. 3, No. 2
Development Tools Migrate From Micro to Mainframe
Discussion of the trend for companies selling expert system software for IBM
PC's to put their systems on higher level machines such as minis and mainframes
and vice versa.
Some companies are porting major applications to microcomputer tools that
ostensibly offer "less functionality." Examples of this are a paint
manufacturing application ported from KEE to Insight and another port
from Inference's ART to ACORN.
__________________________________________________
Connecting to the Corporate Database
KEE connection provides an interface with the SQL query language. A data base
relation maps into a class with a database attribute mapping into a slot.
Data is downloaded from the database as needed to solve the problem.
Projects to directly integrate the expert system into the database include
Postgres at Berkeley, Probe at Computer Corporation of America and
Starburst at IBM. The prices for development versions of the system
range from $18,000 to $45000 with delivery versions ranging from $3000
to $18,750 depending upon size of VAX.
__________________________________________________
Shorts
Hitachi, IBM Japan and Carnegie Mellon are developing a multi-lingual machine
translation system. They have already developed a system for analyzing
the natural language utility specifications.
Fuji Electric has developed an expert system to control turbines for a thermal
power generation system.
Also, thermostats are selected and configured for Tohoku oil.
Fanac plans to build an intelligent robot integrating three-dimensional
vision and touch sensors.
Matsushita is developing a LISP machine with over 50 times the power of
a VAX 8600.
Expertelligence is selling an application builder for the Macintosh for
non-programming users.
Applied Expert Systems (APEX) has laid off a number of employees.
They are selling a system to help financial institutions expand client
relationships.
Digitalk has announced a new release of Smalltalk/V. Extensions provide
EGA capabilities, multiprocessing, DOS call features and music.
Teknowledge reports revenues of $10,867,7000 for the latter half of
1986.
Symbolics will be financing Whitney/Demos, a Los Angeles-based developer
of computer graphics and animation technology. Symbolics will be getting
marketing rights to various in-house programs of Whitney/Demos and will
be providing them with various graphic workstations
Europeans spent $200 million on expert system development. Ovum sells
a complete report on European expert system development for $495.00.
Halbrecht associates predicts a great deal of senior and mid-level turnover
of AI professionals.
___________________________________________________________________
Review of the Sixth International Workshop on Expert Systems and
Their Applications (Proceedings).
------------------------------
End of AIList Digest
********************
∂04-Mar-87 0131 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #63
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 4 Mar 87 01:30:53 PST
Date: Tue 3 Mar 1987 22:57-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #63
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 4 Mar 1987 Volume 5 : Issue 63
Today's Topics:
Administrivia - Moderating Best Lispm/WorkStation Discussion &
Timing of the INtelliGenT Discussion,
Expert systems - Definition
----------------------------------------------------------------------
Date: Tue, 3 Mar 87 09:29:45 PST
From: TAYLOR%PLU@ames-io.ARPA
Subject: Moderating Best Lispm/WorkStation(again)
I am posting this again(?) because I am not sure it was successful the
first time (it came back undelivered).
It has been suggested that I moderate, summarize and the post summary of
this discussion, instead of dumping it on Ken Laws (AIList).
I agree.
Therefore, please e-mail all responses, questions, flames, etc. to me.
Thanks - Will
Will Taylor - Sterling Software, MS 244-17,
NASA-Ames Research Center, Moffett Field, CA 94035
arpanet: taylor@ames-pluto.ARPA
usenet: ..!ames!plu.decnet!taylor
phone : (415)694-6525
[It wasn't my suggestion, but sounds good to me. Thanks. -- KIL]
------------------------------
Date: 3 Mar 87 14:56:47 GMT
From: allegra!ether@ucbvax.Berkeley.EDU (David Etherington)
Subject: Re: What is this "INtelliGenT"?
Please, can we skip recycling the discussion of what AI *is*?
If people really must post on the subject, perhaps they could
read the last few months' postings first.
Deja vu!
------------------------------
Date: 2 Mar 1987 1415-EST
From: Bruce Krulwich <KRULWICH@C.CS.CMU.EDU>
Subject: Expert systems
There seems to be a trend nowadays to use the phrase "expert systems" to
mean rule-based systems, not to mean any systems that mimick expert
behavior. While I'm not sure I like the terminology, I think that it's
beneficial to have a seperate catagory for rule-based-systems work,
since that's often very different from other A.I. work (especially in
describing research work) This opinion may, however, be biased by my
opinions of current work in AI and expert systems. What do others think??
Bruce Krulwich If you're right 95% of the time,
why worry about the other 3% ??
arpa: krulwich@c.cs.cmu.edu
bitnet: krulwich@c.cs.cmu.edu Any former B-CC'ers out there??
uucp: ... !seismo!krulwich@c.cs.cmu.edu
------------------------------
Date: 2 Mar 87 03:06:55 GMT
From: rpics!yerazuws@seismo.css.gov (Crah)
Subject: Re: dear abby....
In article <178@arcsun.UUCP>, roy@arcsun.UUCP (Roy Masrani) writes:
>
> Dear Abby. My friends are shunning me because i think that to call
> a program an "expert system" it must be able to explain its decisions.
> "The system must be able to show its line of reasoning", I cry. They
> say "Forget it, Roy... an expert system need only make decisions that
> equal human experts. An explanation facility is optional". Who's
> right?
While you're developing an expert system, you have to know not just
that it inferred something incorrectly, but WHY it inferred it incorrectly.
Looking through 4,000 rules trying to find the one with a typo is
no fun, no fun at all.
Secondly, once you and your expert have convinced yourself that the
system is right, you must now convince your first set of users that the
system is right, too. These users may not be as expert as *your* expert,
but they have some knowledge of the subject. Perhaps a few of them are even
more expert than your expert in some narrow subfield.
It behooves you to gain acceptance and knowledge from this group, and
if they perceive that the expert system is a "black box", they will have
no encouragement to assist in the final tweaking and debugging. To be
useful, your system must not only be correct. It must be accepted and
used!
Personal experience- People, including the expert whose knowledge has been
captured, don't like (maybe don't trust?) a black-box expert system, if
they can't ask it why it gave the answer it did.
-Bill Yerazunis
"...these guys had "Thugs 'R' Us" stencilled all over them"
------------------------------
Date: 2 Mar 87 15:58:29 GMT
From: cbatt!osu-eddie!tanner@ucbvax.Berkeley.EDU (Mike Tanner)
Subject: Re: dear abby....
Leaving aside the utility of explanations in developing a system and
in convincing users it is behaving properly there is this:
Experts are capable of explaining their reasoning, justifying
conclusions, etc. Hypothesis: they are able to do this partly
because of the way their knowledge is organized and used in
problem-solving.
Therefore, if your expert system is incapable of explaining itself you
probably haven't got the knowledge organization and problem solving
strategy right. (Granted, it's only a hypothesis. It seems right to
me. I'm in the process of working on a PhD dissertation on how
knowledge organization and problem-solving strategy can help produce
good explanations. Doesn't exactly support the hypothesis, but it
should clarify it a bit.)
This assumes you're interested in how knowledge-based problem-solving
works. If all you want is an expert system, ie, a system which gets
right answers, then you're back to utility arguments for explanation.
(Though, I don't think you'll be successful at getting good
performance without this understanding.)
-- mike
ARPA: tanner@ohio-state.arpa
UUCP: ...cbosgd!osu-eddie!tanner
------------------------------
Date: 2 Mar 87 15:36:17 GMT
From: ulysses!sfmag!sfsup!saal@ucbvax.Berkeley.EDU
Subject: Re: dear abby....
In article <178@arcsun.UUCP> roy@arcsun.UUCP (Roy Masrani) writes:
>
>Dear Abby. My friends are shunning me because i think that to call
>a program an "expert system" it must be able to explain its decisions.
>"The system must be able to show its line of reasoning", I cry. They
>say "Forget it, Roy... an expert system need only make decisions that
>equal human experts. An explanation facility is optional". Who's
>right?
>Signed,
>Un*justifiably* Compromised
>Roy Masrani, Alberta Research Council
It all depends. During development it is absolutely necessary
for the system to give its reasoning, if only as a useful
debugging tool. (Is the system using the correct logic to get to
the decision.) Once it is "in production" (the field) it may not
be as important tot give an explanation every time. This is
particularly the case when the expert system is used to help do
some of the more mundane tasks on a very frequent basis. There
are 2 reasons for this. (1) the user may be able to agree
intuitively after deriving the answer - the machine has just
helped speed the process. OR (2) If a production ES has been
converted to a compiled language, the code to express the
rationale may be removed to speed up run time.
Sam Saal
------------------------------
Date: 2 Mar 87 20:24:38 GMT
From: tektronix!sequent!mntgfx!franka@ucbvax.Berkeley.EDU (Frank A.
Adrian)
Subject: Re: dear abby....
In article <178@arcsun.UUCP> roy@arcsun.UUCP (Roy Masrani) writes:
>"expert system" ... must be able to explain its decisions.
VS.
>... expert system need only make decisions that equal human experts.
> An explanation facility is optional".
Well, given the level of explaination most human experts give (e.g., "Well,
I did it this way because it felt right," or "Gosh, I don't know, it
seemed like a good idea at the time."), I tend to agree with number two.
In fact, has anyone done an expert system which automatically spits out
one of the above phrases (or any number of similar phrases) as an
"explaination"? Could bring the damn things closer to Turing capability
as percieved by the user... "What the hell are YOU asking for," might
get the proper amount of arrogance I've seen in most experts (:-).
Frank Adrian
Mentor Graphics, Inc.
------------------------------
Date: 2 Mar 87 20:37:59 GMT
From: ihnp4!alberta!calgary!arcsun!rob@ucbvax.Berkeley.EDU (Rob
Aitken)
Subject: Re: dear abby....
In article <178@arcsun.UUCP>, roy@arcsun.UUCP (Roy Masrani) writes:
>
> Dear Abby. My friends are shunning me because i think that to call
> a program an "expert system" it must be able to explain its decisions.
> "The system must be able to show its line of reasoning", I cry. They
> say "Forget it, Roy... an expert system need only make decisions that
> equal human experts. An explanation facility is optional". Who's
> right?
>
> Signed,
>
> Un*justifiably* Compromised
>
Dear Mr. Compromised:
You should ask yourself whether you want a complete, intelligible
explanation facility, or just the basics (i.e. "The answer is X because
Rule Y says so"). If it is the latter, your friends are wrong and you
should tell them so. If the former, your friends are probably programmers
and lazy ones at that. You should find new friends.
Abby.
> Roy Masrani, Alberta Research Council
> Roy Masrani, Alberta Research Council
P.S. You don't need to specifically include a .signature
------------------------------
Date: Tue, 3 Mar 87 13:29:38 EST
From: Bruce Nevin <bnevin@cch.bbn.com>
Subject: RE: dear Abby
We humans do not usually backtrack over a line of reasoning that led to
a conclusion. Instead, we reconstruct what such a line of reasoning
might plausibly be. It's called rationalization.
How wonderful it is to be rational beings, for we can make
plausible whatever conclusions we cherish.
--Ben Franklin (paraphrase from memory)
As the ordinary usage of the term suggests, rationalization can and
often does lead us astray, but that is a critique of the quality of the
particular line of reasoning that an individual might reconstruct to
rationalize or `make rational' a given conclusion. We reach conclusions
by means that are not guaranteed. We need valid rationalization to
check them out.
Pearce made the point that mathematical reasoning is a tidy pyramidal
structure erected after the fact, and that it is better both for
presentation and for pedagogy to show the path actually followed, even
though it appears less elegant. Few have done this.
Does this mean Pearce would advocate expert systems explaining by
retracing? I think not, because he explicitly recognized the importance
of intuitive hunches in mathematical and logical work. The proof is
merely to validate conclusions reached by a less respectable path--to
rationalize them.
Since our expert systems cannot emulate hunches, a useful approach is to
check out conclusions human users have a hunch about. Can they validly
be rationalized? Isn't this in fact the use to which many users prefer
to put expert systems like Palladian's financial consultant?
What is an expert?
Some say: an expert is someone who knows a great deal about his
subject.
I prefer: an expert is someone who knows some of the worst
mistakes that can be made in his subject, and how to avoid them.
--Werner Heisenberg
Bruce Nevin
bn@cch.bbn.com
(This is my own personal communication, and in no way expresses or
implies anything about the opinions of my employer, its clients, etc.)
------------------------------
Date: 3 Mar 87 17:54:03 GMT
From: trwrb!aero!coffee@ucbvax.Berkeley.EDU (Peter C. Coffee)
Subject: Re: dear abby....
In article <3269@osu-eddie.UUCP> tanner@osu-eddie.UUCP (Mike Tanner) writes:
>If all you want is an expert system, ie, a system which gets
>right answers, then you're back to utility arguments for explanation.
I agree with everything else Mike said about this issue, but it seems to
me that the label "expert system" _should_ mean something _more_ than "a
system that gets right answers." We've had useful programs, implicitly
applying "expert" knowledge, for a long time: the new label should reflect
new capabilities. Hayes-Roth et alia, in _Building_Expert_Systems_, say the
following:
"...[E]xpert systems differ from the broad class of AI tasks in several
respects...they employ self-knowledge to reason about their own inference
processes and provide explanations or justifications for conclusions
reached."
This is one of the milestone texts in the field, and definitions are useful
things: it seems to me that disputes over whether explanation is "needed"
before you can call it an expert system are missing the point. We _have_ what
seems to me to be a mainstream definition for the term; if we want
to talk about a system that _doesn't_ do explanation, can't we just call
it a computer program (or a parser, or a pattern recognizer, or whatever)
instead of trying to stretch the popular label to fit it?
Constructively, I hope, Peter C.
------------------------------
End of AIList Digest
********************
∂04-Mar-87 0324 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #61
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 4 Mar 87 03:24:30 PST
Date: Sun 1 Mar 1987 18:57-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #61
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 2 Mar 1987 Volume 5 : Issue 61
Today's Topics:
Seminars - Motion Planning in Time-Varying Environment (UPenn) &
A Step Toward a Logic Machine (SMU) &
VLSI Approach to the ELIS Lisp Machine (SU),
Conference - Columbia AI Symposium
----------------------------------------------------------------------
Date: Sat, 28 Feb 87 14:01:15 EST
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Motion Planning in Time-Varying Environment (UPenn)
COLLOQUIUM
Computer and Information Science
University of Pennsylvania
Philadelphia PA
10:30am 3/2/87, 307 Towne Bldg.
Motion Planning in Time-varying Environment
Kamal Kant Gupta
Computer Vision and Robotics Lab
McGill University
Motion Planning Problem is to determine the motion of an object,
from a start position to a goal position, while avoiding collision
with other objects (obstacles) in its enviroment. Most Motion Planning
research, up until very recently, has considered static obstacles, i.e.,
plan the path to avoid the static obstacles, called the path planning
problem, or, the PPP. We consider the problems of planning collision-
free trajectories (path as a function of time) for an object among
moving as well as static obstacles. We call it the Trajectory Planning
Problem (TPP) in time-varying enviroments.
Our approach to formulating the TPP is to consider space-time, where
time is represented explicitly. Such a representation leads to a
geometric view of trajectory - as a curve in space-time-and lends itself
to use of computational geometric techniques in space-time. Such techniques
are quite novel in the sense that they do not occur in the case of only
static obstacles.
We propose a heuristic but natural decomposition of the TPP into two
sub-problems: (i) plan a path to avoid the static obstacles, i.e.
solve the PPP, and (ii) plan the velocity of the robot along the
path to avoid collision with the moving obstacles. We call the
second sub-problem the velocity planning problem, the VPP. The
main motivation behind the decomposition is to reduce the
complexity of the full problem, and present efficient algorithms
for collision-free trajectories.
Standard algorithms may be used to sovle the PPP. We then present
fast, efficient and complete algorithms to solve the VPP. The essence
of these algorithms lies in forulating the VPP in 2-dimensional path-
time. In the process, we also explore some properties of the path-
time space.
These algorithms have applications in several domains of robotics. In
particular, we shall illustrate the use of these algorithms in two
domains: i) for autonomous navigation of a mobile robot, and ii)
for motion co-ordination of multiple robots.
------------------------------
Date: Sat, 28 Feb 1987 13:19 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Seminar - A Step Toward a Logic Machine (SMU)
Seminar Announcement, Computer Science and Engineering, Southern
Methodist University, MOnday, March 2, 1987, Room 315 SIC, 1:30PM
A Step Toward a Logic Machine, C. S. Tang, Carnegie-Mellon University
XYZ is a software development support system to unify various ways
of programming programming [sic] with HLL (Pascal, Ada, Fortran etc.),
programming with abstract specification (temporal logic, production systems,
Prolog, pre-post condition specification, etc.) and programming with graphics
(structured flow chart, Petri Nets, Data Flow Diagrams, etc.) It is based on
a linear-time temporal logic language with a uniform framework of programs,
to combine the abstract behavior description with dynamic state transition.
It could be used to represent the dynamic semantics of HLLs, which
could serve as the basis of a semantics-directed compiler generation and source
to source transformation system, and also to represent different layers of
abstract specification, from the very abstract level down to the assembly
like efficiently executable level, such that a method is introduced for
programming by decompositional specification and verification
within this identical famework. And on this basis, related with programming
with Dataflow Diagram, an approach to connect the informal methodology of
sytem design with the fomral method of programming such as specification,
verification, program decomposition and transformation are suggested. It
is considered as a step toward a model of an architecture really based
on logic, which could do logic reasoning and abstract specification
conveniently and is still able to execute conventional programs as
efficiently as on conventional Von Neumann computers.
This "uniform program framework" appraoch is different from those to
express program state transition by introducing new logic variants
such as interval logic or branching logic in that: 1) This approach
can avoid the task of building new metamathematical foundations and is
easier to understand to use; 2) It could be implemented efficiently;
3) Prolog-like production systems are its sublanguage, so it is
different from those systems to extend Prolog with temporal logics.
The latter could not execute algorithmic programs efficiently; 4) It is
even more expressive.
------------------------------
Date: 28 Feb 87 1027 PST
From: Carolyn Talcott <CLT@SAIL.STANFORD.EDU>
Subject: Seminar - VLSI Approach to the ELIS Lisp Machine (SU)
Title: VLSI approach to the ELIS Lisp machine
Speaker: Yasushi Hibino
Director of Second Research Section
NTT Basic Research Laboratories
Nippon Telegraph and Telephone
Time: Monday March 2, 3:30pm
Place: 352 Margaret Jacks
Abstract:
The LISP Machine ELIS was designed to achieve a comfortable
interactive programming environment by a fast microcoded LISP
interpreter. ELIS is a microprogram control machine with a 32k
64-bits-words writable control store. ELIS also has a 32K word
hardware stack and special memory interface registers. VLSI ELIS chip
is developed by two-micron double metal layer CMOS technology. The
VLSI ELIS is compatible with an ELIS breadboard machine in the level
of microcodes. Therefore, TAO Lisp, which is a dialect of CommonLisp
and assimilates object oriented programming, logic programming and
concurrent programming within the Lisp world, is running on the VLIS
ELIS. The speed of interpreted codes in TAO is comparable to that of
compiled codes of MIT's Lisp machines. THis good performance is
attained by a simple internal bus structure and a design of fucntion
blocks with iterative circuit structures.
In my talk, the architecture of ELIS is briefly introduced and a VLSI
approach for it is discussed. The approach is not like Meed and
Conway's. It is rather orthodox approach, because in the case of a
dedicated machine it is not desirable that VLSI design methodology
restricts an architecture of the machine.
[CLT -- Sorry for the short notice, please pass this on to anyone
you think might be interested.]
------------------------------
Date: Sun 1 Mar 87 18:46:18-EST
From: Michael Lebowitz <LEBOWITZ@CS.COLUMBIA.EDU>
Subject: Conference - Columbia AI Symposium
ARTIFICIAL INTELLIGENCE DAY
SPONSORED BY DEPT. OF COMPUTER SCIENCE
COLUMBIA UNIVERSITY
MARCH 6, 1987
DAG ROOM, SCHOOL OF INTERNATIONAL AFFAIRS
10:00 Brian Reiser "An Intelligent Tutoring Systems"
Princeton Univ.
11:00 Coffee Break
11:30 Edward H. Shortliffe "Graphical Access to an Expert System:
Stanford Univ.
2:00 Carl Hewitt "Due Process"
MIT
3:00 Ruzena Bajcsy "Errors and Mistakes in Sensory
Univ. of Pennsylvania Programming"
4:00 Reception Computer Science Lounge
------------------------------
End of AIList Digest
********************
∂05-Mar-87 0027 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #64
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 5 Mar 87 00:27:23 PST
Date: Wed 4 Mar 1987 21:43-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #64
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 5 Mar 1987 Volume 5 : Issue 64
Today's Topics:
Seminars - A Stochastic Genetic Search Method (CMU) &
Hypothesis Formation (Rutgers) &
Creative Analogies in Scientific Progress (UPenn) &
On Visual Formalisms (CMU),
Conference - Workshop on Coupling Symbolic and Numeric Computing &
AAAI Workshop on Planning for Autonomous Mobile Robots &
Computing and Society in Seattle, Preceding AAAI &
HICSS-21 Call For Papers
----------------------------------------------------------------------
Date: Sun 1 Mar 87 17:49:12-EST
From: Dave Ackley <David.Ackley@C.CS.CMU.EDU>
Subject: Seminar - A Stochastic Genetic Search Method (CMU)
David H. Ackley
Carnegie Mellon Computer Science doctoral dissertation defense
Tuesday, February 24, 1987 at 1pm
Wean Hall 5409
"Stochastic iterated genetic hillclimbing"
Abstract
In the "black box function optimization" problem, a search strategy is
required to find an extremal point of a function without knowing the
structure of the function or the range of possible function values.
Solving such problems efficiently requires two abilities. On the one
hand, a strategy must be capable of "learning while searching": It must
gather global information about the space and concentrate the search in
the most promising regions. On the other hand, a strategy must be
capable of "sustained exploration": If a search of the most promising
region does not uncover a satisfactory point, the strategy must redirect
its efforts into other regions of the space.
This dissertation describes a connectionist learning machine that
produces a search strategy called "stochastic iterated genetic
hillclimbing" (SIGH). Viewed over a short period of time, SIGH displays
a coarse-to-fine searching strategy, like simulated annealing and
genetic algorithms. However, in SIGH the convergence process is
reversible. The connectionist implementation makes it possible to
"diverge" the search after it has converged, and to recover
coarse-grained information about the space that was suppressed during
convergence. The successful optimization of a complex function by SIGH
usually involves a series of such converge/diverge cycles.
SIGH can be viewed as a generalization of a genetic algorithm and a
stochastic hillclimbing algorithm, in which genetic search discovers
starting points for subsequent hillclimbing, and hillclimbing biases the
population for subsequent genetic search. Several search
strategies---including SIGH, hillclimbers, genetic algorithms, and
simulated annealing---are tested on a set of illustrative functions and
on a series of graph partitioning problems. SIGH is competitive with
genetic algorithms and simulated annealing in most cases, and markedly
superior in a function where the uphill directions usually lead \away/
from the global maximum. In that case, SIGH's ability to pass
information from one coarse-to-fine search to the next is crucial.
Combinations of genetic and hillclimbing techniques can offer dramatic
performance improvements over either technique alone.
------------------------------
Date: Mon, 2 Mar 87 13:04 EST
From: FAWCETT@RED.RUTGERS.EDU
Subject: Seminar - Hypothesis Formation (Rutgers)
On Thursday, March 19th at 10:30 AM, Prof. Lindley Darden from the
University of Maryland will speak on her work on hypothesis formation. The
room will be announced shortly. An abstract and a summary of her interests
follow.
"Hypothesis Formation Using Part-Whole Interrelations"
Lindley Darden
This paper discusses an implementation, called SUTTON, of
strategies for rediscovering the chromosome theory of heredity.
Walter Sutton formulated the theory in the early 20th century, by
postulating interrelations between the fields of cytology and
genetics. Knowledge from these fields during that period is
represented in a frame-based system, and rules for using
knowledge from one field to guide hypothesis formation in
the other are implemented in LISP. In particular, the discovery
that the gene is part of the chromosome is simulated, and general
rules for part-whole reasoning are investigated, including rules
for inheritance and propagation of causal relations in part-whole
hierarchies.
Keywords: Hypothesis formation, scientific discovery, learning,
identity relation, part-whole relation, causality.
Lindley Darden is an Associate Professor in the Departments of
Philosophy and History and a member of the graduate faculty in
the Committee on the History and Philosophy of Science at the
University of Maryland, College Park. She is currently serving
in the second year of a half-time research appointment in the
University of Maryland Institute for Advanced Computer Studies.
This work was done in collaboration with Roy Rada of the National
Library of Medicine. Her research interests include reasoning in
scientific discovery (including analogical reasoning and
formation of abstract theory types) and knowledge representation
techniques for biological knowledge. Her address is Department
of Philosophy, University of Maryland, College Park, Maryland
20742 and darden@mimsy.umd.edu.
(In addition, Prof. Darden gave an invited talk at last summer's AAAI
entitled "Viewing History of Science as Compiled Hindsight".)
------------------------------
Date: Tue, 3 Mar 87 19:11 EST
From: Tim Finin <Tim@cis.upenn.edu>
Subject: Seminar - Creative Analogies in Scientific Progress (UPenn)
SPECIAL JOINT COLLOQUIUM
Computer Science, Psychology and Physics
University of Pennsylvania
THE ROLE OF CREATIVE ANALOGIES IN SCIENTIFIC PROGRESS: COMPUTER MODELING
Professor Douglas R. Hofstadter, University of Michigan
2:30 p.m. Wednesday, March 4, 1987
Tea served at 2:00 in the Faculty Lounge (2E17)
David Rittenhouse Lab - Auditorium A1
The Copycat project is a computer model of analogical thought processes,
particularly ones in which a creative or daring leap is made of the sort that
when done in science often postulates new theoretical constructs or objects
(genes, particles, etc.). Examples of such analogies in science will be
presented and the copycat model will be discussed.
------------------------------
Date: 3 Mar 87 10:23:53 EST
From: Theona.Stefanis@g.cs.cmu.edu
Subject: Seminar - On Visual Formalisms (CMU)
PS SEMINAR
MONDAY, 9 March
WeH 5409
3:30
On Visual Formalisms
David Harel
Weizmann Inst., Rehovot, Israel
(At CMU for the year)
A general mathematical object of diagrammatic nature, the higraph, is
presented. Higraphs borrow and extend ideas from Venn-diagrams, graphs and
hypergraphs. They constitute a visual formalism for describing various
kinds of complex entities, particularly those that involve many sets of
objects having intricate structural (i.e., set-theoretic) interrelationships
as well as additional relations af dynamic, causal or other nature.
Higraphs appear to have many applications, as well as a rich theory that
awaits further research. We shall exhibit a number of applications in
database theory (entity-relationship diagrams), artificial intelligence
(semantic and associative nets) and concurrent reactive systems (statecharts).
Statecharts constitute a natural extension of conventional state-transition
diagrams in ways that make them appropriate for describing large real-world
systems, and they will be described in the talk in some detail.
__________________________________________
------------------------------
Date: 4 Mar 87 02:29:21 GMT
From: ssc-vax!bcsaic!tedk@BEAVER.CS.WASHINGTON.EDU (Ted Kitzmiller)
Subject: Conference - Workshop on Coupling Symbolic and Numeric
Computing
Due to electronic mail system problems and other manifestations of Murphy's
law, the deadline for paper submittals to the workshop on coupling symbolic
and numeric computing (see AAAI magazine Winter issue) has been extended
until late March.
If you had previously sent me an electronic mail message about the workshop
and have not received a response, please resend your message. It appears
that in many instances in which I responded to queries about the workshop
via the network, the responses were not successfully delivered. Unfortunately,
in these instances no evidence of a problem was indicated.
Please contact me at the e-mail address, telephone, or mail address below
(if you have not done so within the last week) if you are interested.
Please include both your phone number and US mail address along with
an explicit e-mail incantation to your site.
Ted Kitzmiller
Boeing Advanced Technology Center
US Mail: MS 7L-64 / PO Box 24346 / Seattle / Washington / 98124-0346
Parcel Post: MS 7L-64 / 2760 160th Avenue SE / Bellevue / Washington / 98008
Phone: (206) 865-3227 E-mail: tedk@boeing.com
------------------------------
Date: Thu, 26-FEB-1987 15:45 EST
From: MILLER%VTCS1.BITNET@wiscvm.wisc.edu
Subject: Conference - AAAI Workshop on PLANNING FOR AUTONOMOUS MOBILE
ROBOTS
Call for Participation and abstracts:
Workshop on PLANNING FOR AUTONOMOUS MOBILE ROBOTS
July 16, 1987, The University of Washington,
Seattle, WA
Sponsored by AAAI
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
Most mobile robot projects have concentrated on robots with specific
missions (e.g., complete errands one and two, follow this road for three
miles). Yet a truly autonomous robot would have its mission described
at a much higher level. Its programming would have to derive specific
tasks to be accomplished based on unpredictable (and perhaps not even
previously classifiable) conditions in its environment. This opens new
issues for the type of planning system necessary to guiding autonomous
robots.
The purpose of this workshop would be to discuss the planning and
knowledge requirements of an autonomous exploratory robot such as a Mars
Rover. How would such a robot decide on a course? What kind of risk
assessment is necessary before deciding to make a dangerous observation?
What types of knowledge are necessary for recognizing something as being
interesting, or dangerous? What role will physical knowledge play in
safe navigation? Is either incremental or opportunistic planning
necessary for dealing with a dynamic world? What kind of demands would
the planning system place on the sensory system?
Among the topics of interest are:
*Spatial Representation *Map Building
*Planning Under Uncertainty *Risk Analysis
*Planning in Dynamic Domains *Physical Reasoning
*Spatial and Temporal Reasoning *Sensor Coordination
*Experience-Based Planning *Route Planning
Those interested in participating in the workshop should submit a short
abstract (no more than two pages) of your work you would wish to
present. Mail two copies of your abstract (hard copy only) before April
15, 1987, to either of the workshop organizers. Invitations for
workshop participation will be sent out by May 15, 1987.
David Miller David Atkinson
562 McBryde Mail Stop 510-202
Department of Computer Science Jet Propulsion Laboratory
Virginia Tech Cal Tech
Blacksburg, VA 24061 4800 Oak Grove Drive
Pasadena, CA, 91109
(703) 961-5605 (818) 577-6603
miller%vtcs1@bitnet-relay.arpa atkinson@usc-ecl.arpa
------------------------------
Date: Tue, 03 Mar 87 08:59:31 PST
From: jon@june.cs.washington.edu (Jon Jacky)
Subject: Conference - Computing and Society in Seattle, Preceding AAAI
(This was sent around in early December - due date 4/1 now approaching)
Call for Papers
DIRECTIONS AND IMPLICATIONS OF ADVANCED COMPUTING
Seattle, Washington July 12, 1987
The adoption of current computing technology, and of technologies that
seem likely to emerge in the near future, will have a significant impact
on the military, on financial affairs, on privacy and civil liberty, on
the medical and educational professions, and on commerce and business.
The aim of the symposium is to consider these influences in a social and
political context as well as a technical one. The social implications of
current computing technology, particularly in artificial intelligence, are
such that attempts to separate science and policy are unrealistic. We
therefore solicit papers that directly address the wide range of ethical
and moral questions that lie at the junction of science and policy.
Within this broad context, we request papers that address the following
particular topics. The scope of the topics includes, but is not limited
to, the sub-topics listed.
RESEARCH FUNDING DEFENSE APPLICATIONS
- Sources of Research Funding - Machine Autonomy and the Conduct of War
- Effects of Research Funding - Practical Limits to the Automation of War
- Funding Alternatives - Can An Automated Defense System Make War
Obsolete?
COMPUTING IN A DEMOCRATIC SOCIETY COMPUTERS IN THE PUBLIC INTEREST
- Community Access - Computing Access for Handicapped People
- Computerized Voting - Resource Modeling
- Civil Liberties - Arbitration and Conflict Resolution
- Risks of the New Technology - Educational, Medical and Legal Software
- Computing and the Future of Work
Submissions will be read by members of the program committee, with the
assistance of outside referees. The program committee includes Andrew
Black (U. WA), Alan Borning (U. WA), Jonathan Jacky (U. WA), Nancy Leveson
(UCI), Abbe Mowshowitz (CCNY), Herb Simon (CMU) and Terry Winograd
(Stanford).
Complete papers, not exceeding 6000 words, should include an abstract,
and a heading indicating to which topic it relates. Papers related to
AI and/or in-progress work will be favored. Submissions will be judged
on clarity, insight, significance, and originality. Papers (3 copies)
are due by April 1, 1987. Notices of acceptance or rejection will be
mailed by May 1, 1987. Camera ready copy will be due by June 1, 1987.
Proceedings will be distributed at the Symposium, and will be on sale
during the 1987 AAAI conference.
For further information contact Jonathan Jacky (206-548-4117) or Doug
Schuler (206-783-0145).
Sponsored by Computer Professionals for Social Responsibility
P.O. Box 85481
Seattle, WA 98105
------------------------------
Date: Tue 3 Mar 87 16:30:34-EST
From: Gail E. Kaiser <KAISER@CS.COLUMBIA.EDU>
Subject: Conference - HICSS-21 Call For Papers
CALL FOR PAPERS
21ST ANNUAL
HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES
(HICSS-21)
Papers are invited for the session(s) on Use of AI Techniques in Software
Design and Implementation in the software track of the 21st annual Hawaii
International Conference on System Sciences (HICSS-21), to be held in Kona,
Hawaii next January 5-8, 1988.
Topics of interest include, but are not limited to, the following artificial
intelligence areas as they apply to software design and implementation,
particularly for large-scale software systems. Techniques may apply to any or
all phases of the software development process: project management,
requirements, functional specification, design specification, modular
decomposition, coding, integration, testing, maintenance, documentation,
delivery, etc. Example applications are given in parentheses.
- Automatic deduction (detecting inconsistencies among programmers'
assumptions, automatic programming)
- Knowledge representation (semantic nets, frames, etc. for
representing programming information)
- Learning (self-tuning of software tools to specific programs,
generalization of program fragments to support reusability)
- Natural language (matching functionality of program parts with the
corresponding program documentation, explaining program components
and their interactions to new project member)
- Planning (detecting interactions among planned changes)
- Rule-based systems (program transformation, performance tuning)
- Search (retrieval of reusable program fragments)
Six copies of the full paper (maximum 20 double-spaced pages) should be sent
to the session chairman at the address given below. Papers must arrive by July
1, 1987. Authors will be notified of acceptance by September 7, 1987.
Camera-ready copies will be due by October 19, 1987.
Session chairman: Prof. Gail E. Kaiser, Columbia University, Department of
Computer Science, New York, NY 10027. Phone: 212-280-3856. Electronic mail:
kaiser@cs.columbia.edu, ...!columbia!cs!kaiser
Software track chairman: Dr. Bruce D. Shriver, IBM T.J. Watson Research
Center, P.O. Box 704, Yorktown Heights, NY 10598. Phone: 914-789-7626.
Electronic mail: shriver@ibm.com
------------------------------
End of AIList Digest
********************
∂05-Mar-87 0234 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #65
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 5 Mar 87 02:34:06 PST
Date: Wed 4 Mar 1987 21:56-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #65
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 5 Mar 1987 Volume 5 : Issue 65
Today's Topics:
Queries - Frame+Rule-Based Systems & Case-Based Reasoning &
Tracking Multiple Agents & AI Software on Intel-310 w/ Xenix &
AML-V on RS-1 or RS-2,
Reasoning - What is the Color of Clyde?,
Methodology - Algorithm Description & Expert System Explanations,
Philosophy - Consciousness,
Seminar - AI from the Bottom Up (CMU)
----------------------------------------------------------------------
Date: Mon, 2 Mar 87 21:30 EST
From: STREIFF%HARTFORD.BITNET@wiscvm.wisc.edu
Subject: Frame+Rule Based Systems
Hi,
Im looking into writing a rule based expert system that uses frames
for knowledge representation. It will be written in common lisp. Has anyone
had any experience writing something of this nature? What are the advantages
and drawbacks? Any help would be appreciated. Thank you.
S. David Streiff
Univ of Hartford
West Hartford CT
BitNet: STREIFF@HARTFORD.BITNET
------------------------------
Date: 4 Mar 87 19:12:46 GMT
From: pulli@seismo.css.gov (Jay Pulli)
Subject: case-based reasoning
I am not a regular reader of this newsgroup and am thus unaware if
this subject has been discussed at length. I am interested in finding
some references on case based reasoning in ai. I'm interested in using
it in conjunction with some signal characterization work I have been doing.
Direct email to my address below would be greatly appreciated. Thanks in
advance.
/\
Jay J. Pulli / \ /\
Center for Seismic Studies _____/ \ / \ /\_____
Arlington, VA \ / \/
703/276-7900 \/
pulli@seismo
------------------------------
Date: Mon, 2 Mar 87 12:18 EST
From: DON%atc.bendix.com@RELAY.CS.NET
Subject: Request for information
I'm looking for references or discussions on associating
observations with agents in multi-agent domains. My concern
is not so much with determining the goodness of association
as it is with controlling which associations are explored
(i.e. controlling the search).
In particular, consider a domain in which the particular agents
are not known but the general types and proportions of each type
are known. There is a fixed set of sensors for observing these
agents. None of the sensors provides absolute identification nor
continuous observation. There is some knowledge about the
typical behaviors of the different types of agents. The
reasoner's problem is, when presented with a new sensor report,
to determine whether to associate the report with a new agent or
with a previously observed agent. The problem quickly becomes
one of controlling the search of previously observed agents
in order to see which are most likely to be associated with
the new report.
I have some ideas about the search, but I'd like to see other
published ideas or talk to those wiser than I before I expose
myself. Thank you for any consideration.
Don Mitchell Don@atc.bendix.com or
Bendix Aero. Tech. Ctr. Don%atc.bendix.com@relay.cs.net
9140 Old Annapolis Rd. (301)964-4156
Columbia, MD 21045
------------------------------
Date: 3 Mar 87 16:10:00 GMT
From: hqda-ai!merlin@smoke.brl.mil (David S. Hayes)
Subject: AI software on Intel-310 w/ Xenix
We're looking for any AI or lisp software that runs on an
Intel 310 under Xenix. We have some of these, and would like to
start using them, but we don't know what sorts of things are
available.
Please provide then name of the product, a short description,
the name of the vendor, and the vendor's phone number. Reply via
e-mail, as I don't want to saturate these newsgroups.
Thanks for the help,
--
David S. Hayes, The Merlin of Avalon
PhoneNet: (202) 694-6900
ARPA: merlin%hqda-ai.uucp@brl.arpa
UUCP: ...!seismo!sundc!hqda-ai!merlin
------------------------------
Date: Mon, 2 Mar 87 10:38:31 PST
From: John B. Nagle <jbn@glacier.stanford.edu>
Subject: AML-V on RS-1 or RS-2?
Is anyone running AML-V ("Gold Filling") on an IBM RS-1 (model 7510,
model E CPU)?
AML-V is a robot programming language. The RS-1 and RS-2 are IBM
robots, impressive six-axis machines with force-sensing grippers. If
you have an IBM disk pack, an RS-series robot probably built it. CMU,
and MIT have RS-2 robots; Stanford has an RS-1, which was the pre-production
model. IBM donated quite a number of these machines to various schools;
these robots are more general-purpose than most manufacturing plants
really need, but are excellent research tools.
AML stands for A Manufacturing Language. AML-V is an experimental
version developed at IBM's Yorktown Heights facility. Current work is on
AML-X, which runs on an IBM PC/AT. AML-V was developed around 1985 and
runs on the now-obsolete IBM Series I computers. The people who wrote AML-V
are known to me but no longer have the Series I machines running that
could build me the version I need. But such versions existed at one time,
and if someone out there has one configured for an RS-1, it would be
very valuable to me. The odds are excellent that someone who reads
AILIST has an 8" floppy around that is just what I'm looking for.
I'm working on a new approach to common-sense reasoning, one which
involves the use of solid geometric modelling techniques to provide deep
knowledge about the physical world. This leads naturally to robotic
applications. One distinct advantage to working with robots, incidentally,
is that the hype level is distinctly lower in the robotics community than
in the rest of the AI world. Robotics people tend to shut up until they
can demo.
Is anyone running AML-V ("Gold Filling") on an IBM RS-1 (model 7510,
model E CPU)? This usually runs on an RS-2, model 7565, with an
model F CPU, but I'm trying to get it to run on an RS-1, which is supposedly
possible. Is a different kernel required, or is it sufficient
to put the configuration file on the boot floppy using the programs on the
basic diagnostic diskette?
I presently have the original RS-1 software installed (7505-AAA), but
am upgrading to 7505-AAE ("Silver Lining 2 on 1") next week. 7505-AAA
doesn't seem to recognize the AML-V distribution diskette as a valid
volume. The tools for dealing with such problems are better in 7505-AAE,
(the QVOLS command, for example) and I may be able to solve the problem
then. But any advice from RS-1/RS-2 users would be appreciated.
John Nagle
Center for Design Research, Stanford.
415-856-0767.
------------------------------
Date: 2 Mar 87 10:15:57 GMT
From: Dekang Lindek <mcvax!cs.strath.ac.uk!lindek@seismo.CSS.GOV>
Reply-to: lindek@cs.strath.ac.uk (Dekang Lindek)
Subject: What is the color of Clyde?
Look, WORLD, here is a little default reasoning exercise:
95% of elephants have color grey.
40% of Royal Elephants have color yellow.
Clyde is a Royal Elephant.
The color of Clyde is likely to be:
a) Grey b) Yellow c) Red d) Unknown
Dekang Lin
Dept. of CS
Univ. of Strathclyde
26 Richmond Street
Glasgow, G1 1XH, U.K.
E-mail: ....!siesmo!mcvax!ukc!strath-cs!lindek
------------------------------
Date: Mon, 2 Mar 87 08:59 EST
From: Seth Steinberg <sas@bfly-vax.bbn.com>
Subject: Re: Vulgar tongue
Mr. Talmon misunderstood my argument. I did not come out against
symbolic notation - I argued that mathematical and logical notation are
not the appropriate symbolic notation for computer science. That is
why I gave a series of examples showing that many fields have developed
their own formalisms which are not variants of mathematical and logical
notation.
APL may look a lot like matrix algebra at first glance but it is
decidedly procedural. Similarly, PROLOG may look like mathematical
logic, but I don't recall Aristotle, Aquinas or Quine discussing
anything even vaguely like 'cut'. I could base a programming language
on chemical notation or architectural renderings, but understanding it
would STILL require reasoning about procedural execution.
Seth
------------------------------
Date: Wed, 4 Mar 87 08:08:46 est
From: m06242%mwvm@mitre.ARPA
Subject: Value of explanation facility in expert systems
In considering the value of an explanation facility to an expert
system, it is worthwhile to address the possible role of the system as
a training facility. The student who follows the reasoning process is
being led through the analytical structure devised by the systems
builders. Since courtesy requires us to assume they chose a rational,
efficient structure, the student can see an efficient approach to the
problem.
George Swetnam@MITRE
"Cats elsewhere may be green, but the cats here don't care."
-Kesh proverb
*
* George
------------------------------
Date: 2 Mar 87 10:55:00 EST
From: "WHITE::PSOTKA" <psotka%white.decnet@ari-hq1.ARPA>
Reply-to: "WHITE::PSOTKA" <psotka%white.decnet@ari-hq1.ARPA>
Subject: RE: AIList Digest V5 #58
It seems to me that we generally have very clear criteria
for consciousness (unlike much of the current discussion).
We usually ask someone if they remember what happened: if they
don't remember we tend to say they were unconscious. There
are some general exceptions that prove this rule; namely, people
do forget specific things but they generally know that they
have forgotten: i.e., some fragmented memories still hang around
to produce things like the Tip Of Tongue phenomenon where one knows
one knows something but can't retrieve it. That kind of
forgetting is clearly distinguished from being unconscious.
On the whole there are two kinds of unconsciousness: when one is
traumatized with a blow to the head, and when one is sleeping
(either naturally or drug-induced). Football players provide
everyday examples of the former: often after a violent blow someone
stands beside a player asking him what he remembers. A few minutes
later he is asked again. Usually when he remembers less the second
time, he is pronounced to have a concussion and removed from the
game for a while.
Sometimes then, he has no recollection of
having been asked the first time. Was he unconscious during
that first interrogation even though he replied clearly and firmly?
Well, on the whole I think that the event is strange and hard to
categorize. My response seems to be, "Well, he didn't APPEAR to be
unconscious, but I guess he was." It seems to fall into the
same category as sleepwalking or talking in one's sleep.
My speculative hunch about the topic is that consciousness produces memories
because consciousness involves a wierd kind of multiplexing
of a person's entire identity, the whole history of all
existing memories, with the current percept, the current end segment
of the stream of consciousness. There is an ongoing search and
matching and resolution of all existing memories, plans, predicates,
images, etc. with the current context. This seems to be necessary for
awareness, recognition, inferences, etc. and it also somehow results
in consciousness or IS consciousness.
Let's get to work to find out how and why!
------------------------------
Date: 26 Feb 87 16:46:17 EST
From: Marcella.Zaragoza@isl1.ri.cmu.edu
Subject: Seminar - AI from the Bottom Up (CMU)
AI SEMINAR
TOPIC: "Artificial Intelligence from the Bottom Up"
SPEAKER: Hans Moravec, Robotics
WHEN: Tuesday, March 3, 1987, 3:30 pm
WHERE: Wean Hall 5409
ABSTRACT
Computers were created to do arithmetic faster and better than
people. AI attempts to extend this superiority to other mental arenas.
Some mental activities require little data, but others depend on
voluminous knowledge of the world. Robotics was pursued in AI labs
partly to automate the acquisition of world knowledge. It was soon
noticed that the acquisition problem was less tractable than the mental
activities it was to serve. While computers often exhibited adult
level performance in difficult mental tasks, robotic controllers were
incapable of matching even infantile perceptual skills.
In hindsight the dichotomy is not surprising. Animal genomes
have been engaged in a billion year arms race among themselves, with
survival often awarded to the quickest to produce a correct action from
inconclusive perceptions. We are all prodigous olympians in perceptual
and motor areas, so good that we make the hard look easy. Abstract
thought, on the other hand, is a small new trick, perhaps less than a
hundred thousand years old, not yet mastered. It just looks hard when
we do it.
How hard and how easy? Average humans beings can be beaten at
arithmetic by a one operation per second machine, in logic problems
by 100 operations per second, at chess by 10,000 operations per second,
in some narrow "expert systems" areas by a million operations. Robotic
performance can not yet provide this same standard of comparison, but
a calculation based on retinal processes and their computer visual
equivalents suggests that 10 BILLION (10↑10) operations per second are
required to do the job of the retina, and a TRILLION (10↑12) to match the
bulk of the human brain.
Truly expert human performance may depend on mapping a problem
into structures originally constructed for perceptual and motor tasks -
so it can be internally visualized, felt, heard or perhaps smelled and
tasted. Such transformations give the trillion operations per second
engine a purchase on the problem. The same perceptual-motor structures
may also be the seat of "common sense", since they probably contain a
powerful model of the world - developed to solve the merciless life and
death problems of rapidly jumping to the right conclusion from the
slightest sensory clues.
Semilog plots of computer power hint that trillion operation per
second computers will be common in twenty to forty years. Can we
expect to program them to mimic the "hard" parts of human thought in
the same way that current AI program capture some of the easy parts?
It is unlikely that introspection of conscious thought can carry us
very far - most of the brain is not instrumented for introspection, the
neurons are occupied efficiently solving the problem at hand, as in the
retina. Neurobiologists are providing some very helpful
instrumentation extra-somatically, but not fast enough for the forty
year timetable.
Another approach is to attempt to parallel the evolution of
animal nervous systems by seeking situations with selection criteria
like those in their history. By solving similar incremental problems,
we may be driven, step by step, through the same solutions (helped,
where possible, by biological peeks at the "back of the book"). That
animals started with small nervous systems gives confidence that small
computers can emulate the intermediate steps, and mobile robots provide
the natural external forms for recreating the evolutionary tests we
must pass. By this "bottom up" route I hope one day to meet my "top
down" colleagues half way. Together we can then metaphorically drive
the golden spike that unites the two efforts.
------------------------------
End of AIList Digest
********************
∂05-Mar-87 1031 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #66
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 5 Mar 87 10:31:12 PST
Date: Wed 4 Mar 1987 22:18-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #66
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 5 Mar 1987 Volume 5 : Issue 66
Today's Topics:
Bibliography - Order Addresses & Definitions for AI.BIB4XC &
Leff Bibliography AI.BIB49TR
----------------------------------------------------------------------
Date: Tue, 3 Mar 1987 16:36 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: ORDER.ADDRESSES4
Publications Office Computer Science Division
573 Evans Hall, University of California
Berkeley, California 94720
Department of Computer Science
405 Upson Hall
Cornell University
Ithaca, New York 14853
Department of Computer Science
University of Missouri-Rolla
325 Math-C. Sc. Building
Rolla, Missouri 65401
Technical Reports
Department of Computer Science
Oregon State Univeristy
Corvallis, OR 97331
Center for Research on Information Systems
Graduate School of Business Administration
New York University
90 Trinity Place, Room 720
New York, NY 10006
no charge for single copies, additional copies $5.00 per additional copy
Technical Report Facility
James Lotkowski
Department of Computer and Information Science
School of Engineering and Applied Science
University of Pennsylvania
Philadelphia, PA 19104/D2
Boston University
Computer Science Department
111 Cummington Street
Boston, Mass 02215
Nancy Garrett
Computer Science Department
Indiana University
Bloomington, Indiana 47405
Computer Science Department
226 Computer Science Building
Iowa State University
Ames, Iowa 50011-1040
Department of Computer Sciences
Technical Report Center
Taylor Hall 2.124
The University of Texas at Austin
Austin, Texas 78712-1188
Arpanet Box CS.TECH@UTEXAS-20
Department of Computer Science
University of New Hampshire
Durham, New Hamshire
MCC Technical Library
Microelectornics and Computer Technology Corporation
3500 West Balcones Center Drive
Austin, Texas 78759-6509
Technical Reports
Computer Sciences Department
University of Wisconsin
1210 West Dayton Street
Madison, Wisconsin 53706
Department of Computer Science
University of Illinois at Urbana-Champaign
1304 West Springfield Avenue
Urbana, Illinois 61801
Stanford University
Department of Computer Science
Stanford, CA 94305-2140 (prepayment required, CA residents add tax)
------------------------------
Date: Tue, 3 Mar 1987 16:37 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: DEFINITIONS FOR AI.BIB4XC
D BOOK56 Advances in Automation and Robotics\
%V 1\
%I JAI Press\
%D 1985\
%C Greenwich, Connecticut
D MAG93 COMPINT 85\
%D 1985
D MAG94 The Second Conference on Artificial Intelligence Applications\
%D 1985
D MAG95 Automation and Remote Control\
%V 47\
%N 2 Part 2\
%D FEB 1986
D BOOK57 Approximate Reasoning in Expert Systems\
%E Madan M. Gupta\
%E Abraham Kandel\
%E Wyllis Bandler\
%E Jerry B. Kiszka\
%I North Holland Publishing Co.\
%C Amsterdam-New York\
%D 1985
D BOOK58 Proceedings of the European Symposium on Programming held at the Univer
sitat\
des Saarlandes,Saarbrucken, March 17-19 1986\
%E B. Robinet\
%E R. Willhelm\
%V 213\
%I Springer-Verlag\
%C Berlin-Heidelberg-New York\
%D 1985
D MAG95 Soviet Journal of Computer and Systems Sciences\
%V 24\
%N 2\
%D MAR-APR 1986
D MAG96 Pattern Recognition Letters\
%V 4\
%N 3\
%D JUL 1986
D MAG97 Fuzzy Sets and Systems\
%V 20\
%N 2\
%D OCT 1986
D BOOK59 Artificial Intelligence and Man-Machine Systems\
%E H. Winter\
%V 80\
%S Lecture Notes in Control and Information Sciences\
%I Springer-Verlag\
%C Berlin-Heidelberg-New York\
%D 1986
D BOOK60 Topics in the Theory of Computation (Borgholm, 1983)\
%V 102\
%S North-Holland Math. Stud.\
%I North Hold\
%C Amsterdam-New York\
%D 1985
D BOOK61 CAAP 86 (Nice, 1986)\
%V 214\
%I Springer-Verlag\
%C Berlin-Heidelberg-New York\
%D 1986
D MAG98 Electrical Communication\
%V 60\
%N 2\
%D 1986
D MAG99 SADHANA-Acad. Proc. Eng. Sci\
%V 9\
%D SEP 1986
D MAG100 Computer Vision, Graphics, and Image Processing\
%V 35\
%N 3\
%D SEP 1986
D MAG101 Computer Vision, Graphics and Image Processing\
%V 36\
%N 1\
%D OCT 1986
D MAG102 The Computer Journal\
%V 29\
%N 5\
%N 11\
%D OCT 1986
D MAG103 Le Travail Human\
%V 49\
%N 3\
%D SEP 1986
D MAG104 Image and Vision Computing\
%V 4\
%N 3\
%D AUG 1986
D MAG105 Computer Vision, Graphics and Image Processing\
%V 36\
%N 2-3\
%D NOV-DEC 1986
D MAG106 Pattern Recognition\
%V 19\
%N 6\
%D 1986
D BOOK62 Annual Review of Computer Science\
%I Annual Reviews Inc\
%C Palo Alto, CA\
%D 1986
D BOOK63 Proceedings of the Sixth International Conference on Robot Vision and\
Sensory Controls\
%I IFS Publications Limited\
%C Kempston\
%D 1986
------------------------------
Date: Tue, 3 Mar 1987 16:36 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: AI.BIB49TR
%A Fil Fuma
%A Erick Krotkov
%A John Summers
%T The Pennsylvania Active Camera System
%I University of Pennsylvania
%R MS-CIS-86-15
%K AI06
%A Tim Finin
%A Aravind K. Joshi
%A Bonnie Lynn Webber
%T Natural Language Interactions with Artificial Experts
%I University of Pennsylvania
%R MS-CIS-86-16
%K AI01 AI02 O01
%A Dale A. Miller
%A Gopalan Nadathur
%T Higher-Order Logic Programming
%I University of Pennsylvania
%R MS-CIS-86-17
%K AI10 T02
%A Eric Krotkov
%T Focusing
%I University of Pennsylvania
%R MS-CIS-86-22
%K AI06
%X automatic focusing of a computer controlled camera
%A Rusena Bajcsy
%A Eric Krotkov
%A Max Mintz
%T Models of Errors and Mistakes in Machine Perception
%I University of Pennsylvania
%R MS-CIS-86-26
%K AI06 stereo
%A Aravind K. Joshi
%A Bonnie L. Webber
%A Ralph M. Weischedel
%T Some Aspects of Default Reasoning in Interactive Discourse
%I University of Pennsylvania
%R MS-CIS-86-27
%K AI02
%A Yuen-Wah Eva Ma
%A Ramesh Krishnamurti
%A Bhagirath Narahari
%A Dennis G. Shea
%A Kwang-shi Shu
%T High Performance Special-Purpose Computer Architectures for Robotics
Applications
%I University of Pennsylvania
%R MS-CIS-86-28
%K H03 AI06 AI07
%A Dale A. Miller
%A Gopalan Nadathur
%T Some Uses of Higher Order Logic in Computational Linguistics
%I University of Pennsylvania
%R MS-CIS-86-31
%K AI10 AI02
%A Robert Rubinoff
%T Adapting Mumble: Experience with Natural Language Generation
%I University of Pennsylvania
%R MS-CIS-86-32
%K text generation
%K AI10 T02
%A Ethel Schuster
%T Towards a Computational Model of Anaphora in Discourse: References to
Events and Actions
%R MS-CIS-86-34
%I University of Pennsylvania
%K AI02
%A Tim Finin
%A David Drager
%T $GUMS sub 1$: A General User Modeling System
%R MS-CIS-86-35
%I University of Pennsylvania
%K AI08 O01 AA15
%A Robert Kass
%A Ron Katriel
%A Tim Finin
%T Breaking the Primitive Concept Barrier
%R MS-CIS-86-36
%I University of Pennsylvania
%K AI16 KL-ONE
%X describes extensions to KL-ONE
%A Anthony S. Kroch
%A Aravind K. Joshi
%T Analyzing Extraposition in A Tree Adjoining Grammar
%R MS-CIS-86-37
%I University of Pennsylvania
%K AI02
%A Martha Elizabeth Pollack
%T Inferring Domain Plans in Question-Answering
%R MS-CIS-86-40
%I University of Pennsylvania
%K AI08 O01
%A Brant A. Cheikes
%T Research in Artificial Intelligence at the University of Pennsylvania
%R MS-CIS-86-41
%I University of Pennsylvania
%K AT09 AI16
%A Susan B. Davidson
%A Mark M. Winkler
%T Conflict Resolution in Class Conflict Graph Analysis
%R MS-CIS-86-43
%I University of Pennsylvania
%K conflict resolution AI16
%A Jean H. Gallier
%A Stan Raatz
%T Extending SLD-Resolution to Equational Horn Clauses Using E-Unification
%I University of Pennsylvania
%R MS-CIS-86-44
%K AI10
%A Dale Miller
%A Amy Felty
%T An Integration of Resolution and Natural Deduction Theorem Proving
%I University of Pennsylvania
%R MS-CIS-86-47
%K AI11
%A Sharon A. Stansfield
%T A Rudimentary Active Multimodal, Intelligent System for Object
Categorization
%I University of Pennsylvania
%R MS-CIS-86-48
%K AI06
%A Mark Turner
%T Texture Discrimination by Gabor Functions
%I University of Pennsylvania
%R MS-CIS-86-51
%K AI06
%A Megumi Kameyama
%T A Property-Sharing Constraint in Centering
%I University of Pennsylvania
%R MS-CIS-86-52
%K AI02 pronoun resolution
%A Dale Miller
%T A Theory of Modules for Logic Programming
%I University of Pennsylvania
%R MS-CIS-86-53
%K AI10
%A Claire Socolovsky Caine
%T An Expert System for Marine Umbrella Liability Insurance Underwriting
%I University of Pennsylvania
%R MS-CIS-86-54
%K AA06
%A Gerald P. Stoloff
%T Lanpick -- An Expert System for Recommendation of Local Area Network
Hardware and Software Products
%I University of Pennsylvania
%R MS-CIS-86-55
%K AA08
%A Franc Solina
%T Object Recognition Using Function Based Category Models
%I University of Pennsylvania
%R MS-CIS-86-56
%K AI06
%A Robert Kaas
%T The Role of User Modelling in Intelligent Tutoring System
%I University of Pennsylvania
%R MS-CIS-86-58
%K AA07 AI08
%A Jean H. Gallier
%A Stan Raatz
%T Refutation Methods for Horn Clauses with Equality Based on Unification
%I University of Pennsylvania
%R MS-CIS-86-59
%K AI10
%A Megumi Kameyama
%T Japanese Zero Pronominal Bindings: Where Syntax and Discourse Meet
%I University of Pennsylvania
%R MS-CIS-86-60
%K AI02
%A Robert Kaas
%A Tim Finin
%T The Role of User Models in Question Answering Systems
%I University of Pennsylvania
%R MS-CIS-86-63
%K AI01 AI08 personal investment AA06
%A Aravind K. Joshi
%T An Introduction to Tree Adjoining Grammars
%I University of Pennsylvania
%R MS-CIS-86-64
%K AI06 AT08
%A Alex Pelin
%A Jean Gallier
%T Solving Word Problems in Free Algebras Using Complexity Functions
%I University of Pennsylvania
%R MS-CIS-86-65
%K AI11
%A Jugal Kalita
%A Sunish Shende
%T Generation of Natural Language Text Describing a System of
Asynchronous, Concurrent Processes
%I University of Pennsylvania
%R MS-CIS-86-66
%A Hugh F. Durrant-Whyte
%T Integration, Coordination and Control of Multi-Sensor Robot Systems
%I University of Pennsylvania
%R MS-CIS-86-67
%K AI06 AI07 blackboard AI01
%A Greg Hager
%A Hugh F. Durrant-Whyte
%T Information and Multi-Sensor Coordination
%I University of Pennsylvania
%R MS-CIS-86-68
%K AI07 AI06 H03
%A Tim Finin
%T NFL- A Novices Frame Language
%I University of Pennsylvania
%R MS-CIS-86-71
%K AT18 T01 T03
%A Bonnie Lynn Webber
%T Two Steps Closer to Event Reference
%I University of Pennsylvania
%R MS-CIS-86-74
%K AI02 AI16
%A Greg Hagar
%T Active Reduction of Uncertainty in Multi-Sensor Systems
%I University of Pennsylvania
%R MS-CIS-86-76
%K H03 O04
%A Lokendra Shastri
%T Massive Parallelism in Artificial Intelligence
%I University of Pennsylvania
%R MS-CIS-86-77
%K H03
%A Lokendra Shastri
%A Raymond L. Wairous
%T Learned Phonetic Discrimination Using Connectionistic Networks
%I University of Pennsylvania
%R MS-CIS-86-78
%K H03 AI05
%A Linda Ness
%T Reducing Linear Recursion to Transitive Closure
%I University of Texas at Austin, Department of Computer Sciences
%R TR-86-25
%K AA09 AI10
%D NOV 1986
%X shows how to deal with a recursively expressed logic program that
is designed to query a database
%A David A. Schmidt
%A Jacek Leszczylowski
%T On Developing a Logic for Program Derivation and Verification
%I Iowa State University Computer Science Department
%R TR#86-16
%D NOV 1986
%K AA08 AI10 intuitionistic type theory predicate calculus
%A James M. Bieman
%A Albert L. Baker
%A Paul M. Clites
%A David A. Gustafson
%A Austin C. Melton
%T A Standard Representation of Imperative Language Programs
%I Iowa Sate University Computer Science Department
%R TR #86-17
%D NOV 1986
%K AA08
%A Ken-Chih Liu
%A Rajshekhar Sunderraman
%T Applying an Extended Relational Model to Indefinite Deductive Databases
%I Iowa State University Computer Science Department
%R TR #86-18
%D NOV 1986
%K AI10 AA09
%A Jacek Leszczylowski
%A Jan Maluszynski
%T Logic Programming with External Procedures: Introducing S-Unification
%I Iowa State University Computer Science Department
%R TR #86-21
%D DEC 1986
%K AI10
%A Chen
%A Chi
%A Ost
%A Sabbaugh
%A Spring
%T Scheme Graphics Reference Manual
%I Indiana University Computer Science Department
%R TR 144
%D 1984
%K T01
%A Daniel P. Friedman
%A Pee-Hong Chen
%T Prototyping Data Flow by Translation Into Scheme
%I Indiana University Computer Science Department
%R TR 147
%D 1983
%K T01
%A Mitchell Wand
%T A Semantic Algebra for Logic Programming
%I Indiana University Computer Science Department
%R TR 148
%D August 1983
%K AI10
%A Kent Dybvig
%T C-Scheme Reference Manual
%I Indiana University Computer Science Department
%R TR 149
%D SEP 1983
%K T01
%A J. Barnden
%T On Short-Term Information-Processing in Connectionist Theories
%I Indiana University Computer Science Department
%R TR 152
%D JAN 1984
%K H03
%A D. Friedman
%A C. Hayes
%A E. Kohlbecker
%A M. Wand
%T Scheme 84 Interim Reference Manual
%R TR 153
%D JUN 1985
%I Indiana University Computer Science Department
%K T01
%A E. Kohlbecker
%T eu-Prolog: Reference Manual and Report
%R TR 155
%D APR 1984
%I Indiana University Computer Science Department
%K T02
%A C. D. Halpern
%T An Implementation of 2-Lisp
%R TR 160
%D JUN 1984
%I Indiana University Computer Science Department
%K T01
%A L. D. Sabbagh
%T Scheme as an Interactive Graphics Programming Environment
%R TR 166
%D FEB 1985
%I Indiana University Computer Science Department
%K T01
%A J. A. Barnden
%T Representations of Intensions, Representations as Intensions,
and Propositional Attitudes
%R TR 172
%D JUN 1985
%I Indiana University Computer Science Department
%K AI02 AI16
%A Johnathan Rees
%A W. D. Clinger
%T Revised Report on Scheme
%R TR 174
%D AUG 1986
%I Indiana University Computer Science Department
%K AI06
%$ 6.00
%A M. W. Lugowski
%T Why Artificial Intelligence is Necessarily Ad Hoc: One's Thinking/Approach/
Model/Solution Rides on One's Metaphors
%R TR 176
%D AUG 1985
%I Indiana University Computer Science Department
%K AI16
%$ 2.00
%A S. C. Kwasny
%A J. Dalby
%A R. Port
%T Rules for Automatic Mapping Between Fast and Slow Speech
%R TR 175
%D JUL 1985
%I Indiana University Computer Science Department
%K AI05
%A Matthias Felleisen
%T Transliterating Prolog into Scheme
%R TR 182
%D OCT 1985
%I Indiana University Computer Science Department
%K T01 T02
%A Christopher T. Haynes
%T Logic Continuations
%R TR 183
%D NOV 1985
%I Indiana University Computer Science Department
%K AI10
%A John A. Barnden
%T Imputations and Explications: Representational Problems in Treatments
of Propositional Attitudes
%R TR 187
%D JAN 1986
%I Indiana University Computer Science Department
%K AI16
%A Erich J. Smythe
%T The Pleasures of SINN: A System for Programming Connectionist Models
%R TR189
%D FEB 1986
%I Indiana University Computer Science Department
%K FEB 1986
%A Matthias Felleisen
%A Daniel P. Friedman
%T Control Operators, the SECD-Machine and the $lambda$-calculus
%R TR 197
%D JUN 1986
%I Indiana University Computer Science Department
%K T01
%A Eugene E. Kohlbecker
%T Syntactic Extensions in the Programming Language Lisp
%R TR 199
%D AUG 1986
%I Indiana University Computer Science Department
%K T01
%$ 12.00 (Ph. D. Dissertation)
%A Matthias Felleisen
%T A Final Scheme-Word on Landin's J-Operator
%R TR 205
%D NOV 1986
%I Indiana University Computer Science Department
%K T01
%A Bipin Indurykha
%T Analogies and Metaphors: An Interdisciplinary Perspective
%R BUCS Tech Report #86-012
%D DEC 1986
%I Boston University Department of Computer Science
%K AI08 AI16 AI02
%A Michael Siegel
%T Automatic Rule Derivation for Semantic Query Optimization
%R BUCS Tech Report #86-013
%D DEC 1986
%I Boston University Computer Science Department
%K AA09 AI01
%A Leonard Uhr
%T Toward a Computational Information-Processing Model of Object
Perception
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR651
%D JUL 1986
%K AI08 AI06
%X describes what is known and is necessary for development of a model
of visual perception in humans as well as those points of information
that are lacking.
%A Matthew J. Thazhuthaveetil
%T A Structured Memory Access Architecture for LISP
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR658
%D AUG 1986
%K H02 T01
%A Udi Manber
%T Using Mathematical Induction to Design Computer Algorithms
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR660
%D AUG 1986
%K AA08 AI11
%A M. A. Sridhar
%T Efficient Algorithms for Multiple Pattern Matching
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR661
%D AUG 1986
%K O06
%A Charles V. Steward
%A Charles R. Dyer
%T A Scheduling Algorithm for the Pipelined Image-Processing Engine
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR664
%D SEP 1986
%K AI06 H03
%A Nian Li
%A Leonard Uhr
%T Comparative Timings for a Neuron Recognition Program on Serial and
Pyramid Computers
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR665
%D SEP 1986
%K AA10 AI06 H03
%X a system to recognize neurons in photomicrographs
%A Gilbert Verghese
%A Shekhar Mehta
%A Charles R. Dyer
%T Image Processing Algorithms for the Pipelined Image-Processing Engine
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR668
%D SEP 1986
%K local peak detection median filtering thinning Hough transform photometric
stereo AI06 O06 H03
%A Mitali Bhattacharyya
%A David Cohrs
%A Barton Miller
%T Implementation of a Visual UNIX Process Connector
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR677
%D DEC 1986
%X An environment for connecting several UNIX processes. Not specifically
AI related
%A Ze-Nian Li
%A Leonard Uhr
%T Pyramid Vision Using Key Features to Integrate Image-Driven Bottom-Up
and Model-Driven Top Down Processes
%I University of Wisconsin-Madison, Computer Sciences Department
%D DEC 1986
%R TR678
%K H03 AI06
%A Charles R. Dyer
%T Multiscale Image Understanding
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR679
%D DEC 1986
%K texture AI06
%A G. T. Toussaint
%T Computational Geometry and Morphology
%I McGill University, School of Computer Science
%R TR-SOCS-86.3
%D FEB 1986
%K AA10 AI06 O06
%X applications of such algorithms as hulls, medial axis, geodesic
and visibility for polygons to understanding biological shape and shape
change.
%A R. De Mori
%A L. Lam
%A M. Gilloux
%T Learning and Plan Refinement in a Knowledge-Based System for Automatic
Speech Recognition
%R TR-SOCS-86.14
%I McGill University, School of Computer Science
%D MAY 1986
%K AI09 AI04 AI05
%X experimental work on recognition of connected letters by 100 speakers
%A Heedong Ko
%A Kunwoo Lee
%T Toward a Practical Planning System for Assembly Tasks
%R Department of Computer Science File 957
%I University of Illinois at Urbana-Champaign
%D SEP 1986
%K AA26
%A Carl Thomas Uhrik
%T A Rule Exerciser for Knowledge Base Enhancement in Expert Systems
%R Department of Computer Science File 969
%I University of Illinois at Urbana-Champaign
%D SEP 1986
%K AI01 O04 AA23 AA10
%X The system has been applied to soybean diagnosis and monkey behavior
discrimination
%A Kenneth D. Forbus
%A Dedre Gentner
%T Learning Physical Domains: Toward a Theoretical Framework
%R Department of Computer Science File 1247
%I University of Illinois at Urbana-Champaign
%D DEC 1986
%K AI08 AI04
%A Steven Greenbaum
%T Input Transformations and Resolution Implementation Techniques for
Theorem Proving in First-Order Logic
%R Department of Computer Science File 1298
%I University of Illinois at Urbana-Champaign
%D SEP 1986
%K AI11
%X the aim is opposed to solve small sized problem with little or no
human guidance as opposed to other systems which are designed to
solve large problems with human guidance. Uses priority-based search
strategy, discrimination networks and Knuth-Bendix method
%A Brian Falkenhainer
%T An Examination of the Third State in the Analogy Process: Verification-
Based Analogical Learning
%R Department of Computer Science File 1302
%I University of Illinois at Urbana-Champaign
%D OCT 1986
%K AI04 qualitative models liquid flow and heat flow
%A Y-L. Steve
%A Daniel D. Gajski
%T LES: A Layout Expert System
%R Department of Computer Science File 1308
%I University of Illinois at Urbana-Champaign
%D NOV 1986
%K AA04
%X A layout system that is competitive with human designers
%A Krish Purswani
%A Larry Rendell
%T A Probabilistic Reasoning-Based Approach to Machine Learning
%R Department of Computer Science File 1311
%I University of Illinois at Urbana-Champaign
%D DEC 1986
%K AI03 O04
%A Yoram Ofer Moses
%T Knowledge in a Distributed Environment
%D MAR 1986
%R STAN-CS-86-1120
%I Stanford University Computer Science
%K H03
%X Discusses the effects of unreliable communications on coordination
of an expert system, the Byzantine agreement problem and the "cheating
wives" puzzle
.br
br
15.00 104 pages
%A Glenn Douglas Rennels
%T A Computational Model of Reasoning from the Clinical Literature
%D JUN 1986
%I Stanford University Computer Science
%R STAN-CS-86-1122
%K AA01 AI01
%X discusses getting information from the clinical literature into
an AI system for patient care. Example problem is "breast cancer
management options."
.br
br
244 pages 15.00
%A H. Penny Nii
%T Blackboard Systems
%D JUN 1986
%I Stanford University Computer Science
%R STAN-CS-86-1123
%X general review of black board systems
.br
br
86 pages, 10.00
%A Daniel J. Scales
%T Efficient Matching Algorithms for the SOAR/OPS5 Production System
%D JUN 1986
%I Stanford University Computer Science
%R STAN-CS-86-1124
%K T03 AI01
%X 50 pages 10.00
%A Eric Schoen
%T The CAOS System
%D MAR 1986
%I Stanford University Computer Science
%R STAN-CS-86-1125
%K H03 O03
%X a real time Lisp distributed system for signal interpretations
.br
br
69 pages 10.00
%A Byron Davies
%T CAREL: A Visible Distributed Lisp
%D MAR 1986
%R STAN-CS-86-1126
%I Stanford University Computer Science
%K H02 H03 T01
%X A system programming language that runs on the TI Explorer that
includes real time display of the processor activity and data
communications; useful as an educational tool
.br
br
15 pages 5.00
%A Yonathan Malachi
%T A Timely Resolution
%D MAR 1986
%R STAN-CS-86-1127
%I Stanford University Computer Science
%K AI11 AI10 T01 T02 H03 TABLOG unification
%X 15.00 145 pages
%A Evan R. Cohn
%A Ramsey W. Haddad
%T Beta Operations: Efficient Implementation of a Primitive Parallel Operation
%D AUG 1986
%R STAN-CS-86-1129
%I Stanford University Computer Science
%K H03
%X The Beta Operation can be performed in O(log N + log **2 M) time
on a hypercube where N is the size of the input and M is the size
of the output.
.br
br
5.00, 18 pages
%A Vishvjit S. Nalwa
%A Thomas O. Binford
%T On Detecting Edges
%R STAN-CS-86-1130
%D MAR 1986
%I Stanford University Computer Science
%K AI06
%X Proposed method will localize edges to within a thilrd of a pixel
if step-size over noise ratio > 2.5
.br
br
50 pages 10.00
%A Yehoshua Sagiv
%T Optimizing Datalog Programs
%R STAN-CS-86-1132
%D MAR 1986
%I Stanford University Computer Science
%K AI10
%X Prolog programs without function symbols are optimized. Also defines
a new form of equivalence under which such programs can be compared.
.br
br
30 pages, 50.00
%A Richard James Treitel
%T Sequentialization of Logic Programs
%R STAN-CS-86-1135
%D NOV 1986
%I Stanford University Computer Science
%K AI10
%X 16 pages 15.00
%A Harold Brown
%A Erich Schoen
%A Bruce Delogi
%T An Experiment in Knowledge-based Signal Understanding Using Parallel
Architectures
%R STAN-CS-86-1136
%D OCT 1986
%I Stanford University Computer Science
%K H03 AA18 T01
%X System was tested on radar emissions from air craft
.br
br
36 pages 5.00
------------------------------
End of AIList Digest
********************
∂06-Mar-87 1051 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #67
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 6 Mar 87 10:51:32 PST
Date: Fri 6 Mar 1987 07:03-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #67
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 6 Mar 1987 Volume 5 : Issue 67
Today's Topics:
Bibliography - Leff AI.BIB48TR
----------------------------------------------------------------------
Date: Tue, 3 Mar 1987 16:36 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: AI.BIB48TR
%R AI-013-85
%T The LRC Machine Translation System
%I Microelectronics and Computer Technology Corporation
%D MAR 1985
%K AI02
%R AI-012-85
%T A Machine-Aided Translation Bibliography
%I Microelectronics and Computer Technology Corporation
%D MAR 1985
%K AT09 AI02
%R AI-011-85
%T A Survey of Machine Translation: Its History, Current Status and
Future Prospects
%I Microelectronics and Computer Technology Corporation
%D MAY 1985
%K AI02 AT08
%R AI-010-85
%T Machine Translation: Viewpoint From Both Sides
%I Microelectronics and Computer Technology Corporation
%D FEB 1985
%K AI02
%R AI-009-85
%T Machine Translation
%I Microelectronics and Computer Technology Corporation
%D FEB 1985
%K AI02
%R AI-008-85
%T A Practical Comparison of Parsing Strategies
%I Microelectronics and Computer Technology Corporation
%D MAY 1985
%K AI02
%R AI-007-85
%T Parser Construction Techniques: A Tutorial
%I Microelectronics and Computer Technology Corporation
%D MAY 1985
%K AI02 AT08
%R AI-006-85
%T Transportability to Other Languages: The Natural Language Processing
Project in the AI Program at MCC
%I Microelectronics and Computer Technology Corporation
%D MAR 1985
%K AI02
%R AI-0100-05
%T Using Explicit Contradictions to Provide Explanations in a TMS
%I Microelectronics and Computer Technology Corporation
%D APR 1985
%K AI15
%R AI/CAD-162-85
%T Analogical Reasoning for Digital System Synthesis
%I Microelectronics and Computer Technology Corporation
%D MAY 1986
%K AA04
%R DB-081-86
%T A Computational Logic for Database Programs
%I Microelectronics and Computer Technology Corporation
%D March 12, 1986
%K AA09
%R DB-064-86
%T Analyzing the Run-Time Behavior of Logic Programs
%I Microelectronics and Computer Technology Corporation
%D March 6, 1986
%K AI10
%R DB-058-86
%T Some extensions to the Closed World Assumption in Databases
%I Microelectronics and Computer Technology Corporation
%D March 3, 1986
%K AA09 AI16
%R DB-026-86
%T LDL: A Logic Based Data-Language
%I Microelectronics and Computer Technology Corporation
%D February 11, 1986
%K AI10 AA09
%R DB-021-86
%T Optimizing the Rule/Data Interface in a Knowledge Management System
%I Microelectronics and Computer Technology Corporation
%D February 3, 1986
%K AA09 AI01
%R DB-171-85
%T Tools for the Analysis of Large Prolog Programs
%I Microelectronics and Computer Technology Corporation
%D DEC 3, 1985
%K T02 O02
%R DB-132-85
%T Parallel Evaluation of Recursive Rule Queries
%I Microelectronics and Computer Technology Corporation
%D October 1985
%K AI01
%R DB-121-85
%T Magic Sets and Other Strange Ways to Implement Logic Programs
%I Microelectronics and Computer Technology Corporation
%D October 28, 1985
%K AI10
%R DB-101-85
%T On the Implementation of a Simple Class of Logic Queries for Databases
%I Microelectronics and Computer Technology Corporation
%D October 14, 1985
%K AI10 AA09
%R DB-088-85
%T Safety and Compilation of Non-Recursive Horn Clauses
%I Microelectronics and Computer Technology Corporation
%D September 20, 1985
%K AI10
%R DB-038-85
%T Object Oriented Database Systems and Knowledge Systems
%I Microelectronics and Computer Technology Corporation
%D July 9, 1985
%K AI16
%R DB-021-85
%T A Logic-Programming/Object-Oriented Cocktail
%I Microelectronics and Computer Technology Corporation
%D September 10, 1985
%K AI10
%R Mcc/db/dbsa-7/rev.0
%T Database and Knowledge Based System Opportunities
%I Microelectronics and Computer Technology Corporation
%D October 5, 1986
%K AA09
%R mcc/db/kbs-77/rev.1
%T The Representation and Deductive Retrieval of Complex Objects
%I Microelectronics and Computer Technology Corporation
%D May 6, 1985
%K AI16
%R mcc/db/kbs-75/rev.1
%T The Transition from Data Management to Knowledge Management
%I Microelectronics and Computer Technology Corporation
%D April 30, 1985
%K AI16
%R mcc/db/kbs-52/rev.1
%T Opportunities for Parallelism in Knowledge Management Systems:
A Bibliography
%I Microelectronics and Computer Technology Corporation
%D December 11, 1984
%K AT09 H03
%R mcc/db/kbs-49/rev.1
%T Logic Programming/Database Interfaces
%I Microelectronics and Computer Technology Corporation
%D December 5, 1984
%K AA09 AI10
%R mcc/db/kbs-44/rev.1
%T Rule Support in Prolog
%I Microelectronics and Computer Technology Corporation
%D November 30, 1984
%K AI01 T02
%R mcc/db/kbs-43/rev.1
%T Logics for Semantic Data Models
%I Microelectronics and Computer Technology Corporation
%D November 30, 1984
%K AI10 AI16
%R mcc/db/kbs-33/rev.0
%T KBS Requirements, Rev.0
%I Microelectronics and Computer Technology Corporation
%D October 31, 1984
%K AI16
%R mcc/db/kbs-29/rev.1
%T Knowledge Base Development and Use in Deductive Data Management
%I Microelectronics and Computer Technology Corporation
%D October 31, 1984
%K AI16
%R HI-294-86
%T Human Computer Interactions and Intelligent Tutoring Systems
%I Microelectronics and Computer Technology Corporation
%D September 8, 1986
%K AA07 O01
%R HI-200-86
%T Speech Processing for the User Interface
%I Microelectronics and Computer Technology Corporation
%D July 1986
%K AI05
%R HI-179-86
%T A Parser for Portable NL Interfaces Using Graph-Unification-Based Grammars
%I Microelectronics and Computer Technology Corporation
%D June 1986
%K AI02
%R HI-075-86
%T Parsing as Heuristic Graph Search
%I Microelectronics and Computer Technology Corporation
%D Mar 6, 1986
%K AI02
%R HI-073-86
%T Ambiguity and Procrastination in NL Interfaces
%I Microelectronics and Computer Technology Corporation
%D March 1986
%K AI02
%R HI-012-86
%T Some Properties of Combinatory Categorical Grammars of Relevance to Parsing
%I Microelectronics and Computer Technology Corporation
%D January 22, 1986
%K AI02
%R HI-017-86
%T A General User Model, Part 1: Connectionist Framework
%I Microelectronics and Computer Technology Corporation
%D January 31, 1986
%K AI08
%R HI-118-85
%T Extraposition from NP as Anaphora
%I Microelectronics and Computer Technology Corporation
%D October 23, 1985; revision one: March 1986
%K AI02
%R HI-111-85
%T Memory for Spatial Locations and Related Topics: A Review and Annotated
Bibliography
%I Microelectronics and Computer Technology Corporation
%D October 18, 1985
%K AI08 AT09
%R HI-089-85
%T Graphic Interfaces for Knowledge-Based System Development
%I Microelectronics and Computer Technology Corporation
%D September 1985; revision one: December 1985
%K O01 O02
%R HI-084-85
%T Analysis of User-Expert Dialogues: Task Networks, Subdialogue Boundary
Markers and Antecedent Distribution
%I Microelectronics and Computer Technology Corporation
%D December 1, 1985
%K AI08 AI01 AI02
%R HI-074-85
%T Natural Language Understanding: How Natural Can it Be?
%I Microelectronics and Computer Technology Corporation
%D September 13, 1985
%K AI02
%R HI-066-85
%T Applications of Speech Technology in the CAD Workstation
%I Microelectronics and Computer Technology Corporation
%D April 26, 1985
%K AI05 AA04 AA15
%R HI-85-103-04
%T On the Applied Use of Computer Models of Human Memory: A Proposal
for a Large-Scale Personal Filing System
%I Microelectronics and Computer Technology Corporation
%D 1985
%K AA14 AI08
%R HI-85-102-04
%T Memory Structure, Focusing, and Anaphora Resolutions: A Study and
Comparison of Computer and Human Memory
%I Microelectronics and Computer Technology Corporation
%D 1985
%K AI08
%R HI-85-100-04
%T Speech Processing State of the Art Report
%I Microelectronics and Computer Technology Corporation
%D 1985
%K AI05 AT08
%R HI/STP-054-86
%T Artificial Intelligence and Advanced User Interfaces
%I Microelectronics and Computer Technology Corporation
%D February 25, 1986
%K AI02
%R PP-083-86
%T Goal Scheduling and Memory Management in Parallel Logic Systems
%I Microelectronics and Computer Technology Corporation
%D March 15, 1986
%K H03 AI10
%R PP-020-86
%T Potentials for Parallel Execution of Common Lisp Programs
%I Microelectronics and Computer Technology Corporation
%D January 30, 1986
%K T01 H03
%R PP-154-85
%T An Abstract Machine for Restricted And-Parallel Execution of Logic
Programs
%I Microelectronics and Computer Technology Corporation
%D November 26, 1985
%K AI10 H03
%R PP-140-85
%T A Study of the Parallelism Inherent in Combinator Reduction
%I Microelectronics and Computer Technology Corporation
%D Nov 11, 1985
%K H03
%R PP-104-85
%T A Restricted and-Parallel Execution Model and Abstract Machine for
Prolog Programs
%I Microelectronics and Computer Technology Corporation
%D October 2, 1985
%K T02 H03
%R PP-079-85
%T Parallel Execution of a Rule-Based Expert System
%I Microelectronics and Computer Technology Corporation
%D 1985
%K AI01 H03
%R PP-024-85
%T Expert System Application Study
%I Microelectronics and Computer Technology Corporation
%D 1985
%K AI01
%R PP-019-85
%T Proceedings of the MCC Workshop on LFP (Logical/Functional)
programming Languages
%I Microelectronics and Computer Technology Corporation
%D July 1, 1985
%K AI10
%R STP-053-86
%T Biggertalk* = Biggertalk + Gordion
%I Microelectronics and Computer Technology Corporation
%D November 1, 1985
%K AI10
%R TR 86-1
%T Data and Resource Abstraction Mechanisms on an Object-Based Architecture
%A Kanad Gose
%A R. M. Steward
%I Iowa State University
%D JAN 1986
%R TR 86-16
%T On Developing a Logic for Program Derivation and Verification
%A David A. Schmidt
%A Jacek Leszczylowski
%I Iowa State University
%D NOV 1986
%K AA08 AI10 predicate calculation
%R TR 86-21
%T Logic Programming with External Procedures: Introducing S-Unification
%A Jacek Lesczylowski
%A Jan Maluszynski
%I Iowa Sate University
%D DEC 1986
%K AI10
%R 83-5
%A Helen M. Gigley
%A Jean-Francois Boulicaut
%A Eric Ramahefarivony
%T Grasper-Insa -- A Graph Processing Tool for Knowledge Engineering
%I University of New Hamshire
%D SEP 1983
%K T01
%R 83-6
%A Helen M. Gigley
%T Processing Word Ambiguities: Availability of Multiple Meanings of Ambiguous
Words in Aphasic Patients and Normal Controls
%I University of New Hampshire, Department of Computer Science
%D SEP 1983
%K AA08 AA11 AI02
%R 83-8
%A Sylvia Weber Russell
%T Conceptual Analysis of Partial Metaphor
%I University of New Hampshire, Department of Computer Science
%D OCT 1983
%K AI02
%R 83-9
%A Michael J. Quinn
%T On the Speedup of Parallel Depth-First Branch-and-Bound Algorithms
%I University of New Hampshire, Department of Computer Science
%D NOV 1983
%K H03 AI03
%R 84-13
%A Eugene C. Freuder
%T Utilizing Subgraph Isomorphism in Constraint Graphs
%I University of New Hampshire, Department of Computer Science
%D JAN 1984
%K constraint satisfaction AI03
%R 84-14
%A Eugene C. Freuder
%T A Sufficient Condition for Backtrack-Bounded Search
%I University of New Hampshire, Department of Computer Science
%D JAN 1984
%K AI03 constraint satisfaction
%R 84-15
%A Eugene C. Freuder
%T Direct Independence of Variables in Constraint Satisfaction Problems
%I University of New Hampshire, Department of Computer Science
%D MAR 1984
%K AI03 H03
%A Lee Tibbert
%A R. Daniel Bergeron
%R 84-18
%T Graphics Programming For Knowledge-Guided Interaction
%I University of New Hampshire, Department of Computer Science
%D JAN 1984
%K O01
%A Eugene C. Freuder
%A Michael J. Quinn
%T Taking Advantage of Stable Sets of Variables in Constraint Satisfaction
Problems
%R 84-20
%I University of New Hampshire, Department of Computer Science
%D DEC 1984
%K AI03
%A Eugene C. Freuder
%A Michael J. Quinn
%T Parallelism in an Algorithm that Takes Advantage of Stable Sets of Variables
to Solve Constraint Satisfaction Problems
%R 85-21
%I University of New Hampshire, Department of Computer Science
%D Jan 1985
%K AI03 H03
%A Michael J. Quinn
%A Narsingh Deo
%R 85-23
%T An Upper Bound for the Speedup of Parallel Branch-and-Bound Algorithms
%I University of New Hampshire, Department of Computer Science
%D FEB 1985
%K AI03 H03
%A Helen M. Gigley
%T Computational Neurolinguistics -- What is it all About
%R 85-24
%I University of New Hampshire, Department of Computer Science
%D JAN 1985
%K AI08 AI02
%A Helen M. Gigley
%T Grammar Viewed as a Functioning Part of a Cognitive System
%R 85-25
%I University of New Hampshire, Department of Computer Science
%D JAN 1985
%K AI02 AI08
%A Helen M. Gigley
%T Computational Neurolinguistic Modelling Integrating 'Natural Computation'
Control with Performance Defined Representatives
%R 85-26
%I University of New Hampshire, Department of Computer Science
%D SEP 1985
%K AI02 AI08 HOPE
%A Michael J. Quinn
%A Narsingh Deo
%T An Upper Bound for the Speedup of Parallel Best-Bound Branch-and-Bound
Algorithms
%R 85-27
%I University of New Hampshire, Department of Computer Science
%D SEP 1985
%K AI03 H03
%A Helen M. Gigley
%T Studies in Artificial Aphasia - Experiments in Processing Change
%R 85-28
%I University of New Hampshire, Department of Computer Science
%D OCT 1985
%K AI08 AA11 AI02
%A Bruce Barker
%T An Abstract Prolog Machine
%R 85-29
%I University of New Hampshire, Department of Computer Science
%D DEC 1985
%K H02 T02 Warren
%A Henk J. Haarmann
%A Helen M. Gigley
%T Neural-like Modelling of Synchronization Deficits in Aphasic Comprehension
%R 86-32
%I University of New Hampshire, Department of Computer Science
%D MAR 1986
%K AI02 AA11 AI08
%A Eugene C. Freuder
%T Applying Constraint Satisfaction Search Techniques to Concept Learning
%R 86-33
%I University of New Hampshire, Department of Computer Science
%D MAR 1986
%K AI03 AI04
%A Brian Otis
%A Eugene C. Freuder
%T Subdivision of Knowledge for Igneous Rock Identifications
%R 86-35
%I University of New Hampshire, Department of Computer Science
%D APR 1986
%K AI01 AA03
%A Sylvia Weber Russell
%R 86-36
%T A Perspective from Computer Analysis
%I University of New Hampshire, Department of Computer Science
%D APR 1986
%K metaphor AI02
%A Helen M. Gigley
%R 86-36
%T Lexical Ambiguity Resolution in Aphasia
%I University of New Hampshire, Department of Computer Science
%D MAY 1986
%K AA11 AI02
%A Helen M. Gigley
%T Sentence Comprehension Processing - A Serial ORder, Time-Synchronous Process
%R 86-39
%I University of New Hampshire, Department of Computer Science
%D APR 1986
%K AI02 HOPE
%A Michael J. Quinn
%T Implementing Best-First Branch-And-Bound Algorithms on Hypercube
Multiprocessors
%R PCL 86-02
%I University of New Hampshire, Parallel Computing Laboratory, Department
of Computer Science
%D SEP 1986
%K AI02 H03
%A Saul Gorn
%T Who Can Be Replaced by A Computer
%R MS-CIS-85-04
%I University of Pennsylvania
%K O05
%A Saul Gorn
%T Self-Annihilating Sentences: Saul Gorn's Compendium of Rarely Used
Cliches
%R MS-CIS-85-03
%I University of Pennsylvania
%K AI02
%A Robert Ruminoff
%T Explaining Concepts in Expert Systems: The Clear System
%R MS-CIS-85-06
%I University of Pennsylvania
%K O01 AI01
%A Vijay-Shankar
%A Aravind Joshi
%T Some Computational Properties of Tree Adjoining Grammars
%R MS-CIS-85-07
%I University of Pennsylvania
%K AI02
%A D. Smitley
%A S. M. Goldwasser
%A I. Lee
%T IPON - Advanced Architectural Framework for Image
%R MS-CIS-85-13
%I University of Pennsylvania
%K AI06 H03 MIMD
%A Eric P. Krotkov
%T Results in Finding Edges and Corners in Images Using the First Directional
Derivative
%R MS-CIS-85-14
%I University of Pennsylvania
%K AI06
%A Anthony S. Kroch
%A Aravand K. Joshi
%T The Linguistic Relevance of Tree Adjoining Grammars
%R MS-CIS-85-16
%I University of Pennsylvania
%K AI02
%A Dale A. Miller
%A Gopalan Nadathur
%T A Computational Logic Approach to Syntax and Semantics
%R MS-CIS-85-17
%I University of Pennsylvania
%K AI10 AI11
%A Paul A. Fishwick
%T Hierarchical Reasoning: Simulating Complex Processes over Multiple
Levels of Abstraction
[Dissertation Exam Version]
%R MS-CIS-85-21
%I University of Pennsylvania
%K simulation
%A Aravind K. Joshi
%T Tree Adjoining Grammars: How Much Context-Sensitivity is Required to
Provide Reasonable Structural Descriptions
%R MS-CIS-85-23
%I University of Pennsylvania
%K AI02
%A David Smiley
%T The Design and Analysis of a Stereo Vision Algorithm
%R MS-CIS-85-27
%I University of Pennsylvania
%K AI06
%A Peter Allen
%A Ruzena Bajcsy
%T Two Sensors Are Better Than One: Examples of Integration of Vision and
Touch
%R MS-CIS-85-29
%I University of Pennsylvania
%K AI06 AI07
%A Samuel Goldwasser
%A Ruzena Bacsy
%T A Distributed Active Sensor Processor System
%R MS-CIS-85-30
%I University of Pennsylvania
%K AI06 AI07 AI01
%A Franc Solina
%T Errors in Stereo Due to Quantization
%R MS-CIS-85-34
%I University of Pennsylvania
%K AI06
%A David A. Klein
%T An Expert Systems Approach to Realtime, Active Management of a Target
Resource
%R MS-CIS-85-40
%I University of Pennsylvania
%K AI01 AA08
YES/MVS IBM O03
%X (describes part of a system for monitoring IBM systems)
%A Robin F. Karlin
%T Romper Mumble
%R MS-CIS-85-41
%I University of Pennsylvania
%K text generation
%A Brant A. Cheikes
%T Monitor Offers an a Dynamic Database [sic]: The Search for Relevance
%R MS-CIS-85-43
%I University of Pennsylvania
%K AA09
%A Aravind K. Joshi
%T Grammar, Phrase Structure
%R MS-CIS-85-45
%I University of Pennsylvania
%K AI02
%A Ethel Shuster
%T Code Switching in Yiddish and Spanish: Evidence for the Translation Model
%R MS-CIS-85-49
%I University of Pennsylvania
%K AI02 AI08
%X discusses second-language acquisition
%A Bonnie Lynn Webber
%T Question, Answer and Responses: Interacting with Knowledge Base Systems
%R MS-CIS-85-50
%I University of Pennsylvania
%K O01
%A Paul A. Fishwick
%T Hires: Hierarchical Reasoning System
%R MS-CIS-85-52
%I University of Pennsylvania
%K simulation
%X manual for system
%A A. Zwarico
%A I. Lee
%T Proving a Network of Real-Time Processes Correct
%R MS-CIS-85-53
%I University of Pennsylvania
%K AA08
%A Ruzena Bajcsy
%T Active Perception vs. Passive Perception
%R MS-CIS-85-54
%I University of Pennsylvania
%K AI06 AI16
%X getting a system to "look" as opposed to just "see."
%A Greogry Donald Hager
%T Computational Aspects of Proofs in Modal Logic
%R MS-CIS-85-55
%I University of Pennsylvania
%K AI10
%A Kathleen Filliben McCoy
%T Correcting Object-Related Misconceptions
%R MS-CIS-85-57
%I University of Pennsylvania
%K AI08 AI01
%X discusses how human experts correct misconceptions as they use the ROMPER
system
%A Peter Kirby Allen
%T Object Recognition Using Vision
%R MS-CIS-85-60
%I University of Pennsylvania
%K AI06 AI07
%X includes discussion of the use of vision and exploratory tactile sensing
in object recognition
%A Aravind K. Joshi
%A K. Vijay-Shanker
%A David J. Weir
%R MS-CIS-86-01
%T The Relationship Between Tree Adjoining Grammars and Head Grammars
%I University of Pennsylvania
%K AI02
%A Hossam A. Elgindy
%T Efficient Algorithms for Computing the Weak Visibility Polygon from
an Edge
%I University of Pennsylvania
%R MS-CIS-86-04
%K O06
%A Jean H. Gallier
%T A Fast Algorithm for Testing Unsatisfiability of Ground Horn Clauses
with Equations
%I University of Pennsylvania
%R MS-CIS-86-06
%K AI10
%A Richard Paul
%A Hugh F. Durrant-Whyte
%A Max Mintz
%T A Robust, Distributed Sensor and Actuation Robot Control System
%I University of Pennsylvania
%R MS-CIS-86-07
%K AI06 AI07
%X proposal for a blackboard based robot system
%A Hugh F. Durrant-Whyte
%T Consistent Integration and Propagation of Disparate Sensor Observations
%I University of Pennsylvania
%R MS-CIS-86-08
%K AI07 AI06
%A Eric P. Krotkov
%A Jean-Paul Maritan
%T Range From Focus
%I University of Pennsylvania
%R MS-CIS-86-09
%K AI07 AI06
%A Jean H. Gallier
%A Stan Raatz
%T Hornlog: A Graph Based Interpreter for General Horn Clauses
%I University of Pennsylvania
%R MS-CIS-86-10
%K AI10
%A Stan Raatz
%A George Drastal
%T Relating Expert System Rule Interactions to Norms of Rule-based Programming
%I University of Pennsylvania
%R MS-CIS-86-12
%K AI01
%A Ruzena Bajcsy
%A Max Mintz
%A Erica Liebman
%T A Common Framework for Edge Detection and Region Growing
%I University of Pennsylvania
%R MS-CIS-86-13
%K AI06
------------------------------
End of AIList Digest
********************
∂06-Mar-87 1419 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #68
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 6 Mar 87 14:19:36 PST
Date: Fri 6 Mar 1987 07:07-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #68
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 6 Mar 1987 Volume 5 : Issue 68
Today's Topics:
Bibliogrpahy - Leff AI.BIB43TR
----------------------------------------------------------------------
Date: Tue, 3 Mar 1987 16:35 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: AI.BIB43TR
%A Ashar A. Butt
%T Cell Design in Prolog
%I University of California, Berkeley
%R CSD 86/286
%K AA04 T02
%X $3.50
%A David Michael Ungar
%T The Design and Evaluation of a High Performance Smalltalk System
%I University of California, Berkeley
%R CSD 86/287
%X $9.00
%A Yigal Arens
%T CLUSTER: An Approach to Contextual Language Understanding
%I University of California, Berkeley
%R CSD 86/293
%K Unix Consultant AI02 AA15
%X $8.25
%A Robert Wilensky
%T Some Problems and Proposals for Knowledge Representation
%I University of California, Berkeley
%R CSD 86/294
%K AI02 AI16 kodiak AT14
%X $3.25
%A Joseph Pasquale
%T Knowledge Based Distributed System Management
%I University of California, Berkeley
%R CSD 86/295
%K AA08
%X $2.50
%A Paul Schafran Jacobs
%T A Knowledge Based Approach to Language Production
%I University of California, Berkeley
%R CSD 86/254
%K AI02 O01
%X $7.50
%A Jung-Herng Chang
%T High Performance Execution of Prolog Programs Based on a Static Data
Dependence Analysis
%I University of California, Berkeley
%R CSD 86/263
%K T02
%X $5.00
%R CS-86-147 Computer Science Department
%I Washington State University
%C Pullman, WA 99164-1210
%T COREL - A CONCEPTUAL RETRIEVAL SYSTEM
%A M. Kathryn Di Benigno
%A George R. Cross
%A Gary G. deBessonet
%K AI16
%X Corel is an experimental retrieval system that employs techniques of
artificial intelligence. Articles of the Civil Code of Louisiana have been
conceptually indexed using frame-based knowledge structures in hope of
improving accessibility over traditional key-word retrieval systems. A set
of macro packages has been developed to allow a domain expert to
implement a retrieval system based on this methodology.
%R CS-86-149 Computer Science Department
%I Washington State University
%C Pullman, WA 99164-1210
%T THE STRUCTURE OF CCLIPS
%A Mohammed Nasiruddin
%A George R. Cross
%A Cary G. deBessonet
%K AA24
%X The Civil Code Legal Information Processing System (CCLIPS) is a conceptual
retrieval system whose domain is the Louisiana Civil Code. Statutes are
coded in Atomically Normalized Form (ANF) and entered into a database. Legal
situations are entered by the user in ANF and relevant statutes are retrieved.
We discuss the current status of the system and some plans for further
development.
%R CSL T.R. 86-291
%T Lisp and Prolog Memory Performance
%A Evan Tick
%D January 1986
%I Stanford University Computer Systems Laboratory
%X This report presents a comparison between a Lisp and Prolog architecture bas
ed
on memory performance. Four Lisp programs were translated into Common Lisp and
Prolog abstract machine instruction sets. The translated programs were
emulated and memory reference counts collected. Memory usage statistics
indicate how the two languages do fundamental computations different ways with
varying efficiency. Additional measurements of production systems running on a
conventional host are presented.
%R CSL-TN-86-286
%T Microprogram Control of a Prolog Machine
%A Kiyomi Koyama
%D January 1986
%X
.br
br
A Prolog machine design and its control are described. The machine features
two-stage pipelining, a triple bus interconnection data path and support for
concurrent control of micro-operations. The objective of this design is to
improve execution of a Prolog processor by simultaneously performing multiple
micro-operations. Capabilities of concurrent operation support are described
in detail and demonstrated using some example Prolog functions. Two-stage
pipeline technique as applied to non-deterministic control of Prolog program
execution will be presented.
.br
br
37 pages.....$4.35
%R 1260
%T The AQ15 Inductive Learning System: An Overview and Experiments
%A R. S. Michalski
%A I. Mozetic
%A J. Hong
%A N. Lavrac
%I The University of Illinois at Urbana-Champaign, Department of Computer Scienc
e
%D JUL 1986
%K AI04
%R 1268
%T Automated Reference Librarians for Program Libraries and
Their Interaction with Language Based Editors
%A J. J. Shilling
%I The University of Illinois at Urbana-Champaign, Department of Computer Scienc
e
%D AUG 1986
%K AA14
%R 1293
%T Induction, Of and By Probability
%A Larry Rendell
%R 1268
%I The University of Illinois at Urbana-Champaign, Department of Computer Scienc
e
%D AUG 1986
%K AI04
%A Marianne Winslett Wilkins
%T A Model-Theoretic Approach to Updating Logical Databases
%D JAN 1986
%R STAN-CS-86-1096
%I Stanford University, Department of Computer Science
%D JAN 1986
%K AI10 AA09
%$ 5.00
%A Jitendra Malik
%T Interpreting Line Drawings of Curved Objects
%D DEC 1985
%R STAN-CS-86-1099
%I Stanford University, Department of Computer Science
%K AI06
%$ 15.00
%A Martin Abadi
%A Zohar Manna
%T Modal Theorem Proving
%D MAY 1986
%R STAN-CS-86-1100
%I Stanford University, Department of Computer Science
%K AA13 AI11
%$ 5.00
%A David E. Foulser
%T On Random Strings and Sequence Comparisons
%D FEB 1986
%R STAN-CS-86-1101
%I Stanford University, Department of Computer Science
%K O06
%$ microfiche only charge listed as N/A
%A Devika Subramanian
%T A Survey of AI Classnotes for Winter 84-85
%D APR 1986
%R STAN-CS-86-1104
%I Stanford University, Department of Computer Science
%K AI16
%$ 15.00
%A Martin Abadi
%A Zohar Manna
%T A Timely Resolution
%D APR 1986
%R STAN-CS-86-1106
%I Stanford University, Department of Computer Science
%K AI11 temporal logic AI10
%A David E. Smith
%T Controlling Inference
%D APR 1986
%R STAN-CS-86-1107
%I Stanford University, Department of Computer Science
%K AI03
%$ 15.00
%A K. Morris
%A J. Ullman
%A A. Van Gelder
%T Design Overview of the NAIL! System
%D MAY 1986
%R STAN-CS-86-1108
%I Stanford University, Department of Computer Science
%K AI10 AA09
%X Nail = Not another implementation of logic
%$ 5.00
%A Ross Casley
%T A Proof Editor for Propositional Temporal Logic
%D MAY 1986
%R STAN-CS-86-1109
%I Stanford University, Department of Computer Science
%K AI11
%$ 5.00
%A Y. Malachi
%A Z. Manna
%A R. Waldinger
%T TABLOG: A New Approach to Logic Programming
%D MAR 1985
%I Stanford University, Department of Computer Science
%R STAN-CS-86-1110
%K AI10
%$ 5.00
%A Paul Rosenbloom
%A John Laird
%T Mapping Explanation-Based Generalization onto Soar
%D JUN 1986
%R STAN-CS-86-1111
%I Stanford University, Department of Computer Science
%K AI16 explanation-based generalization
%$ 5.00
%A Jeffrey F. Naughton
%T Optimizing Function-Free Recursive Inference Rules
%D MAY 1986
%R STAN-CS-86-1114
%I Stanford University, Department of Computer Science
%K AI10
%$ 5.00
%A B. G. Buchanan
%A B. Hayes-Roth
%A O. Lichtarge
%T The Heuristic Refinement Method for Deriving Solution Structures of Proteins
%R STAN-CS-86-1115
%D MAR 1986
%I Stanford University, Department of Computer Science
%K AA10 AI01
%$ 5.00
%A Li-Min Fu
%A Bruce G. Buchanan
%T Inductive Knowledge Acquisition for Rule-based Expert Systems
%R STAN-CS-86-1116
%I Stanford University, Department of Computer Science
%D OCT 1985
%K AI01
%$ 5.00
%A D. Howe
%T Implementing Number Theory: An Experiment with NUPRL
%I Cornell University, Department of Computer Science
%D MAY 1986
%R 86-752
%K AA13 AI11 AI14
%A J. Sasaki
%T Extracting Efficient Code From Constructive Proofs
%I Cornell University, Department of Computer Science
%D JUNE 1986
%R 86-757
%K AA08
%A M. P. Mendler
%T First and Second Lambda Calculi with Recursive Types
%I Cornell University, Department of Computer Science
%D JUL 1986
%R 86-764
%K T01
%A J. Bates
%T THEFRL Mathematics Environment: A Knowledge Based Medium
%I Cornell University, Department of Computer Science
%D AUG 1986
%R 86-768
%K AA13
%A C. Kreitz
%T Constructive Automata Theory Implemented with the Nuprl Proofl Development
Systems
%I Cornell University, Department of Computer Science
%D SEP 1986
%R 86-779
%K AA13 AA08 AI11
%A A. Moitra
%A P. Panangaden
%T A Proof System for Dataflow Networks with Indeterminate
Modules
%I Cornell University, Department of Computer Science
%D SEP 1986
%R 86-782
%K AA13 AA08 AI11
%A J. D. Ward
%A B. E. Gillett
%A A. R. DeKock
%T CIGEN: A System for Testing Knowledge Base Compilation
Heuristics on a Microcomputer
%I University of Missouri-Rolla Department of Computer Science
%R CSC 84-10
%D 1984
%K AA08
%A K. W. Whiting
%A A. R. DeKock
%A J. B. Prater
%T A Focus of Attention Algorithm for Expert Systems
%I University of Missouri-Rolla Department of Computer Science
%R CSC 84-12
%D 1984
%K AI01
%A R. M. Butler
%A A. R. DeKock
%T An Algorithm for Parallel Subsumption
%I University of Missouri-Rolla Department of Computer Science
%R CSc 84-1
%D 1985
%K H03 AI11
%A R. L.Boehning
%A B. E. Gillett
%T A Parallel Branch and Bound Algorithm for Integer Linear
Programming Models
%I University of Missouri-Rolla Department of Computer Science
%R CSC 85-2
%D 1985
%K H03 AI03
%A R. S. Dare
%A A. R. DeKock
%T Genesis of an Expert System for UMR Degree Auditing
%I University of Missouri-Rolla Department of Computer Science
%R CSC 86-3
%D 1986
%K AI01 AA07
%A J. H. Marchal
%A A. R. DeKock
%T MICA: prototyping an Expert System Consultant
%I University of Missouri-Rolla Department of Computer Science
%R CSC 86-5
%D 1986
%K AI01
%A J. A. Vila Ruiz
%A A. R. DeKock
%T A Computerized Audio-Visual Speech Model
%I University of Missouri-Rolla Department of Computer Science
%R CSC 86-4
%D 1986
%K AI05
%A D. Wise
%T The Applicative Style of Programming
%I Oregon State University, Department of Computer Science
%R CSTR 84-2
%D 1984
%A F. Springsteel
%T Expert Systems for Exploratory Data Analysis: Towards Automated Research
%I Oregon State University, Department of Computer Science
%R CSTR 85-30-1
%D 1985
%K AA12 AI01 automated knowledge acquisition
%A F. Springsteel
%T Biomedical Knowledge Acquisition: Three Systems Reviewed
%I Oregon State University, Department of Computer Science
%R CSTR-86-60-1
%D 1986
%K AA01 AI01 AA12 automated knowledge acquisition
%A T. Dietterich
%T Learning at the Knowledge Level
%I Oregon State University, Department of Computer Science
%R CSTR-86-30-1
%D 1986
%K AI04
%A T. G. Dietterich
%A N. S. Flann
%A D. C. Wilkins
%T A Summary of Machine Learning Papers from IJCAI-85
%I Oregon State University, Department of Computer Science
%R CSTR-86-30-2
%D 1986
%K AI04
%A N. S. Flann
%A T. G. Dietterich
%T Two Short Papers on Machine Learning
%I Oregon State University, Department of Computer Science
%R CSTR-86-30-3
%D 1986
%K AI04
%A A. Birjandi
%A T. G. Lewis
%T YASHAR: A Ruled Based Meta-tool for Program Development
%I Oregon State University, Department of Computer Science
%R CSTR-86-10-1
%D 1986
%K AI01 AA08
%X this system does computer language to language translations and
restructuring of code
%A A. Birjandi
%A T. G. Lewis
%T ARASH: A Re-Structuring Environment for Building Software Systems
From Reusable Components
%I Oregon State University, Department of Computer Science
%R CSTR-86-10-2
%D 1986
%K AA08
%A A. Birjandi
%A T. G. Lewis
%T Artimis: A Module Indexing and Source Program Reading and Understanding
Environment
%I Oregon State University, Department of Computer Science
%R CSTR-86-10-3
%D 1986
%K AA14 AA08
%A J. S. Bennett
%A T. G. Dietterich
%T The Test Incorporation Hypothesis and the Weak Methods
%I Oregon State University, Department of Computer Science
%R CSTR-86-30-4
%D 1986
%K AI03
%A N. S. Flann
%A T. G. Dietterich
%T Selecting Appropriate Representations for Learning From Examples
%I Oregon State University, Department of Computer Science
%D 1986
%R CSTR-86-30-5
%K AI16 AI04
%A C. S. Rapp
%T Algebra READER: An Expert Algebra Work Problem Reader
%I Oregon State University, Department of Computer Science
%D 1986
%R CSTR-86-30-6
%K AA07 AA13 AI02 AI01
%A W. S. Bregar
%A A. M. Farley
%A G. Bayley
%T Knowledge Sources for an Intelligent Algebra Tutor
%I Oregon State University, Department of Computer Science
%R CSTR-86-30-7
%D 1986
%K AA07 AA13
%A C. Swart
%A D. Richards
%T On the Inference of Strategies
%I Oregon State University, Department of Computer Science
%R CSTR-86-20-3
%D 1986
%K AI04 O06
%A W. G. Rudd
%A K. Uppuluri
%A G. R. Cross
%A S. Haley
%T Expert Systems for Management of Pests of Agricultural Crops
%I Oregon State University, Department of Computer Science
%R CSTR-86-60-4
%D 1986
%K AA23 AI01
%A T. G. Dietterich
%A D. G. Ullman
%T FORLOG: A Logic-based Architecture for Design
%I Oregon State University, Department of Computer Science
%R CSTR-86-30-8
%D 1986
%K AA05 AI10
%A D. G. Ullman
%A L. A. Stauffer
%A T. G. Dietterich
%T Preliminary Results of an Experimental Study of the Mechanical Design
Process
%I Oregon State University, Department of Computer Science
%R CSTR-86-30-9
%D 1986
%K AA05 AI08
%A Edward A. Stohr
%A Jon A. Turner
%A Yannis Vassiliou
%A Norman H. White
%T Research in Natural Language Retrieval Systems
%I New York University, Center for Research on Information Systems
%R 30
%K AA09 AI02
%A Jon A. Turner
%A Matthias Jarke
%A Edward A. Stohr
%A Yannis Vassiliou
%A Norman H. White
%T Using Restricted Natural Language for Data Retrieval: A Plan for Field Evalua
tion
%I New York University, Center for Research on Information Systems
%R 38
%K AA09 AI02
%A Yannis Vassiliou
%A James Clifford
%A Matthias Jarke
%T How Does an Expert System Get its Data?
%I New York University, Center for Research on Information Systems
%R 50
%K AI01
%A Matthias Jarke
%A Jacob Shalev
%T A Knowledge-Based Approach to the 'Analysis and Design of Business Transactio
n
Processing Systems
%I New York University, Center for Research on Information Systems
%R 53
%K AA09 AA06
%A Yannis Vassiliou
%A Matthias Jarke
%A Edward A. Stohr
%A Jon A. Turner
%A Norman H. White
%T Natural Languages for Database Queries: A Laboratory Study
%I New York University, Center for Research on Information Systems
%R 55
%K AI02 AA09
%A Matthias Jarke
%A Yannis Vassiliou
%T Coupling Expert Systems with Database Management Systems
%I New York University, Center for Research on Information Systems
%R 54
%K AI01 AA09
%A James Clifford
%A Matthias Jarke
%A Yannis Vassiliou
%T A Short Introduction to Expert Systems
%I New York University, Center for Research on Information Systems
%R 59
%K AI01 AT08
%A Matthias Jarke
%A Jon A. Turner
%A Edward A. Stohr
%A Yannis Vassiliou
%A Norman H. White
%A Ken Michielsen
%T A Field Evaluation of Natural Language for Data Retrieval
%I New York University, Center for Research on Information Systems
%R 62
%K AI02 AA09
%A Matthias Jarke
%A James Clifford
%A Yannis Vassiliou
%T An Optimizing Prolog Front End to a Relational Query Systems
%I New York University, Center for Research on Information Systems
%R 65
%K AA09 T02
%A Taracad Sivasankaran
%A Matthias Jarke
%T Logic-Based Formula Management Strategies in an Actuarial Consulting System
%I New York University, Center for Research on Information Systems
%R 69
%K AA06 AA12 AI01
%A Matthias Jarke
%A Jurgen Krause
%A Yannis Vassiliou
%T Studies in the Evaluation of a Domain-Independent Natural Language Query Syst
em
%I New York University, Center for Research on Information Systems
%R 72
%K AI02 AA09
%A Yannis Vassiliou
%A Jim Clifford
%A Matthias Jarke
%T Database Access Requirements of Knowledge Based Systems
%I New York University, Center for Research on Information Systems
%R 74
%K AA09
%A Matthias Jarke
%T External Semantic Query Simplification: A Graph Theoretic Approach and its
Implementation in Prolog
%I New York University, Center for Research on Information Systems
%R 75
%K AA09 T02
%A Vasant Dhar
%A Casey Quayle
%T An Approach to Dependency Directed Backtracking Using Domain Specific Knowled
ge
%I New York University, Center for Research on Information Systems
%R 89
%K AI03
%A Vasant Dhar
%T On the Plausibility and Scope of Expert Systems in Management
%I New York University, Center for Research on Information Systems
%R 98
%K AI01 AA06
%A James Clifford
%A Matthias Jarke
%A Henry C. Lucas
%T Designing Expert Systems in a Business Environment
%I New York University, Center for Research on Information Systems
%R 99
%K AI01
%A Vasant Dhar
%A Matthias Jarke
%T Analogical and Dependency-Directed Reasoning Strategies for Large Systems
Evolution
%I New York University, Center for Research on Information Systems
%R 100
%K AI16
%A Jae B. Lee
%A Edward A. Stohr
%T Representing Knowledge for Portfolio Management Decision Making
%I New York University, Center for Research on Information Systems
%R 101
%K AA06 AI01 AI13
%R AI-208-86
%T Some Thoughts on Proof Discovery
%I Microelectronics and Computer Technology Corporation
%D JUN 1986
%K AI16
%R AI-160-86
%T Models of Technology Transfer at MCC
%I Microelectronics and Computer Technology Corporation
%D MAY 1986
%K AT19
%R AI-159-86
%T A Man-Machine Procedure for Building a Medium Sized Knowledge Base by
Analogy and Learning: Preliminary Report
%I Microelectronics and Computer Technology Corporation
%D MAY 1986
%K AI16 AI04
%R Ai-158-86
%T The Use of Analogy in Automatic Proof Discovery: Preliminary Report
%I Microelectronics and Computer Technology Corporation
%D MAY 1986
%K AI16
%R AI-157-86
%T Algorithms for Subpixel Registration
%I Microelectronics and Computer Technology Corporation
%D APR 1986
%K AI06
%R AI-102-86
%T Extended Contradiction Resolution
%I Microelectronics and Computer Technology Corporation
%D MAR 1986
%K AI16
%R AI-101-86
%T Expert Systems in the Marketplace
%I Microelectronics and Computer Technology Corporation
%D MAR 1986
%K AI01
%R AI-082-86
%T Automating Knowledge Acquisition From Experts
%I Microelectronics and Computer Technology Corporation
%D MAR 1986
%K AI01
%R AI-016-86
%T A Diffusing Computation for Truth Maintenance
%I Microelectronics and Computer Technology Corporation
%D 1985
%K AI15
%R AI-013-86
%T Rule-Based Geometrical Reasoning for the Interpretation of Line Drawings
%I Microelectronics and Computer Technology Corporation
%D JAN 24, 1986
%K AI01 AI06
%R AI-181-85
%T Efficient Management of Backtracking in And-Parallelism
%I Microelectronics and Computer Technology Corporation
%D DEC 12, 1985
%K AI10 H03 AI03
%R AI-119-85
%T A Knowledge Engineering Bibliography
%I Microelectronics and Computer Technology Corporation
%D NOV 1985
%K AI01 AT09
%R AI-109-85
%T An Encoding Technique for the Efficient Implementation of Type
Inheritance
%I Microelectronics and Computer Technology Corporation
%D DEC 1985
%K O06
%R AI-100-85
%T Suggested Reading List for an Introduction to Artificial Intelligence
%I Microelectronics and Computer Technology Corporation
%D OCT 1985
%K AT09 AI16
%R AI-083-85
%T Machine Translation: An American Perspective
%I Microelectronics and Computer Technology Corporation
%D AUG 1985
%K AI02 GA02
%R AI-082-85
%T Integrating Data Type Inheritance into Logic Programming
%I Microelectronics and Computer Technology Corporation
%D AUG 1985
%K AI10
%R AI-076-85
%T Logic and Inheritance
%I Microelectronics and Computer Technology Corporation
%D JUL 1985
%K AI10
%R AI-068-85
%T LOGIN: A Logic Programming Language with Built-In Inheritance
%I Microelectronics and Computer Technology Corporation
%D JUL 1985
%K AI10
%R AI-062-85
%T An Algorithm for Truth Maintenance
%I Microelectronics and Computer Technology Corporation
%D APR 1985
%K AI15
%R AI-055-85
%T CYC: Using Common Sense Knowledge to Overcome Brittleness and
Knowledge Acquisition Bottlenecks
%I Microelectronics and Computer Technology Corporation
%D JUL 15, 1985
%K AI16
%R AI-054-85
%T "I Had A Dream" AAAI Presidential Address
%I Microelectronics and Computer Technology Corporation
%D AUG 19, 1985
%K AI16
%R AI-017-85
%T Extraction of Expert System Rules From Text
%I Microelectronics and Computer Technology Corporation
%D JUN 1985
%K AI01 AI02
%R Ai-015-85
%T The Treatment of Grammatical Categories and Word Order in Machine
Translation
%I Microelectronics and Computer Technology Corporation
%D MAR 1985
%K AI02
%R AI-014-85
%T An Evaluation of Metal: The LRC Machine Translation System
%I Microelectronics and Computer Technology Corporation
%D MAR 1985
%K AI02
------------------------------
End of AIList Digest
********************
∂06-Mar-87 1731 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #69
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 6 Mar 87 17:31:31 PST
Date: Fri 6 Mar 1987 07:11-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #69
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 6 Mar 1987 Volume 5 : Issue 69
Today's Topics:
Bibliography - Leff AI.BIB47C
----------------------------------------------------------------------
Date: Tue, 3 Mar 1987 16:36 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: AI.BIB47C
%A D. W. Murray
%A A. Kashko
%A H. Buxton
%T A Parallel Approach to the Picture Restoration Algorithm of
Geman and Geman on an SIMD Machine
%J MAG104
%P 133-142
%K AI06 H03
%A M. A. Sutton
%A Mingqi Cheng
%A W. H. Peters
%A Y. J. Chao
%A S. R. McNeill
%T Application of an Optimized Digital Correlation Method to Planar Deformation
Analysis
%J MAG104
%P 143-150
%K AI06
%A H. S. Ranganath
%T Hardware Implementation of Image Registration Algorithms
%J MAG104
%P 151-158
%K AI06
%A J. R. T. Lewis
%A T. Sopwith
%T Three-dimensional Surface Measurement by Microcomputer
%J MAG104
%P 159-166
%K AI06 H01
%A S. Sitharama Iyengar
%A Stephan W. Miller
%T Efficient Algorithm for Polygon Overlay for Dense Map Image Data Sets
%J MAG104
%P 167
%K AI06 O06
%A Ron Bauman
%A Tom A. Turano
%T Production Based Language Simulation of Petri Nets
%J Simulation
%V 47
%N 5
%D NOV 1986
%P 191-198
%K AA08 AI01
%A P. Dubois
%T Artificial Intelligence and Living Logic (French)
%J Cybernetica
%V 29
%N 3
%D 1986
%P 175-192
%K AI16
%A Sabah U. Randhawa
%A William J. Barton Jr.
%A Salahuddin Faruqui
%T Wavesolder Assistant: An Expert System to Aid Troubleshooting of the
Wave Soldering Process
%J Computers and Industrial Engineering
%V 10
%N 4
%P 325-334
%K AA26 AA05
%A Martien J. Quaak
%A Frans Westerman
%A Jan A. Schouten
%A Arie Hasman
%A Jan H. van Bemmel
%T Appraisal of Computerized Medical Histories: Comparisons between
Computerized and Conventional Records
%J Computers and Biomedical Research
%V 19
%N 6
%P 551-564
%D DEC 1986
%K AA01
%A Lawrence O. Hall
%A Sue Szabo
%A Abraham Kandel
%T On the Derivation of Memberships for Fuzzy Sets in Expert Systems
%J Information Sciences
%V 40
%N 1
%D NOV 1986
%P 39-52
%K AI01 O04
%A R. A. Aliyev
%A A. E. Tserkovnyy
%T An Intelligent Robot for Quality Estimation and Sorting of Components
for Automated Quality Control
%J Soviet Journal of Computer and Systems Sciences
%V 24
%N 3
%D MAY-JUN 1986
%P 113-119
%K AI07
%A D. A. Pospelov
%A I. Ya. Sil'dmyae
%T Role Structures in the in the Representation of Knowledge and in
Interactive Systems
%J Soviet Journal of Computer and Systems Sciences
%V 24
%N 3
%D MAY-JUN 1986
%P 53-58
%K AI16
%A A. P. Guminskiy
%A V. V. Martynov
%T Construction and Implementation of a Scheduling Algorithm in a Calculus
Based on Universal Semantic Code
%J Soviet Journal of Computer and Systems Sciences
%V 24
%N 3
%D MAY-JUN 1986
%P 48-52
%K AI07
%A Ye. I. Yefimov
%T Calculation of Probability in Fuzzy Human Interface
%J Soviet Journal of Computer and Systems Sciences
%V 24
%N 3
%D MAY-JUN 1986
%P 34-47
%K AI07
%A Thomas Jupille
%T Expert Systems are New Textbooks
%J Research and Development
%V 28
%N 12
%D DEC 1986
%P 52-58
%K AI01 AT08
%A Jorge G. Moser
%T Integration of Artificial Intelligence and Simulation in a Comprehensive
Decision Support System
%J Simulation
%V 47
%N 6
%P 223-232
%K AI13
%A E. Hisdal
%T Infinite-Valued Logic Based on Two-Valued Logic and Probability.
Part 1.2 Different Sources of Fuzziness
%J International Journal of Man-Machine Studies
%V 25
%N 2
%D AUG 1986
%P 113-138
%K O04
%A K. L. Norman
%A L. J. Weldon
%A B. Schneiderman
%T Cognitive Layouts of Windows and Multiple Screens for User Interfaces
%J International Journal of Man-Maachine Studies
%V 25
%N 2
%D AUG 1986
%P 229
%K AA15 AI08
%A Su-Shing Chen
%A Michael Penna
%T Shape and Motion of Nonrigid Bodies
%J MAG105
%P 175-207
%K AI06
%A Chew L. Tan
%A W. N. Martin
%T A Distributed System for Analyzing Time-Varying Multiresolution Imagery
%J MAG105
%P 162-174
%K AI06 H03
%A Muralidhara Subbarao
%A Allen M. Waxman
%T Closed Form Solutions to Image Flow Equations for Planar Surfaces in
Motion
%J MAG105
%P 208-228
%K AI06
%A H. S. Yang
%A A. C. Kak
%T Determination of the Identity, Position and Orientation of the Topmost
Object in a Pile
%J MAG105
%P 229-255
%K AI06
%A C. H. Chien
%A J. K. Aggarwal
%T Identification of 3D Objects from Multiple Silhouettes Using Quadtrees/
Octrees
%J MAG105
%P 256-273
%K AI06
%A Prasanna G. Mulgaonkar
%A Linda G. Shapiro
%A Robert M. Haralick
%T Shape from Perspective: A Rule-Based Approach
%J MAG105
%P 298-320
%K AI06 AI01
%A Vincent Shang-Shouq Hwang
%A Larry S. Davis
%A Takashi Matsuyama
%T Hypothesis Integration in Image Understanding Systems
%J MAG105
%P 321-371
%K AI06
%A Robert M. Haralick
%T Computer Vision Theory: The Lack Thereof
%J MAG105
%P 372-386
%K AI06 AI16
%A J. Stojanovski
%T A Note on Implementing Prolog in Lisp
%J Information Processing Letters
%V 23
%N 5
%D NOV 24 1986
%P 261-264
%K T01 T02
%A R. A. King
%T Expert Systems for Material Selection and Corrosion
%J The Chemical Engineer (London)
%N 431
%D DEC 1986
%P 42-45
%K AA05 AI01
%A J. Mantas
%T An Overview of Character Recognition Methodologies
%J MAG106
%P 425-430
%K AI06
%A J. Cerella
%T Pigeons and Perceptrons
%J MAG106
%P 431-438
%K AI06 AI08 AA10
%A A. Goshtasby
%T Piecewise Linear Mapping Functions for Image Registration
%J MAG106
%P 459-466
%K AI06
%A J. N. Kapur
%T Application of Entropic Measures of Stochastic Dependence on Pattern
Recognition
%J MAG106
%P 473-476
%K AI06
%A M. A. Ismail
%A S. Z. Selim
%T Fuzzy c-means: Optimality of Solutions and Effective Termination of
the Algorithm
%J MAG106
%P 481
%K O04 O06
%A A. J. P. Theuwissen
%A C. H. L. Weitjins
%T The Accordian Imager, A New Solid State Image Sensor
%J Philips Technical Review
%P 1-9
%V 43
%N 1-2
%K AI06
%A A. D. Goldfinger
%A G. M. Oderda
%A R. F. Wachter
%T IPECAC: An Expert System for the Management of Poisoning Incidents
%J John Hopkins APL Technical Digest
%V 7
%N 4
%D OCT-DEC 1986
%P 372-378
%K AI01 AA01
%A Andrew Russell
%T Vision System Based on a Single-chip Microcomputer
%J Microprocessors and Microsystems
%V 10
%N 9
%D NOV 1986
%P 485-490
%K H01 AI06
%X describes an image processing system based on an 8751 microcontroller
with a Dynamic Ram as a vision sensor
%A Min De Cheng
%A Xie Chang Shen
%A Min Qiang Zhou
%A Quing Yun Shi
%A Min Ping Qian
%T Introduction to Pattern Recognition
%I Shanghai Kexu Jishu Chubanshe
%C Shanghai
%D 1983
%K AT15 AI06
%X in Chinese
%A A. I. Degtyarev
%A A. A. Voronkov
%T Methods of Control of Equality in Mechanical Proofs of Theorems
%J Kibernetika (Kiev)
%V 1986
%N 3
%P 34-41
%K AI11 AI03
%A Francois Fages
%A Gerard Huet
%T Complete Sets of Unifiers and Matchers in Equational Theories
%J Theoretical Computer Science
%V 43
%N 2-3
%P 189-200
%K AI11
%A N. V. Gogoberidze
%A Sh. G. Mgeladze
%T An Approach to the Problem of Automation of Logical Inference
%J Soobshch. Akad. Nauk Gruzin SSR
%V 119
%D 1985
%N 3
%P 581-584
%K AI11
%X Russian. English and Georgian Summaries
%A Jan Grabowski
%T Unificational Dynamic Logic
%J Elektron. Informationsverarb. Kybernet.
%V 22
%D 1986
%N 5-6
%P 325-338
%K AI11
%A Ryszard Jakubowski
%T A Structural Representation of Shape and Its Features
%J Inform. Sci
%V 39
%D 1986
%N 2
%P 129-151
%K AI06 AI16
%A V. I. Vasil'ev
%A F. P. Ovsyannikova
%T Learning Pattern Recognition with a Given Reliability
%J Kibernetika (Kiev)
%V 1986
%N 3
%P 50-56
%K AI06 AI04
%A P. Ecsedi-Toth
%T On the Expressive Power of Equality-Free First Order Languages
%J Z. Math. Logik Grundlag. Math
%V 32
%D 1986
%N 4
%P 371-375
%A V. K. Kabulov
%T Proof of Theorems in the Propositional Calculus
%J Dokl. Akad. Nauk UzSSR
%D 1986
%N 5
%P 5-6
%K AI11
%A Daniel N. Osherson
%A Michael Stob
%A Scott Weinstein
%T Aggregating Inductive Expertise
%J Inform. and Control
%V 70
%D 1986
%N 1
%P 69-95
%K AI04
%A A. A. Voronkov
%A A. I. Degtyarev
%T Automatic Theorem Proving I.
%J Kibernetika (Kiev)
%V 1986
%N 3
%P 27-33
%A A. A. Lorents
%T Cluster Invariant Transformations of Images
%B Methods and Means of Transforming Information
%E G. G. Gromov
%N 3
%P 39-75
%I "Zinatne"
%C Riga
%D 1985
%A P. T. Cox
%A T. Pietrzykowski
%T Incorporating Equality into Logic Programming via Surface Deduction
%J Ann. Pure Appl. Logic
%V 31
%D 1986
%N 2-3
%P 177-189
%K AI10 AI11
%A Judith V. Grabiner
%T Computers and the Nature of Man: A Historian's Perspective on Controversies
About Artificial Intelligence
%J Bull. Amer. Math. Soc. (n. S.)
%V 15
%D 1986
%N 2
%P 113-126
%K AA11 AA25 AT20 AI16
%A Rolf Wiehagen
%T On the Complexity of Program Synthesis from Examples
%J Elektron. Informationsverarb. Kybernet
%V 22
%D 1986
%N 5-6
%P 305-323
%K AA08 AI04
%A Kunihiko Kaneko
%T Complexity in Basin Structures and Information Processing by the
Transition Among Attractors
%B Dynamical Systems and Nonlinear Oscillations (Kyoto 1985)
%P 194-209
%S World Sci. Adv. Ser. Dyn. Syst.
%I Word Sci. Publishing
%C Singapore
%D 1986
%K AI08
%A G. S. Pospelov
%A D. A. Pospelov
%A V. F. Khoroshevskyi
%T International Basic Laboratory on Artificial Intelligence
%J Vestnik Akademii Nauk SSSR
%N 8
%D 1986
%P 76
%K AT19
%A R. G. Palmer
%T How Expert Systems Can Improve Crop Production
%J Agricultural Engineering
%V 67
%N 6
%D SEP-OCT 1986
%P 28-35
%K AA05 AA23 AI01
%A G. Papakonstantinou
%A C. Moraitis
%A T. Panayiotopoulos
%T An Attribute Grammar Interpreter as a Knowledge Engineering Tool
%J Angewandte Informatik
%N 9
%D SEP 1986
%K AI16
%A L. I. Lipkin
%T Correct Models in Problems of Recognition with Random Information
%J Dokl. Akad. Nauk SSSR
%V 289
%D 1986
%N 4
%P 793-795
%K AI06
%X (in Russian)
%A Maria Viorica Stefanescu
%T The Problem of Best Approximation in the Theory of Hierarchical Classificatio
n
%J Stud. Cerc. Mat
%V 38
%D 1986
%N 4
%P 392-408
%K O06
%X in Romanian with an English summary
%A Xu Ding Zhu
%A Xue Mou Wu
%T Transformation of Pansystems Relations, Pansystems Clustering and Pansystems
Recognition
%J J. Huazhong Univ. Sci. Tech.
%V 13
%D 1985
%N 6
%P 71-74
%X in Chinese with English summary
%A S. S. Goncharov
%A D. I. Sviridenko
%T Mathematical Foundations of Semantic Programming
%J Dokl. Akad. Nauk SSSR
%V 289
%D 1986
%N 6
%P 1324-1328
%K AI10 AI11 AI16
%X in Russian
%A Yoshihito Toyama
%T On Equivalence Transformations for Term Rewriting
%J RIMS Symposia on Software Science and Engineering II (Kyoto 183/184)
%P 44-61
%S Lecture Notes in Computer Science
%V 220
%I Springer-Verlag
%C Berlin-New York
%D 1986
%K AI10
%A Sergiu Hart
%A Micha Sharir
%T Probabilistic Propositional Temporal Logics
%J Inform. and Control
%V 70
%D 1986
%N 2-3
%P 97
%K AI10
%A Dell, Gary S.
%T A Spreading-Activation Theory of Retrieval in Sentence Production
%J Psychological Review
%V 93
%N 3
%D 1983
%P 283-321
%K AI12 AI02
%A Fahlman, Scott E.
%T Representing Implicit Knowledge
%B Parallel Models of Associative Memory
%E E Geoffrey E. Hinton
%E James A. Anderson
%D 1981
%I Lawrence Erlbaum Associates
%C Hillsdale, New Jersey
%K AI12 AI08
%A Fanty, Mark
%T Context-Free Parsing in Connectionist Networks
%R Tech Report TR174
%I Department of Computer Science, University of Rochester
%D Nov. 1985
%K AI12 AI02
%A Feldman, Jerome A.
%T A Connectionist Model of Visual Memory
%B Parallel Models of Associative Memory
%E Geoffrey E. Hinton
%E James A. Anderson
%D 1981
%I Lawrence Erlbaum Associates
%C Hillsdale, New Jersey
%K AT15 AI12
%A Feldman, Jerome A.
%A Dana H. Ballard
%T Connectionist Models and Their Properties
%J Cognitive Science
%V 6
%P 205-254
%D 1982
%K AI08 AI12
%A Feldman, Jerome A.
%T Dynamic Connections in Neural Networks
%J Biological Cybernetics
%I Springer-Verlag
%V 46
%D 1982
%P 27-39
%K AI08 AI12
%A Fodor, Jerry A.
%T Information and Association
%O This paper is a critique of connectionism. Author is with department
of Philosophy, MIT, Cambridge Massachussetts.
%K AI08 AI12
%A Hopfield, John J.
%T Neural Networks and physical systems with emergent collective
computational abilities
%J Proceedings National Academy of Science
%V 79
%P 2554-2558
%D Apr. 1982
%K AI08 AI12
%A Hopfield, John J.
%A David W. Tank
%T Simple "Neural" Optimization Networks: An A/D Converter, Signal Decision
Circuit, and a Linear Programming Circuit
%J IEEE Transactions on Circuits and Systems
%V CAS-33
%N 5
%P 533-541
%D May 1986
%K AI12 AA04
%A Hopfield, John J.
%A David W. Tank
%T Collective Computation with Continuous Variables
%B Disordered Systems and Biological Organization
%I Springer-Verlag
%O In press, 1986
%K AI12
%A Hopfield, John J.
%A David W. Tank
%T "Neural" Computation of Decisions in Optimization Problems
%J Biological Cybernetics
%I Springer-Verlag
%V 52
%D 1985
%P 141-152
%K AI12
%A Kosslyn, Stephen M.
%A Gary Hatfield
%T Representation without Symbol Systems
%J Social Research
%V 51
%N 4
%D 1984
%P 1019-1044
%O Winter 1984
%K AI12
%A Matthews, Robert J.
%T Problems with Representationalism
%J Social Research
%V 51
%N 4
%D Winter 1984
%P 1065-1097
%K AI12
%A McClelland, James L.
%A Jerome Feldman
%A Beth Adelson
%A Gordon Bower
%A Drew McDermott
%T Connectionist Models and Cognitive Science: Goals, Directions and
Implications
%D Jan. 1987
%O National Science Foundation Grant Proposal
%K AI12
%A Plaut, David C.
%J Visual Recognition of Simple Objects by a Connection Network
%R Tech Report TR143
%I Computer Science Department, University of Rochester
%D Aug. 1984
%K AI12 AI06
%A Pylyshyn, Zenon W.
%T Computation and Cognition: Toward a Foundation for Cognitive Science
%I MIT Press
%D 1984
%C Cambridge, Massachusetts
%K AI12 AI08
%A Reiss, Richard F.
%T An Abstract Machine Based on Classical Association Psychology
%B Proceedings 1962 Joint Computer Conference
%I AFIPS
%D 1962
%V 21
%K AI12 AI08
%A Shastri, Lokendra
%A Jerome A. Feldman
%T Semantic Networks and Neural Nets
%R Tech Report TR131
%I Computer Science Department, University of Rochester
%D June 1984
%K AI12
%A Schwartz, Robert
%T "The" Problems of Representation
%J Social Research
%V 51
%N 4
%D 1984
%P 1047-1064
%O Winter 1984
%K AI12
%A Touretzky, David S.
%A Geoffrey E. Hinton
%T Symbols Among the Neurons: Details of a Connectionist Inference
Architecture
%J IJCAI
%D Aug. 1985
%K AI12
%T Mathematical Methods in Software Science and Technology
%I Kyoto University, Research Institute for Mathematical Sciences, Kyoto
%C Kyoto
%K AT15
%X Proceedings of a symposium held at the Research Institute for Mathematical
Sciences, Kyoto University, Kyoto, October 4-6 1985
%A Cecylia M. Rauszer
%T Remarks on Logic for Dependencies
%J Bull. Polish Acad. Sci. Math
%V 34
%D 1986
%N 3-4
%P 249-252
%A A. Aiello
%A E. Burattini
%A A. Massarotti
%A F. Ventriglia
%T Heuristic Evaluation Techniques for Bin Packing Approximation Algorithms
%J Calcolo
%V 22
%D 1985
%P 319-334
%A Ernest G. Manes
%A Michael A. Arbib
%T Algebraic Approaches to Program Semantics
%S AKM Series in Theoretical Computer Science
%I Springer-Verlag
%C New York-Berlin
%D 1986
%K AA08 AT15
%X ISBN 0-387-96324-3 351 pages
%A Kazunori Ueda
%T On the Operational Semantics of Guarded Horn Clauses
%B Mathematical Methods in Software Science and Technology
%C Kyoto
%P 263-283
%D 1985
%K AI10
%X (in Japanese)
%A A. I. Kondratev
%T Game Theoretic Models in Problems of Recognition
%I "Nauka"
%C Moscow
%D 1986
%K AT15 AI06 AI16
%X In Russian
%A Etienne Paul
%T On Solving the Equality Problem in Theories Defined by Horn Clauses
%J Theoret. Comput. Science
%V 44
%D 1986
%N 2
%P 127-153
%A Zbigniew Ras
%A Maria Zemankova
%T Learning in Knowledge Based Systems, A Possibilistic Approach
%J Bull. Polish Acad. Sci. Math
%V 34
%D 1986
%N 3-4
%P 235-247
%K AI04 O04
%A Takashi Yokomori
%T Representation Theorems and Primitive Predicates for Logic Programs
%B Mathematical Methods in Software Science and Technology
%C Kyoto
%D 1986
%P 1-17
%K AI10
%A Eric Degreef
%A Jean-Paul Doignon
%A Andre Ducamp
%A Jean-Claude Falmagne
%T Languages for the Assesment of Knowledge
%J J. Math. Psychology
%V 30
%D 1986
%N 3
%P 243-256
%K AA10 AI16
%A E. Diday
%T A Visual Representation of Overlapping Clusters: Pyramids
%J RAIRO Automat. Prod. Inform. Ind
%V 20
%D 1986
%N 5
%P 475-526
%K O06
%A Michael Leyton
%T A Theory of Information Structure. II. A Theory of Perceptual
Organization
%J J. Math Psychol.
%V 30
%D 1986
%N 3
%P 257-305
%K AA10 AI08 AI16
%A Eliezer L. Lozinski
%T A Problem Oriented Inferential Database System
%J ACM Trans. Database Systems
%V 11
%D 1986
%N 3
%P 323-356
%K AA09
%A R. P. Bergstrom
%T AI - Shifting into High Gear
%J Manufacturing Engineering
%V 98
%N 1
%D JAN 1987
%K AI16 AT08
%A Gail A. Carpenter
%A Stephen Grossberg
%T A Massively Parallel Architecture for a Self-Organizing Neural Pattern
Recognition Machine
%J Computer Vision, Graphics, and Image Processing
%V 37
%N 1
%D JAN 1987
%P 54-115
%K AT12 AI06 H03
%A Stephen Grossberg
%A Ennio Mingollao
%T Neural Dynamics of Surface Perception: Boundary Webs, Illuminants and
Shape from Shading
%J Computer Vision, Graphics and Image Processing
%V 37
%N 1
%D JAN 1987
%P 116
%K AT12 AI06 AA10
%A Salvatore J. Stolfo
%A Daniel P. Miranker
%T DADO: A Tree-Structured Architecture for Artificial Intelligence
Computation
%B BOOK62
%P 1-18
%K H03
%A C. Raymond Perrault
%A Barbara J. Grosz
%T Natural-Language Interfaces
%B BOOK62
%P 47-82
%K AI02 AA15 AT08
%A Hector J. Levesque
%T Knowledge Representation and Reasoning
%B BOOK62
%P 255-288
%K AI16 AT08
%A V. B. Robinson
%A A. U. Frank
%A M. A. Blaze
%T Expert Systems Applied to Problems in Geographic Information Systems -
Introduction, Review and Prospects
%J Computers, Environment and Urban Systems
%V 11
%N 4
%D 1986
%P 161-174
%A Michael W. Parks
%T Artificial Intelligence, Part 2: Expert Systems Fill in the Missing Link
%J Industrial Engineering
%V 19
%N 1
%D JAN 1987
%P 36-47
%K AT08 AI16
%A M. B. Gorzalczany
%T A Method For Inference in Approximate Reasoning Based on Interval Valued
Fuzzy Sets
%J Fuzzy Sets and Systems
%V 21
%N 1
%D JAN 1987
%P 1-18
%K O04
%A N. Y. Salmina
%A I. A. Khodashinskii
%T Methods and Means of Automatic Correction of Spelling Errors
%J Nauchno-tekhnicheskaya Informatsiya Seriya II - Informatsionnye Protessy
I Sistemy
%N 10
%D 1986
%P 25-28
%K AA15
%A J. Bartholdi, III
%A M. A. Trick
%T Stable Matching with Preferences Derived from a Psychological Model
%J Operations Research Letters
%V 5
%N 4
%D OCT 1986
%P 165-170
%K O04 AA11
%A K. K. Paliwal
%A V. Ramsubramanian
%T Vector Quantization in Speec Coding: A Review
%J Indian Journal of Technology
%V 24
%N 10
%D OCT 1986
%P 613-621
%K AI05
%A P. Leith
%T Fundamental Errors in Legal Logic Programming
%J The Computer Journal
%V 29
%N 6
%D DEC 1986
%P 545-552
%K AA24 AI10
%A R. A. Frost
%T Improving Output from Research (in the Domain of Knowledge Base Systems)
%J The Computer Journal
%V 29
%N 6
%P 572
%K AI01 AT19
%A P. Hajek
%T A Simple Dynamic Logic
%J Theoretical Computer Science
%V 46
%N 2-3
%D 1986
%P 239-260
%K AI10
%A C. H. Huang
%A C. Lengauer
%T The Automated Proof of a Trace Transformation for a Bitonic Sort
%J Theoretical Computer Science
%V 46
%N 2-3
%D 1986
%P 261-284
%K AI11 AA08
%A A. Dicky
%T An Algebraic and Algorithmic Method for Analysing Transition Systems
%J Theoretical Computer Science
%V 46
%N 2-3
%D 1986
%P 285-304
%A T. Hardinne
%A A. Levinne
%T Proof of Termination of the Rewriting System SUBST on CCL (Note)
%J Theoretical Computer Science
%V 46
%N 2-3
%D 1986
%P 305-312
%A Anton Bigelmaier
%T Profile of a Geometrical Knowledge Base for CAD Systems
%J Computers and Graphics
%V 10
%N 4
%D 1986
%P 297-306
%K AA05
%A Taha I. Elareef
%T Flavor System and Message Passing as Representation of Knowledge
for Solid Modeling in CAD Expert System
%J Computers and Graphics
%V 10
%N 4
%D 1986
%P 351-358
%K AA05 T01 AI01
%A J. Bajon
%A M. Cattoen
%A L. Llang
%T Identification of Multicoloured Objects Using a Vision Module
%B BOOK63
%P 21-30
%K AI06
%A H. A. Laird
%A K. R. Gilmour
%A D. McKeag
%T A Vision for Strain Analysis
%B BOOK63
%P 31-40
%K AI06
%A H. Vanbrussel
%A H. Belien
%T A High Resolution Tactile Sensor for Part Recognition
%B BOOK63
%P 49-60
%K AA26 AI07 AI06
------------------------------
End of AIList Digest
********************
∂07-Mar-87 0017 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #70
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 7 Mar 87 00:17:29 PST
Date: Fri 6 Mar 1987 22:08-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #70
To: AIList@SRI-STRIPE.ARPA
AIList Digest Saturday, 7 Mar 1987 Volume 5 : Issue 70
Today's Topics:
Policy - Hardware Discussions,
Query - Eliza, Doctor, Parry, Ractor, etc,
Applications - Analysis of Unknown Data & AI in Network Protocols
----------------------------------------------------------------------
Date: Thu, 5 Mar 87 12:24 EST
From: Phil Stanhope <Phil@JASPER.PALLADIAN.COM>
Subject: Policy - Hardware Discussions
>Date: Wed, 25 Feb 87 10:41:16 -0800
>From: Amnon Meyers <meyers@CIP.UCI.EDU>
>Subject: Hardware vs. AI
>
> I disagree with the notion that hardware problems have 'nothing to do with
> AI'. While discussions of LISP and PROLOG dialects are interesting, they
> appear to me to have no more relevance to 'AI' than do hardware issues.
> Likewise discussion of the operation and environment provided by LISP
> machines and other workstations. Likewise philosophical discussions of
> the mind. My point is that it is not useful to try to define AI too
> narrowly. There is a theory and practice of AI, and AILIST seems to stress
> the theory. It would be nice if the 'practice' were taken up somewhere
> as well.
>
> I can certainly understand that the AILIST is already overburdened, and
> that the moderator already does too much work (and a fine job as well).
> THOSE should be the reasons for excluding hardware issues, not arbitration
> about what is and is not relevant to AI.
I concur but would also like to add something that my father, who has never
worked in the fields of computer science or artificial intelligence said
to me awhile ago. He thought that AI should stand for the "Avoidance
of Ignorance," which implies a few things:
(1) intelligent behaviour, or the emulation thereof, helps one to
solve problems ...
(2) learning from mistakes, i.e., not remaining ignorant or naive
about problems and their solutions ...
(3) being able to inform other people/machines/users of ones knowledge
that they've gained through experience ...
If doing the above means learning more about:
(1) software engineering techniques, algorithms, and languages
(2) current research and its applications
(3) hardware that is currently available
(4) last but not least, the philosophical and epistemological
underpinnings of intelligence and behaviour,
then these are all valid topics of discussion that, given space and interest,
should be posted on this list.
Philip Stanhope
Palladian Software, Inc.
Cambridge, MA. 02142
[Agreed, but it is that "given space and interest" that is the
troublesome part. My own orientation is towards algorithms and
techniques. Software (e.g., expert system shells) is also
discussed in AIList since it is so closely tied to techniques.
The coupling to hardware is much looser, and there are already
several lists relating to workstations and particular hardware
systems. It seems logical to break off hardware as a separate
discussion topic so that only those who are interested need to
scan (and pay for) the traffic. The same may be true of other
topics currently carried by AIList, but there seems to be a
shortage of moderators. Most of the lists that have spun off
(e.g., NL-KR@Rochester, neuron%ti-csl.csnet@RELAY.CS.NET) seem
to be doing just fine, and I'm sure the readers appreciate the
increased ease of culling and saving the messages of interest
to them. -- KIL]
------------------------------
Date: 4 Mar 87 10:54:19 GMT
From: mcvax!ukc!its63b!dougie@seismo.css.gov (D Nisbet)
Subject: Eliza, Doctor, Parry, Ractor, etc, ...
I have heard about the various "chatty" programs which have been written
to imitate Psychiatrists (sp?), Doctors, Scribe's, etc, but have never
had the opportunity to play (play?!) use any of these programs. This kind
of software interests me a lot and would like to know if any of them
(or similar type) are freely available.
There is a book, I believe, titled "The Policeman's Beard is Half-Constructed"
which chronicles the 'works' of one of these programs (I can't remember which).
Does anyone know of its availability/publisher/price, and if there are any
other recommended books in this kind of area.
Any info appreciated. I will summarise any e-mail to me if there is
any interest.
[ .. I *know* this article is already in misc.misc. before anyone flames
me for bad netiquette. I've had trouble trying to post to the more
relevant ones. DJN ]
--
Dougie Nisbet
University of Edinburgh | <UUCP> ...seismo!mcvax!ukc!its63b!dougie
Medical Statistics Unit | <JANET> dougie@uk.ac.ed.its63b
Medical School
Teviot Place
Edinburgh
Scotland
------------------------------
Date: 6 Mar 87 00:20:25 GMT
From: sonia!cracraft@locus.ucla.edu (Stuart M. Cracraft)
Subject: Re: Eliza, Doctor, Parry, Ractor, etc, ...
In article <310@its63b.ed.ac.uk> dougie@its63b.ed.ac.uk (D Nisbet) writes:
>
>I have heard about the various "chatty" programs which have been written
>to imitate Psychiatrists (sp?), Doctors, Scribe's, etc, but have never
>had the opportunity to play (play?!) use any of these programs. This kind
>of software interests me a lot and would like to know if any of them
>(or similar type) are freely available.
>
Ractor is one of the funniest programs I've ever seen.
I ran it on a Macintosh over at the local software shop,
and it had me in stitches for almost an hour.
(The stiches were recently removed by GNU-EMACS's `doctor' mode.)
Stuart
------------------------------
Date: 5 Mar 87 12:40:36 GMT
From: dave@mimsy.umd.edu (Dave Stoffel)
Subject: analysis of unknown data
What systematic methods and techniques would you apply to the
following problem?
Determine the representation, organization, and content of a
"file" containing up to 156MB. There are no assumptions. The
methods and techniques applied must be automated (if not fully
automatic) and applicable to an unlimited supply of "files".
------------------------------
Date: 6 Mar 87 17:18:42 GMT
From: ihnp4!houxm!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: analysis of unknown data
In article <5681@mimsy.UUCP>, dave@mimsy.UUCP (Dave Stoffel) writes:
>
> What systematic methods and techniques would you apply to the
> following problem?
>
> Determine the representation, organization, and content of a
> "file" containing up to 156MB. There are no assumptions.
What systematic or unsystematic methods and techniques would you apply
to the following (seemingly easier) problem?
Determine the machine language of a computer with a 64K address space,
8K of RAM, and 48K of ROM containing an operating system and BASIC.
There is user documentation but no system documentation. The operating
system has undocumented capabilities for writing in RAM, reading any
byte, and starting execution at any byte in the address space. Ignore
secondary storage.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 6 Mar 87 16:40:49 GMT
From: ihnp4!houxm!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: analysis of unknown data
In article <5681@mimsy.UUCP>, dave@mimsy.UUCP (Dave Stoffel) writes:
> What systematic methods and techniques would you apply to the
> following problem?
>
> Determine the representation, organization, and content of a
> "file" containing up to 156MB. There are no assumptions....
I thought that would be impossible. Theoretically, I would think that
if there are no assumptions there can be no reasoning. In fact, there
are always tacit assumptions that even the author isn't aware of. If
I'm wrong, please post to the net, as I imagine there are others as
naive as I am.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 6 Mar 87 18:55:17 GMT
From: Robert Stanley <roberts%cognos%math.waterloo.edu@RELAY.CS.NET>
Subject: Re: AI in Network Protocols.
In article <8702280810.AA09316@cs-gw.D.UMN.EDU> ramarao@umn-cs.UUCP.UUCP writes:
>
>topic : EXPERT SYSTEMS OR AI IN NETWORKS AND PROTOCOLS
>
> I am trying to find out if there has been any attempt at
>applying AI techniques, AI languages to the field of network protocols.
>
There seems to be more than one question being asked here, and some fairly
fundamental confusion about so-called AI languages. It is perfectly
possible to create communications protocols of almost any kind using LISP
or PROLOG (or less well-known object-oriented languages such as NEON) provided
that there is a clean interface to the underlying system. The InterLisp-D
world on the Xerox 1100 series machines is a good example. However, this
has nothing to do with AI.
Is it possible to apply AI techniques in creating protocols? Yes, of course,
but most of the work that has come to my attention appears to have been
tackling the problems of network configuration, diagnostics, and routing. Why
would anyone want to to "use AI" to write a protocol? This is a hard-science
engineering issue, and one that is pretty well nailed shut for existing
protocols. The key to protocols has tended to be universal standardization, so
that many people can use them. One area that it would be interesting to see
AI applied is the smart "automatic" conversion between protocols.
I suppose the last interptretation of the question is: could a new protocol be
created which is based on AI techniques? Again, one supposes so, but such
things have a habit of being created only when there is a clearly apparent
need. I have not currently got any communications problems (telecommunications
problems, anyway) that can't be solved by applying existing protocols, and I
find that 10megabit LAN and 1.27megabit GAN are sufficiently wide bandwidths
for all my current needs.
Perhaps the original posting could be rephrased or expanded slightly, to open a
possibly interesting topic for discussion.
Robert Stanley
--
Robert Stanley decvax!utzoo!dciem!nrcaer!cognos!roberts
Voice: (613) 738-1440 (on EST) Tuesdays only
don't ask-----'
Cognos Inc., 3755 Riverside Drive, Ottawa, Ontario, K1G 3N3 CANADA
------------------------------
End of AIList Digest
********************
∂07-Mar-87 0207 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #71
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 7 Mar 87 02:07:45 PST
Date: Fri 6 Mar 1987 22:14-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #71
To: AIList@SRI-STRIPE.ARPA
AIList Digest Saturday, 7 Mar 1987 Volume 5 : Issue 71
Today's Topics:
News - IJCAI Research Excellence Award,
Expert Systems - Explanations,
Philosphy - Consciousness
----------------------------------------------------------------------
Date: Fri, 6 Mar 87 09:35:16 GMT
From: Alan Bundy <bundy%aiva.edinburgh.ac.uk@Cs.Ucl.AC.UK>
Subject: Announcement: IJCAI Research Excellence Award
THE 1987 IJCAI AWARD FOR RESEARCH EXCELLENCE
I regret to announce that the IJCAI-87 Awards Committee,
having considered all the candidates nominated for the Research
Excellence Award, have decided not to make an award.
The Award is given in recognition of an Artificial
Intelligence scientist who has carried out a program of research of
consistently high quality yielding several substantial results. The
first recipient of this award was John McCarthy in 1985. In the
opinion of the Awards Committee none of the nominated candidates
reached the high standard required. Several members of the Committee
afterwards suggested candidates that, in their opinion, did reach the
required standard, but who had not been nominated.
Nominations for the Award were invited from all in the
artificial intelligence international community. The Award Committee
was the union of the Programme, Conference and Advisory Committees of
IJCAI-87 and the Board of Trustees of IJCAII, with nominees excluded.
It is the sincere hope of all the Committee that, in future
years, a greater effort will be made by the artificial intelligence
community to nominate suitable candidates.
Alan Bundy
IJCAI-87 Conference Chairman
------------------------------
Date: Fri, 6 Mar 87 9:42:17 EST
From: Bruce Nevin <bnevin@cch.bbn.com>
Subject: Re: dear Abby
The bounds of a field are subject to redefinition. Many established
fields of today were interdisciplinary in the past. Thus, `when not to
step past them' is a complex matter.
Is it possible for users of an expert system to ask for information outside
its domain, and for it to answer naively, overstepping its proper bounds?
Has anyone worked with this level of meta-expertise? For instance, are there
systems that address multiple domains and select the appropriate one (or
combination) by deduction from interactions with the user?
Bruce Nevin
bn@cch.bbn.com
(This is my own personal communication, and in no way expresses or
implies anything about the opinions of my employer, its clients, etc.)
------------------------------
Date: Thu, 05 Mar 87 08:13:33 EST
From: sriram@ATHENA.MIT.EDU
Subject: Expert Systems and Explanations
Knowledge-based system technology is a programming methodology, which
facilitates the incorporation of "human or expert" knowledge. Hence, the
criterion that explanation facilitiy is a must for a knowledge based
system (or an expert system once you add the expert's knowledge) is
to be questioned.
In fact, our experience with building expert systems indicates that
the end user is least bothered about seeing things like:
Rule XX concluded that YY is true.
That stuff is good for debugging purposes. For the explanations
to be accepted by end users a more robust ENGLISH translation should be
provided (for example Swartout's work). Further, I feel the selling
point for any expert system will be the USER INTERFACE (with nice graphics).
Sriram
------------------------------
Date: 5 Mar 87 15:08:41 GMT
From: ihnp4!ihuxv!arrgh@ucbvax.Berkeley.EDU (Hill)
Subject: Explanations in expert systems
I have to put in my $0.02 into the expert systems discussion.
In real life, an expert system probably will not be used unless it possesses
a sound explanation facility. For most users, this does not mean merely
dumping rules or whatever, e.g., "the system is trying to satisfy rule-518", but
rather being able to turn the knowledge encoded in each unit of representation
into meaningful natural language.
An example may make this requirement clearer. One of the systems I have
built is the Michael Reese-IIT Stroke Consultant. This program is a large
neurology expert system designed to assist house physicians with the
diagnosis and treatment of stroke.
One of the treatments this system recommends is to prep the patient for surgery,
take him into the OR, remove the back of his head, and proceed to dig around
in the cerebellum for a hematoma.
Naturally enough, any reasonable physician will want to ask the machine "WHY?"
it recommends such a radical treatment, and expect an answer in a form that
a physician (not a computer scientist) can understand. The explanation system
will furnish: an English statement of the problem, e.g., "diagnosis is
hemorrhage into the cerebellum", and justifications for the treatment, e.g.,
"Evacuation of cerebellar hematoma is recommended because it greatly reduces
mortality when the following signs are present... Refer to the following
references [references to the neurology literature are cited]."
Lets take a more common case. Last spring, I built an expert system that
is designed to diagnose problems in candy wrapping machinery. In fact, if
you eat candy bars, you have almost certainly eaten candy wrapped on one of
these machines. The operators of these machines needed additional help
in diagnosing and troubleshooting problems in this new equipment, and we
built an expert system for this specific task.
Machine operators, unlike many of you, have absolutely no understanding of
production rules, and moreover, they are not interested. This system had to be
able to furnish the following explanations on line at all times: (1) how to
use system itself, (2) how the candy wrapping equipment was supposed to
operate (an on line tutorial on the machine), (3) how to answer the questions
the system was asking, e.g., where was IC 9 pin 7 on the Micro controller "A"
board, and (4) an explanation of the reasoning the system was using at that
time.
The moral of this rather long posting is that if you want to build expert
systems that will actually be used by real people you will need a good
explanation facility. While this is necessary, it is of course, not
sufficient. The knowledge engineer will need good debugging facilities
(something not provided on most tools today).
Hope this clears up some confusion.
--
Howard Hill, Ph.D.
------------------------------
Date: 6 Mar 87 23:01:45 GMT
From: cbatt!osu-eddie!tanner@ucbvax.Berkeley.EDU (Mike Tanner)
Subject: Re: Explanations in expert systems
In article <1800@ihuxv.ATT.COM> arrgh@ihuxv.ATT.COM (Hill) writes:
>
>In real life, an expert system probably will not be used unless it possesses
>a sound explanation facility. For most users, this does not mean merely
>dumping rules or whatever, e.g., "the system is trying to satisfy
>rule-518", but
>rather being able to turn the knowledge encoded in each unit of representation
>into meaningful natural language.
>
While I agree that spitting out rules is generally inadequate for
explanation I disagree that explanations *must* be in natural language.
For some kinds of explanation drawing and pointing is more useful.
"I think the wonkus is broken. Try replacing it."
"Wonkus!? What's that?"
"Take a look at the zweeble smasher. See this gizmo? That's the wonkus."
I'm not saying natural language is useless. But the above interaction
would have taken a lot more words without the picture. (With the
picture it might have needed no words at all. But I don't know what a
zweeble smasher is, much less how to draw one.) Sometimes a picture
really is worth a thousand words.
Keep in mind that when you talk about explanation as giving back rules
you're assuming expert systems are simple, flat rule-bases. This is
not necessarily true. If all your expert system knows is rules then:
(a) the system isn't doing anything interesting
OR
(b) you're actually using the rule language as a general
purpose programming language (because rules qua rules
don't give you the control features needed to navigate a
large knowledge base)
In case (a), there's no need to worry about real world usefulness. In
case (b), there should be no surprise that the rules themselves are
not informative explainers. No more than a listing of code would, in
general, be an explanation of a program.
-- mike
ARPA: tanner@ohio-state.arpa
UUCP: ...cbosgd!osu-eddie!tanner
------------------------------
Date: Thu, 5 Mar 87 09:24:51 pst
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Consciousness
Do not confuse consciousness with memory. Consciousness is not
a dualistic phenomena which your "speculation" (your word) tends
to imply. Consider that you did not mentioned subconscious (explicitly),
and but you did mention a dual unconscious.
Your comments on memory can also be refined by the cognitive
literature such as the distinction between recall, recognition, and the two
other types of memory tests I am forgetting. You also should make a
distinction between forgetting and interference (this is good).
My suggestion is for you to visit a nearby college or university and
get some literature on cognition (of which I am NOT a proponent).
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
Date: Fri, 06 Mar 87 12:01:36 n
From: DAVIS%EMBL.BITNET@wiscvm.wisc.edu
Subject: philosphy - consciousness
Could an unconscious machine be a good psychologist ?
*****************************************************
During the recent discussions on consciousness, Stevan Harnad has,
in the face of many claims about its role/origin, given us the demanding
question "well, if X is achieved *with* consciousness, why couldn't it
be accomplished *without* ?" (I hope I have understood this much correctly).
I think that many of those arguing with Harnad, myself included, have not
appreciated the full implications of this question - I wish now to give
one example of "an X" designed to at least point in the direction of an
answer to Harnad's question.
I hope that Stevan would accept, as a relatively axiomatic truth,
that for complex systems (eg; ourselves, future compsys'), interaction
and 'social development' are a *good thing*. That is to say, a system will
do better if it can interact with others (particularly of its kind), and
even more so if such interactions are capable of development towards
structures resembling 'societies'. We can justify this simply on the grounds
of efficiency, information exchange, and altruistically-based mutual survival
arrangements (helping each other out). I think that this is as true of computer
systems as human beings, although its curent implementation lacks any real
capacity for self-development.
Given this axiom - that complex systems will do better if they
interact - we may return to the hypothesis of Armstrong, recently raised
by M.Brilliant on the ailist, that the selective advantage conferred by
being conscious is connected with the ability to form developing social
systems. Harnad's question in this context (previously raised) is "why couldn't
an unconscious TTT-indistinguishable automaton accomplish the same thing ?".
So, lets look at this proposition. In order to accomplish meaningful
social interactions in a way that opens up such relations to future development
it is necessary to be able to predict - not, of course with 100% accuracy,
but to an extent that permits mutual acts to occur without running through
all the verbal preliminaries every time (conceptually similar to installing
preamble macros in TeX - a facetious statement!). Our ability to do this
is described in every day experience as 'understanding other people', and
permits us to avoid asking the boss for a raise when he is obviously in
a foul mood.
Rephrasing Harnad's question in an even more specific (and revealing)
manner, we now have " why couldn't an unconscious TTT-indistinguishable
automaton make similarly good predictions about other conscious objects ?".
We now have a useful fusion of biological, psychological and computer terms.
What sort of computer systems do we know of that are able to make predictions?
Although the exact definition is currently under debate ( see the list ),it
seems that we may subsume such systems under the general term "expert systems"-
used here in the most general sense of being an electronic device with access
to a knowledge base and some method of drawing conclusions given this knowledge
and a specific query or situation. I hope that Stevan will go along with
this as a possible description of his TTT-indistinguishable automaton.
So, could such a system 'understand' other people ? I believe that
it could not, for the following reasons. As sophisticated as this 'inference
engine' may be, its methods of reasoning must still, even in some high level
sense, be instantiated by its designers. Moreover, its knowledge base is
expandable only by observation of the world. To behave in a way that was
TTT-indistinguishable from a human in its capacity to 'understand' people,
this automaton would either (1) have to have a built in model of human
psychology or (2) be capable of collecting information that enabled it to
form its own model over time.
Here we have reached the kernel of the problem. Do we have, or are
we ever likely to have our own model of human psychology that is capable
of being implented on a computer ? Obviously, this is open to debate, but
I think not. The human approach to psychology seems to me to be incapable
of developing in a context which does not take the participation and prior
knowledge of the psychologist into consideration. As sophisticated as it
gets, I feel (though you're welcome to try and change my mind) that psychology
will always be like a dictionary - you look up the meaning of one word,
and find you have to know 30 others to understand what it means. Alternatively,
suppose that our fabulous machine were to try and 'figure it out fo itself'.
It will very soon run into a problem. When it asks someone why they did
something, it will recieve a reply which often involves a reference to an
'inner self' - a world, which as any good psychologist will tell you, has
its own rules, its own objects and its own interactions. The machine asks,
and asks, observes and observes - will it ever be able to put together a
picture of the 'inner life' of these conscious humans ?
And now we are at the end. Its obviously a statement of faith, but
I believe that what consciousness gives us is the ability to do just what
this machine cannot - to be a good psychologist. It makes this possible
by allowing us to *compare and contrast* our own behavior and 'inner self'
with other's behaviour - and hence to make the leap of understanding that
gives rise to the possibility of meaningful social interaction and development.
We have our *own* picture of 'inner life' (this is not meant to be mystical!)
and hence we have no need to seek to develop a model by inference. I do
not believe (now!) that an unconscious device could do the latter, and hence
I do not think that it is possible, even in principle, to build an unconscious
TTT-indistinguishable automaton that is capable of interacting with conscious
objects.
Thankyou, and good night.
Paul Davis
wetmail: embl, postfach 10.2209, 6900 heidelberg, west germany
netmail: davis@embl.bitnet
petmail: homing pigeons to .......
------------------------------
End of AIList Digest
********************
∂08-Mar-87 2348 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #72
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 8 Mar 87 23:48:41 PST
Date: Sun 8 Mar 1987 21:50-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #72
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 9 Mar 1987 Volume 5 : Issue 72
Today's Topics:
Seminars - TI AI Satellite Symposium &
Ping Pong Playing Robot (UPenn) &
Using Uncertainty to Solve Analogies (SMU) &
AI and Expert Systems PDS (Los Angeles ACM) &
Updating Databases with Incomplete Information (UPenn) &
Filter Model of Types for Flexible Programming (UPenn)
----------------------------------------------------------------------
Date: 4 Mar 87 17:06:57 EST
From: Peter.Capell@gnome.cs.cmu.edu
Subject: Seminar - TI AI Satellite Symposium
IEEE sponsors...
The TEXAS INSTRUMENT'S Third Artificial Intelligence Satellite Symposium
Wednesday, April 8, 1987 8:30 AM - 3:30 PM
Presenters:
Dr. Edward A. Feigenbaum - AI pioneer, author and lecturer, Stanford
University educator and past president of the American Association of
Artificial Intelligence.
Dr. George Heilmeier - Senior Vice President and Chief Technical Officer of
Texas Instruments, former Director of the Defense Advanced Research Projects
Agency (DARPA).
Dr. Alan C. Kay - Apple fellow, pioneer and key innovator in personal
computing and artificial intelligence. Invented "Smalltalk" computer
language and pioneered the use of icons.
Dr. Douglas B. Lenat - Principal Scientist for Microelectronics and Computer
Technology Corporation (MCC), pioner in machine learning through study of
the nature of heuristics.
Dr. Roger C. Schank - Professor of Computer Science and Psychology, Yale
University, and Chairman of Cognitive Systems, Inc. Pioneer in development
of computer models of memory and learning.
Dr. Herbert Schorr - Group Director of Products and Technology, IBM.
Responsible for the introduction of new advanced technology and
applications.
Dr. Harry R. Tennant - roundtable host, Senior Member Technical Staff and
Manager of AI Research in Texas Instruments Computer Science Laboratory.
Inventor of the concept of menu-based natural language understanding.
Abstract: (see February IEEE Spectrum for more details)
In four hours, Symposium III will examine the very latest developments,
applications and future potential - from diverse perspectives. It will
broaden the view of AI beyond knowledge-based systems to include natural
language processing and rapid prototyping of both AI and conventional
software.
Site (for CMU): The APICS "castle" in Wilmerding
Directions: Lee Ann Goettel: 825-3000
Fee: $6.00 (to cover doughnuts and lunch, Texas Instruments isn't charging
anything for the downlink)
Checks payable to: "APICS" or cash accepted
Registration and information: Call or write -
Attn: Peter Capell (Education Chair)
Center for Art and Technology
111 CFA
Carnegie Mellon University
Pittsburgh, PA 15213
X-8862
------------------------------
Date: Thu, 5 Mar 87 13:02:22 EST
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Ping Pong Playing Robot (UPenn)
Dissertation Defense
Computer and Information Science
University of Pennsylvania
Real Time Expert System to Control a Robot Ping Pong Player
R.L. Andersson
A real time "expert" control system has been designed
and forms the nucleus of a functioning robot ping pong
player.
Robot ping pong is underconstrained in the task
specification (hit the ball back), and heavily constrained
by the manipulator capabilities. The expert system must
integrate the sensor data, robot capabilities, and task
constraints to generate an acceptable plan of action. The
robot ping pong task demands that the planner anticipate
environmental changes occurring during planning and robot
motion. The inability to generate accurate, timely plans
even in the face of a capricious environment and limited
actuator performance would result in a nonfunctional system.
The program must continuously update the task plan as
new sensor data arrives, selecting appropriate modifications
to the existing plan, rather than treating each datum
independently. The difficult task and the stream of sensor
data result in an interesting system architecture. The
expert system operates in the symbolic and numeric domains,
with a blackboard to enable global optimization by local
agents. The architecture interrelates initial planning,
temporal updating, and exception handling for robustness.
A sensor and processing system produces three
dimensional position, velocity, and spin vectors plus a time
coordinate at 60 Hz. Novel processing algorithms and
careful attention to camera modeling were necessary to
obtain adequate accuracy.
A robot controller provides accurate, predictable
performance close to the envelope of robot capabilities
using modeling and feed-forward techniques. The controller
allows motions to be planned in the temporal domain
including specified terminal velocities, and supports smooth
changes to motions in progress.
Performance of the sensor subsystem, actuator and robot
controller, and expert system will be demonstrated. The
system successfully plays against both human and machine
opponents.
COMMITTEE: DR. LOU PAUL (ADVISOR)
DR. TIM FININ
DR. RUZENA BAJCSY
DR. ROD BROOKS (MIT)
DATE: MARCH 27, 1987
TIME: 10-12 NOON
LOCATION: 129 MOORE (FACULTY LOUNGE)
------------------------------
Date: Thu, 5 Mar 1987 17:34 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Seminar - Using Uncertainty to Solve Analogies (SMU)
Seminar Announcement, Southern Methodist University, Department
of Computer Science, Wednesday, Mar 11, 1987, 315 SIC, 1:30PM
USING UNCERTAINTY TO SOLVE ANALOGIES
David Rogers
Cognitive Science and Machine Intelligence Laboratory
University of Michigan
Abstract
Analogy involves the conceptual mapping of one situation
onto another, assigning correspondences between objects in each situation.
Uncertainty concerning the values of the objects' attributes or the
correct category of an object is commonly considered
a nuisance of little theoretical importance. In contrast,
in this approach uncertainty is central: all attributes
are to some degree uncertain, and category assignment of
objects is fluid. Thanks to this all-pervading uncertainty
(rather than dispite it), this architecture allows the system
to represent the multiple, often conflicting pressures that guide
our perceptions of situations in an analogy. Further, parallelism
without global control is intrinsic in this architecture. Control
is distributed throughout the system, at the level of its most
primitive objects -- entities -- each entity communicating with
a small number of other entities in the world.
I will present a domain that uses deceptively simple strings
of letters, followed by a description of the architecture used to
solve problems in this domain. Finally, some results from a program
written to implement these ideas will be presented.
------------------------------
Date: 6 Mar 87 06:40:39 PST (Friday)
From: Chapman.ESM8@Xerox.COM
Subject: Seminar - AI and Expert Systems PDS (Los Angeles ACM)
(I am not on this dl, so please direct any questions directly to me.
Thanks.)
LA ACM is sponsoring a Professional Development Seminar on Artificial
Intelligence and Expert Systems Saturday 18 April 9am-5pm at the LAX
Hilton, 5711 Century Blvd., Los Angeles. Registration begins at 8 am.
Lunch and course notes are included.
PROGRAM
Richard Korf: Introduction to AI & Expert Systems
Ron Citrenbaum: A Practical Approach to Expert System Development
Michael Dyer: Language and Thought: Symbolic and Subsymbolic
Bill Swartout: Making Expert Systems Explainable
Pat Langley: Overview of Problems and Techniques of Machine Learning
COST: before 31 March after 31 March
ACM member $80 $100
non-ACM $100 $120
full-time students*
$5 call Cheryl
*(with proof of full-time student status. Lunch & notes not included;
on a space-available basis only.)
Attendance is limited to 150.
TO REGISTER: send your name, company name, address, home and business
phone numbers, and cheque payable to LA ACM to: Cheryl Chapman, Xerox
Corp, 701 S. Aviation Blvd ESM8-003, El Segundo, CA 90245
(213)606-0639. (For statistics purposes, please mention this message.)
------------------------------
Date: Fri, 6 Mar 87 14:12:57 EST
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Updating Databases with Incomplete Information
(UPenn)
COLLOQUIUM
Computer and Information Science
University of Pennsylvania
UPDATING DATABASES WITH INCOMPLETE INFORMATION
Marianne Winslett
Stanford University Computer Science Department
Suppose one wishes to construct, use, and maintain a database of facts
about the real world, even though the state of that world is only
partially known. In the artificial intelligence domain, this problem
arises when an agent has a base set of beliefs that reflect partial
knowledge about the world, and then tries to incorporate new, possibly
contradictory knowledge into this set of beliefs. In the database
domain, one facet of this situation is the well-known null
values problem. We choose to represent such a database as a logical
theory, and view the models of the theory as representing possible
states of the world that are consistent with all known information.
How can new information be incorporated into the database? For
example, given the new information that ``b or c is true,'' how can one
get rid of all outdated information about b and c, add the new
information, and yet in the process not disturb any other information
in the database? In current-day database management systems, the
difficult and tedious burden of determining exactly what to add and
remove from the database is placed on the user. The goal of our
research was to relieve users of that burden, by equipping the
database management system with update algorithms that can
automatically determine what to add and remove from the database.
Under our approach, new information about the state of the world is
input to the database management system as a well-formed formula that
the state of the world is now known to satisfy. We have constructed
database update algorithms to interpret this update formula and
incorporate the new information represented by the formula into the
database without further assistance from the user. In this talk we
will show how to embed the incomplete database and the incoming
information in the language of mathematical logic, explain the
semantics of our update operators, and discuss the algorithms that
implement these operators.
March 9, 1987
Room 216 Moore
3:00 to 4:30
Refreshments Available
2:30 to 3:00
------------------------------
Date: Fri, 6 Mar 87 17:00:25 EST
From: dale@linc.cis.upenn.edu (Dale Miller)
Subject: Seminar - Filter Model of Types for Flexible Programming
(UPenn)
Math/CS Logic Seminar
Filter Model of Types for Flexible Programming
Atsushi Ohori
(ohori@cis.upenn.edu)
CIS Dept, Univ of Penn
16 March 1987
In this talk, I will present a mathematical model of data types for
flexible programming. This model can give precise semantics to (1)
polymorphic types, (2) type inheritance used in object-oriented
programming, (3) parametric types, (4) dependent types, (5) recursive
types and (6) higher-order types. I will also discuss some
connections to ``formulae-as-types'' principle.
We consider types as properties of values and define the semantics of
types as the sets of values having those properties. This idea leads
us to define types as principal filters in the underlying value domain
(in the sense of Scott.) Since principal filters are represented by
their minimal elements, types are represented by values. Simple type
constructors are then correspond to operations on the value domain.
The polymorphic type constructor corresponds to the least upper bound
operation. Parametric types and dependent types are represented by
functions on the value domain. Since the set of all principal filters
is isomorphic to the underlying value domain, the semantic space of
types is isomorphic to the value domain. This property allows us to
give semantics to arbitrarily higher-order types without any
inconsistencies.
[Talk will be in Math Seminar Room, 4th floor DRL.]
------------------------------
End of AIList Digest
********************
∂09-Mar-87 0257 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #73
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 9 Mar 87 02:57:06 PST
Date: Sun 8 Mar 1987 21:54-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #73
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 9 Mar 1987 Volume 5 : Issue 73
Today's Topics:
Administrivia - AI Hardware & Related Lists,
Games - Computer Chess Article in March 6 New Yorker,
Conferences - Volunteers for AAAI-87 &
ACL Europe Copenhagen Conference &
European Conference on Object-Oriented Programming 1987
----------------------------------------------------------------------
Date: Sat, 7 Mar 87 13:12:24 est
From: Arun Welch <welch@ohio-state.ARPA>
Subject: Re: Policy - AI Hardware
About 6 months ago, I offered to moderate a list for discussing AI
hardware, and asked that people who would be interested in such a
list send me their names and email addresses. I got all of 5 responses.
It didn't seem to me to be worth starting up a list for that small
an audience... The offer still stands, I guess, though I doubt if
I'm going to get more response....
...arun
----------------------------------------------------------------------------
Arun Welch
Lab for AI Research, Ohio State University
{ihnp4,cbosgd}!osu-eddie!welch
welch@ohio-state.{CSNET,ARPA}
welch@red.rutgers.edu (a guest account, but mail gets to me eventually)
------------------------------
Date: Sun 8 Mar 87 20:56:40-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Reply-to: AIList-Request@SRI-AI.ARPA
Subject: Related Lists
John Snyder has asked that I publish a list of AI-related discussion
lists. The following is taken from the welcome message that I
send to new AIList subscribers. I don't have a corresponding list
of Usenet interest groups.
Logic programming, theorem proving PROLOG@SUSHI.STANFORD.EDU
AI in education, user modeling AI-ED@SUMEX-AIM
Natural language, representation NL-KR@ROCHESTER
Information retrieval IRLIST%VPI.CSNET@CSNET-RELAY
Philosophy METAPHILOSOPHERS%MIT-OZ@MC.LCS.MIT.EDU
Psychology EPSYNET%UHUPVM1.BITNET@WISCVM
Neural networks neuron%ti-csl.csnet@CSNET-RELAY
Vision algorithms, perception VISION-LIST@ADS
Color and vision research CVNET%YORKVM1@WISCVM.WISC.EDU
Programming languages, interfaces SOFT-ENG@MIT-XX
Common Lisp COMMON-LISP@SU-AI
Common Lisp windows CL-WINDOWS@SAIL.STANFORD.EDU
X windows XPERT@ATHENA.MIT.EDU
Scheme (a Lisp dialect) SCHEME@MC.LCS.MIT.EDU
XLisp INFO-XLISP@SPICE.CS.CMU.EDU
Workstations WORKS@RUTGERS
Symbolics products SLUG@UTEXAS-20
Xerox Lisp machines, Interlisp INFO-1100@SUMEX-AIM
BUG-1100@SUMEX-AIM
Texas Instruments workstations INFO-TI-EXPLORER@SUMEX-AIM
BUG-TI-EXPLORER@SUMEX-AIM
Parallel symbolic computing PARSYM@SUMEX-AIM
Symbolic math NET.MATH.SYMBOLIC (USENET)
Arpanet list policy LLP@MC.LCS.MIT.EDU
The list moderator can usually be reached by appending -REQUEST to the
list name. For a full list of lists and their moderators contact
Zellich@SRI-NIC.
-- Ken Laws
------------------------------
Date: 07-Mar-1987 1749
From: minow%thundr.DEC@decwrl.DEC.COM (Martin Minow THUNDR::MINOW
ML3-5/U26 223-9922)
Subject: Computer Chess article in March 6 New Yorkr
An interesting article in the current (on newstands till next Tuesday
or so) New Yorker on the Fifth World Computer Chess Championship interviews
many of the participants (Hans Berliner and Ken Thompson, for example)
and touches on many of the "intelligence" and "conscious" issues.
The article was written by Brad Leithauser.
Martin Minow
minow%thundr.dec@decwrl.dec.com
------------------------------
Date: Sat, 7 Mar 87 12:32:13 PST
From: feifer@CS.UCLA.EDU
Reply-to: feifer@CS.UCLA.EDU (Richard Feifer)
Subject: Conference - Volunteers for AAAI-87
ANNOUNCEMENT:
Student Volunteers Needed for
Artificial Intelligence Conference
AAAI-87
AAAI-87 (American Association on Artificial Intelligence) will
be held July 13-17, 1987 in beautiful Seattle, Washington.
Student volunteers are needed to help with local arrangements
and staffing of the conference. To be eligible for a Volunteer
position, an individual must be an undergraduate or graduate
student in any field at any college or university.
This is an excellent opportunity for students to participate in
the conference. Volunteers receive FREE registration at AAAI-87,
conference proceedings, "STAFF" T-shirt, and are invited to the
volunteer party. More importantly, by participating as a volunteer,
you become more involved and meet students and researchers with
similar interests.
Volunteer responsibilities are varied, including conference
preparation, registration, staffing of sessions and tutorials
and organizational tasks. Each volunteer will be assigned
twelve (12) hours.
If you are interested in participating in AAAI-87 as a Student
Volunteer, apply by sending the following information:
Name
Electronic Mail Address
USMail Address
Telephone Number(s)
Dates Available
Student Affiliation
Advisor's Name
to:
feifer@locus.ucla.edu
or
Richard Feifer
UCLA
Center for the Study of Evaluation
145 Moore Hall
Los Angeles, California 90024
Thanks, and I hope you join us this year!
Richard Feifer
Student Volunteer Coordinator
AAAI-87 Staff
------------------------------
Date: Sun, 8 Mar 87 18:04:03 est
From: walker@flash.bellcore.com (Don Walker)
Subject: Conference - ACL Europe Copenhagen Conference, 1-3 April 1987
ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: EUROPEAN CHAPTER
Third Conference and General Meeting
April 1-3 1987, University of Copenhagen
Due to communication problems, the first registration circular announcing
the Conference did not get sent to most ACL members. The attached
information contains the programme, which was just released, together
with information on registration (which because of the short time must
now be down at the meeting) and hotels. For further information,
contact: Bente Maegaard (ACL)
IAML
Njalsgade 96
DK-2300 Kobenhavn S, DENMARK
45-1-542 211, x2478
Bente_Maegaard_eurotra-dk%eurokom@mit-multics.arpa
The conference will be held at the University of Copenhagen (Amager),
Njalsgade 80, DK-2300 Copenhagen S, DENMARK, which is about 10 minutes
by bus from the center of the city.
REGISTRATION will take place on March 31 from 17 p.m. to 21 p.m., at
the Institute of Applied and Mathematical Linguistics (Institut for
Anvendt og Matematisk Lingvistik=IAML), University of Copenhagen/Amager,
room 6.3.65 (stairway 6, third floor, room 65). The registration room
will be easily found if you enter the university by the main entrance
(Njalsgade 80) and follow the signs. It will also be possible to
register on April 1st from 8.30 a.m. to 9.30 a.m. or, if necessary,
during the conference.
[... I'll let the NL-KR list carry the full provisional programme and
hotel details. Or reply to the message author for a copy. -- KIL]
------------------------------
Date: Tue, 3 Mar 87 12:51 N
From: DESMEDT%HNYKUN52.BITNET@wiscvm.wisc.edu
Subject: Conference - ECOOP 1987
Here is an Advance Program for the European Conference on Object Oriented
programming which was sent to me by Henry Lieberman (Henry@ai.ai.mit.edu):
Advance Program ECOOP'87
June 15-17
Paris
Palais des Congres
Monday, June 15
2pm-3pm
Invited Lecture
Adele Goldberg (Xerox PARC & ParcPlace Systems)
Session-1 METHODOLOGY Chairman: Luc Steels (Brussels University)
3:00-3:30
Delta Talk: An Empirical and Aesthetical Motivated Simplification
of the Smalltalk-80 Language.
Alan Borning (University of Washington) & Tim O'Shea (Xerox PARC)
3:30-4:00
Reversible Object-Oriented Interpreters
Henry Lieberman (MIT)
4:30-5:00
Using Types and Inheritance in Object-Oriented Languages
Daniel C. Halbert (DEC Hudson) & Patrick D. O'Brien (DEC Hudson)
5:00-5:30
Inheritance Mechanisms in Object-Oriented Concurrent Languages
Jean-Pierre Briot (TIT,LITP) & Akinori Yonezawa (TIT)
5:50-6:00
On Including Part Hierarchies in Object-Oriented Languages,
with an implementation in Smalltalk
Edwin Blake (Queen Mary College) & Steve Cook (Queen Mary College)
Tuesday, June 16
9:00-10:00
What is Object Oriented Programming?
Bjarne Stroustrup (AT&T,Bell)
Session-2: IMPLEMENTATION Chairman: J.F. Perrot (University of Paris 6)
10:00-10:30
Object Representation of Scope During Translation
S. C. Dewhurst (AT&T)
11:00-11:30
Dynamic Grouping in an Object Oriented Virtual Memory Hierarchy
Ifor Williams, Mario Wolczko & Trevor Hopkins (University of Manchester)
11:30-12:00
Traveler: The Apiary Observatory
Carl Manning (MIT)
2:00-3:00
Strenghts and Weaknesses of Object Oriented Programming Paradigm
Carl Hewitt (MIT)
Session-3: THEORY Chairman: H. Stoyan (Konstanz University)
3:00-3:30
Classification of Actions or Inheritance also for methods
Bent Krinstensen (University of Alborg), Ole Madsen (University of Alborg),
Birger Moller-Pedersen (Norwegien Computing Center) & Kristen Nyggard
(University of Oslo)
3:30-4:00
Semantics of Smalltalk-80
Mario Wolczko (University of Manchester)
Session-4: INTERFACE Chairman: P. Greussay (University of Paris-8)
4:30-5:00
The Construction of User Interfaces and the Object Paradigm
Joelle Coutaz (IMAG)
5:00-5:30
The ZOO Metasystem: A Direct-Manipulation Interface to Object-Oriented
Knowledge Bases.
Wolf Riekert (University of Stuttgart)
5:30-6:00
The Filter Browser. Defining Interfaces Graphically
Raimund Ege (Oregon Graduate Center), David Maier (Oregon Graduate Center)
and Alan Borning (University of Washington)
Wednesday, June 17
Session-5: DISCUSSION-PAPERS (9:00-10:00) see end of this message
Session-6: LANGUAGE IMPLEMENTATION Chairman: G. ATTARDI (DELPHI)
10:30-11:00
Concurrency Features for the Treillis/Owl Language
J. Moss & W. Kohler (University of Massachusetts)
11:00-11:30
Objects as Communicating Prolog units
Paola Mello & Antonio Natali (University of Bologna)
11:30-12:00
An Object Modeling Technique for Conceptual Design
M. Loomis, A. Shah & J. Rumbaugh (Calma Compagny)
2:00-3:00
Invited lecture
Kristen Nygaard (University of Oslo)
Session-7: SIMULATION Chairman: J. Vaucher (University of Montreal)
3:00-3:30
A Modeller's Workbench: Experiments in Object Oriented Simulation Programming
W. Kreutzer (University of Canterbury)
3:30-4:00
Behavioral Simulation Based On Knowledge Objects
Takeo Maruichi, Tesuya Uchiki and Mario Tokoro (Keio University)
Session-8: INHERITANCE Chairman: Peter Wegner (Brown University)
4:30-5:00
Conformance, Genericity, Inheritance and Enhancement
Chris Horn (Trinity College Dublin)
5:00-5:30
Inheritance and Subtyping in a Parallel Object Oriented Language
Pierre America (Philips Research Lab)
5:30-6:00
On Some Algorithms for Multiple Inheritance In Object Oriented Programming
R. Ducourneau (SEMA-METRA) & M. Habib (LIB)
**************
Reserve Papers
**************
Principles for Programming Concurrent Object-Oriented Systems
Gul Agha (MIT)
FORK: A System for Object - and Rule - Oriented Programming
C. Beckstein, G. Goerz and M. Tielemann (University of Erlangen-Nurnberg)
Overview of a Parallel Object Oriented Language CLIX
Jin Hur and Kilnan Chon (Korea Advanced Institute of Science and Technology)
*******************************************
Discussions Papers
Wednesday, June 17
Chairman P. GLOES (University of Compiegne)
*******************************************
9:00-9:10
GALOPIN: un systeme oriente objet pour le demarrage automatique des
unites chimiques
R. Loubeyre (Rhone-Poulenc) & C. Melin (Universite de Compiegne)
9:10-9:20
Conception d'une base de connaissance orientee objet pour l'EAO
de la geometrie
Eugene Chouraqui & Carlo Inghilterra (CNRS Marseille)
9:20-9:30
Microprogramming in Object Oriented Style: An experience
with a Lisp co-processor
Jean-Jacques Codani & Louis Audoire (GIPSI-SM90 INRIA)
9:30-9:40
An Application of Object-Oriented Programming to Petri Net Models of
Discrete Event-Driven Simulation
Cydney Minkowitz and Peter Henderson (University of Stirling)
9:40-9:50
A Novel Rule Based Facility For Smalltalk
Wilf LaLonde (Carleton University - Canada)
9:50-10:00
Integrating Prolog in the Smalltalk/V Environment
Mike Teng (Digitalk Inc)
------------------------------
End of AIList Digest
********************
∂09-Mar-87 0501 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #74
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 9 Mar 87 05:01:07 PST
Date: Sun 8 Mar 1987 21:59-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #74
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 9 Mar 1987 Volume 5 : Issue 74
Today's Topics:
Query - Checking Rule-Based Expert Systems &
Public-Domain Expert System Request,
Source - Eliza, Doctor, Parry, Ractor, etc,
Expert Systems - Explanation & Analysis of Unknown Data,
Philosophy - Self-Recursive Functions == Consciousness
----------------------------------------------------------------------
Date: Sun, 8 Mar 87 9:31:01 WET
From: "G. Joly" (Birkbeck) <gjoly@Cs.Ucl.AC.UK>
Subject: Checking Rule-Based Expert Systems (Info Request).
We are at the start of a project which is examining the area
of validation and verification of rule-based expert systems.
CHECK [1] and ONCOCIN [2] are the two major systems of which
we are aware. Are there any others? How isomorphic are rule-based
systems; can these and other techniques be applied in general?
Are any other (e.g. database) techniques applicable?
Thanks in advance for any pointers and information,
Gordon Joly,
Dept. of Computer Science,
Birkbeck College,
University of London.
ARPA: gjoly@cs.ucl.ac.uk
BITNET: UBACW59%uk.ac.bbk.cu@AC.UK
UUCP: ...{seismo,decvax,ucbvax}!mcvax!ukc!uk.ac.bbk.cs!gordon
[1] T.A.Nguyen, W.A.Perkins, T.J.Laffey and D.Pecora, "Checking
an Expert Systems Knowledge Base for Consistency and Completeness".,
IJCAI 1985, pp 375-378.
[2] M.Suwa, C.Scott and E.H.Shortliffe, "An Approach to Verifying
Completeness and Consistency in a Rule-Based Expert System",
The AI Magazine, Fall 1982, pp 16-21.
------------------------------
Date: 6 Mar 87 12:20:04 GMT
From: ulysses!sfmag!sfsup!saal@ucbvax.Berkeley.EDU (S.Saal)
Subject: Expert System Request
I am trying to set up a seminar to review expert systems. Is
there any public domain expert systems available that I could
get my hands on so that we can walk through the source code?
Beggers can't be choosers so I really don't care what language
it is in. All I want is source (commented code would be nicer,
though :-).
Please reply by E-MAIL to
Sam Saal ..!attunix!sfbai!saal
------------------------------
Date: 6 Mar 87 16:00:12 GMT
From: copp@bellcore.com (David H. Copp)
Subject: Re: Eliza, Doctor, Parry, Ractor, etc, ...
"The Policeman's Beard is Half Contructed,"
authored by Racter (with a little help from
William Chamberlain), Warner Books Inc., 666 Fifth Avenue,
New York, NY 10103, USA. First printing Oct 1984.
This is a new publisher. You may have to write directly to
Warner Books, P.O. Box 690, New York, NY 10019, USA.
They ask for a check for the list price ($9.95) plus
$0.75 per order and $0.50 per copy.
This is not a technical book. It tells you very little about
Racter. It is an amusing addition to your coffee table.
Martin Gardner (or was it Hofstedder?) devoted two or
three pages to Racter about three years ago (Scientific American).
Good article. The program itself can be purchased, IBM PC format,
for about $75--see the SA article.)
--
David H. Copp
(201) 829-4337
bellcore!copp
------------------------------
Date: 6 Mar 87 21:58:32 GMT
From: jennifer!lyang@sun.com (Larry Yang)
Subject: Re: dear abby....
In article <886@rpics.RPI.EDU> yerazuws@rpics.RPI.EDU (Crah) writes:
>In article <178@arcsun.UUCP>, roy@arcsun.UUCP (Roy Masrani) writes:
>>
>> Dear Abby. My friends are shunning me because i think that to call
>> a program an "expert system" it must be able to explain its decisions.
>> "The system must be able to show its line of reasoning", I cry. They
>> say "Forget it, Roy... an expert system need only make decisions that
>> equal human experts. An explanation facility is optional". Who's
>> right?
In medical decision systems, the ability to explain the decision
is very important. I believe that most medical 'expert' systems
(MYCIN and INTERNIST come to mind) have a 'why' or 'explain'
feature. My understanding is that these systems were to
have applications in teaching, and such a feature would help
medical students understand the medical decision-making process.
But beyond the educational application, it seems that an 'expert'
system will gain greater acceptance if it had an 'explain'
feature. Would you accept a solution that some black-box,
electronic oracle offered you, without any why or wherefore?
Imagine two doctors diagnosing a condition. Suppose one were
asking the other for his/her advice. Would the first doctor
accept just a diagnosis from the second, or would he/she also
ask for an explanation?
================================================================================
--Larry Yang [lyang@sun.com,{backbone}!sun!lyang]| A REAL _|> /\ |
Sun Microsystems, Inc., Mountain View, CA | signature | | | /-\ |-\ /-\
"Build a system that even a fool can use and | <|_/ \_| \_/\| |_\_|
only a fool will want to use it." | _/ _/
------------------------------
Date: 5 Mar 87 17:39:06 GMT
From: mcvax!ukc!cheviot!rosa@seismo.css.gov ( U of Dundee)
Subject: Re: dear abby....
Dear Abby,
My problem is that I think I may be schizophrenic..
When I say "expert system" I mean a program which advises
or searches for solutions in a restricted domain of data.
Since I am British this program would be written at first
in prolog. When others use the phrase "Expert System"
they mean some kind of all singing, all dancing REAL WORLD
EXPERT ... a human being not a program....
I have the same mismatch problem with the words "knowledge based",
"knowledge aquisition", "intelligent", and most
importantly with explanations...
If a friend wants an "expert system" to help diagnose faults
in cooking(say), I write a program to choose oven settings
and help out with sensible advice for drooping souffles.
When they ask for "the reason why" should I have written
a huge explanation database instead of relying on the
programming language internal logic control???????
Abby please help me decide if I should use a different,
more technical phrase like advice giving database program
instead of the confusing and misunderstood "expert system"
or join a less demanding profession like brain surgery?
yrs, a sad hacker.
------------------------------
Date: Sat, 7 Mar 87 17:23:29 est
From: zs01#@andrew.cmu.edu (Zalman Stern)
Subject: Re: Dear Abby, Analysis of unknown data.
Dear Abby:
Explanation of results in an expert system should be viewed as a method of
communication between intelligent entities. Conventional groups of human
experts tend to fail very badly when nobody tells anybody else what is going
on. If you expect anything different to happen with artificial experts, you
are very disillusioned. I think explanation facillities must be designed into
the standard interface a program uses to communicate with humans and other
expert systems. Of course teling too much tends to bore people also... Why
not view AI as a chance to fix some of the bugs in human communication?
Analysis of unknown data:
I guess the idea here is to come up with an expert version of the UNIX file
program. (file is a program which is executed like "file core" and it tells
you "core: core file from 'loseprog'") The file program is written
using very ad hoc techniques. It knows about all the magic numbers commonly
used in a UNIX system, about keywords for common languages, patterns that
occur in various kinds of text... As you can guess, it assumes a lot.
One of the first things to realize is that there are files for which your
system is not going to be able to come up with any useful information. Try
feeding it 156MB of perfectly random numbers for example. One must also
figure out what kind of explanations this system is going to give. In the
organization category do you want explanations of the form "The file is
columnized data." or "This file is in the proper format of a doctoral
disertation in Computer Science at Carnegie Mellon University?"
Once the program has figured out what the file is, it can easily extract the
"representation, organization, and content" of the file using information
from its knowledge base. So the problem has become one of designing a pattern
matcher, and coming up with a knowledge base that knows about all kinds of
files. Optionally, the program could try and deduce all the information
desired from the file, but I think that would be much more difficult to do.
Here is one way to approach this problem:
Design a number of representations of a file. Examples of these are:
- ASCII text in line format. (i.e. like your favorite editor does
it).
- A numerical dump of the file.
Also, there are many formats specific to certain programs. For these, the
representation is derived from firing up the appropriate program on the file.
For example, if you are trying to classify a system executable, you will want
to run the system debugger (or disassembler) on the file. There is an
assumption here that files don't exist in a vacuum. If they did, they would
be useless.
Now that this is done, you are ready to start building a knowledge base. To
do this you want to have a driver program that allows an expert to examine
files and enter information into the system. The driver progam will need
enoug "intelligence" to ask the expert why he did certain things. Of course
you can have humans analyze the experts answers and encode them
appropriately. Then just get a bunch of experts, and a large file system and
let them hack at it...
I think this may even be doable, but I doubt it would be worthwhile.
Have I made too many assumptions? Is this general enough? Is this what you
consider automated?
Sincerely,
Zalman Stern
ARPA: zs01#@andrew.cmu.edu
Disclaimer: I am not involved in any kind of AI research and never have been.
------------------------------
Date: Sun, 8 Mar 87 00:30:56 EST
From: mckee%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: self-recursive functions == consciousness
While trying to come up with some "characteristically lisp" code
to benchmark different implementations with (since we didn't have
R.Gabriel's collection at the time), the following argument occurred
to me:
Suppose one has two large, intelligent systems, both of which
can speak English, know about baseball and politics, and can accurately
report on their past experiences, yet one is conscious and the other
is not. If we take away language, baseball, politics, and the past,
we are left with two *content-free* mental systems, i.e. pure structure.
One structure exhibits the properties of consciousness, while the other
does not. What are the differences in structure that cause the differences
in properties? Can we write them in Lisp? Since we have by hypothesis
removed all content from the systems, we are left with no data, but
pure control flow, i.e. an unnamed lambda expression.
Now the intuitive essence of consciousness seems to be self-
reference. Without self-reference we have only unidirectional
entropy-processing, which is done by everything. Can one write a
content-free self-referential function, which gets its work done
by pure control flow and lambda-binding? How about:
(LAMBDA (self n) (COND ((ZEROP n) 0)
(T (+ n
(self self (1- n))
))))
The function this expresses is very simple because what's important
is how it's expressed, not what it does. In order to work, it has
to be called with itself and an integer as arguments; it then computes
the sum of the first n integers. But it can do this without touching
the static part of its environment, not by define's, defun's, set's,
or anything else. (It does require a quote to get it started.)
It is completely dynamic, as pure consciousness seems to be.
The key feature of self-recursive functions like this appears
to be the applicative loop that occurs when the function is a lambda-
expression that (1) has been given itself as an argument and (2) calls
itself (i.e. its arg) recursively using the self-arg in the same
argument position. A general pattern for this looks like:
(LAMBDA (A1 ... Ai ... An)
... (Ai Bi ... Ai ... Bn) ...)
where any corresponding Aj and Bj pair may be identical, but at least
one Bj must be different from its Aj or an infinite recursion will
result. (There are other conditions on how they have to differ which
are irrelevant as long as they guarantee termination.) Again, this
only works if it is initiated with itself as argument Ai.
It seems to me that this pattern captures the only aspect
of consciousness that is writable in lambda calculus and essential
for consciousness while not essential for not-necessarily-conscious
activities such as speech, memory, vision or problem-solving.
The fact that it's a pattern explains a lot of the trouble people
have with consciousness, since its elements could be broken apart,
scattered, renamed, and passed through other functions before
being resurrected as one funcall among many. (In a system as complex
as a human mind, make that "many, many, many, many"...)
A function that recognizes self-recursion in an arbitrary
function definition is not small even in a tiny language, since
it has to be able to track the components of the critical argument
through potential decomposition and reconstruction, quoting, lambda-
binding and other tortures. The recognition function for a real AI
language like common lisp will be even bigger, since it will have to
deal with macros, reader modifications and STRING/MAKE-SYMBOL pairs.
It may even turn out to not be a computable function, for all I can tell.
It seems to me that there are four classes of reasonable
objections to this claim that self-recursion is the essence of
consciousness:
1. "Consciousness is an ill-posed problem" in the sense that Tomaso
Poggio has been talking about in vision. There's no unitary,
simple, elegant way of expressing what we're talking about.
I'm unhappy with this because it means we'll never "understand"
consciousness, though we may be able to construct large
more-or-less-convincing systems that appear to act as if they
were conscious.
2. "Consciousness cannot be expressed in pure lisp." A strong
claim, since accepting it requires modification of Church's
Thesis, and claiming that there are material objects that
{_ perform computations that cannot be expressed in the lambda
calculus. I'm not entirely opposed to this, since one can
envision massively parallel systems becoming so large that
it might be useful to start thinking in terms of "density of
computation" and taking the limit as the density approaches
continuity in the same way the rational numbers approach
the reals. Physically, you run into quantum limitations first,
but continuous computation may be theoretically interesting.
(No, I don't think this is the same as analog computation,
but I can't explain why.)
3. "Consciousness can be expressed in lisp, but the pattern
shown here isn't it." Please show us the correct answer.
But remember Occam's razor: in science, small is beautiful.
4. "Consciousness is an illusion. It can't be expressed in lisp
because it doesn't exist." This is my favorite. Steven Harnad's
colleague Julian Jaynes has written a fascinating book which
argues that consciousness first appeared on the planet less
than 3000 years ago. I see no reason why consciousness couldn't
vanish once we learn how to avoid spending valuable mental
resources on introspection. It of course remains to be explained
why consciousness has been such a powerful illusion.
I apologize if I'm rediscovering ground already covered in this forum;
I've only been reading the AIlist for a few months. This is about
all I have to say on the subject, so if the moderator decides to
distribute this, I hope he doesn't mind if I request that responses
be sent to the net, not to me.
"...a region of sight, of sound, of mind.
Submitted for your consideration, from"
- George McKee
College of Computer Science
Northeastern University
------------------------------
End of AIList Digest
********************
∂12-Mar-87 0306 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #75
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 12 Mar 87 03:06:46 PST
Date: Thu 12 Mar 1987 00:51-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #75
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 12 Mar 1987 Volume 5 : Issue 75
Today's Topics:
Seminars - Artificial and Natural Intelligence (UCB) &
Fluid Concepts and Creative Analogies (UMich) &
Representational Alignment (UCB) &
Induction, Knowledge, and Expert Systems (GMR) &
Search and Reasoning in AI (CMU) &
Multilisp (CMU)
----------------------------------------------------------------------
Date: Mon, 9 Mar 87 11:22:39 PST
From: admin%cogsci.Berkeley.EDU@berkeley.edu (Cognitive Science Program)
Subject: Seminar - Artificial and Natural Intelligence (UCB)
Berkeley Cognitive Science Program Presents a Special IDS 237B Seminar
Time: Thursday, March 19, 11:00-12:30
Place: Building T-4, Room 200
Speaker: Klaus Fuchs-Kittowski, Dept. of Theory and Organization of Science,
Humboldt University, Berlin, GDR
Visiting Professor, John Hopkins University
Chairman, Working Group 1 of TC9 of IFIP Computers
Title: ``Philosophical Views and Methodological Assumptions Regarding
the Relationships between Artificial and Natural Intelligence"
ABSTRACT
Computers are general agents of change in the information revo-
lution in the same way that Watt's steam engine revolutionized
industry. The problem of defining the relationship between
human and artificial intelligence is central to the problem of
applying computer power in a humane way in society. Resolution
of these questions requires application of multidisciplinary
approaches to what has traditionally been a mechanistic
approach. The multidisciplinary approach requires understanding
the unity of the syntax, semantics, and effects of information.
------------------------------
Date: Sun, 8 Mar 87 17:25:12 est
From: mm@farg.umich.edu (Melanie Mitchell)
Subject: Seminar - Fluid Concepts and Creative Analogies (UMich)
WEEKLY AI SEMINAR, UNIVERSITY OF MICHIGAN, ANN ARBOR
SPEAKER: Melanie Mitchell, EECS Dept., University of Michigan
DATE: Tuesday, March 17
TIME: 4:30 pm
PLACE: 1303 EECS Building (North Campus)
TITLE: "Fluid Concepts and Creative Analogies:
A Theory and its Computer Implementation"
Abstract
This talk is based on research done by Douglas R. Hofstadter,
Melanie Mitchell, and Robert M. French. We describe the principles
of Copycat, a computer model of how humans use concepts fluidly in
order to create analogies. Our model is centered on the Slipnet, a
network of overlapping concepts whose shapes are determined dynamically
by the situations faced by the program. Reciprocally, the state of the
Slipnet controls how Copycat perceives situations. The heart of what
Copycat does, given two situations, is to produce a worlds-mapping: a
coarse-grained mental correspondence between the situations, involving
two interdependent and mutually consistent facets: an object-to-object
mapping realized in structures called bridges, and a concept-to-concept
mapping realized in structures called pylons. Each pylon expresses a
so-called conceptual slippage, borrowed from the slipnet. Taken together,
the slippages constitute a recipe for translating actions in one situation
into their analogues in the other. Through the "coattails effect",
slippages can induce closely related slippages, allowing deeper and more
subtle analogies to be produced than would otherwise be possible.
For copies of a paper describing this research, send messages to
mm@farg.umich.EDU
------------------------------
Date: Wed, 11 Mar 87 10:36:25 PST
From: admin%cogsci.Berkeley.EDU@berkeley.edu (Cognitive Science
Program)
Subject: Seminar - Representational Alignment (UCB)
SESAME Colloquium 10/16
Jeff Shrager
Xerox Palo Alto Research Center
Monday 16 March 1987
2515 Tolman Hall
4:00 pm
Abstract
Analogy and conceptual combination deal with more than one knowledge
structure. Only structures which are based on the same terms and
relations can generally be combined by these mechanisms. In order to
make conceptual combination work smoothly with large representationally
heterogeneous knowledge bases, I am working toward automated high-level
to high-level representational alignment. My approach is based upon the
intuitive model of how two speakers would communicate if they had
incompatible understandings of some domain. The process involves
"grounding" terms and relations in the high-level representations into
common lower-level representations and then constructing constraints
based upon the structure of this grounding trace. This talk will focus
on the cognitive motivations for grounding and ground-directed alignment
and on the cognitive implications of the requirements imposed on mental
models by ground-directed alignment. Grounding highlights the
difference in the content terms of mental models: grounded terms versus
ungrounded terms, which have a counterpart in the difference between
empirical and derived terms in qualitative mental models. I show how
the grounding of such models into animations gives us a concrete handle
on the relationship between imagery and the symbolic processes.
------------------------------
Date: Wed, 11 Mar 87 15:55 EST
From: "R. Uthurusamy" <SAMY%gmr.com@RELAY.CS.NET>
Subject: Seminar - Induction, Knowledge, and Expert Systems (GMR)
Seminar at the General Motors Research Laboratories in Warren, Michigan.
Friday, March 20, 1987 at 10 a.m.
INDUCTION, KNOWLEDGE, and EXPERT SYSTEMS
J. ROSS QUINLAN
Head, School of Computing Sciences
New South Wales Institute of Technology, Sydney, Australia
ABSTRACT
This general talk examines inductive inference as a knowledge acquisition
methodology, both from the perspective of the performance characteristics
of the knowledge so acquired and its intelligibility. A relatively simple
class of induction methods that generate decision trees for classification
tasks is outlined and illustrated. A case study in which this approach was
used to generate diagnostic knowledge in the domain of thyroid assays is
presented, and the performance of the decision trees is compared with that
of a conventional expert system constructed by interviewing endocrinologists.
Finally, recent work in which decision trees are re-expressed as collections
of production rules has been found to improve both the accuracy and
comprehensibility of the inductively acquired knowledge.
Non-GMR personnel interested in attending please contact
R. Uthurusamy [ samy@gmr.com ] 313-986-1989
------------------------------
Date: 9 Mar 87 16:59:31 EST
From: Patty.Hodgson@isl1.ri.cmu.edu
Subject: Seminar - Search and Reasoning in AI (CMU)
AI SEMINAR
TOPIC: Search and Reasoning in AI
SPEAKER: Herb Simon
PLACE: Wean Hall 5409
DATE: Tuesday, March 10, 1987
TIME: 3:30 pm
ABSTRACT: What is the relation between the search paradigm in AI and
the reasoning or deductive paradigm implicit or explicit in most theorem
proving programs, PROLOG, and Nilsson's text?? The talk will undertake to
show that these two points of view cannot be distinguished on logic grounds
but that they represent very different heuristic viewpoints about how
AI systems are to be constructed, and about the relation of these systems
to the "real world." The talk will develop and extend views published in
Artificial Intelligence 28 21:7-29 (1983).
------------------------------
Date: 10 Mar 87 11:55:40 EST
From: Karen.Olack@h.cs.cmu.edu
Subject: Seminar - Multilisp (CMU)
Speaker: Robert Halstead
Date: March 16, 1987
Time: 2:00 p.m.
Place: Wean Hall 8220
Topic: Multilisp: A Language for Parallel Symbolic Computing
ABSTRACT
Multilisp is an extension of Scheme with additional operators and
additional semantics for parallel execution. These have been added
without removing side effects from the language. The principal
parallelism construct in Multilisp is the "future," which exhibits some
features of both eager and lazy evaluation. Current work focuses on
making Multilisp a more humane programming environment, on expanding the
power of Multilisp to express task scheduling policies, and on measuring
the properties of Multilisp programs with the goal of designing a
parallel architecture well tailored for efficient Multilisp execution.
Multilisp has been implemented, and runs on the shared-memory
Concert multiprocessor, using as many as 27 processors. The
implementation uses interesting techniques for task scheduling and
garbage collection. The task scheduler helps control excessive resource
utilization by means of an unfair scheduling policy; the garbage
collector uses a multiprocessor algorithm modeled after the incremental
garbage collector of Baker.
The talk will briefly describe Multilisp, discuss the areas of
current activity, and indicate the future direction of the project in
the areas of language design, application development, and
multiprocessor architecture.
------------------------------
End of AIList Digest
********************
∂12-Mar-87 0608 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #76
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 12 Mar 87 06:07:53 PST
Date: Thu 12 Mar 1987 01:01-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #76
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 12 Mar 1987 Volume 5 : Issue 76
Today's Topics:
Discussion Lists - AI-CHI & Info-1100/Bug-1100,
Queries - Washington-Area TI Seminar & Chess Evaluator &
AI bibliographies & 3-D Clustering Algorithms &
Comparative Psychology of Intelligence
----------------------------------------------------------------------
Date: Mon, 9 Mar 87 11:00:38 PST
From: wiley!sherman@lll-lcc.ARPA (Sherman Tyler)
Subject: AI Lists
You recently sent a message about existing mailing lists on ARPANET that
related to AI. Not long ago, we started another list called AI-CHI to look
at artificial intelligence applications to computer-human interaction.
We would appreciate it if you could appropriately update your own list of
AI lists with this item. The list is:
wiley!ai-chi@lll-lcc.arpa
and requests to be added to the list can be sent to:
wiley!ai-chi-request@lll-lcc.arpa
Thanks very much.
------------------------------
Date: Mon 9 Mar 87 21:52:30-PST
From: Christopher Schmidt <SCHMIDT@SUMEX-AIM.STANFORD.EDU>
Subject: Info-1100/Bug-1100
For the record, Info-1100 and Bug-1100 have been merged into
one list; Info-1100.
--Christopher
------------------------------
Date: 9 Mar 87 09:27:00 EST
From: "WHITE::PSOTKA" <psotka%white.decnet@ari-hq1.ARPA>
Reply-to: "WHITE::PSOTKA" <psotka%white.decnet@ari-hq1.ARPA>
Subject: Washington-Area TI Seminar?
Is anyone in the greater Washington D.C. area going to be showing the
TI AI seminar in a semi-public facility? I would like to attend.
Psotka (202)274-5540
------------------------------
Date: 10 Mar 87 14:43:09 GMT
From: mcvax!ukc!its63b!gvw@seismo.css.gov (G Wilson)
Subject: HHelp needed with computer chess
I am writing a chess program to run on a Meiko Computing Surface,
a highly parallel MIMD machine containing 40 transputers. I started
by converting the Free Software Foundation's GNUChess program, and I have
move generation and tree search fairly well in hand, but I desperately
need a better board evaluation function. All of the literature I have
been able to locate on computer chess describes some of the features
a good function should have, but no-one actually lists a set of
numerical weights!
Does anywhere out there in net.land have an old chess program running
on an Apple-II or a BBC Micro or even source code for the standard
UNIX chess program that has an evaluation function I could use? Any
language will do. Failing that, does anyone have pointers to
literature which doesn't just talk about such functions, but actually
lists one or two (or three, or four, or ...)?
Much appreciated.
Greg Wilson
------------------------------
Date: Wed, 11 Mar 87 17:17:42 EST
From: Raul.Valdes-Perez@B.GP.CS.CMU.EDU
Subject: AI bibliographies
Does anyone have a file containing all the titles of papers published
in the leading AI sources e.g. Journal, IJCAI, AAAI, ECAI etc.? It
would be nice to do a string search for certain topics and find relevant
papers instantly.
------------------------------
Date: Mon, 09 Mar 87 18:31:38 n
From: DAVIS%EMBL.BITNET@wiscvm.wisc.edu
Subject: 3D Clustering algorithms
The subject just about sums it up......anyone out there in the 'lectronic
village overly proud, or overly knowledgeable, or even just familiar with
clustering algorithms for use in three dimensions ? That is to say, I have
a bunch of points in a 3D space, and I want to cluster them. Simple huh ?
Tell me how, or tell me how to find out how......replies directly to me,
or post them on the list.
with thanks,
Paul Davis
Euopean Molecular Biology Laboratory,
Postfach 10.2209
6900 Heidelberg
West Germany
bitnet: davis@embl.bitnet
uucp: ...psuvax!embl.bitnet!davis
petnet: homing pigeons to....
"a time for dreams, a time for sleep, a time for love .... its now!"
[What makes three-space special? Any similarity or dissimilarity
metric that works in three dimensions should work in N dimensions.
The really interesting cases are those where no reasonable weighting
exists for combining distances in the different dimensions.
Any of the major subroutine packages -- BMD, SPSS, etc. -- have
clustering routines and associated documentation. Euclidean space
is generally assumed, which causes problems with circular scales
such as hue in a color space. (One heuristic for color spaces is
to linearize the usual 256↑3 cells by tracing through the space with
a fractal curve, then search for clusters in the 1-D result.)
Other 3-D spaces are best analysed in terms of direction cosines
for vectors to the points from some origin. Statistical metrics
based on within-cluster and between-cluster variances are optimal
for some applications, but gravitational or potential-based models
are better in others. ISODATA is a time-honored heuristic method
for growing and splitting clusters, but is only suitable for
circular clusters in isometric spaces. Zahn's method of analyzing
minimal spanning trees is one way of overcoming the common faults
(e.g., chaining or lack thereof) of heuristic approaches.
The book on Pattern Recognition and Image Processing by Duda and
Hart offers an easy introduction to some of the statistical and
heuristic methods. Other pattern recognition books are more
thorough. Clustering is still a black art, though, and you are
probably best off getting a commercial package and trying a few
of the options to get a feel for what works with your data. -- KIL]
------------------------------
Date: Wed, 11 Mar 87 23:17:17 est
From: Stevan Harnad <princeton!mind!harnad@seismo.CSS.GOV>
Subject: Comparative Psychology of Intelligence: BBS Call for
Commentators
The following is the abstract of a forthcoming article on which BBS
[Behavioral and Brain Sciences -- An international, interdisciplinary
Journal of Open Peer Commentary, published by Cambridge University Press]
invites self-nominations by potential commentators.
(Please note that the editorial office must exercise selectivity among the
nominations received so as to ensure a strong and balanced cross-specialty
spectrum of eligible commentators. The procedure is explained after
the abstract.)
-----
THE COMPARATIVE PSYCHOLOGY OF INTELLIGENCE
Euan M. Macphail
Department of Psychology
University of York
Heslington, York YO1 5DD
United Kingdom
Recent decades have seen a number of influential attacks on
the comparative psychology of learning and intelligence. Two
specific charges have been that the use of distantly related
species has prevented making valid evolutionary inferences and that
learning mechanisms are species-specific adaptations to
ecological niches and hence not properly comparable between
species. It is argued here that investigating distantly related
species may allow valuable insights into the structure of
intelligence and that the question of whether learning
mechanisms are niche-specific is one that can only be answered
by comparative work in "non-natural" situations. The problems
involved in the definition and assessment of intelligence are
discussed. Experimental work has not succeeded in
demonstrating differences in intellect among nonhuman
vertebrates; hence the null hypothesus that there exist no
differences in intellect amongst nonhuman vertebrates should
be adopted. The superiority of human intelligence stems from
our possession of a species-specific language-aquisition
device. One implication of the null hypothesis is that general
problem-solving capacity is independent of niche-specific
adaptations. A second implication is that problem-solving may
involve relatively simple mechanisms: Association formation in
particular may play a central role in nonhuman intelligence,
allowing the successful detection of causal links between
events, causality being a common constraint to all niches.
-----
This is an experiment in using the Net to find eligible commentators
for articles in the Behavioral and Brain Sciences (BBS), an
international, interdisciplinary journal of "open peer commentary,"
published by Cambridge University Press, with its editorial office in
Princeton NJ.
The journal publishes important and controversial interdisciplinary
articles in psychology, neuroscience, behavioral biology, cognitive science,
artificial intelligence, linguistics and philosophy. Articles are
rigorously refereed and, if accepted, are circulated to a large number
of potential commentators around the world in the various specialties
on which the article impinges. Their 1000-word commentaries are then
co-published with the target article as well as the author's response
to each. The commentaries consist of analyses, elaborations,
complementary and supplementary data and theory, criticisms and
cross-specialty syntheses.
Commentators are selected by the following means: (1) BBS maintains a
computerized file of over 3000 BBS Associates; the size of this group
is increased annually as authors, referees, commentators and nominees
of current Associates become eligible to become Associates. Many
commentators are selected from this list. (2) The BBS editorial office
does informal as well as formal computerized literature searches on
the topic of the target articles to find additional potential commentators
from across specialties and around the world who are not yet BBS Associates.
(3) The referees recommend potential commentators. (4) The author recommends
potential commentators.
We now propose to add the following source for selecting potential
commentators: The abstract of the target article will be posted in the
relevant newsgroups on the net. Eligible individuals who judge that they
would have a relevant commentary to contribute should contact the editor at
the e-mail address indicated at the bottom of this message, or should
write by normal mail to:
Stevan Harnad
Editor
Behavioral and Brain Sciences
20 Nassau Street, Room 240
Princeton NJ 08542
(phone: 609-921-7771)
"Eligibility" usually means being an academically trained professional
contributor to one of the disciplines mentioned earlier, or to related
academic disciplines. The letter should indicate the candidate's
general qualifications as well as their basis for wishing to serve as
commentator for the particular target article in question. It is
preferable also to enclose a Curriculum Vitae. (This self-nomination
format may also be used by those who wish to become BBS Associates,
but they must also specify a current Associate who knows their work
and is prepared to nominate them; where no current Associate is known
by the candidate, the editorial office will send the Vita to
approporiate Associates to ask whether they would be prepared to
nominate the candidate.)
BBS has rapidly become a widely read read and highly influential forum in the
biobehavioral and cognitive sciences. A recent recalculation of BBS's
"impact factor" (ratio of citations to number of articles) in the
American Psychologist [41(3) 1986] reports that already in its fifth year of
publication (1982) BBS's impact factor had risen to become the highest of
all psychology journals indexed as well as 3rd highest of all 1300 journals
indexed in the Social Sciences Citation Index and 50th of all 3900 journals
indexed in the Science Citation index, which indexes all the scientific
disciplines.
Potential commentators should send their names, addresses, a description of
their general qualifications and their basis for seeking to comment on
this target article in particular to the address indicated earlier or
to the following e-mail address:
{allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet
[Subscription information is available from Harry Florentine at
Cambridge University Press: 800-221-4512]
------------------------------
End of AIList Digest
********************
∂13-Mar-87 1526 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #77
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 13 Mar 87 15:25:41 PST
Date: Fri 13 Mar 1987 10:08-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #77
To: AIList@SRI-STRIPE.ARPA
AIList Digest Friday, 13 Mar 1987 Volume 5 : Issue 77
Today's Topics:
Queries - Addresses & Genetic Algorithms & Planning and Scheduling &
TI Satellite Symposium Locations,
Funding - AFOSR Announcement,
Games - ICCA Journal,
Expert Systems - Checking Rule-Based Expert Systems,
Application - Analysis of Unknown Data
----------------------------------------------------------------------
Date: Tue 10 Mar 87 14:39:19-EST
From: John C. Akbari <AKBARI@CS.COLUMBIA.EDU>
Subject: whereabouts
Does anyone have email or snail mail addresses for any of these people?
They are some Brits who have published very interesting work in
knowledge acquisition for expert systems. any assistance will be
appreciated.
Anna Hart
Alison Kidd
Lisanne Bainbridge
Margaret Welbank
ad...THANKS...vance!
john c akbari
ARPANET & Internet akbari@CS.COLUMBIA.EDU
BITnet akbari%CS.COLUMBIA.EDU@WISCVM.WISC.EDU
uucp & usenet ...!seismo!columbia!cs!akbari
DECnet akbari@cs
PaperNet 380 riverside drive, no. 7d
new york, new york 10025 usa
SoundNet 212.662.2476
------------------------------
Date: Thu, 12 Mar 87 18:08 EST
From: Olasov@MIT-MULTICS.ARPA
Subject: Network_addresses_of_Contributors
Hello,
This is a response to several bibliographical entries in the AI-List
forum on the ARPANET.
I'm interested in sending network mail to a number of individuals who were
contributors of one or more entries in the AI-List, however I don't have
their network mail stops. Can you help me out with this, or if you don't
have their network addresses, could you forward this letter to someone
who might? The individuals I wish to contact are:
John S. Gero
or John Radford
or P. Hing
authors of New Rules of Thumb from Computer Aided Structural Design:
Aquiring Knowledge for Expert Systems
Proceedings CADD-84
UK
1984
AIME
Hitoshi Furuta
King Sun Tu
Minhai Bambuceanu, author of Knowledge Engineering in CAD
North Holland
Daniel Rehak
H. Craig Howard
authors of Interfacing Expert Systems with Design Databases in Integrated
CAD Systems
P. Haren
M. Montalban
authors of Prototypical objects for CAD systems
Dennis J. Nicklaus
Siu S. Tong
creators of Engineous: A Knowledge Directed Computer Aided Design Shell
If you know the network address of even one of these individuals, I'd
appreciate it more than I can express if you would send it to me.
Thanks.
Best Regards,
Ben Olasov <Olasov@MULTICS.MIT.EDU>
[King-Sun Fu died in April of '85, so you may have difficulty reaching
him. John Gero is with the Dept. of Architectural Science at the
University of Sydney (Sydney 2006 Australia), and can probably be
reached as "munnari!archsci.su.oz!john"@seismo.CSS.GOV. (Note the
lower-case seismo.) Most contributors to AIList can be reached via
the From address in the message; I can help interpret it if you send
me a copy. -- KIL]
------------------------------
Date: 11 Mar 87 00:57:31 GMT
From: amdcad!amd!intelca!mipos3!omepd!uoregon!hp-pcd!hpcvlo!karen@ucbv
ax.Berkeley.EDU (Karen Helt)
Subject: Genetic Algorithms
I am investigating genetic algorithms as they relate to
machine learning and in particular classifier systems.
I hope to do my master's thesis in this area. I am
trying to locate literature in this area. Does anyone
know how I can get a copy of the "Proceedings of an International
Conference on Genetic Algorithms and Their Applications,1985"?
Also, it appears that a lot of work on genetic algorithms
has been done at the University of Michigan. There are a number
of Ph D theses of Univ. of Michigan students referenced in the
articles I have found. Is Univ. of Michigan on the net? Will
someone there please contact me and tell me how I can get copies
of some of the theses? I would appreciate any help and information
anyone can give me.
Thanks.
Karen Helt
Hewlett-Packard Company
Corvallis Workstation Operation
Corvallis, Oregon
part-time graduate student at Oregon State University
hplabs!hp-pcd!karen
------------------------------
Date: Thu, 12 Mar 87 15:03:40 est
From: nancy@grasp.cis.upenn.edu (Nancy Orlando)
Subject: Planning and scheduling survey
I have recently begun a project to examine the current techniques and
capabilities of planning and scheduling systems. This covers a wide range of
potential techniques and implementations; the systems of interest can range
from robotic task planners to mission planners to job shop schedulers, using
structures ranging from expert systems to classical programs to neural nets,
using techniques ranging from means-ends analysis to constraint propagation to
simplex algorithms.
Pointers to any systems, either from the literature or work currently in
progress, would be appreciated. I particularly am interested in acquiring
information concerning the problem domain, the structure and technique(s) used
aspects of the domain of the system that lead to the choice of structure and
techniques, the strengths and weaknesses of the system, and an opinion as to
the portability of the system to other domains.
Maybe its deja vu, but I seem to recall another recent request to AIList
concerning planning systems. A pointer to that source would also be
appreciated.
Results of this survey can be posted to the net if there is sufficient
interest.
USmail would be appreciated, as my net address is capricious:
Nancy Sliwa
MS 152D
NASA Langley Research Center
Hampton, VA 23665-5225
An E-mail address, if absolutely necessary:
nancy%upenn-grasp@upenn
Much thanks!
------------------------------
Date: 12-Mar-87 16:13:58
From: Dan Cerys <cerys@XX>
Subject: TI Satellite Symposium locations
A number of people have been posting queries about the the viewing
locations for the third Texas Instruments Satellite Symposium on
Artificial Intelligence. There are two ways that a person can "attend"
the symposium.
1) If you can receive satellite video broadcasts, TI will provide the
information you need to set your location up as viewing site.
2) There are a number of public viewing locations around the world.
These are free unless the location is sponsored by another organization
(eg, IEEE). Most of these locations require advance registration.
In either case, there is a toll-free number you can call to receive more
information and/or register at a viewing location: (800) 527-3500.
(I'm not sure if this works for those outside of North America).
I have only few details on the conference. It is titled "AI
Productivity Roundtable" and will be held on April 8, 9:00 EST - 13:00
EST, followed by a 1 1/2 hour condensation of the 2nd Symposium
beginning at 14:00 EST.
------------------------------
Date: 25-FEB-1987 14:44
From: GILES@AFSC-HQ.ARPA
Subject: AFOSR Announcement
[Forwarded from the Neuron Digest.]
PROGRAM ANNOUNCEMENT: NEURAL COMPUTING AND PROCESSING
The Air Force Office of Scientific Research (AFOSR) announces a
new program of support for basic research on the computational
aspects of neural networks.
Research that could yield computational neural models of
information processing, learning, and cognition in complex
biological systems is specifically encouraged. AFOSR is
interested in multidisciplinary theoretical and empirical
approaches. Research focused on neural architectures subserving
learning and cognition or on computational aspects of
neuromorphic structures and systems is also of interest.
Research proposals are now being accepted by AFOSR. All
proposals received before July 1, 1987 will be considered for the
first cycle of support to begin in October. Support from AFOSR
is typically provided as multi-year grants or contracts.
FOR ADDITIONAL INFORMATION CONTACT:
Dr. C. Lee Giles Architectures and Computation
202-767-4931 GILES@AFSC-HQ.ARPA
Dr. William O. Berry Life Sciences
202-767-5021
Dr. Vincent Sigillito Artificial Intelligence
202-767-5028
Dr. John F. Tangney Life Sciences
202-767-5021 TANGNEY@AFSC-HQ.ARPA
AIR FORCE OFFICE OF SCIENTIFIC RESEARCH
BOLLING AFB, BLDG 410
WASHINGTON, DC 20332-6448
------------------------------
Date: Tue, 10 Mar 87 14:42:35 EST
From: @um.cc.umich.edu@umix.cc.umich.edu,
Subject: ICCA journal
Can you post this to mod.ai? Thank you.
The December 1986 issue of the ICCA Journal is now available. The
ICCA (International Computer Chess Association) produces a quarterly
journal, organizes the triennial World Computer Chess Championship,
strengthen ties and promote co-operation amoung computer chess re-
searchers, etc.
This month's issue contains:
RESEARCH PAPERS:
Fuzzy Production Rules in Chess, P.W. Frey
Influence of Ordering on Capture Search, P. Bettadapur
Computer Analysis of a Queen Endgame, E.A. Komissarchik
and A.L. Futer
REPORTS:
ACM's 17th North American Computer Chess Championship
The 6th World Microcomputer Chess Championship
OTHER:
Compressing Databases down to Micro Size, H. Zellner
An example of QPvQ, K. Thompson
A note on KBBK, H.J. van den Herick and I.S. Herschberg
Swedish Rating List, G. Gottling
as wells as reviews, conference announcements, etc. A total of 60 pages.
ICCA memberships are $20 US per year. For more information, contact
ICCA
c/o Jonathan Schaeffer
Department of Computing Science
University of Alberta
Edmonton, Alberta
Canada T6G 2H1
ihnp4!alberta!jonathan
------------------------------
Date: Mon, 09 Mar 87 14:50:31 -0800
From: mcguire@aero2.aero.org
Subject: Re: Checking Rule-Based Expert Systems (Info Request).
We have been working in this area for a while. In addition to checking
for completeness and consistency we analyze a rule-base for the
"effectiveness" of its information. It is possible for rules or
distinctions to appear to have meaning, but through faulty interaction
they wind up never influencing the answers the system gives. This sort
of interference is unbounded in scope. We have developed propagation
style algorithms for finding ineffective information in simple types of
rule bases.
A paper on this work is almost ready for release. I can mail out copies
then.
Roderick McGuire
The Aerospace Corporation
Box 92957
Los Angeles, CA 90009
ARPA: mcguire@aerospace.aero.org
------------------------------
Date: 9 Mar 87 14:01:51 GMT
From: Dave Stoffel <dave@mimsy.umd.edu>
Subject: Re: Dear Abby, Analysis of unknown data.
>I guess the idea here is to come up with an expert version of the UNIX file
>program.
The problem with the `file' approach is that it assumes one
has already a knowledge of the "files" he is attacking. So,
this technique might become more and more useful, but only "might".
>One of the first things to realize is that there are files for
>which your system is not going to be able to come up with any
>useful information. Try feeding it 156MB of perfectly random
>numbers for example.
Testing for randomness might be the first test; sure would save
a lot of subsequent computing if it were random.
>files. Optionally, the program could try and deduce all the information
>desired from the file, but I think that would be much more difficult to do.
Yep. It would be nice to take a goal-driven, top-down approach,
but sometimes data-driven inference, e.g., auto-correlation,
is what there is.
>representation is derived from firing up the appropriate program on the file.
>For example, if you are trying to classify a system executable, you will want
>to run the system debugger (or disassembler) on the file. There is an
>assumption here that files don't exist in a vacuum. If they did, they would
>be useless.
Their uselessness and whether they exist in a vacuum is an assumption.
--
Dave Stoffel (703) 790-5357
seismo!mimsy!dave
dave@Mimsy.umd.edu
Amber Research Group, Inc.
------------------------------
Date: 11 Mar 87 18:38:32 GMT
From: tektronix!sequent!mntgfx!franka@ucbvax.Berkeley.EDU (Frank A.
Adrian)
Subject: Re: analysis of unknown data
In article <5681@mimsy.UUCP> dave@mimsy.UUCP (Dave Stoffel) writes:
>
>
> What systematic methods and techniques would you apply to the
> following problem?
>
> Determine the representation, organization, and content of a
> "file" containing up to 156MB. There are no assumptions. The
>methods and techniques applied must be automated (if not fully
>automatic) and applicable to an unlimited supply of "files".
Actually, there are several ways to approach this problem. It is a statement
of finding out what is happenning inside a classical "black box". You can
start by monitoring all requests and replies from the file, searching for
patterns based on location of access and length of access. You can examine
the bytes returning from the device to try to detect patterns. You can use
a traffic analysis approach by find out what types of programs access this
file at which times for a given purpose. You can go ask the NSA, CIA, and
other intellegence agencies what they do when they try to crack a black box
(though I doubt that they'd tell you :-). Finally, most boxes are not com-
pletely black. In general, you can tell information by the location, size,
etc. of a box. But unless the box is completely isolated (in which case, why
are you all that interested in what it does?) you can always get some infor-
mation, upon which you can make your own assumptions, can try experiments,
and finally uncover the nature of an object. You might also try any good
text on experimental methods to point you in the right direction.
Frank Adrian
Mentor Graphics, Inc.
------------------------------
Date: 12 Mar 87 21:47:26 GMT
From: dave@mimsy.umd.edu (Dave Stoffel)
Subject: Re: analysis of unknown data
In article <564@franka.mntgfx.MENTOR.COM>, franka@mntgfx.MENTOR.COM
(Frank A. Adrian) writes:
> Actually, there are several ways to approach this problem. It is a statement
> of finding out what is happenning inside a classical "black box". You can
> start by monitoring all requests and replies from the file, searching for
> patterns based on location of access and length of access. You can examine
> the bytes returning from the device to try to detect patterns. You can use
> a traffic analysis approach by find out what types of programs access this
> file at which times for a given purpose.
the "file" of 156MB is not exactly a black box. The traditional
black box problem describes functions whose structure is not known.
The "file" is data, not procedure. An unknown number of procedures
may have participated in creation of the data. The "file" is
sitting on my machine after being read off of a tape which an
archeologist(sp?) dug up. What is the data? Maybe it is one logical
file, maybe hundreds. If hundreds, maybe each one is a different
type. Maybe the bytes on the tape are not ordered as logical files,
but as physical blocks from some disk pak. Put it back together,
so you can tell the archeologist what information is on the
tape, so he learns something about the civilization which left it.
Dave Stoffel (703) 790-5357
seismo!mimsy!dave
dave@Mimsy.umd.edu
Amber Research Group, Inc.
------------------------------
End of AIList Digest
********************
∂15-Mar-87 0021 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #78
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 15 Mar 87 00:21:27 PST
Date: Sat 14 Mar 1987 21:33-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #78
To: AIList@SRI-STRIPE.ARPA
AIList Digest Sunday, 15 Mar 1987 Volume 5 : Issue 78
Today's Topics:
Queries - Printed Circuit Board Software &
Toshiba Voice Recognition Chip & Expert System/CAD Interfaces,
Funding - AFOSR Commendation,
Jargon - Maths as a Science,
Expert Systems - Explanations
----------------------------------------------------------------------
Date: 14 Mar 87 00:36:07 GMT
From: ucsdhub!hp-sdd!ncr-sd!se-sd!rich@sdcsvax.ucsd.edu (Rich Hume)
Subject: Printed Circuit Board Software
Question: Can someone point me to (or better yet send me)
some public domain software for doing printed circuit board
layout? Even somewhat out of date source would be useful.
Please send responses to me.
Thanks for any info!
Rich Hume
Application Environment Products
NCR Corp.
UUCP: ...!ncr-sd!se-sd!rich
...!seismo!scubed/
------------------------------
Date: 14 Mar 87 02:13:10 GMT
From: hoptoad!gnu@sun.com (John Gilmore)
Subject: Toshiba voice recognition chip
A recent article in Newsbytes Japan mentions:
Toshiba's Voice Recognition LSI -- Toshiba (Tokyo) has developed
a powerful LSI for recognizing human speech. This new product
recognizes a variety of spoken sounds with 95% accuracy.
Toshiba plans to use this LSI for a voice input system for its
word processors.
I am interested in building a voice control system for my house, which
will be fully wired for sound. Does anyone have further information
about this chip (e.g. press releases, other mentions in the press,
papers at conferences, or actual product numbers and specs)?
--
John Gilmore {sun,ptsfa,lll-crg,ihnp4}!hoptoad!gnu gnu@ingres.berkeley.edu
Love your country but never trust its government.
-- from a hand-painted road sign in central Pennsylvania
------------------------------
Date: Sat, 14 Mar 87 15:40 EST
From: Olasov@MIT-MULTICS.ARPA
Subject: Expert_system/_CAD_interfaces
I'm doing research on applications of various expert system
techniques in architectural design <and, secondarily,
engineering design>, with emphasis on interfacing knowledge
based systems with CAD systems.
In my research, I've developed a number of shells external
to the CAD system, that are written in LISP, and that use
different entry points to the CAD system. I've used rule
based pattern matching shells and binary discrimination networks.
I've also tried writing shells for an IBM-PC CAD package
called AutoCAD, which has an internal LISP interpreter, with
interesting results. I expected that an interpreter resident
within the CAD system should be a superior strategy to that
of having an interface of an external shell to the CAD
package. I found that in the case of AutoLISP however, the
internal LISP interpreter in AutoCAD, memory requirements for
even trivial pattern matching algorhythms usually proved to
be too great (yes, even in the latest versions of AutoCAD).
Also, AutoLISP functions represent a very small subset of a
full Common LISP, which makes ES applications exceedingly
difficult to write, as functions which would otherwise be
primitively defined must be defined at the interpreter level,
thus using much of the precious memory it has to allocate to
function definitions. Generally, small applications were
successful.
I would be very interested to learn about the research and
experiences of others who are using, or attempting to use,
expert system applications in CAD, particularly for
architectural design purposes.
Cheers,
Ben Olasov <Olasov@MIT-MULTICS.ARPA>
------------------------------
Date: Fri, 13 Mar 1987 19:14 EST
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #77
Subject: AFOSR Announcement
<The Air Force Office of Scientific Research (AFOSR) announces a
<new program of support for basic research on the computational
<aspects of neural networks.
This is nice to see. Nearly thirty years ago, some brave and
imaginative officers at the AFOSR stuck their necks out and funded
several individuals working on early connectionist and symbolic AI
ideas. Many observers considered them irresponsible, but it led to a
lot of stimulating discoveries. Now that the field has become
respectable, their foresight ought to be acknowledged.
------------------------------
Date: 4 Mar 87 10:44:29 GMT
From: mcvax!ukc!its63b!hwcs!aimmi!gilbert@seismo.css.gov (Gilbert Cockton)
Subject: Re: Maths as a Science (aka: Learning AI aka: List AI beginners Books)
In article <3800004@nucsrl.UUCP> ragerj@nucsrl.UUCP (John Rager) writes:
>Logic is a branch of mathematics. The last time I checked mathematics
>was a science.
Where did you check? We have no local index of official scientific
subjects over here :-). Perhaps some US professor has mapped out the whole of
knowledge and categorised it while we were all asleep :-).
In English secondary education, the official policy is that Maths
is NOT a science, as it does not rest on any empirical
methods at all (empirical in the sense of observing the natural world,
perhaps in a controlled experiment). Neither is applied maths a
science, as the modelling process may involve abstracting intuitively
and the return to the real problem domain also involves unobservable
judgement.
Whilst the only thing most people could need to know about
epistemology is how to spell it, folk in AI need to get right to grips
with it if their talk of 'Knowledge Representation/Elicitation' is to
be anything more than one big amateur pose. Throw in some cognitive
sociology and the faint-hearted will probably go back to chess
games and tic-tac-toe (real everyday intelligence that) :-).
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.aimmi ARPA: gilbert%aimmi.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..!{backbone}!aimmi.hw.ac.uk!gilbert
------------------------------
Date: 6 Mar 87 19:18:37 GMT
From: ssc-vax!bcsaic!michaelm@BEAVER.CS.WASHINGTON.EDU (Michael
Maxwell)
Subject: Re: dear abby....
In article <1147@sfsup.UUCP> saal@/guest5/saalUUCP (45444-AUG871-S.Saal) writes:
>In article <178@arcsun.UUCP> roy@arcsun.UUCP (Roy Masrani) writes:
>>Dear Abby. My friends are shunning me because i think that to call
>>a program an "expert system" it must be able to explain its decisions.
>>"The system must be able to show its line of reasoning", I cry. They
>>say "Forget it, Roy... an expert system need only make decisions that
>>equal human experts...
>
>...Once it is "in production" (the field) it may not
>be as important to give an explanation every time. This is
>particularly the case when the expert system is used to help do
>some of the more mundane tasks on a very frequent basis. There
>are 2 reasons for this. (1) the user may be able to agree
>intuitively after deriving the answer - the machine has just
>helped speed the process. OR (2) If a production ES has been
>converted to a compiled language, the code to express the
>rationale may be removed to speed up run time.
I'm not an ES expert, but when I talk to a human expert in a field, I commonly
ask "why?" or "what alternatives are there?" (which is the same thing for the
user, I think, although perhaps not for the expert). This is even true in
"mundane" or frequently performed tasks.
An example is when I went to the AAA to ask what the best route was to drive
from Seattle to Miami in early spring. Since I'm going to an expert for the
solution, there's a reason, and almost by definition it's not routine.
I may have asked them how to drive from A to B many times, but in this case I
asked why they routed me the way they did, because I'm unsure of
the weather conditions over passes in Montana and Colorado.
If the ES is to not just "make decisions that equal human experts" but
replace and/or augment a human, I would want to be able to ask it the same
questions. Hence I think that while point (2)--by deleting explanation
code we can speed up the run time system--may be true, it is beside the point
(pun). If anything, it is an argument for faster hardware.
Or maybe I'm just suspicious...
--
Mike Maxwell
Boeing Advanced Technology Center
arpa: michaelm@boeing.com
uucp: uw-beaver!uw-june!bcsaic!michaelm
------------------------------
Date: Wed, 11 Mar 87 18:02:33 GMT
From: Vic Churchill <mcvax!stl.stc.co.uk!jvc@seismo.CSS.GOV>
Reply-to: Vic Churchill <mcvax!stl.stc.co.uk!jvc@seismo.CSS.GOV>
Subject: Re: Expert systems
In article <8703040725.AA27188@ucbvax.Berkeley.EDU>
KRULWICH@C.CS.CMU.EDU (Bruce Krulwich) writes:
>
>There seems to be a trend nowadays to use the phrase "expert systems" to
>mean rule-based systems, not to mean any systems that mimick expert
>behavior. While I'm not sure I like the terminology, I think that it's
>beneficial to have a seperate catagory for rule-based-systems work,
>since that's often very different from other A.I. work ....
I'm inclined to agree. Once upon a time, "Knowledge Based System"
equalled "Expert System" equalled "Rule Based System", none of which
equalled "AI System". AI sympathists looked askance at the sudden
mushrooming of expert systems with suspicion and cynicism as a band-
wagon for squeezing as much cash as possible out of gullible sponsors.
(And perhaps the old "if it's *that* easy to do, it can't be AI"
attitudes came around again...)
But KBS work is now returning to the stable, and concerning itself more
and more with "real AI" (!) issues - use of metaknowledge for planning
and control, problems of learning, ... so now when people say "expert
system" they could mean a KBS or they could mean a "first generation"
rule-based system. My guess is that KBS will replace ES as the
preferred term for forthcoming systems, and that ES will shrink to
denoting the things that you make using a commercially- available
ES shell: typically, rule-based (and that don't mean much more than
computer-based) systems.
As for the other question of whether an ES should explain itself: it's
fairly easy to make a RBS give some kind of explanation, and so it's
been done frequently. The domain and user context might not require it,
and the nature of the explanation might be useless anyway, but ....
I'd go along with the other correspondents who argue that a KBS might
just not have access any more (at the time you asked for it) to the
'exact' reasons for its outputs and that maybe there is no 'exact'
reason if there is indeterminacy/context-dependency built in.
Generally, the ability to give explanation on demand seems to be
only an optional, useage-dependent, external characteristic rather than
an essential universal internal one.
Vic Churchill ( ...!mcvax!ukc!stl!jvc +44-279-29531 x 2546)
STL Ltd., London Road, Harlow, Essex CM17 9NA, U.K.
------------------------------
Date: Fri, 13 Mar 87 09:53:51 MST
From: Roy Masrani <ubc-vision!calgary!arcsun!roy@seismo.CSS.GOV>
Subject: reply to dear abby
Dear abby (sigh). And I thought you had all the answers!
Just to summarize the responses (wow.. so many of them too!)
1. justification mechanisms are not good enough yet, ergo expert
systems do not need a justification capability.
This is missing the point. Just because current justification
mechanisms (jms) simply print a trace of its reasoning is not an
argument against the utility of jms per se. perhaps the work on
"deep model" reasoning will come up with good jms.
>When they ask for "the reason why" should I have written
>a huge explanation database instead of relying on the
>programming language internal logic control??????? (Michaelson)
No, but *when* they ask why, you should get the (current state of
the art) explanation module that was keeping track of the reasoning
system to spit out what it has. Pretty difficult to do in prolog
unless you build some kind of es shell on top of it.
1b. Humans do not backtrack over a line of reasoning. Humans dont
justify themselves.
An interesting comment by B. Nevin.
>....Instead, we reconstruct what such a line of reasoning
> might plausibly be. It's called rationalization.
To me, a doctor who says "S**t, I prescribed x... better
cover myself" is one who is rationalizing his/her decisions. (but
at least s/he is providing a justification for the decision (:->))
Even if the expert is reconstructing the reasoning, it is based on
the knowledge of the field, and it is difficult (for me) to argue that the
"rationalization" wasn't a trace of the line of reasoning since you
dont have access to the reasoning in the first place.
I dont ask my doctor to always explain herself, but if she was not
able to when i did, i would leave pretty quickly.
2. the term "expert system" is not well defined.
I couldn't agree more with this more. Three terms are often used
interchangeably "expert system, rule-based system, knowledge-based
system".
A program that behaves as an expert (i.e. makes expert-like
decisions) cannot be considered an expert system. Is SPSS (the
statistical package written in fortran) an expert system.. it sure
performs functions similar to an expert statistician (relative to
me, anyway). A program that only has a clear knowledge/control
separation cannot be called an es. any system written on top of a
spreadsheet has a clear knowledge/control separation.
>Knowledge-based system technology is a programming methodology, which
>facilitates the incorporation of "human or expert" knowledge. Hence, the
>criterion that explanation facilitiy is a must for a knowledge based
>system (or an expert system once you add the expert's knowledge) is
>to be questioned. [...users don't like rule printouts, they like
>"a more robust ENGLISH translation and "nice graphics" (Sriram)
I dont see how your (pretty broad) definition of a knowledge-based
system negates the need for an explanation facility (if kb-system
in your reality == expert system). The second comment simply supports
my view (cf 1)
>...it seems to me that disputes over whether explanation is "needed"
>before you can call it an expert system are missing the point... (Coffee)
Wish I had said that.
3. depends on what the es will be used for. es will be more accepted
if they have an explanation facility.
I guess when i think of expert systems' use, i usually think in
terms of it being used as a consultant or advisor (cf "our
expert is overworked, and getting old" stories). Using an "expert
system" in "production" seems analogous to human experts writing a
set of instructions for use when they are not available. Would
consulting the set of instructions constitute a session with the
expert?
Putting a justification mechanism if/when needed is another way
of saying that the facility is a "luxury" and not really
necessary. I think that perhaps I have a very tight view of the
term "expert system" and its use.
Thanks for the feedback,
roy
------------------------------
End of AIList Digest
********************
∂15-Mar-87 0232 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #79
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 15 Mar 87 02:31:52 PST
Date: Sat 14 Mar 1987 21:46-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #79
To: AIList@SRI-STRIPE.ARPA
AIList Digest Sunday, 15 Mar 1987 Volume 5 : Issue 79
Today's Topics:
Philosophy - Consciousness,
Review - Eliza/Parry/Ractor,
Humor - Humor Interface Project
----------------------------------------------------------------------
Date: 9 Mar 87 09:23:00 EST
From: "WHITE::PSOTKA" <psotka%white.decnet@ari-hq1.ARPA>
Reply-to: "WHITE::PSOTKA" <psotka%white.decnet@ari-hq1.ARPA>
Subject: RE: AIList Digest V5 #71
Consciousness and memory appear to be connected: but
what is the connection? Davis in a posting on March
7, 1987 offers the opinion that consciousness allows
us to be good psychologists; to understand other
humans in ways that a Turing machine could not. It
seems an interesting suggestion. If consicousness is
tied into memory, it is to personalize the memory and
make it distinguishable from external events; the
environment; the reality that exists continuously
outside and that we use so intensively to support our
mental apparatus. The external world helps us to
think in so many ways; cues for arithmetic in
supermarkets; support for troubleshooting complex
equipment (What would we do if we could not see the
instruments?); questions raised implicitly by
mystifying situations, etc. etc. How can we tell what
is our own input (memory) from what comes naturally:
we are "conscious" of the real world and this
consciousness becomes part of the record of the world.
So consciousness is functional; we could not separate
our memories from outside reality without it.
At least, that appeasrs to be an interesting clue to
add to the puzzle.
------------------------------
Date: Tue, 10 Mar 87 08:03 EST
From: Seth Steinberg <sas@bfly-vax.bbn.com>
Subject: Historical Perspective on the Consciousness Debate
I couldn't help noticing that this debate has its antecedants:
"Whatever does this, reasons: and if a machine produces the effects of
reason, I see no more ground for denying it the reasoning power,
because it is unconscious, than I see for refusing Mr. Babbage's engine
the title of a calculating machine on the same grounds."
From T.H. Huxley's 1871 essay Mr. Darwin's Critics - discussing whether
a hunting dog reasons. While this essay is largely concerned with the
origins of the species, it examines the arguments for the necessity of
the special creation of human consciousness (one of Wallace's key
reservations). Examining some of the anti-evolutionary arguments shows
just how shocking Freud's emphasis on the subconscious would be.
Seth
------------------------------
Date: Tue, 10 Mar 87 11:31 CDT
From: "Alan McDonley M/S 3719 (303) 593-5356"
Subject: Minds are a terrible thing to explain
While contemplating about methods of measuring conciousness, I was asked
a *WHO* question. Before I could say the name of the person as an
answer, another thought stream began. I knew the name of the person, I
knew which person I was thinking of, but for some reason I could not say
or bring to *mind* the name of the person. In fact the recognition of
the inability to recall the words flooded my thoughts. I contemplated on
the subject of inferences rapidly happening but not yet creating the
path to the name in my memory. I wondered if I should stop *worrying*
about remembering so that more processing resources would be available
to connect to the name I was attempting to retrieve, when the name burst
into my thoughts. Now after reading the AILIST for some time, I am humbled
to have had what some have called first and second order conciousness
experiences and wonder if there are separate processors for each level
or are thoughts the postings of time sliced knowledge sources on some
blackboard?
Ps. Since Clyde is an elephant, Clyde is a Republican.
------------------------------
Date: 12 Mar 87 15:07:15 GMT
From: mcvax!ukc!its63b!dougie@seismo.css.gov (D Nisbet)
Subject: Eliza/Parry - A summary
I have had a fair response concerning my Ractor/eliza query. Here follows
a summary of the e-mail I received.
Thanks to all who replied.
From: "BARNETTE,JAMES RICHARD JR"
<gt5951b%gitpyr%edu.gatech.gatech@net.cs.relay>
Message-Id: <8703051751.AA00500@gitpyr.gatech.edu>
Subject: Re: Eliza, Doctor, Parry, Ractor, etc, ...
Organization: Georgia Institute of Technology
"The Policeman's Beard is Half-Constructed" is published by
Warner Brothers. When I bought it it was about eleven dollars.
The author of the book is Racter, a program which writes English
prose. The program itself is by William Chamberlain (he also wrote
the introduction.) There was an article a few years ago in Scientific
American describing Racter. It was in the regular feature "Computer
Recreations" by A.K. Dewdney. Sorry, but I don't remember more.
The book is really just a collection of various short writings:
short (two paragraph) essays, free verse poetry (which might be called
structured prose), and even two pages of (horribly bad) limericks.
There is also one short story, "Soft Ions", which was originally
published in Omni magazine. (Sorry, no idea of what issue). The book
is very interesting; I would recommend it if you want to see what kind
of prose computers can write.
Although Racter writes grammatically correct English, the meaning
of his (its?) writing is usually quite bizarre. For instance, in one
of the first short essays of the book, an essay on love, Racter asks
"...does steak love lettuce?". Racter is good enough that his writing
might be mistaken for a human's, but a psychiatrist would probably
diagnose him as very psychotic.
Richard Barnette
Georgia Tech P.O. Box 35951
Atlanta, GA 30332
USA
--
BARNETTE,JAMES RICHARD JR
Georgia Insitute of Technology, Atlanta Georgia, 30332
uucp: ...!{akgua,allegra,amd,hplabs,ihnp4,seismo,ut-ngp}!gatech!gitpyr!gt5951b
ARPA: gt5951b@pyr.ocs.gatech.edu
====================
From copp@bellcore.UUCP Mon Mar 9 16:43:10 GMT 1987
From: copp@bellcore.UUCP (David H. Copp)
Subject: Re: Eliza, Doctor, Parry, Ractor, etc, ...
Message-ID: <231@bellcore.UUCP>
Reply-To: copp@bellcore.UUCP (David H. Copp)
Organization: Bell Communications Research
Keywords: Eliza, Ractor, Parry, Doctor, software, literature.
"The Policeman's Beard is Half Contructed,"
authored by Racter (with a little help from
William Chamberlain), Warner Books Inc., 666 Fifth Avenue,
New York, NY 10103, USA. First printing Oct 1984.
This is a new publisher. You may have to write directly to
Warner Books, P.O. Box 690, New York, NY 10019, USA.
$0.75 per order and $0.50 per copy.
This is not a technical book. It tells you very little about
Racter. It is an amusing addition to your coffee table.
Martin Gardner (or was it Hofstedder?) devoted two or
three pages to Racter about three years ago (Scientific American).
Good article. The program itself can be purchased, IBM PC format,
for about $75--see the SA article.)
--
David H. Copp
(201) 829-4337
bellcore!copp
=================
Subject: police mans beard is half constucted
The policemans beard is half constructed was written by
Ractor. Its pres ently being released on micros by Hayden i belive.
Ive seen it for the mac and i bm pc. it an excelent program.
S.David Streiff
Univ of Hartford
W Hartford CT
BitNet: STREIFF@HARTFORD.BITNET
====================
From: Robert Farrell <farrell-robert@arpa.yale>
Subject: Eliza
I have a small but interesting Eliza that I wrote in T (a dialect of
Scheme). I could put it in the public domain if you want it. It
emulates a car mechanic and is a lot of fun. It would be easy to add
more rules or convert it to another lisp, since it is written clearly
and is pretty well documented. Why do you want an Eliza - just for fun
or for something you are doing (e.g. teaching pattern-matching)? I
have included a transcript and a few notes about the program below.
Just send me a note and I will give you the whole program ... it is
only about 700 lines long. If you don't have some sort of LISP to
convert it to, or don't want to do any work converting the program,
then this isn't the Eliza for you.
E E
D D --> "Rob calling"
C C
G--G
Farrell@YALE.ARPA *** decvax!yale!Farrell.UUCP *** BITNET:
Farrell@yalecs.BITNET
====================
From: Chris Price <cjp@uk.ac.aber.cs>
Subject: Re: Eliza...
Eliza should be easily available at Edinburgh.
I can think of two places where it is free:
1) In Poplog as a library, you do pop11 -eliza
2) In GNU emacs - a free version of emacs widely distributed.
Cheers,
Chris Price.
=======================
From: Mike Urban <uucp@uucp.sdcrdcf>
Organization: TRW Inc., Redondo Beach, CA
In article <310@its63b.ed.ac.uk> you write:
>
>I have heard about the various "chatty" programs which have been written
>to imitate Psychiatrists (sp?), Doctors, Scribe's, etc, but have never
>had the opportunity to play (play?!) use any of these programs. This kind
>of software interests me a lot and would like to know if any of them
>(or similar type) are freely available.
>
>There is a book, I believe, titled "The Policeman's Beard is
>Half-Constructed" which chronicles the 'works' of one of these
>programs (I can't remember which).
I have ported a version of "DOCTOR" (a.k.a. Eliza) to run with David Betz's
Xlisp 1.6. Xlisp is a public-domain version of LISP and has been posted
to the net in its Unix incarnation. My version includes an Esperanto
translation of DOCTOR's "script", intended to provide language practice.
"The Policeman's Beard" is based on Racter. I don't know about its
availability.
--
Dougie Nisbet
University of Edinburgh | <UUCP> ...seismo!mcvax!ukc!its63b!dougie
Medical Statistics Unit | <JANET> dougie@uk.ac.ed.its63b
Medical School
Teviot Place
Edinburgh
Scotland
------------------------------
Date: Thu, 12 Mar 87 16:01:37 CST
From: Will Hill <hill%hi.mcc.com@mcc.com>
Subject: Humor Interface Project
For the AIlist.
Remember the Viet Cong? Well, I'll get back to them in a minute.
This memo announces the formation of a new project, the Humor
Interface Project, sometimes known in revolutionary circles as the
Interface-esE liberation Army, or, IEA, (pronounced at the top of
your lungs, as EYEEE-EEEEE-AHHHHH... while drumming your chest).
The members seek no official status whatsoever and will accept none
when they succeed.
I am not a member of this group but have been retained by them as
their publicist for an indecent sum of money. They have requested
that I set before the public their noble raisin d'etre [sic],
their altruistic intentions, their anti-establishment methods, and
of course, their consulting fee scale and answering service number.
This project formed at a recent conference during the "HCI and
All Possible Universes" session. Or was it the "HCI and All Possible
Universes Containing Alcohol" session? Anyway, the group intends to
implement, study, reflect and publish about humorous interface
techniques.
The idea started with the question, "Suppose we tried to make a
computer act like Robin Williams or Jonathan Winters? Not staged
humor, not joke telling, not static cartoons but interactive...
contextual humor, adlibbing on material provided by the combination
of user and system programmer?" From there things went straight down
or straight up depending upon your perspective.
The group shared their favorites. Windows that crack or melt into a
slag heap. The MacIntosh IBM DOS emulator that, when fired up,
begins to put up a zippy MacIntosh screen, stops halfway down the
screen to declare, "Oops? Sorry. You wanted 195Os technology." It
then goes into command line mode. The supposed unused ROM hook in
the Mac that would have caused a monkey to dance across the screen
ONCE upon the 7698th (or whatever) boot of the machine. Insects
crawling around the screen.
As you read this, project programmers in ski-masks are already coding
up:
ELUSIVE MENU: When the mouse cursor enters such menus, the menus
dodge away while insulting the user with appropriate language and
gestures. Somebody informed us, this is just like the Mac Bomb
program.
CRASHING WINDOWS: You begin to move a window. Suddenly it
accelerates out of your control up toward the corner of the screen.
When it reaches the corner, it smashes to pieces, falling to the
bottom of the screen. Appropriate sounds effects are heard. Email
is sent to the site manager blaming you for the broken window.
AEROBIC WINDOWS: You begin to move a window and suddenly it
accelerates out of your control bouncing around the screen faster
and faster. It finally slows down an sits on your screen off in the
direction you were moving it, but huffing and puffing, sort of
expanding in and out. You begin working again, it's breathing slows
and stops after a few moments.
FONTS: that scream, melt, sigh or beg as you delete them. Giggle as
you transpose characters. Yawn when you come back to them in the
morning. Burp when you edit them after lunch.
PEOPLE INSIDE THE MONITOR: You get an error. A large face leans in
from the left, gives you a "Lettermanesque look", like he's got a
horrible flavor on his tongue, and then leans back out of the
monitor.
ENCRYPTION WAVES undulate through your current text buffer
occasionally stopping at your cursor to make stupid demands. They
go away for a while when you give in.
GIGANTIC SCREEN-FILLING BODY PART MOUSE CURSOR ICONS: You can move
them no more than a half inch in each direction. Need the
Interface-esE liberation Army say more?
The group suspects that a lot could learned about the un-obvious
communication possibilities of computational media by analyzing
successful and failed humor attempts. At least unspoken
expectations of interface experience should stand out in bold relief
as humor violates them. Misunderstandings of those same
expectations and experiences should stand out as humor fails.
Back to the Viet Cong. Remember that a large percentage of the South
Vietnamese Government was V.C.? Its the same way with the Humorous
Interface Project. You're part of it. We're collecting examples
of humorous interface techniques. They might be implemented or not If
you know of some, please send them along to will@mcc.com . We'd much
appreciate it. At sometime, somehow, we'll publish the best of what
you send in back out into the community. Send code if you like.
I'll end with a quote from the HIP group.
"The project is putting together a macro, With-Humorous-Interface.
Dare you run inside it? Who knows what you'll see and hear next
time you cycle through text called back from the kill ring. Text
YOU killed."
will@mcc.com
publicist for The Humor Interface Project,
Alias "Humor In Your Face", "Humid Interface" And "Interface-Ese
liberation Army (EYEEE-EEE-AHHH...)
------------------------------
End of AIList Digest
********************
∂16-Mar-87 0017 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #80
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 16 Mar 87 00:17:24 PST
Date: Sun 15 Mar 1987 21:52-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #80
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 16 Mar 1987 Volume 5 : Issue 80
Today's Topics:
Seminars - Machine Learning: Unifying Principles, Progress (GMR) &
Search Algorithms (CMU) &
Anatomy of a Case-Based Inference (CMU),
Conference - AI and Law (Program and Registration Info)
----------------------------------------------------------------------
Date: Thu, 12 Mar 87 16:41 EST
From: "R. Uthurusamy" <SAMY%gmr.com@RELAY.CS.NET>
Subject: Seminar - Machine Learning: Unifying Principles, Progress (GMR)
Seminar at the General Motors Research Laboratories in Warren, Michigan.
Friday, March 27, 1987 at 10 a.m.
MACHINE LEARNING : UNIFYING PRINCIPLES and RECENT PROGRESS
RYSZARD S. MICHALSKI
Director of the Artificial Intelligence Laboratory and
Professor of Computer Science and Medical Information Science
University of Illinois, Urbana-Champaign, Illinois 61801
Machine learning, a field concerned with developing computational theories
of learning and constructing learning machines, is now one of the most active
research areas in artificial intelligence. An inference-based theory of
learning will be presented that unifies the basic learning strategies.
Special attention will be given to inductive learning strategies, which
include learning from examples and learning from observation and discovery.
We will show that inductive learning can be viewed as a goal-oriented and
resource-constrained inference process. This process draws upon the
learner's background knowledge, and involves a novel type of inference
rules, called 'inductive inference' rules. In contrast with truth-preserving
deductive rules, inductive rules are falsity-preserving.
Several projects conducted at our AI Laboratory at Illinois will be briefly
reviewed, and illustrated by examples from implemented programs.
Non-GMR personnel interested in attending please contact
R. Uthurusamy [ samy@gmr.com ] 313-986-1989
------------------------------
Date: 12 Mar 1987 0717-EST
From: Rich Thomason <THOMASON@C.CS.CMU.EDU>
Subject: Seminar - Search Algorithms (CMU)
COMPUTER SCIENCE COLLOQUIUM PITT/CMU
SPEAKER: David Mutchler (Naval Research Laboratory)
TITLE: What Search Algorithm Gives Optimal Average-Case Performance
When Search Resources Are Highly Limited?
DATE: March 13, 1987
TIME: 1:00 - 2:00 P.M.
PLACE: 228 Alumni Hall, University of Pittsburgh
Searching the state-space for an acceptable solution is a
fundamental activity for many AI programs. Complete search of the
state-space is typically infeasible. Instead, one relies on whatever
heuristic information is available. Here is one interesting question
that then arises: Given n search resources, how can one dynamically
utilize those resources to achieve (on average) as good a solution as
possible?
In this talk, I will:
(1) present a probabilistic model in which to study this
question;
(2) state two theorems that together answer the above
question in the context of that model;
(3) explain how branching processes and branching random
walks are used to prove the theorems.
Here is a brief description of the model I will be using. A
least-cost root-to-leaf path is sought in a random tree. The tree is
known to be binary and complete to depth N. Arc costs are
independently set either to 1 (with probability p) or to 0 (with
probability 1-p). The cost of a leaf is the sum of the arc costs on
the path from the root to that leaf. The searcher (scout) can learn
n arc values; after having done so, a leaf must be selected. It is
easy to see how the leaf should be chosen. The interesting question
is that: how should the scout dynamically allocated the n search
resources to minimize the average cost of the leaf selected?
------------------------------
Date: 13 Mar 87 15:59:55 EST
From: Marcella.Zaragoza@isl1.ri.cmu.edu
Subject: Seminar - Anatomy of a Case-Based Inference (CMU)
AI SEMINAR
TOPIC: "The Anatomy of a Case-Based Inference"
SPEAKER: Janet Kolodner, Georgia Tech
WHEN: Tuesday, March 17, 1987, 3:30 p.m.
WHERE: Wean Hall 5409
***If you wish to meet with the speaker on Tuesday,***
please call Marce at x8818
ABSTRACT: Case-based reasoning is reasoning done on the basis of one
or a set of previous experiences (or cases), rather than from general
reasonable rules. Case-based inference is an inference made from a
previous experience. In this medium, we can look at how case-based
inference can be controlled, requirements for making a careful case-based
inference, and what support mechanisms are necessary to make case-based
inference feasible.
------------------------------
Date: Fri, 13 Mar 87 19:01:56 EST
From: hafner%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: Conference - AI and Law (Program and Registration Info)
The First
International Conference on Artificial Intelligence and Law
May 27-29, 1987
Northeastern University, Boston, Massachusetts
Sponsored by: The Center for Law and Computer Science
Northeastern University
In Co-operation with ACM SIGART
Schedule of Activities:
Wednesday, May 27
8:30 a.m. - 12:30 p.m. - Tutorials
2:00 p.m. - 6:00 p.m. - Research Presentations (see list below)
7:00 p.m. - 10:00 p.m. - Welcoming Reception - NU Faculty Center
Thursday and Friday, May 28-29
8:30 a.m. - 6:00 p.m. - Research Presentations (continued)
Thursday evening, May 28 - 7:00 p.m. - Gala Banquet at the Colonnade Hotel
Tutorials:
A. "Introduction to Artificial Intelligence (For Lawyers)." Edwina L.
Rissland,
Associate Professor of Computer and Information Sciences, University of
Massachusetts at Amherst, and Lecturer in Law, Harvard Law School, will
present the fundamentals of AI from the perspective of a legal expert.
B. "Applying Artificial Intelligence to Law: Opportunities and Challenges."
Donald H. Berman, Richardson Professor of Law, and Carole D. Hafner,
Associate Professor of Computer Science, Northeastern University, will
survey the past accomplishments and current goals of research in AI and Law.
Panels:
"The Impact of Artificial Intelligence on the Legal System."
Moderated by Cary
G. deBessonet, Director of the Law and Artificial Intelligence Project,
Louisiana State Law Institute.
"Modeling the Legal Reasoning Process: Formal and Computational Approaches."
Moderated by L. Thorne McCarty, Professor of Computer Science and Law, Rutgers
University.
List of Research Presentations: (final schedule is not yet determined)
"Expert Systems in Law: The Datalex Project"
Graham Greenleaf, Andrew Mowbray, Alan L. Tyree
Faculty of Law, University of Sydney, AUSTRALIA
"The Application of Expert Systems Technology to Case-Based Law"
J.C. Smith, Cal Deedman
Faculty of Law, University of British Columbia, CANADA
"Legal Reasoning in 3-D"
Marvin Belzer
Advanced Computational Methods Center
University of Georgia, USA
"Explanation for an Expert System that Performs Estate Planning"
Dean A. Schlobohm, Donald A. Waterman
Moraga, California, USA
"Expert Systems in Law: Out of the Research Laboratory and into the
Marketplace"
Richard E. Susskind
Ernst & Whinney
London, ENGLAND
"An Expert System for Screening Employee Pension Plans for the
Internal Revenue Service"
Gary Grady, Ramesh S. Patil
Internal Revenue Service
Washington, D.C. USA
"Conceptual Legal Document Retrieval Using the RUBRIC System"
Richard M. Tong, Clifford A. Reid, Peter R. Douglas, Gregory J. Crowe
Advanced Decision Systems
Mountain View, California USA
"Conceptual Retrieval and Case Law"
Judith P. Dick
Faculty of Library and Information Science, University of Toronto
Toronto, Ontario CANADA
"A Process Specification of Expert Lawyer Reasoning"
D. Peter O'Neill
Harvard Law School
Cambridge, Massachusetts USA
"Conceptual Organization of Case Law Knowledge Bases"
Carole D. Hafner
The Center for Law and Computer Science, Northeastern University
Boston, Massachusetts USA
"A Case-Based System for Trade Secrets Law"
Edwina L. Rissland Kevin D. Ashley
Department of Computer and Information Science,
University of Massachusetts, Amherst, Massachusetts USA
"But, See, Accord: Generating Blue Book Citations in HYPO"
Kevin D. Ashley, Edwina L. Rissland
Department of Computer and Information Science
University of Massachusetts, Amherst Massachusetts USA
"A Connectionist Approach to Conceptual Information Retrieval"
Richard K. Belew
Computer Science and Engineering Department, Univ. of California
San Diego, California USA
"System = Program + Programmers + Law"
Naftaly H. Minsky, David Rozenshtein
Department of Computer Science, Rutgers University
New Brunswick, New Jersey USA
"A Natural Language Based Legal Expert System Project for Consultation
and Tutoring -- The LEX Project"
F. Haft, R.P. Jones, Th. Wetter
IBM Heidelberg Scientific Centre
Heidelberg, WEST GERMANY
"Handling of Significant Deviations from Boilerplate Text in the SPADES
System"
Gary Morris, Keith Taylor, Maury Harwood
Internal Revenue Service
Washington, D.C. USA
"Legal Data Modeling: The Prohibited Transaction Exemption Analyst"
Keith Bellairs
Management Science Department, University of Minnesota
Minneapolis, Minnesota USA
"Reasoning about `Hard' Cases in Talmudic Law
Steven Weiner
Somerville, Massachusetts USA
"Designing Text Retrieval Systems for `Conceptual Searching'"
Jon Bing
Norwegian Research Center for Computers and Law
Oslo, NORWAY
"Support for Policy Makers: Formulating Legislation with the Aid of
Logical Models"
T.J.M. Bench-Capon
Department of Computing, Imperial College
London, ENGLAND
"Further Comments on McCarty's Semantics for Deontic Logic"
Andrew J.I. Jones
University of Oslo
Oslo, NORWAY
"Experiments Using Expert Systems Technology for Teaching Law: Special
Knowledge Representation Approaches in DEFAULT and EVAN"
Roger D. Purdy
School of Law, The University of Akron
Akron, Ohio USA
"OBLOG-2: A Hybrid Knowledge Representation System for Defeasible Reasoning"
Thomas F. Gordon
FS-INFRE, GMD
Sankt Augustin, WEST GERMANY
"ESPLEX: A Rule and Conceptual Model for Representing Statutes"
Carlo Biogioli, Paola Mariana, Daniela Tiscornia
Istituto per la Documentazione Giuridica
Florence, ITALY
"A PROLOG Model of the Income Tax Act of Canada"
David M. Sherman
Maintnix Services
Thornhill, Ontario CANADA
"Some Problems in Designing Expert Systems to Aid Legal Reasoning"
Layman E. Allen, Charles S. Saxon
Law School, The University of Michigan
Ann Arbor, Michigan USA
"Precedent-Based Legal Reasoning and Knowledge Acquisition in Contract Law:
A Process Model"
Seth R. Goldman, Michael G. Dyer, Margot Flowers
Artificial Intelligence Laboratory, University of California, Los Angeles
Los Angeles, California USA
"Logic Programming for Large Scale Applications in Law: A Formalism of
Supplementary Benefit Legislation"
T.J.M. Bench-Capon, G.O. Robinson, T.W. Routen, M.J. Sergot
Department of Computing, Imperial College
London, ENGLAND
___________________________________________________________________________
Program Committee Conference Information
----------------- ----------------------
L.Thorne McCarty, Chair Prof. Carole D. Hafner, Conference Chair
Donald H. Berman (617) 437-5116
Michael G. Dyer Ms. Rita Laffey, Registration
Anne v.d. L. Gardner (617) 437-3346
Edwina L. Rissland
Marek J. Sergot
Housing Information
Special Conference Rates are available at the following hotels:
(Mention "Northeastern University Computers and Law Conference")
1. The Colonnade Hotel - $75 single/$95 double + tax ($8 parking)
120 Huntington Avenue, Boston, MA (617) 424-7000
2. The Midtown Hotel - $58 single/$63 double + tax (includes free parking)
220 Huntington Avenue, Boston, MA (617) 262-1000 or 1-800-343-1177
Both of these hotels are less than a 10-minute walk from the Conference.
Rooms have also been arranged at Boston University dormitories, a
20-minute walk from the conference, or a 10-minute bus ride and a 5-minute
walk. The rates are $29 single/$24 (per person) double. To reserve a
room in the dormitory, use the attached registration form.
SPACE IS LIMITED - RESERVE EARLY!!
Conference Registration Fee (does not include tutorial or banquet)
Regular Full-time Student
------- -----------------
Received by April 20 $95 $55
Received after April 20 $135 $85
Gala Banquest - May 28 ($40/person)
Tutorial Fee: ($50 with conference registration $100 otherwise)
Dormitory Fee ($29/night single, $24/night double)
------------------------------
End of AIList Digest
********************
∂16-Mar-87 0219 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #81
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 16 Mar 87 02:19:15 PST
Date: Sun 15 Mar 1987 21:55-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #81
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 16 Mar 1987 Volume 5 : Issue 81
Today's Topics:
Conference - 2nd SUNY Grad. Conf. on CS (Review)
----------------------------------------------------------------------
Date: Fri, 13 Mar 87 14:19:02 EST
From: "William J. Rapaport" <rapaport%buffalo.csnet@RELAY.CS.NET>
Subject: Conference - 2nd SUNY Grad. Conf. on CS (Review)
SECOND ANNUAL SUNY BUFFALO GRADUATE CONFERENCE ON COMPUTER SCIENCE
William J. Rapaport
Department of Computer Science
SUNY Buffalo
Buffalo, NY 14260
rapaport@buffalo.csnet
On 10 March 1987, the graduate students in the Department of Computer
Science at SUNY Buffalo held their second annual Graduate Conference on
Computer Science. (For a report on the first one, see SIGART No. 99,
pp. 22-24.) This time, the conference took on an international flavor,
with talks by graduate students from the University of Toronto and the
University of Rochester, in addition to talks by our own students. Once
again, the conference was flawlessly mounted. The conference was
sponsored by the SUNY Buffalo Department of Computer Science, the SUNY
Buffalo Computer Science Graduate Student Association, the SUNY Buffalo
Graduate Student Association, and the Niagara Frontier Chapter of the
ACM. Approximately 150 people from area colleges and industry attended.
A SUNY Buffalo Department of Computer Science Technical Report with
extended abstracts of the talks (James Geller & Keith Bettinger (eds.),
_UBGCSS-87: Proceedings of the Second Annual UB Graduate Conference on
Computer Science_, Technical Report 87-04, March 1987) is available by
contacting the chair of the organizing committee, Scott Campbell,
Department of Computer Science, SUNY Buffalo, Buffalo, NY 14260,
campbl@buffalo.csnet. Following are the abstracts of the talks.
Ted F. Pawlicki
SUNY Buffalo
"The Representation of Visual Knowledge"
This paper reports on preliminary research into the representation of
knowledge necessary for visual recognition. The problem is broken down
into three parts: the actual knowledge that needs to be represented,
the form that the representation should take, and how the knowledge
itself and its representation should combine to facilitate the visual
recognition task. The knowledge chosen to represent is a formalization
of the theory of Recognition by Component. The representation chosen is
a semantic network.
John M. Mellor-Crummey
University of Rochester
"Parallel Program Debugging with Partial Orders"
Parallel programs are considerably more difficult to debug than
sequential programs, because successive executions of a parallel program
often do not exhibit the same behavior. Instant Replay is a new
technique for reproducing parallel-program executions. Partial orders
of significant events are recorded during program execution and used to
enforce equivalence of execution replays. This technique (1) requires
less time and space to save information for program replay than other
methods, (2) is independent of the form of interprocess communication,
(3) provides for replay of an entire program, rather than individual
processes, (4) introduces no centralized bottlenecks, and (5) does not
require synchronized clocks or globally-consistent logical time. Some
performance results of a prototype on the BBN Butterfly [TM] Parallel
Processor will be presented, and it will be shown how Instant Replay can
be used in the debugging cycle for parallel programs.
Timothy D. Thomas and Susan J. Wroblewski
SUNY Buffalo
"Efficient Trouble Shooting in an Industrial Environment"
Our work involves designing and implementing a real-time system for
trouble shooting in an industrial environment. The system emulates the
kind of problem-solving knowledge and behavior typical of a human expert
after years of on-the-job experience. Our system, PASTE (Process
Analysis for Solving Trouble Efficiently), is to be used in a real-time
environment. It is because of this constraint that the design of an
efficient system was of great importance. PASTE has a number of
efficiency techniques that eliminate redundancy in remedy suggestion
and that decrease response time.
Ching-Huei Wang
SUNY Buffalo
"ABLS: An Object Recognition System for Locating Address Blocks on
Mail Pieces"
ABLS (Address Block Location System), a system for locating address
blocks on mail pieces, represents both a specific solution to postal
automation and a general framework for coordinating a collection of
specialized image-processing tools to opportunistically detect objects
in images. Images that ABLS deals with range from those having a high
degree of global spatial structure (e.g., carefully prepared letter mail
envelopes which conform to specifications) to those with no structure
(e.g., magazines with randomly pasted address labels). Its
problem-solving architecture is based on the blackboard model and
utilizes a dependency graph, knowledge rules, and a blackboard.
Diane Horton and Graeme Hirst
University of Toronto
"Presuppositions as Beliefs: A New Approach"
Most existing theories of presupposition implicitly assume that
presuppositions are facts and that all agents involved in a discourse
share belief in the presuppositions that it generates. We argue that
these assumptions are unrealistic and can be eliminated by treating
each presupposition as the belief of an agent. We describe a new model,
including an improved definition of presupposition, that takes this
approach. The new model is more realistic and can handle cases of
presupposition projection that could not be handled otherwise.
Norman D. Wahl and Susan E. Miller
SUNY Buffalo
"Hypercube Algorithms to Determine Geometric Properties of Digitized Pictures"
This research focuses on implementing algorithms to solve geometric
problems of digitized pictures on hypercube multiprocessors.
Specifically, in this paper, we present algorithms and paradigms for
solving the connected component labeling problem. Work is ongoing to
complete implementations of these algorithms and obtain running times on
the Intel iPSC and Ncube hypercubes. The goal of this study is to
determine under what circumstances (if any) each of the various
algorithms is most appropriate.
Deborah Walters and Ganapathy Krishnan
SUNY Buffalo
"Bottom-up Image Analysis for Color Separation"
A system for automatic color separation for use in the printing industry
is described. The goal of this research was to automate the
labor-intensive preprocessing required before a graphics system can
process the image. This system makes no assumptions about the semantic
content of the image. The processing is entirely bottom-up and is based
on image features used by the human visual system during the early
stages of processing. The image is convolved with oriented edge
operators, and the responses are stored in the Rho-Space representation.
A number of parallel operations are performed in Rho-Space, and the
image is segmented into perceptually significant parts, which can then
be colored using an interactive graphics system.
Bart Selman
University of Toronto
"Vivid Representations and Analogues"
Levesque introduced the notion of a vivid knowledge representation. A
vivid scheme contains complete knowledge in a tractable form. A closely
related concept is that of an analogical representation or analogue.
Sloman characterizes analogues as representations that are in some sense
direct models of the domain, as opposed to representations consisting of
a description in some general language. The prototypical example of an
analogical representation is a pictorial representation, which is also
an important source of vivid knowledge. We are studying these types of
representations for their possible application in computationally
tractable knowledge-representation systems. In particular, we are
studying how information in a non-analogical (or non-vivid) form can be
translated into an analogical (or vivid) form, using for example
defaults and prototypes. This talk will cover the properties of vivid
and analogical representations, a description of their relationship to
each other, and some initial ideas on the translation process.
Soteria Svorou
SUNY Buffalo
"The Semantics of Spatial Extension Terms in Modern Greek"
In recent years, there have been increasing efforts to uncover the
nature of the human mind by studying the structure of its building
blocks: concepts. Partaking in this enterprise, this study explores
the domain of spatial extension categories by looking at the way
language treats them. It shows that lexical contrasts of Modern Greek
in the domain of spatial extension reflect the perceptual strategies of
"orientation" and "Gestalt" and their interaction with the concept of
"boundedness", which speakers employ in the description of everyday
objects.
Yong Ho Jang and Hing Kai Hung
SUNY Buffalo
"Semantics of a Recursive Procedure with Parameters and Aliasing"
We consider a subset of an Algol-like programming language that
includes blocks and recursive procedures, with value and location
parameter passing. We develop the operational and denotational
semantics for both static and dynamic scope, with their different
aliasing mechanisms. The main advantage of our approach is that the
denotational semantics is compositional and can systematically handle
the various scope and aliasing features.
Josh D. Tenenberg and Leo B. Hartman
University of Rochester
"Naive Physics and the Control of Inference"
Hayes proposed the naive physics program in order eventually to
address problems involving the control of inference. At the time of the
proposal, progress toward solutions of these problems seemed impeded by
the lack of a well-defined body of knowledge of challenging size. The
building of a formally interpretable encoding of the common-sense
knowledge that people use to deal with the physical world seemed to fill
this need. It was argued that the knowledge be expressed in first-order
logic or an equivalent language in order to separate declarative
information from control information. We argue here that no finite
encoding of a formal theory can be completely separated from control
choices by virtue of there being well-defined measures of the depth of a
theorem in the deductive closure of a theory. In addition, any control
choice is a commitment to a particular set of statistical properties of
the problems an agent faces, and the measurement of such properties is
required to evaluate these choices.
Zhigang Xiang
SUNY Buffalo
"Multi-Level Model-Based Diagnostic Reasoning"
Diagnostic systems capable of reasoning from _functional_ and
_structural_ knowledge are _model-based_ systems. The uniqueness of our
work is that problems of diagnosis that need not only functional and
_logical_ structural knowledge but also _spatial_ structural knowledge
are to be the focus. Towards this goal, we propose a framework for
organizing, representing, and reasoning with an integrated knowledge
base that includes multiple levels of abstraction of the physical
system. More specifically, a physical system is decomposed into
physical and logical components. Analogical (geometrical) and
propositional (topological) spatial structural information are
associated with physical components. The latter is mutually related to
logical components. Functional relationships are established between
logical components. Logical reasoning infers the functional status of
logical components, whereas spatial reasoning performs fault
localization. The framework is carried out using semantic-network
representations. The implementation is independent of any given domain
of application. The system, when given a description of a physical
system's spatial structure, logical structure, and functional
relationships between logical components, performs logical as well as
spatial reasoning to locate faulty components, lesions, etc., from
symptoms and findings. Domain-specific examples include circuitry fault
localization and neuroanatomic localization.
------------------------------
End of AIList Digest
********************
∂17-Mar-87 2335 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #82
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 17 Mar 87 23:35:25 PST
Date: Tue 17 Mar 1987 20:56-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #82
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 18 Mar 1987 Volume 5 : Issue 82
Today's Topics:
Queries - Public-Domain Planners & Kyoto Common Lisp &
Toshiba Voice Recognition Chip & OPS5 Public-Domain Code &
Rete match, OPSxx, Charles Forgy & AI in Space Stations &
Connectionist Computing vs Distributed Computing,
Announcement - DEC 10 and PDP-6 History Project,
Review - Borning's "Computers...& Nuclean-War" in NY Times
----------------------------------------------------------------------
Date: Mon, 16 Mar 87 09:07:14 -0100
From: unido!gmdzi!hertz@seismo.CSS.GOV (Joachim Hertzberg)
Subject: Hertzberg2
Does anybody have reimplementations (or the original implementations
or micro-implementations) on standard-machines (VAX, SYMBOLICS, ...)
of one of the "classical" AI-planners publicly available (for
non-profit organizations)?
Joachim Hertzberg
GMD
Postfach 1240
5205 ST. AUGUSTIN
W-GERMANY
hertz%xps@gmdzi.usenet
------------------------------
Date: Mon, 16 Mar 87 15:30:19 est
From: michael@dolphin.BU.EDU (Michael Forte)
Subject: Kyoto Common Lisp
My name is Michael Forte. I work in the Computer Graphics Laboratory at
the Boston University Academic Computing Center. Presently, I am researching
the uses of Lisp for graphics systems, particularly for user interfaces.
We are using a Celerity 1260 dual processor machine for our graphics
number crunching. Unfortunately, there is no Lisp available for this
machine yet, and Celerity says it will be quite a while before Common Lisp
(my preference, for portability reasons) is available for their line of
machines.
I was referred to you for information on the availablity of Kyoto Common Lisp.
We do have a very good C compiler, and if Kyoto Lisp is written in C I could
probably port it to our machine easily.
Would you please send me information about Kyoto Common Lisp, including
pricing, educational discounts, etc.
You may write to me at:
Michael Forte
Computer Graphics Lab
Academic Computing Center
111 Cummington Street
Boston University
Boston, Mass. 02215
if email is not appropriate. I may also be reached by phone at
617-353-2780. Thanks.
------------------------------
Date: 16 Mar 87 18:58:04 GMT
From: ssc-vax!bcsaic!michaelm@BEAVER.CS.WASHINGTON.EDU (Michael
Maxwell)
Subject: Re: Toshiba voice recognition chip
In article <1895@hoptoad.uucp> gnu@hoptoad.uucp (John Gilmore) writes:
>A recent article in Newsbytes Japan mentions:
>
> Toshiba's Voice Recognition LSI -- Toshiba (Tokyo) has developed
> a powerful LSI for recognizing human speech. This new product
> recognizes a variety of spoken sounds with 95% accuracy.
> Toshiba plans to use this LSI for a voice input system for its
> word processors.
This is a rather meaningless statement, even for a press release. How many
sounds? What kind of sounds (individual phones (~=letters), words, phrases,
whistles etc.)? If it's talking about speech sounds (as opposed to any sounds
the human vocal tract can make), what is the size of the
vocabulary one can build with it? Do words have to be separated by silence?
Does it work in real time? Is it even trainable? (I can imagine having to
talk to my computer with a Japanese accent :-) If anyone knows more about
this...
There are lots of voice recognition boards out there. Most are fairly
primitive, which is part of the reason we haven't them used more.
Need I say that my employer doesn't necessarily share my opinion?
--
Mike Maxwell
Boeing Advanced Technology Center
arpa: michaelm@boeing.com
uucp: uw-beaver!uw-june!bcsaic!michaelm
------------------------------
Date: 16 Mar 87 00:22:54 GMT
From: clyde!masscomp!wang7!eric@rutgers.rutgers.edu (eric)
Subject: OPS5 PUBLIC DOMAIN CODE
HELP!!!!!!!!!! I NEED TO GET A COPY OF THE COMMON LISP OPS5 INTERPRETER
IN THE PUBLIC DOMAIN. I need it yesterday! Please email to me. I will
give you my first born son or considerable gratitude.
Eric Van Tassell
clyde!bonnie!masscomp!wang7!eric
clyde!bonnie!masscomp!dlcdev!eric
dlcdev!eric@eddie.mit.edu
------------------------------
Date: 15 Mar 87 23:54:46 GMT
From: clyde!masscomp!wang7!eric@rutgers.rutgers.edu (eric)
Subject: Rete match, OPSxx, Charles Forgy
Hello, I'm a grad student at B.U. doing some investigation
of production systems. I am interested in any and all information people
on the net may have relating to the rete match algorithm and the OPS family
of languages. Also does anyone know if Dr. Charles Forgy can be e-mail to on
the net? Thanks in advance. Remember if you email quickly, the life you save
may be mine.
Eric Van Tassell
clyde!bonnie!masscomp!wang7!eric
clyde!bonnie!masscomp!dlcdev!eric
harvard!mit-eddie!dlcdev!eric
dlcdev!eric@eddie.mit.edu
[CLF@G.CS.CMU.EDU -- KIL]
------------------------------
Date: 17 Mar 87 16:20:57 GMT
From: uwai!mehta@rsch.wisc.edu (Shekhar Mehta.)
Subject: AI - its use in Space stations
I would like to know how AI would be useful for space stations.
I am particularly interested in its application considering the distance
between the space craft and earth ( and therefore there being finite time for
commands to given from earth stations). How and in what way will AI deal with
this problem.
I would like to get some pointers as to where to begin searching for AI's
application in space ( particularly the space station).
shekhar mehta
mehta@ai.wisc.edu
------------------------------
Date: 16 Mar 87 12:40:15 GMT
From: Dekang Lindek <mcvax!cs.strath.ac.uk!lindek@seismo.CSS.GOV>
Reply-to: lindek@cs.strath.ac.uk (Dekang Lindek)
Subject: diff "connectionist computing" "distributed computing"
Any one know the result of the title of this article?
advThanksance.
!-@-#-$-%-↑-&-*-(-)-!-@-#-$-%-↑-&-*-(-)-!-@-#-$-%-↑-&-*-(-)
Dekang Lin
Dept. of CS
Univ. of Strathclyde
26 Richmond St.
Glasgow, G1 1XH, U.K.
lindek%cs.strath.ac.uk@ucl-cs.arpa
....!seismo!mcvax!ukc!strath-cs!lindek
------------------------------
Date: 16 Mar 1987 1311-EST
From: "Joe Dempster, DTN: 336.2252 AT&T: 609.665.8711"
<DEMPSTER@MARLBORO.DEC.COM>
Subject: Announcement of the DEC 10 and PDP-6 history project
(PROJECT-10262)
This message originates from 2 sources:
Les Earnest
Computer Science Department
STANFORD UNIVERSITY
Stanford, CA 94305
415.723.9729
ARPA: LES@SAIL.STANFORD.EDU
Joe Dempster
DIGITAL EQUIPMENT CORPORATION
6 Cherry Hill Executive Campus
Route 70
Cherry Hill, NJ 08002
609.665.8711
ARPA: DEMPSTER@MARLBORO.DEC.COM (MARKET)
The goal of this project is to publish an analysis and history of
the evolution, implementation and use of Digital's 36 bit systems.
This period began with the PDP-6 in 1964 and continues today with
TOPS 10/20 development, which is scheduled to end in 1988.
We are working aggressively to finish the project, and have it
published, by March/April 1988. This will require that the
completed manuscript be ready to go into the publication cycle
by August 1987!
The project will attempt to answer the following questions:
1. In what markets/applications were these systems used?
2. Who were the users of these systems and what impact did
roughly 2,500 TOPS 10/20 systems have on their organizations?
3. Who were the principle system architects of these systems?
What features, and if there had been sufficient time to
implement them, would have significantly improved the
architecture?
4. What impact did the decision to continue to examine design
extensions to the architecture have on the usefulness and
acceptability of these systems. This is in contrast to a
more common practice today to work from a detailed design
specification, sometimes dated, building follow-on systems
which provide increased performance through the use of new
component technologies and packaging techniques.
5. What part of the overall design (TOPS10/20) was technology
dependent and what can still be considered "unequaled" in
relation to other computer architectures still undergoing
active development?
6. What type of development environment (both HW and SW)
supported and contributed to the evolution of 36 bit
systems?
7. What influence did TOPS 10/20 have on other vendors system
development?
This history will undoubtedly be assembled from many sources and
participants. Some information will be anecdotal; there will be
interviews with the people involved (users and developers) and technical
papers will be solicited. Of course there will also be the packaging
and assembly of facts as we see them.
The result will hopefully have sufficient depth to serve as:
1. An introductory or advanced text on system design and
hardware/system software implementation.
2. A analysis of the success and difficulties of marketing
complex systems into a very crowded market of competing
alternatives.
3. A catharsis for those of us who have contributed to the
development and use these systems and who will now move
onto new computing architectures and opportunities.
In addition to interviewing directly 25-50 developers, users and
product managers we will continue to work to identify contributors
and significant events up to when the final draft is submitted to
the publisher. Two "topics" are already under development:
1. Rob Gingell from SUN is working on a paper which looks
at extensions to TOPS 20 which would have enhanced its
capabilities.
2. Frank da Cruz and Columbia are summarizing 10 years of
experience and development of TOPS 20 systems. Some
effort will also be made to detail the process which
lead to their selection of a follow-on architecture to
TOPS 20.
There is a need to develop additional topics which represent the
use and application of the technology (TOPS 10/20) in other areas.
Specific recommendations are welcome as are proposals to develop
them. A short abstract should accompany any such proposal. Every
effort will be made to work with individuals or organizations
interested in making such a contribution.
There will be a standalone (no network connections) DECSYSTEM 2020
(YIPYIP) dedicated to supporting the project. This system has a 3
line hunt group, with all lines accessible from a single number
(201.874.8612).
Both YIPYIP and MARKET will have "public" directories for remote
login (<log>DEMPSTER.PROJECT-10262 <Password>LCGLCG). MARKET can
be accessed by modem (617.467.7437), however disk quota is limited.
MARKET's primary purpose <DEMPSTER.PROJECT-10262> is ARPAnet TELNET
access. YIPYIP is a dedicated PROJECT-10262 system. MAIL can also
be sent to DEMPSTER on either system.
YIPYIP and MARKET will keep a running summary of ideas and comments
up on Columbia's BBOARD software. KERMIT also runs on each system
for uploads.
SAIL.STANFORD.EDU will support ARPAnet transfers to a "public" area:
FTP<ret>
CONNECT SAIL.STANFORD.EDU<ret>
SEND AFN.EXT<ret>
DSK: AFN.EXT [PUB,LES]<ret>
SAIL runs WAITS, an operating system similiar to TOPS 10. File
names are limited to 6 characters and extensions limited to 3.
Implementation details:
1. User input is welcomed and desired from all application
and geographic areas.
2. Input from past and present developers is also desired.
3. Throughout the project a secondary goal will be to build
a list of users/locations (installation date, duration and
disposition) of PDP-6 and KA, KI, KL and KS systems.
Serial numbers, if available, are requested.
4. We anticipate that this project will generate a large
volume of information (which we hope will arrive
electronically). Some information, for any number of
reasons, may not be in line with the project's stated
goals. Therefore, all notes, interview material and
submissions will be donated to the Computer Museum in Boston
at the the completion of the project to be available for
future reference and research.
Ideas, contributions, suggestions and criticism are welcome. As these
36 bit systems were the products of a multitude of people, so too
will be the writing of their history.
------------------------------
Date: 16 Mar 87 17:37:54 GMT
From: jon@june.cs.washington.edu (Jon Jacky)
Subject: AI books and paper (Borning's "Computers...& N-war) in NY
TIMES
Eric Sandberg-Diment's regular column in the business section of
the NEW YORK TIMES, called "The
Executive Computer", this Sunday (3/15/87, p. F18, National Edition) reviews
two popular books on computing: Grant Fjermdahl's THE TOMORROW MAKERS and
Theodore Roszak's THE CULT OF INFORMATION (he criticizes both as being
extreme views). At the end, Sandberg-Diment adds:
The artificial intelligence community and, in fact, the entire computer
cabal are nevertheless trying to mislead us into accepting the notion that
the difference between the "mind" of the computer and the mind of man is
merely a matter of degree, and that not only will this difference be
eliminated in short order, but soon people will rank second to computers in
their cognitive abilities and responsiveness.
In contemplating this thesis, the article "Computer system reliability and
nuclear war," by Alan Borning in the February 1987 issue of Communications
of the ACM ($12 from the ACM, Order Dept., POB 64145, Baltimore, MD 21264)
is must reading. Published in a journal not normally decipherable by the
average individual, it is probably the clearest essay to date on why the
Strategic Defense Initiative is both inevitable and doomed to failure.
Here is an instance where information filtering cannot be gainsaid, for
there is no way the nonspecialist could successfully draw on the 140-plus
sources the author used as background for his thesis. The article is also
one that leaves the reader with a sense of fatalism, along with perhaps an
unspoken addendum to Samuel Johnson's observation that "the future is
purchased by the present" -- how expensive it all will be in terms of
humanity. At a time when there is a very real danger of our subjugating
ourselves to machines to an extent far greater than already realized,
readings such as these may well be all that keep our minds from becoming
irreversibly enslaved."
-Jonathan Jacky
University of Washington
------------------------------
End of AIList Digest
********************
∂18-Mar-87 2334 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #83
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 18 Mar 87 23:34:39 PST
Date: Wed 18 Mar 1987 21:24-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #83
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 19 Mar 1987 Volume 5 : Issue 83
Today's Topics:
Seminars - EFFIGY: Symbolic Execution of Programs (IBM) &
Applying Precedents in Case-Based Reasoning (Rochester) &
Learning Decomposition Methods (CMU) &
Circumscriptive Theories (SU),
Conferences - TI's AI Satellite Symposium III &
AAAI Workshop on Battle Management
----------------------------------------------------------------------
Date: Wed, 18 Mar 87 18:21:19 PST
From: IBM Almaden Research Center Calendar <CALENDAR@IBM.COM>
Subject: Seminar - EFFIGY: Symbolic Execution of Programs (IBM)
IBM Almaden Research Center
650 Harry Road
San Jose, CA 95120-6099
EFFIGY: SYMBOLIC EXECUTION OF PROGRAMS
J. C. King, IBM Almaden Research Center
Computer Science Coll. Thurs., March 26 3:00 P.M. Room: Front Aud.
Long ago and far away, a group in IBM Yorktown Heights devised a
computer system called "EFFIGY" which executed computer programs
"symbolically." On a recent archeological dig in musty old CMS files,
I stumbled upon what appeared to be a genuine EFFIGY MODULE. After a
time, with a new FILEDEF and a long forgotten LINK, I was able to
execute the model, just as the ancients did. It was amazing for me to
remember how advanced civilization was, even then (12-15 years ago).
For some reason, the art of symbolic execution never caught on in a
big way, and it has nearly been lost. For those of the younger
generation, who have never seen the chanting and chest beating of the
symbolic executors (sexers for short), I will try to recreate some of
that ancient spirit. Especially with the new projection system in the
Front Auditorium, which is capable of showing computer terminal output
on-line, I can demonstrate this EFFIGY system, as it was only possible
to do before in a one-on-one situation in a Yorktown cave. The sexers
had discovered that the same leverage obtained by using algebra to
understand and prove things about arithmetic can be applied to
computer programs. If one executes a program using mathematical
symbols, instead of numbers, as program inputs, the same algebraic
leverage can be obtained. Of course, the dynamic aspects of program
execution makes this process tantalizingly non trivial. Combining the
well-known concepts of program execution and algebra, the notions of
"proving the correctness of programs" and "inductive assertions" can
be easily understood without knowingly resorting to heavy mathematical
concepts.
Host: R. Williams
(Refreshments at 2:45 P.M.)
------------------------------
Date: Mon, 16 Mar 87 16:46:45 EST
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Applying Precedents in Case-Based Reasoning
(Rochester)
Colloquium
Computer and Information Science
University of Pennsylvania
"Applying Relevant Precedents in a Case-Based Reasoning System"
Kevin D. Ashley
Department of Computer and Information Science
University of Massachusetts at Amherst
The law is an excellent domain to study Case-Based Reasoning (``CBR")
problems since it espouses a doctrine of precedent in which prior
cases are the primary tools for justifying legal conclusions. The law
is also a paradigm for adversarial CBR; there are ``no right answers",
only arguments pitting interpretations of cases and facts against each
other.
This talk will demonstrate techniques employed in the HYPO program for
representing and applying case precedents and hypothetical cases to
assist an attorney in evaluating and making arguments about a new fact
situation. HYPO performs case-based reasoning and, in particular,
models legal reasoning in the domain of trade secrets law. HYPO's key
elements include: (1) a structured case knowledge base (``CKB") of
actual legal cases; (2) an indexing scheme (``dimensions") for
retrieval of relevant precedents from the CKB; (3) techniques for
analyzing a current fact situation (``cfs"); (4) techniques for
``positioning" the cfs with respect to relevant precedent cases in the
CKB and finding the most on point cases (``mopc"); (5) techniques for
manipulating cases (e.g., citing, distinguishing, hybridizing); (6)
techniques for perturbing the cfs to generate hypotheticals that test
the sensitivity of the cfs to changes, particularly with regard to
potentially adverse effects of new damaging facts coming to light and
existing favorable ones being discredited; and (7) the use of ``3-ply"
argument snippets to dry run and debug an argument.
An extended example of HYPO in action on a sample trade secrets case
will be presented. The example will demonstrate how HYPO uses
``dimensions", ``case-analysis-record" and ``claim lattice" mechanisms
to perform indexing and relevancy assessment of precedent cases
dynamically and how it compares and contrasts cases to come up with
the best precedents pro and con a decision.
March 20, 1987
3:00 to 4:30
Room 216
Refreshments Available
2:30-3:00
Faculty Lounge
------------------------------
Date: 18 Mar 87 01:11:28 EST
From: Steven.Minton@cad.cs.cmu.edu
Subject: Seminar - Learning Decomposition Methods (CMU)
This week's speaker is Sridhar Mahadevan. As usual, the seminar is
in 7220 Wean on Friday at 3:15. Come one, come all.
LEARNING DECOMPOSITION METHODS TO IMPROVE HIERARCHICAL
PROBLEM-SOLVING PERFORMANCE
Previous work in machine learning on improving problem-solving
performance has usually assumed a @i(state-space) or "flat"
problem-solving model. However, problem-solvers in complex domains,
such as design, usually employ a hierarchical or problem-reduction
strategy to avoid the combinatorial explosion of possible operator
sequences. Consequently, in order to apply machine learning to
complex domains, hierarchical problem-solvers that automatically
improve their performance need to designed. One general approach is
to design an @i(interactive) problem-solver -- a @i(learning
apprentice) -- that learns from the problem-solving activity of expert
users. In this talk we propose a technique, VBL, by which such a
system can learn new problem-reduction operators, or @i(decomposition
methods), based on a verification of the correctness of example
decompositions. We also discuss two important limitations of the VBL
technique -- intractability of verification and specificity of
generalization -- and propose solutions to them.
------------------------------
Date: 18 Mar 87 1142 PST
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Circumscriptive Theories (SU)
CIRCUMSCRIPTIVE THEORIES
Vladimir Lifschitz
Thursday, March 19, 4pm
Bldg. 160, Room 161K
The use of circumscription for formalizing commonsense knowledge and
reasoning requires that a circumscription policy be selected for each
particular application: we should specify which predicates are
circumscribed, which predicates and functions are allowed to vary,
what priorities between the circumscribed predicates are established,
etc. The circumscription policy is usually described either informally
or using suitable metamathematical notation. In this talk a simple and
general formalism will be proposed which permits describing circumscription
policies by axioms, included in the knowledge base along with the axioms
describing the objects of reasoning.
------------------------------
Date: Mon, 16 Mar 87 14:33:02 cst
From: "Michael T. Gately" <gately%resbld%ti-csl.csnet@RELAY.CS.NET>
Subject: Conference - TI's AI Satellite Symposium III
This is a short extension to Dan Cerys' message of 12-MAR-87
regarding the TI Artificial Intelligence Satellite Symposium.
First, the phone number, 1-800-527-3500 can be used to answer
many questions; such as how to rent a satellite antenna, what
type of video equipment is necessary for different audience
sizes, etc. Second, take note of the unusual time shifting for
different time zones across North America. Finally, the
following is a list of cities which already have public sites
planned. Please call the toll-free number as soon as possible to
reserve a seat.
AI Satellite Symposium III
"AI Productivity Roundtable"
April 8, 1987
Eastern/Rocky Mountain Time Zones (Daylight Times)
9:00 - 13:00
Pacific/Central Time Zones (Daylight Times)
8:00 - 12:00
AI Symposium II condensation
April 8, 1987
Eastern/Rocky Mountain Time Zones (Daylight Times)
14:00 - 15:30
Pacific/Central Time Zones (Daylight Times)
13:00 - 14:30
Atlanta GA Austin TX Boston MA
Chicago IL Cleveland OH Dallas TX
Dayton OH Denver CO Detroit MI
Hartford CT Houston TX Huntsville AL
Kansas City KS Los Angeles CA Miami FL
Milwaukee WI Minneapolis MN Montreal Canada
New York NY Philadelphia PA Raleigh/Durham NC
San Diego CA San Francisco CA San Jose CA
Seattle WA St. Louis MO Summit NJ
Toronto Canada Washington DC
------------------------------
Date: Mon, 16 Mar 87 12:26:17 est
From: elsaesser%mwcamis@mitre.ARPA
Subject: Conference - AAAI Workshop on Battle Management
Issues Concerning AI Applications To Battle Management
University of Washington
Thursday, July 16, 1987
Sponsored by AAAI
Success in applying AI technologies to battle management (e.g., production
and blackboard systems for sensor fusion, constraint propagation for
non-temporal planning tasks) has generated growing interest in the defense
community in developing intelligent battle management aids, workstations,
and systems. Along with this growing interest, there has been an order of
magnitude increase in funding for battle management AI projects (e.g.,
Army-DARPA's Air-Land Battle Management, SAC-JSTPS-RADC-DARPA's
Survivable Adaptive Planning Experiment).
Past successes belie the lag of the AI community in solving technical
issues associated with these projects. These issues include those
associated with cooperating knowledge-based systems, distributed problem
solving, uncertainty management, non-monotonic reasoning, planning,
real-time performance requirements (i.e., the need for parallel or other
advanced architectures), and the ability of users to maintain understanding
and control of the automation.
The purpose of this workshop is to gather together researchers who are
attempting to find solutions to these and related issues and to discuss the
current state of these arts. We believe that not enough has been done in
these key areas areas, and that one result of the workshop might be some
road map of how the community ought to proceed. The issues are so numerous
and the area is large enough that we feel the initial workshop will only
allow us to delineate how much has been done and what needs to be done in
key areas. Thus, the goal is both to articulate where the major gaps are
and which ones have a reasonable chance of solution in some believable
time-frame.
Interested persons should submit an extended abstract of not more than six
pages to either person listed below (no on-line submissions please) on an AI
subject of relevance to the above workshop objectives not later than 1 May
1987. Authors will be notified of acceptances by 1 June 1987, along with
information relative to the workshop administration.
R. Peter Bonasso Chris Elsaesser
(703) 883 6908 (703) 883 6563
bonasso@mitre elsaesser%mwcamis@MITRE
MITRE Washington AI Center
Mail Stop W410
7525 Colshire Drive
McLean, VA 22102
------------------------------
End of AIList Digest
********************
∂23-Mar-87 0231 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #84
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 23 Mar 87 02:31:35 PST
Date: Sun 22 Mar 1987 23:50-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #84
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 23 Mar 1987 Volume 5 : Issue 84
Today's Topics:
Queries - LOOPS Newgroup & Benchmarks for Production Systems &
Expert Systems on AT&T PC6300,
Comments - Toshiba Voice Recognition Chip,
AI Tools - Genetic Algorithms,
Book - Expert Systems: The User Interface,
Paper - Categories and Counterfactuals,
Funding - White Papers on Basic Research in AI
----------------------------------------------------------------------
Date: 19 Mar 87 15:13:08 GMT
From: uwai!beverly@rsch.wisc.edu (Beverly Seavey)
Subject: LOOPS newgroups
Does anyone know how to subscribe to the LOOPS newgroup at Berkeley?
------------------------------
Date: 19 Mar 87 10:22:18 GMT
From: mcvax!ukc!icdoc!cdsm@seismo.css.gov (Chris Moss)
Subject: Benchmarks for production systems
Could anyone send me or point me to an up-to-date listing of any
benchmark figures for production systems. In particular the monkey
and bananas problem in the OPS5 book is often quoted but I don't
have any figures.
Thanks, Chris Moss.
------------------------------
Date: 20 Mar 87 16:31:35 GMT
From: ihnp4!homxb!houxm!mtuxo!mtgzy!mas@ucbvax.Berkeley.EDU
Subject: Expert Systems on AT&T PC6300
We are currently writing the requirements for an "expert"
system to do wiring designs using AT&T PC6300's. We are
exploring various languages and shells that may work best in
our domain. One of our requirements for the language/shell
is a good interface to C routines and graphic libraries.
Is there any body out there who can give us their experience
with the available expert system tools, specifically in
terms of space, speed, and customizing capabilities.
Thanks in advance.
Masood Shariff & John Kee
AT&T Middletown, NJ 07748
ihnp4!mtgzy!mas
------------------------------
Date: Wed, 18 Mar 87 02:12:33 EST
From: Alex.Waibel@CAD.CS.CMU.EDU
Subject: Toshiba Voice Recognition Chip
With respect to the inquiry about the Toshiba Voice Recognition Chip,
here's two words of caution:
First off, recognition performance claims in percent are nice to know,
but in general should be taken with a grain of salt. These
numbers are HEAVILY dependent on whether speech was recorded in a quiet or
noisy environment, whether the speaker is cooperative or not, whether the
test was done speaker-dependently or independently, whether the vocabulary
in question is ambiguous (BOOK, COOK, TOOK) or not (BOOK, UNIVERSITY).
Most of the current systems are also isolated word systems, i.e., one must
make pauses between words. Whether such a system will work or not therefore
relly depends on your particular recognition task and environment.
Japanese has also two convenient properties:
Words are mostly consonant-vowel sequences, and the Japanese writing
system (Kana) consists of essentially sequences of syllable symbols. Toshiba
and other Japanese manufacturers therefore have systems that allow the speaker
to speak one of the (in the order of 100 or so (including some alternates)
kanas at a time and have the word processor then convert a sequence of kanas
into a kanji (the chinese word symbol). Now, unfortunately, this doesn't
carry over easily into English. Since English syllables employ complex
consonants clusters, there are more in the order of 20,000 English syllables
(with 100,000 possible), which makes for a substantially harder recognition
task. Also speaking these syllables in isolation is a lot less natural than
in Japanese since our writing system isn't syllable based. The corresponding
recognition of phonemes in stead of syllables in English is a VERY hard
problem with good recognition accuracy hard to come by.
Toshiba and other manufacturers (in Japan and the USA) have also whole word
based systems, but most of them require training of the system, i.e,
all words in the vocabulary must be read in at least once by the user.
I've seen the systems at Toshiba and they do indeed do impressive work,
but as far as hooking it up to your home computer and talking away in
English, I'm afraid the story is still a little more complicated than that.
Alex Waibel, CMU
------------------------------
Date: 17 Mar 87 21:15:40 GMT
From: hpda!hpcllla!hpclisp!coulter@ucbvax.Berkeley.EDU (Michael
Coulter)
Subject: Re: Genetic Algorithms
John Holland is (or was) at U. of Mich. and has written a very nice book
on genetic algorithms. I once took a class on the subject which he taught.
If you need more information (title, publisher, isbn number, etc.), send
me a note and I'll see if I can find my copy of the book.
-- Michael Coulter ...hpda!hpcllld!coulter
------------------------------
Date: 21 Mar 87 18:05:00 GMT
From: uiucdcsm!matheus@a.cs.uiuc.edu
Subject: Re: Genetic Algorithms
Proceedings of an International Conference
on Genetic Algorithms and their Applications.
John Grefenstette, editor
July 24-26, 1985, Carnegie-Mellon University
Sponsored by:
Texas Instruments, Inc.
U.S. Navy Center for Applied Research
in Artificial Intelligence (NCARAI)
------
Some additional references:
John Holland, "Escaping Brittleness: The Possibilities of General-Purpose
Learning Algorithms Applied to Parallel Rule-Based Systems."
In, Machine Learning, Vol II, Michalski, Carbonell, Mitchell, (Eds.), 1986.
------
Larry Rendell, "Conceptual Knowledge Acquisition in Search."
In, Computational Models of Learning, L. Bolc (Ed.), Springer-Verlag, 1987.
------
David Goldberg, "Computer-aided Gas Pipeline Operation using Genetic
Algorithms and Rule Learning." Ph.D. dissertation, University of
Michigan, 1983.
Christopher J. Matheus
Inductive Learning Group
University of Illinois.
------------------------------
Date: 20 Mar 87 20:55:00 GMT
From: convex!bernhart@a.cs.uiuc.edu
Subject: Re: Genetic Algorithms
I'm delighted to find someone interested in genetic algorithms. I'm glad
I decided to wander through some notes files.
About 10 years ago I did some work in this area using adaptive hashing
as my application. My faculty advisor turned me on to the subject.
Another student did some work with pattern generation and published a
paper on the subject. His name is Gary Rogers, and last I knew he
was teaching at the Swiss Federal Institute. I'll try to find a copy
of the paper - I just moved so am a little(?!) disorganized.
Two books that will be of interest to you are:
Holland, John H. Adaptation in Natural and Artificial Systems:
An Introductory Analysis with Applications to Biology, Control,
and Artificial Intelligence. Ann Arbor: The University of
Michigan Press, 1975.
Holland is a professor of computer science at the University
of Michigan. His book references a number of dissertations.
Holland, John H., Holyoak, Keith J., Nisbett, Richard E., and
Thagard, Paul R. Induction: Processes of Inference, Learning, and
Discovery. Cambridge, MA: The MIT Press, 1986.
I just got this book a month or two ago and haven't had a
chance to look at it what with moving and all. However, after
just glancing through it, I see there is material on genetic
algorithms and classifier systems. I just happened to order
it because I saw an ad in an MIT Press circular and figured a
John Holland book would interest me. The other authors are
U of M faculty also, two in psychology and one in philosophy.
I'm interested in pursuing my research in this area again. Last Fall
I starting doing a computerized literature search through my company's
Information Center. I didn't come up with anything, but I probably didn't
just hit the right databases at first. I couldn't continue the search
because funding for those activies was cut.
Your note is the first reference I've seen to any conference on genetic
algorithms. I'd love to get my hands on those proceedings, too! Who
sponsored the conference? Where was it held? If I learn anything more,
I'll respond here. If you find out any more, I'll look out for a follow-
up response from you. I'd like to hear of any progress you make in your
research.
My most recent activities have been in the Ada arena, and I'm planning to
convert my genetic modeling work of the past into Ada. I think it's
going to work out very well.
Good luck with your pursuits!
Marcia Bernhardt
Convex Computer Corporation
701 N. Plano Rd.
Richardson, TX 75081
convex!bernhart
------------------------------
Date: Wed, 18 Mar 87 15:37:31 EST
From: Jim Hendler <hendler@brillig.umd.edu>
Subject: Book - Expert Systems: The User Interface
In response to several messages I've received at late asking questions
about a forthcoming book, here's some info:
The book, Expert systems: the user interface, will be published by
Ablex and is not due out until this summer (we hope to hit the conferences
but cannot guarantee it). Queries can be addressed to me or, preferably,
to Ablex publishers. Below is the table of contents. If you are desperate
for a copy of some chapter, please send your requests directly to the first
author. There are no pre-release copies of the entire book available.
-Jim Hendler
(hendler@brillig.umd.edu)
Expert Systems: The User Interface
J. Hendler (Editor)
Ablex Publishing Corp.
Contents
Preface -- Ben Shneiderman
Hendler, J.A. and Lewis, C.
Designing Interfaces for Expert Systems
Musen, M.A., Fagan, L.A., and Shortliffe, E.H.
Graphical Specification of Procedural Knowledge for an Expert System
Tuhrim, S., Reggia, J.A. and Floor, M.
Expert System Development: Letting the domain specialist directly
author knowledge bases.
Mittal, S., Bobrow, D.J. and DeKleer, J.
DARN: Towards a Community Memory for Diagnosis and Repair Tasks
Nau, D.S. and Gray, M.
Hierarchical Knowledge Clustering: A way to represent and Use
Problem-Solving Knowledge
Baroff, J., Simon, R., Gilman, F and Shneiderman, B.
Direct Manipulation User Interfaces for Expert Systems
Fickas, S.
Development Tools For Rule Based Systems
Hayes, P.J.
Using a Knowledge Base to Drive an Expert System Interface
with a Natural Language Component
Faneuf, R. and Zirk, S.
A UIMS for Building Metaphoric User Interfaces
Chandrasekaran, B, Tanner, M.C., and Josephson, J.R.
Explanation: The role of control strategies and deep models
Jacob, R.J.K. and Froscher, J.N.
Facilitating Change in Rule-based Systems
Stelzner, M. and Williams, M.D.
The Evolution of Interface Requirements for Expert Systems
Lehner, P.E. and Kraij, M.M.
Cognitive Impacts Of The User Interface
------------------------------
Date: Tue, 17 Mar 87 00:16:40 est
From: french@farg.umich.edu (Bob French)
Subject: categories and counterfactuals
The Role of Categories in the Generation of Counterfactuals:
A Connectionist Interpretation
by Robert M. French and Mark Weaver
Department of Electrical Engineering and Computer Science
University of Michigan
Ann Arbor, Michigan 48109
Tel. (313) 763-5875
Keywords: counterfactuals, norm theory, connectionism, categories
Abstract
This paper proposes that a fairly standard connectionist category model
can provide a mechanism for the generation of counterfactuals --
non-veridical versions of perceived events or objects. A distinction is
made between evolved counterfactuals, which generate mental spaces (as
proposed by Fauconnier), and fleeting counterfactuals, which do not. This
paper explores only the latter in detail. A connection is made with the
recently proposed counterfactual theory of Kahneman and Miller;
specifically our model shares with theirs a fundamental rule of
counterfactual production based on normality. The relationship between
counterfactuals and the psychological constructs of ``schema with
correction'' and ``goodness'' is examined. A computer simulation in support
of our model is included.
The paper has been submitted to the Cognitive Science Society Conference 1987
to be held in Seattle, WA. in July.
Anyone interested in a copy of the paper, should get in touch with
Bob French as follows: french@farg.umich.edu
------------------------------
Date: Thu, 19 Mar 87 8:21:42 EST
From: "Dr. Ron Green" (ARO | mort) <green@BRL.ARPA>
Subject: White Papers on Basic Research in AI
The Army Research Office would be interested in receiving
short white papers on proposed "Basic Research" in AI.
The pepers should discuss a planned three year research
effort with technical content discussing merits of research
topic. Mail the white papers to the following address:
US Army Research Office
P.O. Box 12211
Electronics Division(Attn: Dr. C. Ronald Green)
Research Triangle Park, NC 27709-2211
Topics of interest are purely AI as well as related topics
as applied to Computer Science.
I would prefer the "white papers" as opposed to a deluge of
telephone calls. E-mail responses will also be acceptable.
green@brl.arpa
Thanks
Ron Green
------------------------------
End of AIList Digest
********************
∂23-Mar-87 0434 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #85
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 23 Mar 87 04:34:01 PST
Date: Mon 23 Mar 1987 00:13-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #85
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 23 Mar 1987 Volume 5 : Issue 85
Today's Topics:
Seminars - Connectionist Networks as Models of Human Learning (SRI) &
Signals to Symbols in Neural Networks (UCB),
Courses - Approaches to AI (SU) &
Problem Solving, Learning, and Hardware Design (SU),
Conference - AAAI-87 Workshop on Real-Time Processing
----------------------------------------------------------------------
Date: Wed, 18 Mar 87 16:19:08 PST
From: lansky@sri-venice.ARPA (Amy Lansky)
Subject: Seminar - Connectionist Networks as Models of Human Learning (SRI)
Anyone interested in giving a talk, please contact Amy Lansky --
LANSKY@SRI-AI.
EVALUATING "CONNECTIONIST" NETWORKS AS MODELS OF HUMAN LEARNING
Mark A. Gluck (GLUCK@SU-PSYCH)
Stanford University
11:00 AM, MONDAY, March 23
SRI International, Building E, Room EJ228
We used adaptive network (or "connectionist") theory to extend the
Rescorla-Wagner/LMS rule for associative learning to phenomena of
human learning and judgment. In three experiments, subjects learned
to categorize hypothetical patients with particular symptom patterns
as having certain diseases. When one disease is far more likely than
another, the model predicts that subjects will substantially
overestimate the diagnosticity of the more valid symptom for the Rare
disease. This illusory diagnosticity is a learned form of "base-rate
neglect" which has frequently been observed in studies of probability
judgments. The results of Experiments 1 and 2 provided support for
this prediction in contradistinction to predictions from probability
matching, exemplar retrieval, or simple prototype learning models.
Experiment 3 addressed representational issues in the design of the
network models. When patients always have four symptoms (chosen from
four opponent pairs) rather than the statistically equivalent
presence/absence of each of four symptoms, as in Experiment 1, the
network model predicts a pattern of results quite different from
Experiment 1. The results of Experiment 3 were again consistent with
the Rescorla-Wagner/LMS learning rule as embedded within an
connectionist network.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Fri, 20 Mar 87 10:05:47 PST
From: admin%cogsci.Berkeley.EDU@berkeley.edu (Cognitive Science
Program)
Subject: Seminar - Signals to Symbols in Neural Networks (UCB)
BERKELEY COGNITIVE SCIENCE PROGRAM
Cognitive Science Seminar - IDS 237B
Tuesday, March 31, 11:00 - 12:30
2515 Tolman Hall
Discussion: 12:30 - 1:30
2515 Tolman Hall
``From Signals to Symbols in Neural Network Models''
Terrence J. Sejnowski
Division of Biology
California Institute of Technology
At the earliest stages of sensory processing and at the
final common motor pathways, neural computation is best
described as signal processing. Somewhere in the nervous system
these signals are used to form internal representations and to
make decisions that appear symbolic. A first step toward under-
standing the transition from signals to symbols can be made by
studying the development and internal structure of massively-
parallel nonlinear networks that learn to solve difficult signal
identification and categorization problems. The concept of
``feature detector'' is explored in a problem concerning sonar
target identification that appears to be solved by humans and
network models in similar ways. The concept of a ``semi-
distributed population code'' is illustrated by the problem of
pronouncing English text in which invariant internal codes
emerge not at the level of single processing units, but at the
level of cell assemblies.
---------------------------------------------------------------
UPCOMING TALKS
Apr. 28: Eran Zaidel, Psychology Dept., Brain Research Insti-
tute, UCLA
---------------------------------------------------------------
ELSEWHERE ON CAMPUS
SESAME Colloquium: Robbie Case, Ontario Institute for Studies in
Education, Monday, March 30, at 4:00 p.m., 2515 Tolman.
------------------------------
Date: Fri 20 Mar 87 18:11:03-PST
From: Nils Nilsson <NILSSON@Score.Stanford.EDU>
Subject: Course - Approaches to AI (SU)
[Forwarded from the Stanford bboard by Laws@SRI-STRIPE.]
SEMINAR ANNOUNCEMENT
CS 520 ARTIFICIAL INTELLIGENCE RESEARCH SEMINAR
APPROACHES TO ARTIFICIAL INTELLIGENCE
Tuesdays 11:00 a.m. Terman Auditorium (Televised over SITN)
Spring Quarter 1987
Convener: Nils Nilsson
The student and/or researcher approaching artificial intelligence cannot
fail to note that research is guided by a number of different paradigms.
Among the most popular are: approaches based on one form or another of
symbolic logic; approaches stressing application-specific data
structures and programs for representing and manipulating knowledge;
approaches involving machine learning; and approaches based on
psychological models of human perception and cognition. There are many
variants and combinations of all of these, and each has contributed to
our broad understanding of how to build intelligent machines. During
this seminar series in 1987, leading exponents of these paradigms will
describe the main features of his approach, what it has achieved so far,
how it differs from other approaches, and what can be expected in the
future.
TENTATIVE SCHEDULE
Mar 31: Nils Nilsson (Stanford), ``Overview of Approaches to AI''
Apr 7: Paul Rosenbloom (Stanford), ``AI Paradigms and Cognition''
Apr 14: Bruce Buchanan (Stanford), title to be announced
Apr 21: Vladimir Lifschitz (Stanford), ``The Logical Approach to AI''
Apr 28: Martin Fischler/Oscar Firschein (SRI), ``Representation and
Reasoning in Machine Vision''
May 5: Richard Fikes (Intellicorp), ``Reasoning in Frame-Based
Representation Systems''
May 12: Terry Winograd (Stanford), ``Is There a Standard AI Paradigm?''
May 19: Hubert Dreyfus (UC Berkeley), ``AI at the Crossroads''
May 26: David Rumelhart (UC San Diego), title to be announced
[Will deal with ``connectionism'']
June 2: Ed Feigenbaum (Stanford), ``AI as an Empirical Science''
June 9: Doug Lenat (MCC), ``The Experimentalist's Approach to AI:
from Learning to Common Sense''
------------------------------
Date: 20 Mar 1987 1446-PST (Friday)
From: Tanya Walker <tanya@mojave.stanford.edu>
Subject: Course - Problem Solving, Learning, and Hardware Design (SU)
[Forwarded from the Stanford bboard by Laws@SRI-STRIPE.]
ELECTRICAL ENGINEERING DEPARTMENT-EE392H
Problem Solving, Learning, and Hardware Design
Spring Quarter, 1987 (3 units)
Instructor: Professor Daniel Weeise, CIS 207, 5-3711
Time: Tuesday and Thursday 4:15 to 5:30 pm
Place: ESMB 138
The aim of this course is to understand state-of-the-art AI techniques for
planning, problem solving, and learning. This course is the starting
point for investigating "self-configurable" systems capable of becoming
expert problem solvers in given domains. Our particular domain of
interest is hardware design. The global problem is automatically
creating expert hardware designers for different types of hardware.
Extant planners, such as Tweak, Molgen, and Soar will be studied first.
We will then look at truth maintenance systems. Then we will
investigate the learning and generalization methods of Strips, Soar,
Hacker, and similar systems. We will briefly discuss domain
exploration (a la Hasse and Lenat) and reflection (a la Smith).
We will then investigate using general problem solving methods to solve
problems from integrated circuit design. Examples include channel
routing, leaf cell generation, logic design, and global routing.
We will study two expert systems: Joobbani's Weaver system for channel
routing, and Kowalski's DAA system for VLSI design. They will be used
as examples of expert systems which might be automatically generated.
This will be largely a reading and discussion course. Students will be
required to write a term paper. Familarity with basic AI techniques
will be assumed. Enrollment is by consent of the instructor.
------------------------------
Date: 22 Mar 1987 18:21-EST
From: cross@afit-ab.arpa
Subject: Conference - AAAI-87 Workshop on Real-Time Processing
The AAAI-87 Workshop committee has approved a workshop to be held on
Tuesday, July 14, 1987 entitled "Real-Time Processing in Knowledge-Based
Systems." A call for participation follows.
Workshop on Real-Time Processing in Knowledge-Based Systems
AI techniques are maturing to the point where application
in knowledge intensive, but time constrained situations is
desired. Examples include monitoring large dynamic systems such
as nuclear power plants; providing timely advice based on time
varying data bases such as in stock market analysis; sensor
interpretation and management in hospital intensive care units,
or in military command and control environments; and diagnoses
of malfunctions in airborne aircraft. The goal of the workshop
is to gain a better understanding of the fundamental issues that
now preclude real-time processing and to provide a focus for
future research. Specific issues that will be discussed include:
Pragmatic Issues: What is real-time performance? What
metrics are available for evaluating performance?
Parallel Computation: How can parallel computation be
exploited to achieve real-time performance? What performance
improvements can be gained by maximizing and integrating the
inherent parallelism at all levels in a knowledge-based system
(e.g., application through the hardware levels).
Knowledge Organization Issues: What novel approaches can be
to maximize the efficiency of knowledge retrieval?
Meta-Level Problem Solving: How can intelligent problem
solving agents reason about and react to varying time-to-solution
resources? What general purpose or domain specific examples
exist of problem solving strategies employed under different
time-to-solution constraints? What are the tradeoffs in terms of
space, quality of solution, and completeness of solution.
Complexity Issues: How can an intelligent agent reason
about the inherent complexity of a problem?
Algorithm Issues: What novel problem solving methods can be
exploited? How can specialized hardware (for example , content
addressable memories) be exploited?
To encourage vigorous interaction and exchange of ideas
between those attending, the workshop will be limited to
approximately 30 participants (and only two from any one
organization). The workshop is scheduled for July 14, 1987, as a
parallel activity during AAAI 87, and will last for a day.
All participants are required to submit an abstract (up to
500 words) and a proposed list of discussion questions. Five
copies should be submitted to the workshop chairman by May 1,
1987. The discussion questions will help the workshop
participant's focus on the fundamental issues in real-time AI
processing.
Because of the brief time involved for the workshop,
participants will be divided into several discussion groups. A
group chairman will present a 30 minute summary of his group's
abstracts during the first session. In addition, the committee
reserves the right to arrange for invited presentations. Each
group will be assigned several questions for discussion. Each
group will provide a summary of their groups discussion. The
intent of the workshop is to promote creative discussion which
will spawn some exciting ideas for research.
Workshop Chairman:
Stephen E. Cross, AFWAL/AAX, Wright-Patterson AFB OH 45433-
6583, (513) 255-5800. arpanet: cross@afit-ab.arpa
Organizing Committee:
Dr. Northrup Fowler III, Rome Air Development Center
Dr. Barbara Hayes-Roth, Stanford University
Dr. Michael Fehling, Rockwell Palo Alto AI Research Lab
Ms. Ellen Waldrum, Computer Science Laboratory, Texas
Instruments
Dr. Paul Cohen, University of Massachusetts at Amherst
Invited Talks From:
Dr. Michael Fehling, Rockwell Palo Alto AI Research Lab
Dr. Barbara Hayes-Roth, Stanford University
*Dr. Vic Lesser, University of Massachuesetts at Amherst
*tentative
------------------------------
End of AIList Digest
********************
∂25-Mar-87 0144 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #86
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 25 Mar 87 01:44:28 PST
Date: Tue 24 Mar 1987 22:54-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #86
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 25 Mar 1987 Volume 5 : Issue 86
Today's Topics:
AI Tools - OPS5 Source & Mickey MICE & Lispm/WorkStation Survey
----------------------------------------------------------------------
Date: 18 Mar 87 23:39:52 GMT
From: clyde!masscomp!dlcdev!eric@RUTGERS.EDU (eric van tassell)
Subject: OPS5 source
Thanks to all the people who sent me OPS5! The response overwhelmed
my spool directory. If you too would like OPS email to me and I will
email to you.
Eric Van Tassell
Data Language Corp.
617-663-5000
clyde!bonnie!masscomp!dlcdev!eric
harvard!mit-eddie!dlcdev!eric
dlcdev!eric@eddie.mit.edu
------------------------------
Date: 17 Mar 87 18:00:54 GMT
From: ihnp4!alberta!calgary!arcsun!rob@ucbvax.Berkeley.EDU (Rob
Aitken)
Subject: Mickey MICE
The following is a review of Machine Intelligence Corporation's MICE Expert
System, which allegedly runs on IBM PC's with MS-DOS 3.1 or greater.
Upon receiving the software, I looked at the directory of disk #1 to see if
there were any installation instructions. There were none, so I opted for
the manual. Under "Getting Started with MICE" there is a discussion of
power failures, with such notable statements as "One can reset a tripped
circuit breaker to recover the power", but nothing about installation. Four
pages later the installation section begins.
In fact, as I was to discover later, there are at least three (mutually
inconsistent) sections about installation in the manual. Each informs me
that I must create a top-level directory called \MICE and copy "all three"
diskettes onto the hard drive. Five diskettes came with the package. I was
unsure which three, so I copied all five. The Tutorial session, which lists
all program variables, including such dandies as "how,9,p10->p10h"
indicated that I must run a program called DEFOPT and provide answers to
six verbose questions (containing, for example, "The memron description of
atomic facts can be used to store customized prompts for the expert advice
consultation"). Naturally, DEFOPT asked seven questions. I guessed that I
did not want the "Initial Data Feature".
A third section of the manual which covers installation states "If you have
followed the procedure up to this point" there should be a directory called
\POWER containing files MEMRON1 through MEMRON5. None of the other
installation sections mentioned this. It turns out, though, that each
knowledge base must be in its own directory and all must contain the
elusive MEMRON* files.
I crashed the system in a variety of amusing ways for half an hour until
finally I discovered, buried deep in an appendix, the statement "MICE
cannot coexist with any RAM based software". MS-DOS is RAM-based, but I
assume that it qualifies as an exception. Nothing else does, however, and
so my network software had to go. With everything else gone, MICE began
running. I think I liked the crashes better.
After using the program for a while I determined that MICE is not an expert
system after all, but rather an adventure game. The goal is to navigate
through the rules. Easy steps are, for example, "Please indicate whether
LIGHTS CAN BE TURNED ON is relevant to the current situation. Respond 'y'
for varying degree of certainties and 'n' if LIGHTS CAN BE TURNED ON is
irrelvant to our discussion". This turns out to mean "Can the lights be turned
on?". A more complex part of the game is guessing the secret key for "Please
respond to .CIRCUIT BREAKER TRIPPED". The answer turns out to be "on" or "off".
If you become expert at the beginner level of the game, expansions can be
purchased all the way up to a 1 Megabyte version.
As you may have guessed, the demo system diagnoses power failures. I wonder
though, in the event of a real power failure, what good is an electronic
expert system? Just asking.
The clever people at MIC continue by informing us that MICE is implemented
in C because its designers believe that LISP and PROLOG are "not adequate
for practical applications" (I suspect this is synonymous with "do not
provide nearly enough scope for sleazy programming") and because of the
"efficiency of the UNIX operating system". PC's run MS-DOS, not Unix, so I
am unsure of the relevance, let alone the veracity, of the preceding
statement.
In conclusion, MICE is a pathetic expert system. Any self-respecting
organization would be embarrassed to be associated with it. There are plenty
of cheaper ways to get a good laugh.
Rob Aitken
{...alberta,...ubc-vision}!calgary!arcsun!rob
P.S. Since writing this, MICE has ceased to function altogether, producing
messages like "Attempting to close file that failed to open" and
writing greek letters all over the screen.
Disclaimer: The Alberta Research Council neither affirms nor refutes the
above review.
------------------------------
Date: 20 Mar 87 00:55:52 GMT
From: mcnc!duke!ravi@seismo.css.gov (Ravi Subrahmanyan)
Subject: Re: Mickey MICE (another review)
I agree. $20 for MICE is a ripoff.
Things they don't tell you in the ad:
1) You need a mouse
2) You need to print out the docs to use it
(I became sufficiently discouraged that I didn't
waste the paper)
It would be nice to have a good system based on semantic nets,
but this is not it. The list of features was too good to be true
anyway.
Michael Lee Gleicher (-: If it looks like I'm wandering
Duke University (-: around like I'm lost . . .
Now appearing at : duke!ravi (-:
Or P.O.B. 5899 D.S., Durham, NC 27706 (-: It's because I am!
------------------------------
Date: Mon, 23 Mar 87 15:05:58 PST
From: TAYLOR%PLU@ames-io.ARPA
Subject: Summary of Best Lispm/WorkStation Responses
This is a summary of responses I received to a request for opinions
and experience on the best Lisp Machine (Lispm) or AI workstation.
I received techical summaries and internal reports from marketing
reps of the following companies:
Symbolics, TI and Integrated Solutions (AI workstations).
Except for the Symbolics vs. Explorer and Symbolics vs. Xerox comparisons
which appeared on the net last year, I received no extensive comparisons
of two or more Lispms/WorkStations.
I did get responses (positive & negative) from users with opinions (op)
and/or experience (ex) on a particular machine. First a short summary,
then some detailed comments.
machine configuration type positive negative
----------------------- ---- -------- --------
Apple Macintosh II op 1 0
Hewlett-Packard 350 workstation op 2 0
HP-UX, integrated Lisp/Prolog
Intel 3086 op 1 0
Golden Common Lisp
LMI - 0 0
Sun 3/160, 2/160 diskless ex 3 0
Sun 3/280 server, 16-20 MB memory
Symbolics - 0 0
Tektronix 4400 AI Work Station op 1 0
VAX AI Work Station ex 2 1/2 1 1/2
Xerox 1186 0 2
As you can see the response was not great.
Now some detailed comments:
-------------------------------------------------------
From: Malcolm Slaney <spar!malcolm@decwrl.DEC.COM>
Organization: Schlumberger Palo Alto Research
In article <8703010658.AA21849@ucbvax.Berkeley.EDU> you write:
>11. A SUN without disks is useless.
No, No, No, No, No.
But you must have enough memory so you don't swap. I have a Sun3/160 on
my desk with 16M of memory.....I NEVER PAGE or SWAP!!!!!
If you do start paging then things lose real fast. Franz Lisp image are
small and you can probably get by with less.
I think the reason that memory is so critical to the current generation
of Sun Lisp's is because of their swapping garbage collection. Every
few minutes it must touch every page of your dynamic area. If you have
to go to disk then chances are you will flush one of the pages you
are currently using (isn't least recently used wonderful???).
I have seen Lucid and Franz Common Lisp running anywhere between .5 and
4 times a Symbolics machine. Things are even faster with a Sun3/260.
It is safe to say that Sun Lisps have caught up with Symbolics machines
on speed.
Now if they just had the environment.... [for program development? - wmt]
P.S. I keep a Sun on my desk because that is my religion of choice...but
whenever I have a real hairy problem debugging my lisp I run to the
Symbolics machine.
--------------------------------------------------------
From: IN%"beane%bartok.DEC@decwrl.dec.com" 13-FEB-1987 07:06
I suppose somebody working at Digital can be expected to have a very
positive opinion of the AI VAXstation, but I do, even so.
I especially like the ability to run lots of completely independent processes,
especially VMS ones doing mail, file transfer, access to other resources in
the network without any LISP overhead.
The editor is especially good, compared to other editors on the VAX. I much
prefer it over EMACS, which I have stopped using. I've written several
editor extensions (eg., menus for common commands) which I'll be glad to
send you in hardcopy (to get the screen images).
Oh, yeah, I've never used any other machine, so no comparison, just
praise.
--------------------------------------------------
From: IN%"@charon.mit.edu:meltsner@athena.mit.edu" 25-FEB-1987 19:09
We use Vaxstation II's + Vax LISP (Ultrix) here, and I'm fairly
happy. But --
1) Lucid's LISP is twice as fast on the same machine, given enough
memory.
2) Ultrix LISP's don't yet support the window system, although the
VMS ones do.
3) DEC memory and disks are notoriously over-priced. Consider buying
a minimal system in a BA123 box, and getting an Emulex disk ($3000
MIT price for a 140 meg drive+ controller, installed) and a third-part
memory board.
Personally, I like the Vaxstation. The machine feels fairly solid,
the software doesn't crash and everything install very easily. DEC
service is expensive, but ubiquitous. In general, the Symbolics stuff
is wonderful if you are willing to devote the guru time to keeping it
running. DEC has an acceptable product which seems much easier to support.
I have never managed a cluster of LISPM's, but I do manage our 5 machines
in not much more than 3-4hours/week (I don't do backups....).
---------------------------------
From: "Christoph M. Hoffmann" <cmh@purdue.edu>
We used the 1180 and 1186 Xerox dandilions at Cornell for a year or so
in our research on solid modeling. We wern't too thrilled about them,
because of the poor floating point handling and because they were very
hard to learn. The trouble with floating point was software related:
The compiler boxed everything, so it made a lot of work for the garbage
collector. Also the fp precision turned out troublesome. The net effect
was that we couldn't work with surfaces of (algebraic) degree 4 or higher,
which excluded for example the torus. Here at Purdue we now use Symbolics
machines, and so does Cornell.
---------------------------------
Well, after all that, what are we going to do?
We now have a configuration of a Symbolics file server, serving:
4 - Symbolics 3640's
2 - Symbolics 3620's
1 - Symbolics 3670
2 - LMI 2+2 (3 lisp, 1 unix)
1 - Xerox 1186
1 - TI Explorer
We also have a beta-test machine from Integrated Inference Machines
and a VAX 780/VMS with Franz, Interlisp, OPS-5, MRS, ITP, etc.
We are tentatively thinking of expanding our facility by adding:
3 - Xerox 1186's. Reasons : ease of learning, superior windowing,
Common Loops, NoteCards, Xerox PARC innovation,
inexpensive
1 - TI Explorers. Reasons : ease of learning, different yet similar to
Symbolics, integrated Lisp/Prolog, source code
2 - Sun 3/260 diskless and Sun 3/260 server. Reasons: fast, NeWS, numeric
speed, work station versatility, easy access to
other languages
It is worth noting that Symbolics, TI Explorer & Sun 3/260 are all in the
same price ballpark. Xerox is considerably less, however it is not designed
for the development of large systems.
Hope that this is of benefit - Will
P.S. Please send me your comments - thanks
--------------------------------------------------------------------------
Will Taylor - Sterling Software, MS 244-17,
AI Research & Applications Branch
NASA-Ames Research Center, Moffett Field, CA 94035
arpanet: taylor@ames-pluto.ARPA
usenet: ..!ames!plu.decnet!taylor
phone : (415)694-6525
------------------------------
End of AIList Digest
********************
∂25-Mar-87 0419 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #87
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 25 Mar 87 04:19:40 PST
Date: Tue 24 Mar 1987 23:12-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #87
To: AIList@SRI-STRIPE.ARPA
AIList Digest Wednesday, 25 Mar 1987 Volume 5 : Issue 87
Today's Topics:
Policy - American Militarism,
Comments - Limitations of AI/Expert Systems & Explanation Capability,
Application - Analysis of Unknown Data
----------------------------------------------------------------------
Date: Fri, 20 Mar 87 14:28:46 +0100
From: mcvax!cwi.nl!tomi@seismo.CSS.GOV (Tetsuo Tomiyama)
Subject: Policy - American Militarism
In Article 1432 of mod.ai, Chris Elsaesser (elsaesser%mwcamis@MITRE.ARPA)
submits a Call for Papers
> Issues Concerning AI Applications To Battle Management
>
> University of Washington
> Thursday, July 16, 1987
>
> Sponsored by AAAI
>
> Success in applying AI technologies to battle management (e.g., production
> and blackboard systems for sensor fusion, constraint propagation for
> non-temporal planning tasks) has generated growing interest in the defense
> community in developing intelligent battle management aids, workstations,
> and systems. Along with this growing interest, there has been an order of
> magnitude increase in funding for battle management AI projects (e.g.,
> Army-DARPA's Air-Land Battle Management, SAC-JSTPS-RADC-DARPA's
> .......
First of all, I really feel doubts about the policy of AAAI to sponsor
such a BLOODY nonsense, but since this is not the right place to
criticize AAAI, I don't write about it. (Since I am a member of AAAI,
I reserve my right to do so, though.)
Now, I am strongly against such a posting circulated ALL AROUND THE
WORLD through the net. Of course, I personally do hate such BLOODY
research and at least I won't do such things. But, this is absolutely
my personal opinion and I know that anyway I don't have power big
enough to stop it. So, as far as it remains an AMERICAN MATTER, I
don't bother guys over there.
However, mod.ai is broadcasted to all over the world and I really do
not want to see OUR computer networks are used to promote such BLOODY
NONSENSE which may contribute only to destroying everything. I think
this kind of postings should be even prohibited from the world wide
net distribution. You (in plural) should be aware that there are lots
of people who work hard for peace and many scientists and engineers are
against the use of modern technology for military purposes even in the
American AI community.
--Tetsuo Tomiyama (UUCP: tomi@cwi.nl)
[I don't believe that this message is offensive to the general AI
community. I regret that it offends you, but can't censor all
such material to suit your preferences. I can only offer you the
same channel for stating your own position.
AIList is a global channel. It could be limited to just the Arpanet,
as it once was, but that would not be in the best interest of all
involved. -- KIL]
------------------------------
Date: Mon, 23 Mar 87 18:04:56 +0100
From: mcvax!cwi.nl!tomi@seismo.CSS.GOV (Tetsuo Tomiyama)
Subject: Re: Re: Submission to mod.ai
[...]
I am not saying that you are prohibited from military research. I am
saying that it is all up to you whether you take part in military
research or not. However, since there are people who do not like
military research, just like there are people who do not want to see
pornography in public or who do not want to get somebody else's smokes
in a public space, you should not at least promote military research in
public.
I propose, therefore, to submit postings relevant to militarism should
NOT be PROHIBITED but at least requested to be MARKED as military
related article at the responsibility of original authors (rather than
by the moderator), just like advertisements from tobacco companies, so
that if I don't want to read it I can skip it.
[...]
... so please give us a method to recognize military related
articles as soon as possible.
--Tetsuo Tomiyama (UUCP: tomi@cwi.nl)
[This is the first time this matter has come up in four years
of AIList. It does not seem to be a problem for the vast majority
of readers, but you are welcome to try convincing submitters
of defense-related messages to add a keyword to their headers.
AIList is primarily an Arpanet discussion list. The Arpanet
was developed by the military, is supported by the military,
and is intended for defense-related communication among
military contractors. One could assume that all Arpanet
messages are military in nature, although that heuristic
does not seem very useful in the case of AIList. What is
really needed here is an intelligent mail reader that screens
your messages and adds the appropriate keywords. -- KIL]
------------------------------
Date: Mon, 23 Mar 87 13:35:16 cst
From: lugowski%resbld%ti-csl.csnet@RELAY.CS.NET
Subject: Oxymoron: Real-time Knowledge-Based Nurse/Nuclear Plant
Operator
Regarding the following...
Date: 22 Mar 1987 18:21-EST
From: cross@afit-ab.arpa
Subject: Conference - AAAI-87 Workshop on Real-Time Processing
Workshop on Real-Time Processing in Knowledge-Based Systems
AI techniques are maturing to the point where application
in knowledge intensive, but time constrained situations is
desired. Examples include monitoring large dynamic systems
such as nuclear power plants... sensor interpretation and
management in hospital intensive care units...
Desired by whom? I wouldn't trust AI techniques with monitoring large dynamic
systems of the class of a medium-sized municipal toilet. I would certainly
want out of any ICU where my fragile well-being did not depend on an ICU
nurse, overworked as though he or she may be. The AI community has had up
to now the good sense of relegating its really questionable achievements to
the battlefield, where they are fondly appreciated. Let's not get too greedy
by introducing the battlefield to our rather safe nuclear plants and ICUs.
-- Marek Lugowski
Texas Instruments
lugowski%crl1@ti-csl.csnet
------------------------------
Date: 22 Mar 87 21:14:25 GMT
From: tektronix!tekcrl!vice!tekfdi!videovax!dmc@ucbvax.Berkeley.EDU
(Donald M. Craig)
Subject: Re: AI Project Information Request
Well, I'm probably over reacting to what will end up being
nothing more than a spelling checker, but I find the thought
of having creative writing graded by a computer program appalling.
It's particularly pernicious in the public school system,
where penalties for failure to conform to some computer
program's judgement of style and content are brought to bear.
The best and most universal writing is about the human condition.
What does a computer program (or indeed its artificially
intelligent author) know about that? What would it do with...
James Joyce? William S. Burroughs? Anthony Burgess? Ogden Nash?
What would happen to literary experiment?
Would there be an image processing version that graded Picasso?
It's bad enough that some smartass robot comes up to me at
trade shows pedalling product, or some auto-dialer phones
me while I'm in the shower to sell carpet cleaner, but
these uppity machines I can be rude to and ignore. The one
that's marking my school essays I cannot.
In law I have the right to be judged by a jury of my peers.
In school I demand that same right. I will NOT be judged by
a machine.
Yours for a better tomorrow,
Don Craig
Whose opinions are his own.
--
Don Craig dmc@videovax.Tek.COM
Tektronix Television Systems ... tektronix!videovax!dmc
------------------------------
Date: 23 Mar 87 15:22:32 GMT
From: mcvax!ukc!warwick!gordon@seismo.css.gov (Gordon Joly)
Subject: Explanation and Justification.
In answer to the question "does an expert system need to
be able to explain itself to be useful", consider teaching.
Anyone who has taught knows, to teach something (ie to explain
it to a class), you really need to understand the issues,
before you can begin to get them across. Also, in the process
of teaching itself, ones own understanding is often deepened.
Gordon Joly -- {seismo,ucbvax,decvax}!mcvax!ukc!warwick!gordon
------------------------------
Date: 18 Mar 87 20:48:17 GMT
From: hpcea!hpfcdc!hpldola!hpldolm!ben@hplabs.hp.com (Benjamin
Ellsworth)
Subject: Re: analysis of unknown data
I have two comments on this discussion; the first is general the second
is specific.
My first comment on this whole discussion, as I understand it, is that
it is silly. We are being asked to find "the" meaning of some large
file without any context for the file. Is it text? Is it integer
data? Is it floating point data? Is it encrypted in any way? The
search for meaning in the absence of context is a waste of time.
(In essence, I agree with M. B. Brilliant as follows.)
What is meaningful in one context is often not meaningful in another.
However, sometimes, it is. A file full of integer measurement data will
usually be indistinguishable from a file of a bit-mapped color image.
A bunch of integers is a bunch of integers (unless some *recognizable*
context information is included). If you take a group of integers and
make a pretty picture with them, what will you do when I tell you that
they were process measurements from a ball-bearing factory? What will
you do when you interpret a Mandelbrot image as a bad lot of wafers
in an otherwise well controlled fab?
I'm sure that you would like to say that you can't make a pretty
picture with ball bearing data. Perhaps not in every case, but I know
of a gentleman who *sells* "art" generated from HP stock performance
data. He has given some stock data meaning in a new context.
The best response to this question was the one from Mr. Adrian
who suggested that you look for the context(s) that the file
was used in. If you can't find the correct context, you cannot
ascertain the correct meaning. If the data exists in a vacuum, you can
choose whatever context that you wish and with enough massaging you
can make the data meaningful.
Second comment:
> Testing for randomness might be the first test; sure would save
Random is too loose of a term. Are they "random" samples from a
uniform distribution, or "random" samples from a Gaussian distribution?
In either case is the distribution a real population, or a mathematical
model of a distribution function?
I don't want to sound like a flame, but testing for randomness is
ridiculous! You *cannot* prove a set of data to be "random." In fact
the key to some encryption schemes is to make a dataset appear "random"
to most simple minded tests. This does not mean that there is no
information in the data. It just means that the context of the
information is well hidden from such simple minded filters.
What you are saying when you say that you will test for randomness is
that you will test to see if the data is meaningful in any known
context. Do you know all possible contexts? Will you live long enough
to test for all of them? What happens when the data is meaningful in
more than one context?
---------
Benjamin Ellsworth
hplabs!hpldola!ben
(303) 590-5849
P.O. Box 617
Colorado Springs, CO 80901
2+2=4 (void where prohibited, regulated, or otherwise restricted by law)
------------------------------
Date: 23 Mar 87 19:01:10 GMT
From: dave@mimsy.umd.edu (Dave Stoffel)
Subject: Re: analysis of unknown data
In article <11160001@hpldolm.HP.COM>, ben@hpldolm.HP.COM (Benjamin
Ellsworth) writes:
> My first comment on this whole discussion, as I understand it, is that
> it is silly. We are being asked to find "the" meaning of some large
> file without any context for the file. Is it text? Is it integer
> data? Is it floating point data? Is it encrypted in any way? The
> search for meaning in the absence of context is a waste of time.
Maybe I am at fault for inadequately describing the problem,
but it is neither silly nor a waste of time. Apart from these
two comments and the later one about test for randomness being
ridiculous, Ben's comments are helpful in further detailing the
possibilities.
> What is meaningful in one context is often not meaningful in another.
> However, sometimes, it is. A file full of integer measurement data will
> usually be indistinguishable from a file of a bit-mapped color image.
> A bunch of integers is a bunch of integers (unless some *recognizable*
> context information is included). If you take a group of integers and
> make a pretty picture with them, what will you do when I tell you that
> they were process measurements from a ball-bearing factory? What will
> you do when you interpret a Mandelbrot image as a bad lot of wafers
> in an otherwise well controlled fab?
> I'm sure that you would like to say that you can't make a pretty
> picture with ball bearing data. Perhaps not in every case, but I know
> of a gentleman who *sells* "art" generated from HP stock performance
> data. He has given some stock data meaning in a new context.
I wouldn't like to say you can't have multiple representations of
a set of data poin
However, one man's "art" is simply another man's pictoral or
imagic presentation of stock data. (Particularly if the raw
stock data was not convaluted by the artist). In fact, it might
be a useful presentation for certain kinds of trend analysis.
> The best response to this question was the one from Mr. Adrian
> who suggested that you look for the context(s) that the file
> was used in. If you can't find the correct context, you cannot
> ascertain the correct meaning. If the data exists in a vacuum, you can
> choose whatever context that you wish and with enough massaging you
> can make the data meaningful.
Certainly there is a pitfall in the analytic process; one may
"discover" meaning that was not the intent of the creator of
the data. So it goes, sometimes.
"finding the correct context" and "finding the meaning" are the
same thing!
> Random is too loose of a term. Are they "random" samples from a
> uniform distribution, or "random" samples from a Gaussian distribution?
> In either case is the distribution a real population, or a mathematical
> model of a distribution function?
> I don't want to sound like a flame, but testing for randomness is
> ridiculous! You *cannot* prove a set of data to be "random." In fact
> the key to some encryption schemes is to make a dataset appear "random"
> to most simple minded tests. This does not mean that there is no
> information in the data. It just means that the context of the
> information is well hidden from such simple minded filters.
Hmm. I think what I mean is that if the data set appears to be a Gaussian
distribution, then I'm not going to apply any other tests.
> What you are saying when you say that you will test for randomness is
> that you will test to see if the data is meaningful in any known
> context. Do you know all possible contexts? Will you live long enough
> to test for all of them? What happens when the data is meaningful in
> more than one context?
I can't possibly imagine all conceivable or theoretic contexts. I
can imagine too many to try. I am looking for an analytic process
that is more efficient than enumerating all the context tests I can
imagine. If multiple context tests yield "reasonable"
representations, I might just have to flip a coin or allow for all
interpretations.
I never said that the data has no context! I simply said that I
don't know a-priori what its context is. It *is* the case that data
points can be analysed in the absence of knowledge of the structure of
the function which produced them. The object is to detect patterns,
if possible, and search for "meaningful" interpretations.
Some of the discussion of this subject sounds like the participants
are frustrated by these two facts:
1. I *won't* live long enough to apply every possible context
test. (Discovery by enumeration).
and
2. they don't know of any more efficient methodology than discovery
by enumeration, ergo the problem is silly or a waste of time.
--
Dave Stoffel (703) 790-5357
seismo!mimsy!dave
dave@Mimsy.umd.edu
Amber Research Group, Inc.
------------------------------
End of AIList Digest
********************
∂26-Mar-87 0027 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #88
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 26 Mar 87 00:27:17 PST
Date: Wed 25 Mar 1987 22:16-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #88
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 26 Mar 1987 Volume 5 : Issue 88
Today's Topics:
Conference - Genetic Algorithms,
Seminars - NUPRL as a Framework for Defining Logics (UPenn) &
Natural Deduction Meets Schubert's Steamroller (SMU) &
Parallel Production System Algorithms (UTexas)
----------------------------------------------------------------------
Date: Tue, 24 Mar 87 14:04:55 est
From: John Grefenstette <gref@nrl-aic.ARPA>
Subject: Genetic Algorithms
Copies of the Proceedings of the First International Conference
on Genetic Algorithms, held at Carnegie-Mellon in 1985 can be
obtained by sending me your US Mail address.
The 2nd GA Conference, sponsored by AAAI, the Navy Center for
Applied research in AI, and Bolt Beranek and Newman, will be
held July 28-31, 1987, at MIT. For registration forms and info
concerning local arrangements, contact:
Mrs. Gayle M. Fitzgerald
Conference services Office
Room 7-111
MIT
77 Massachusetts Ave.
Cambridge, MA 02139
If you would like to submit a paper to the Conference, please send
three copies of the paper to:
John J. Grefenstette
Navy Center for Applied Research in AI
Naval Research Lab
Washington, DC 20375-5000
(202) 767-2685
Arpanet: gref@NRL-AIC.ARPA
The program committee will review papers starting April 10.
Final camera ready versions will be due May 30.
-- JJG
------------------------------
Date: Mon, 23 Mar 87 08:24:18 EST
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - NUPRL as a Framework for Defining Logics (UPenn)
From: dale%linc.cis.upenn.edu@cis.upenn.edu
Math/CS Logic Seminar
University of Pennsylvania
RECENT RESULTS ABOUT NUPRL:
USING NUPRL AS A FRAMEWORK FOR DEFINING LOGICS.
Robert Constable
Cornell University
Abstract: Nuprl can be used to define natural deduction style logic.
We will also mention other recent results about the Nuprl type theory
such as those about representing partial functions.
Math/Physics Building (DRL)
4th floor Math Seminar Room
Monday 23 March 87, 10:30am
------------------------------
Date: Tue, 24 Mar 1987 18:21 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Seminar - Natural Deduction Meets Schubert's Steamroller
(SMU)
Past Seminar, Southern Methodist University, Department of Computer Science
Natural Deduction meets Schubert's Steamroller
Frank Vlach
Texas Instruments
Schubert's Steamroller is a test problem for automatic theorem provers
that has attracted a lot of attention recently, and has proved
difficult for resolution theorem provers. A human theorem prover
would prove Schubert's Steamroller using a `natural' but mechanical
and totally non-creative method that is readily programmable and quite
different from resolution. Hand computations indicate that this
strategy is much less complex than resolution for Schubert's
Steamroller and a number of similar problems. An implementation is in
progress in order to compare this method with resolution (and other
methods) over a wide range of problems.
This strategy also has the advantage that it requires no preprocessing
of formulas (such as Skolemization or conversion to clausal form), and
lends itself to the generation of natural proofs, readable by humans.
------------------------------
Date: Tue 24 Mar 87 14:23:26-CST
From: Adam Farquhar <AI.FARQUHAR@R20.UTEXAS.EDU>
Subject: Seminar - Parallel Production System Algorithms (UTexas)
The COMPUTER SCIENCES GRADUATE STUDENT COUNCIL
PRESENTS
Daniel P. Miranker
Recent Developments in
Parallel Production System Algorithms
at the CSGSC BROWN-BAG SEMINAR
Friday, March 27, 12:00 Noon
Tay 2.106
All Students and Faculty are invited.
Okay to bring your lunch.
The development of a parallel production system interpreters may be
seperated into three nearly independent facets, low-level matching,
partitioning of the rule base and synchronizing the partitions. This
talk will address the partitioning issue.
A problem associated with parallelizing production system execution is
that on any given production system cycle only a small subset of the
rules require processing. Worse, on a given cycle, often the
processing requirements for a single rule will completely dominate the
execution time. "Copy and constrain" is a method by which the
processing requirements for matching a single rule may be distributed
over many processors. This method has been shown to very effectively
reduce the variance of the match times of different rules. Further,
this method has implications for the fault tolerant execution of
production systems. It appears, due to increased processor
utilization, that fault tolerance may be introduced into a parallel
production system interpreter without modification of the hardware and
without significant performance degradation.
------------------------------
End of AIList Digest
********************
∂28-Mar-87 0047 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #89
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 28 Mar 87 00:47:28 PST
Date: Fri 27 Mar 1987 22:30-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #89
To: AIList@SRI-STRIPE.ARPA
AIList Digest Saturday, 28 Mar 1987 Volume 5 : Issue 89
Today's Topics:
Queries - ECOOP'87 & OPS5 for the SUN 3's & AI Expert Sources &
Object Recognition,
AI Tools - Genetic Algorithms,
Expert Systems - Explanation and Justification & Capabilities,
Application - Text Critiquing
----------------------------------------------------------------------
Date: 25 Mar 87 15:45 CET
From: Gabriel_Barta_DEC%EUROKOM@MIT-MULTICS.ARPA
Reply-to: Gabriel_Barta_DEC%EUROKOM@MIT-MULTICS.ARPA
Subject: Info on Advanced Program ECOOP'87, June 15.-17.
We would like to get more information on the seminar mentioned above.
Where can we register, who is the organizer. Please send info to
@ECC.DEC: isakson or phone Nikola Storp [49[(89)9591-1122 at Digital Equipment
GmbH, Munich. Best regards, Nikola Storp
------------------------------
Date: 25 Mar 87 18:02:52 GMT
From: clyde!mcdchg!wucs1!wucs2!posdamer@rutgers.rutgers.edu (Jeff
Posdamer)
Subject: OPS5 for the SUN 3's
We are seeking a source for a compiled version of OPS5 that will run on the
SUN 3/160. Any help would be appreciated. Please reply by e-mail to:
..!{ihnp4,seismo}!wucs!posdamer
Thanks!
------------------------------
Date: 25 Mar 87 18:15:42 GMT
From: ssc-vax!bcsaic!phyllis@BEAVER.CS.WASHINGTON.EDU (Phyllis
Melvin)
Subject: 1986 AI Expert Sources
Can someone tell me where to get copies of November and December
AI Expert magazine sources?
--
Phyllis Melvin uucp: ...uw-beaver!uw-june!bcsaic!phyllis
(206)865-3293 arpanet: phyllis@boeing.com
["imagen!turner"@ucbvax.berkeley.edu has been sending the
source files to the Usenet comp.ai stream and may also be
placing them in comp.sources. Bitnet redistribution is
being handled by Streiff%HARTFORD.BITNET@WISCVM.WISC.EDU.
I have last year's sources in file AIE.SRC and the Jan-Mar
sources in AIE2.SRC; Arpanet readers can FTP them from
directory <AILIST> on SRI-STRIPE. -- KIL]
------------------------------
Date: 27 Mar 87 12:26:44 EST
From: BIESEL@RED.RUTGERS.EDU
Subject: Information request for object recognition papers.
I would appreciate pointers and references to current work in object
recognition. My group is beginning work in the automation of visual
database design for real-time image generators. These databases consist
of polygonal approximations of real-world objects (everything from houses
to bushes). Currently, individual objects are constructed by hand, using
models, maps, photographs, graph paper, geometry, and lots of time and
patience. We would like to develop a modeling station which can extract
the basic geometry of objects from sets of photographs, and which can
produce good approximations to polygonal models of the regular structures,
such as buildings and other cultural features, which it recognizes in the
source photographs.
We expect that such a system will require some operator assistance for
resolving ambiguities, at least initially, but even such a system would be
of great help in the modeling task.
Although we have some papers of current work, please assume that we are
completely ignorant about who is doing what, and what the state of the
art is, and forward all references to me. I realize that there are probably
several netlists which are relevant, but I've not kept in touch with these.
Pointers to the more active and relevant of these are also appreciated.
I will summarize the responses if they are sufficiently general for this
audience, and if the volume of replies warrants it. Many thanks in advance.
Heiner BIESEL@RUTGERS
[The best collections of papers are the DARPA Image Understanding
Workshops. The February '87 proceedings have been made available
to the general public. Much of this work is oriented toward aerial
cartography (as well as target recognition). Other good papers
have appeared in recent vision conferences such as PRIP/CVPR/ICCV
and in journals such as IEEE PAMI and CVGIP.
Some of the most pertinent work is being carried out at SRI by
Pascal Fua and Andy Hanson. They have developed ways of extracting
rectilinear objects (i.e., buildings of complex shape) and are
extending their techniques to identify roads and vegetation.
One of the inputs to their system is a segmentation map derived
from my own work in computer vision. -- KIL]
------------------------------
Date: 25 Mar 87 17:42:00 GMT
From: convex!bernhart@a.cs.uiuc.edu
Subject: Re: Genetic Algorithms
The Proceedings of the conference are copyrighted by John J. Grefenstette
the editor. At the time of the conference (and perhaps now) he was at
Vanderbilt University. You could contact him about procuring the book, or
contact John Holland, the conference chairman, at the University of Michigan.
Your university library should be able to assist with procurement of these
proceedings and any doctoral dissertations you might need. They probably
have extensive inter-library loan resources.
Again, good luck!
Marcia Bernhardt
Convex Computer Corp.
------------------------------
Date: 26 Mar 87 18:21:31 GMT
From: allegra!dougf@ucbvax.Berkeley.EDU (Doug Foxvog)
Subject: Re: Genetic Algorithms
In article <63800001@convex> bernhart@convex.UUCP writes:
>
>Your note is the first reference I've seen to any conference on genetic
>algorithms. I'd love to get my hands on those proceedings, too! Who
>sponsored the conference? Where was it held? If I learn anything more,
>I'll respond here. If you find out any more, I'll look out for a follow-
>up response from you. I'd like to hear of any progress you make in your
>research.
>
The "International Conference on Genetic Algorithms & their Applications"
was held July 24-26, 1985, at Carnegie-Mellon University. It was jointly
sponsored by Texas Instruments & the US Navy Center for Applied Research
in Artificial Intelligence (NCARAI). The editor was Professor John Grefenstette
at Vanderbilt University.
I took a course on Genetic algorithms from Professor Grefenstette last year.
However, I believe that he has moved to another school by now. Vanderbilt
should be able to point you to him, and he has copies of the proceedings.
--
doug foxvog ihnp4!allegra!lcuxlj!dougf
if only Bell Labs would agree with my opinions...
For NSC line eaters:
Names of drug dealing CIA agents working on TEMPEST for NRO encrypted above.
------------------------------
Date: 27 Mar 87 12:49 EST
From: denber.wbst@Xerox.COM
Subject: Re: Explanation and Justification
"does an expert system need to be able to explain itself to be useful"
No.
- Michel
------------------------------
Date: Fri, 27 Mar 87 10:20:41 GMT
From: Martyn Thomas <mcvax!praxis!mct@seismo.CSS.GOV>
Reply-to: ...seismo!mcvax!ukc!praxis!mct (Martyn Thomas)
Subject: Re: Oxymoron: Real-time Knowledge-Based Nurse/Nuclear Plant
Operator
In article <8703250728.AA21290@ucbvax.Berkeley.EDU>
lugowski%resbld@ti-csl.CSNET writes:
> I wouldn't trust AI techniques with monitoring large dynamic
>systems of the class of a medium-sized municipal toilet. I would certainly
>want out of any ICU where my fragile well-being did not depend on an ICU
>nurse, overworked as though he or she may be. The AI community has had up
>to now the good sense of relegating its really questionable achievements to
>the battlefield, where they are fondly appreciated. Let's not get too greedy
>by introducing the battlefield to our rather safe nuclear plants and ICUs.
>
> -- Marek Lugowski
> Texas Instruments
> lugowski%crl1@ti-csl.csnet
I strongly agree. Any safety-critical system should have certain
characteristics: it should be rigorously specified (AT LEAST the safety
aspects); it should be possible to reason rigorously about the
implementation, to convince others that it matches the specification;
it should be developed using QC/QA techniques that guarantee an audit trail
so that any faults discovered after development can be traced to their
cause.
These considerations dictate the use of mathematically rigorous methods, and
a certified Quality Assurance regime. Does anyone know of an AI system
which measures up? Please reply by mail - I'll summarise.
Martyn Thomas mct%praxis.uucp@ukc.ac.uk <or>
Praxis Systems plc ...seismo!mcvax!ukc!praxis!mct
20 Manvers Street, Tel: +44 225 335855
BATH BA1 PX England. Fax: +44 225 65205 (Groups 2&3)
------------------------------
Date: 25 Mar 87 01:44:00 GMT
From: kadie@b.cs.uiuc.edu
Subject: Re: AI Project Information Request
Automatic checking and automatic grading are different things. I think
<<* 3. WEAK: I think *>>↑
automatic computer checking is a good thing, especially for spelling
and simpler grammar.
But there is no reason to grade automatically, just let the students
↑<<* 23. SENTENCE BEGINS WITH BUT *>>
work on their papers (with the automatic checker) until they are satisfied.
<<* 21. PASSIVE VOICE: are satisfied. *>>↑
<<* 17. LONG SENTENCE: 24 WORDS *>>↑
Then have them turn in their work and the final computer critique to a human
grader.
The situation is similar to programming, where the compiler
automatically checks the syntax. It would be unthinkable to make people turn
in programs without letting them compile the programs first. On
the other hand it would unthinkable to leave a syntax error in
when the compiler tells you right were it is.
<<** SUMMARY **>>
READABILITY INDEX: 10.42
Readers need a 10th grade level of education to understand.
STRENGTH INDEX: 0.41
The writing can be made more direct by using:
- the active voice
- shorter sentences
DESCRIPTIVE INDEX: 0.65
The use of adjectives and adverbs is within the normal range.
JARGON INDEX: 0.00
SENTENCE STRUCTURE RECOMMENDATIONS:
1. Most sentences contain multiple clauses.
Try to use more simple sentences.
<< UNCOMMON WORD LIST >>
The following words are not widely understood.
Will any of these words confuse the intended audience?
CRITIQUE 1 SYNTAX 2 UNTHINKABLE 2
<< END OF UNCOMMON WORD LIST >>
Carl Kadie
University of Illinois at Urbana-Champaign
UUCP: {ihnp4,pur-ee,convex}!uiucdcs!kadie
CSNET: kadie@UIUC.CSNET
ARPA: kadie@M.CS.UIUC.EDU (kadie@UIUC.ARPA)
------------------------------
End of AIList Digest
********************
∂28-Mar-87 0242 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #90
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 28 Mar 87 02:42:13 PST
Date: Fri 27 Mar 1987 22:42-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #90
To: AIList@SRI-STRIPE.ARPA
AIList Digest Saturday, 28 Mar 1987 Volume 5 : Issue 90
Today's Topics:
Neural Networks - Newsletters,
Discussion Lists - Symbolic Math List & Impact of Information Services,
Policy - Censorship & Militarism,
Review - Spang Robinson Report, March 1987
----------------------------------------------------------------------
Date: 12-MAR-1987
From: GATELY%CRL1@TI-CSL.CSNET
Subject: Newsletters for Neural Networks
[Forwarded from the Neuron Digest by Laws@SRI-STRIPE.]
This message is ment simply to inform the reader of two monthly
newsletters which seem to be focusing on neural networks. The
first is named "Intelligence," is edited by Edward Rosenfeld, and
is available for $295 per year (published monthly). The address
for more information (and perhaps a free copy) is POBox 20008,
New York, NY 10025, (212) 749-8048.
The second newsletter is titled "Neurocomputers," is edited by
Derek F. Stubbs, and is available (on a new member basis?) for
US$24 (USA, Canada, and Mexico) or US$32 (all other countries) per
year (published bi-monthly). The address is: NEUROCOMPUTERS,
Gallifrey Publishing, POBox 155, Vicksburg, Michigan 49097.
Intelligence seems to be an older (seasoned) newsletter, dealing
with all aspects of AI - but focusing on neural networks. The
issue of Neurocomputers that I have (V1 #1) has a wide variety
of NN items (news, books, results).
I have no ties with either of these newsletters!
------------------------------
Date: Thu, 26 Mar 1987 19:11 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Symbolic Math List
I am now taking over symbolic math list editor/moderator responsibilities.
Please send your submissions to sym-list%smu@csnet-relay.
Sym-list-request%smu@csnet-relay will be for administrative messages.
People with access to bitnet may wish to send mail to my personal
account: E1AR0002@SMUVM1. However, in the event of a change
of moderator, only the [Arpanet] addresses will be automatically forwarded.
I will be copying materials posted in the USENET group sci.math.symbolic
to the ARPANET/CSNET and BITNET mailing lists and vice versa. Needless
to say, I will filter out irrelevant or otherwise inappropriate materials
from the mailing list. Routine queries, such as those asking for ordering
information on various symbolic math systems, will be handled personally
and not forwarded.
------------------------------
Date: Thu, 26 Mar 1987 19:11 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Impact of Information Services
Source: Information Week, March 23, 1987, Page 15
In a survey of DP managers at the largest companies, 92% said
that overnight delivery had high impact on their operations while
only 39% saw E-mail that way. 75% saw facsimile transmission as
high impact and 9% said video conferencing was.
------------------------------
Date: Wed, 25 Mar 87 11:31:11 PST
From: pyramid!ctnews!mitisft!markb@decwrl.DEC.COM
Subject: censoring mod.ai ?
In article <8703231704.AA12675@boring.cwi.nl>, tomi@cwi.nl (Tetsuo
Tomiyama) writes:
<a lot of stuff about military AI research>
While I sympathize with your distaste for military matters, I suggest
that it is in everyone's best interest to be constantly aware of what
the military is doing with AI. Hiding one's head in the sand will not
make matters any better.
So keep the articles coming. The 'n' key works just fine if you're really
offended.
------------------------------
Date: Thu, 26 Mar 87 09:46:24 pst
From: marks@ads.ARPA (Phil Marks)
Subject: AMERICAN-MILITARISM
>
> Date: Fri, 20 Mar 87 14:28:46 +0100
> From: mcvax!cwi.nl!tomi@seismo.CSS.GOV (Tetsuo Tomiyama)
> Subject: Policy - American Militarism
>
> Now, I am strongly against such a posting circulated ALL AROUND THE
> WORLD through the net. [...] I think
> this kind of postings should be even prohibited from the world wide
> net distribution. [...]
>
> I propose, therefore, to submit postings relevant to militarism should
> NOT be PROHIBITED but at least requested to be MARKED as military
> related article at the responsibility of original authors (rather than
> by the moderator), just like advertisements from tobacco companies, so
> that if I don't want to read it I can skip it.
re AMERICAN-MILITARISM:
Very Interesting...that we should get such an opinion from a Japanese.
A review of recent history shows that Japan's main contribution to the
20th century has been a series of brutal attempts to subjugate its
neighbors (China, Korea, the Philippines, etc). The only reason that
Japan was not able to impose its barbarianism on these peoples was
AMERICAN-MILITARISM. If it had not been for AMERICAN-MILITARISM the
infamous and cowardly attack on Pearl Harbor might have ultimately lead
to the subjection of America to the same atrocities as Japan's other
victims. It was the Americans (including the American military) which
rebuilt Japan from a devastated military dictatorship and tried to give
the Japanese people a chance at the opportunities and responsibilities
of freedom...a lesson which is apparently totally lost on mr tomiyama.
It is common practice today for the adherents of all stripes of
totalitarianism to decry AMERICAN-MILITARISM because it is the ONLY
thing which stands between them and their goal of world domination. If
they can get us to reduce our strength and vigilance then they can
resume where they left off 40 years ago.
Philip Marks
[That's a bit strong, isn't it? Mr. Tomiyama can hardly be accused
of desiring world domination just because he's an ardent pacificist.
I'm sure that many Japanese have learned the lessons you mention. The
new generations of Japanese are no more responsible for, or necessarily
prone to, the excesses of past leaders than I am responsible for the
past mistreatment of Native Americans, Negros, or Orientals in this
country.
AIList is a good forum for debating the linkage of AI and militarism,
but let's not debate militarism per se. And for the record, I am the
one who chose the title "American Militarism". I think the original
was just called "Submission for mod.ai". My choice of title still
seems appropriate, but I'm sorry if it rankled anyone. -- KIL]
------------------------------
Date: Fri, 27 Mar 87 02:31 EDT
From: STANKULI%cs.umass.edu@RELAY.CS.NET
Subject: AI militarism
perhaps i am stepping out of my league here, but i feel that Ken Laws and
AILIST should be encouraged to circulate information about all AI-related
applications, especially whatever military issues can be circulated among
us.
tactics is the use of force (a semantics on a fundamental physical
property), and the evolutionary development of it has been an ongoing
process which has been around as long as there has been animal life on this
planet. strategy is a metalanguage on tactics; and, according to clausewitz
(1832, On War), policy is a metalanguage on strategy. human lives have been
lost or saved through the application of these principles. to think that an
artificial intelligence can avoid or ignore the fact that force can break
structure is naive. hide-your-head-in-the-sand moralities which seek to
deny the validity of tactics almost always begin with the preamble "IF
nobody used force..."
democratic societies are directly based on the ability of the populace to
make informed decisions on policy. censorship (the selective hiding of
information) is an inheirent evil in a society which tries distribute
political power across the widest possible base. i believe that atomic
weapons have been so judiciously unused because of the widespread knowledge
of their lethality. the only tactical use of them took place when their
existence was security classified and controlled by a few people.
if AI has the power we believe it does, then the safest use is that which
circulates the information to the widest possible audience-- especially to
those who have do-not-use viewpoints. rather than trying to embarass our
military sponsers when they do share with us insights into tactical AI uses,
we should encourage such rare openness. the danger lies in power that can
exist which is kept secret.
if AI does not have the power we believe it does, then little is lost in
the publication of plausible fiction, and we all gain by the integrity of an
open knowledge base.
stan
[EOF] AI-Military.Mai
------------------------------
Date: 26 March 1987 1527-PST (Thursday)
From: thode@nprdc.arpa
Reply-to: thode@nprdc.arpa
Subject: Censorship of AIList submissions
Tetsuo Tomiyama (mcvax!cwi.nl!tomi@seismo.CSS.GOV) in a recent posting
complained about a call for papers for AI Applications to Battle
Management because of its relationship to US military research. He
suggests that the rest of us somehow mark any military research related
submissions to discussion lists like the AIList so that he can easily
identify them and avoid reading them. I thought Ken Laws' response was
appropriate:
> AIList is primarily an Arpanet discussion list. The Arpanet
> was developed by the military, is supported by the military,
> and is intended for defense-related communication among
> military contractors. One could assume that all Arpanet
> messages are military in nature, although that heuristic
> does not seem very useful in the case of AIList. What is
> really needed here is an intelligent mail reader that screens
> your messages and adds the appropriate keywords. -- KIL
I would go a bit further than Ken. What is REALLY needed is an
intelligent (human) mail reader. Readers of net mail who are afraid of
what they might read shouldn't read anything. This reminds me of those
who want to censor books, prohibit free speech, and otherwise govern
the way we live our lives because they don't like what might be read
or said. Freedom of speech (and electronic postings) should be anyone's
right. If you don't like what someone writes, don't read it--but keep
your hands off my (and others') rights to read and say what we want.
--Walt Thode (thode@NPRDC)
------------------------------
Date: Thu, 26 Mar 1987 19:11 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Review - Spang Robinson Report, March 1987
Spang Robinson Report, Volume Number 3, March 1987, Summary Thereof
The main article discusses AI and Database Technology with the results
of an interview with James Neiser of Ashton. Ashton Tate is going to
be concentrating non-AI decison-rules with natural language and expert systems
to be considered later. The newsletter also includes a two page table
listing various company's plans and products in the database-AI integration
area.
Other items of note in this article include:
Symantec has sold 40,000 copies of their system which is a data base
system with natural language.
Cullinet has agreed to acquire the company selling a COBOL based expert
system shell
Man-Machine systems is marketing G-Base for the LMI Lambda and TI explorers
which allows the interfacing of LISP and PROLOG to the database
IBM has created a natural language and Prolog front end to SQL.
__________________________________________________________
New Applications of Expert Systems:
Cannon - copier maintenance system
Ishikawajima Heavy Industry- engine failure analysis system
Yasukawa Electric Manufacturing System - large crane analysis system
Iwai Mechanical Industry - plant failure analysis sytem
Technical Collaborates - expert system for architects in the area of disaster/
safety regulations (in planning)
Takenaka Engineering - construction, surveying, (in development)
__________________________________________________________
Shorts
Fuji Xerox will be distributing PARC Smalltalk in Japan and ASR
will be marketing ExSys in Japan.
Medical Information Systems has a network allowing people to use medical
expert systems that is accesible via Fujitsu's VAN service.
Level Five Insight 2+ can access DBase II files.
The Senior marketer at Applied Expert Systems, Richard Karash, has left.
Larry Geisel is leaving the Carnegie Group CEO position possibly to start
another company.
__________________________________________________________
The newsletter also contains a review of the recent IEEE conference on AI applic
ations.
Also reviews of the CRI Directory of Expert Systems and SEAI's Expert Systems 19
86:
An Assessment of Technology and Applications.
------------------------------
End of AIList Digest
********************
∂30-Mar-87 0047 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #91
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 30 Mar 87 00:47:08 PST
Date: Sun 29 Mar 1987 22:31-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #91
To: AIList@SRI-STRIPE.ARPA
AIList Digest Monday, 30 Mar 1987 Volume 5 : Issue 91
Today's Topics:
AI Tools - TMYCIN: Free EMYCIN-like ES Tool,
CAD - Solid Modeling & CAD/CAM/Robotics/Vision Policy,
Comments - American Militarism & Ad Hominem Arguments
----------------------------------------------------------------------
Date: Fri 27 Mar 87 17:39:04-CST
From: Gordon Novak Jr. <AI.NOVAK@R20.UTEXAS.EDU>
Subject: TMYCIN: Free EMYCIN-like ES Tool
The following two messages contain the code and documentation for a
small EMYCIN-like expert system tool called TMYCIN (for Tiny EMYCIN).
TMYCIN is written in Common Lisp (in a rather "old" Lisp style to make
it easy to port to other dialects). Since it is only about 10 pages
of code, it does not implement all of the features of EMYCIN, but it
does cover some of the most-used features. The implementation is a
new one, written from scratch, so it is different internally from EMYCIN;
however, I have tried to follow EMYCIN conventions where possible.
TMYCIN was originally written for use in an AI and Expert Systems course
taught at Hewlett Packard. While it is not an "industrial strength" ES
tool, others may find it useful for teaching or for self-study.
The Artificial Intelligence Laboratory at the University of Texas at Austin
receives major support from the U.S. Army Research Office under contract
DAAG29-84-K-0060. The A.I. Lab has also benefitted from major equipment
grants from Hewlett Packard and Xerox.
Enjoy...
Gordon Novak
[Remember the AI Expert sources? I had to set a policy
of not distributing large amounts of code. Granted, the
two digests worth of code and examples is much smaller, but
the same principle seems to apply. I would also prefer not
to be responsible for such distributions because people ask
for the code with fair regularity; I then have to keep it
on disk or repeatedly pull it from tape, and my company has
to bear the cost. I'm open to suggestions for how code should
be handled, but AIList doesn't seem to be the place. (Usenet
has a comp.sources, and there is a Unix code distribution,
but Arpanet really has no mechanism other than contacting the
author or FTPing his files.) -- KIL]
------------------------------
Date: 27 Mar 87 20:12:10 GMT
From: ssc-vax!thornton@BEAVER.CS.WASHINGTON.EDU (Ken Thornton)
Subject: Solid Modeling
Unfortunately, there is no CAD/CAM, Robotics, or Automation newsgroups
so I decided to post here.
I am interested in hearing from people who know about solid modeling systems
and have experience using them. Specific questions I'm interested in are:
What is generally preferred, constructive solid geometry (CSG) representations
or boundary represesentations (B-rep)?
Of the available commercial systems, is CSG or B-rep more predominant?
I am specifically interested in generating procedures for a robotic vision
system to automatically inspect a part, given a solid model of the part.
In addition to the actual part model, it would be necessary to have
information about specific features, relationships between features,
feature tolerances, and object surface reflectance. From what I understand,
commercial systems do not provide this information in the output file
representation of the part.
More than anything, I'm interested in stimulating some discussion about
solid modeling and related computer graphics algorithms. If such a
discussion is considered inappropriate to this newsgroup, I might be interested
in forming another group or starting a mailing list, if anyone is
interested.
Ken
--
Ken Thornton {decvax,ihnp4}!uw-beaver!ssc-vax!ssc-bee!thornton
Boeing Aerospace PO Box 3999 MS 2E-73 Seattle, WA 98124-2499
"A little learning is a dang'rous thing" - Alexander Pope
------------------------------
Date: 29 Mar 87 04:14:36 GMT
From: rpics!chassin@seismo.css.gov (Dave Chassin)
Subject: Re: Solid Modeling
In article <798@ssc-bee.ssc-vax.UUCP>, thornton@ssc-vax.UUCP
(Ken Thornton) writes:
>
>
> Unfortunately, there is no CAD/CAM, Robotics, or Automation newsgroups
> so I decided to post here.
I guess it as good a place as any...
>
> I am interested in hearing from people who know about solid modeling systems
> and have experience using them. Specific questions I'm interested in are:
>
> What is generally preferred, constructive solid geometry (CSG)
> representations
> or boundary represesentations (B-rep)?
>
> Of the available commercial systems, is CSG or B-rep more predominant?
Preference really depends on application (see below), as for predominance, it
depends on what system you using. B-rep modeling is the predominant form
of geometric data representation on microcomputers. This is mainly because
of memory/speed restrictions that have existed since the dawn of micros
(things are changing but not yet enough, and not fast enough). CSG is
far more common on minis and mainframes for the same reasons, but also
because data is much more easily manipulated, and more logically in terms
of geometric thinking (unions, intersections, cutting, etc). My preference
(as an architect) is to use CSG for conceptual manipulations, and B-rep
for detailed representations. Each have their limitations, and if anyone
is interested, we can discuss these at great length sometime later.
>
> I am specifically interested in generating procedures for a robotic vision
> system to automatically inspect a part, given a solid model of the part.
> In addition to the actual part model, it would be necessary to have
> information about specific features, relationships between features,
> feature tolerances, and object surface reflectance. From what I understand,
> commercial systems do not provide this information in the output file
> representation of the part.
CSG seems to me to be the most readily applied to this type of work. The
reason is that CSG can naturally indicate whether two parts geometrically
intersect each other, for example. However surface features like color
and reflectances are not inherently applied to CSG modeling, although I imagine
this could be developed, and might even be worth while. B-rep seems to be
a bit more of a problem in terms of manipulating relationships between parts.
I think that you have another problem when you get involved with robotic
vision,
and this is something that I've never thought about in terms of robotics, but
I am working on in terms of architectonics (architectural modeling of sorts).
That is that you will need to create some sort of algorithm for generating a
3D model from 2D information received by the cameras. Essentially the idea
is to analyse a pair of images, extract the boundary data, assemble a 2D
'image' for each view, project the two images together into a 3D 'image',
and finally take the resulting B-rep data and convert it to CSG type data,
which can then be correlated with the previous frame and the motor algorithms
to properly direct the parts into their desired positions. Piece of cake, eh...
Each of these steps involve some very complicated and SLOW computing. I've
worked out the basics for the first 4 steps, but have a long way to go
still. In any case I would love to talk more about the ins and outs of this
type of analysis because this is the main focus of my work for the next
year or so. By the way, it's all being done on a Sun 2/120 and 2 AT clones...
...wish me luck!!!
I know there are some people who have already done some work in these areas,
but it has always amazed me how little is in fact published. I have NO, get
that, NO references relating to 3D reconstructions other than the following,
and these have nothing to do with computer application thereof:
Wittcower & Carter, "The perspective of Piero della Francesca's
Flagellation", COURTAULD INSTITUTES, vol.16, 1953
In this article the authors explain the method they used for reconstruct
the actual architectural space that Piero painted. The mathematics of
perspective are treated, and discussed.
Since this is obviously not directly related to the subject I would
greatly appreciate any sources anyone might know of. They are rare, and
those that I have found, uninspiring.
So, anyway, I encourage further discussion of this topic as it is a very
difficult one, and it will, I believe, in the long run test what we
computer graphics buffs are really made of. This problem goes beyond
simply one of analysis, to become one of representation and ordering. The
results, or lack thereof, will reveal much more about how we perceive and
order what we see. This is the heart of the problem.
_____________________
David P. Chassin
Rensselaer Polytechnic Institute |
School of Architecture __+__
Troy, NY 12181 / _ \
USA | | | |
/=======/ = \=======\
(518) 266-6461 | _ | _ | _ |
| | | | | | | | | |
chassin@csv.rpi.edu | = | | | | = |
=======================================================================
The above is my opinion, and mine alone. The organization I belong to
may refute these statements at any time. They are however more likely
to take credit for them.
=======================================================================
------------------------------
Date: Sun 29 Mar 87 21:55:16-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Reply-to: AIList-Request@SRI-AI.ARPA
Subject: Policy - CAD/CAM/Robotics/Vision
I hate to turn away AI-related discussions, but CAD/CAM,
Robotics, and Vision are large enough areas that they
should have their own lists. I've heard that there is
a CADinterest↑.es@Xerox.COM list (reachable via seismo
from csnet) that discusses VLSI design, CAD workstations,
etc. There are Arpanet lists for graphics
and for workstations, as well as Vision-List@ADS for
machine-vision discussions. I don't know of any robotics
list, although Vision-List has carried related messages.
(Vision workers are often interested in path planning and
other robotic issues.)
Some of the aforementioned lists have been inactive lately.
You could either "take over" one of their discussions for
awhile or start a new list that combines your own interests.
I'm told that an AI-Hardware list will be formed soon --
perhaps CAD/CAM will be of interest there.
-- Ken Laws
BTW, there is indeed a literature on combining 2-D views to
construct 3-D objects -- both for converting mechanical drawings
to solid models and for extracting buildings from aerial
imagery. I don't have references handy, but Tom Strat
here at SRI published some papers on this a year or so ago.
Underwood also worked on this problem, as have others. There
is also a vast literature on combining stereo views to obtain
3-D models for robotic inspection and grasping.
------------------------------
Date: Sat 28 Mar 87 11:58:49-EST
From: Richard A. Cowan <COWAN@XX.LCS.MIT.EDU>
Subject: Re: American Militarism
(This is a condensed version of a response I sent to Tetsuo Tomiyami:)
Although I may share your sentiments regarding the military emphasis
of computer science, I agree with Ken Laws that the the mention of
military applications in AILIST is appropriate and should not be
censored out, for two reasons.
First, if there is military research going on in AI on the automated
battlefield, I think it is better that this be acknowledged openly
than hidden from view. Keeping military work shielded from view
merely makes this work more difficult to criticize. Acknowledging
its presence allows affected communities (such as the AI community) to
openly debate the nature of such work and reach a community decision.
Second, I don't think your analogy (to showing pornography in public)
holds. The harmful effects of showing pornography (not erotica, but
degrading, sexually exploitative material) come directly from showing
it, but the harmful effects of military work do not come from merely
acknowledging its presence.
I think it would be more constructive to engage people on the AILIST
in discussions of the implications of military AI. If people
responded by saying that discussion about the effects of AI research
on society are irrelevant to the list because they are political
questions, *then* you might have something to gripe about. Why?
Because scientists and engineers (especially those who receive public
funds) have a responsibility to society to consider the implications
of their work. Therefore, discussion of the implications of military
AI (or civilian AI) is totally appropriate, and should not be
suppressed in one of the major forums for communication used by AI
scientists. (Though it is certainly appropriate for a moderator to
cut out stuff to prevent flaming from getting out of control.)
Now that Artificial Intelligence, having found uses in society, is no
longer an ivory tower avocation, politics is not extraneous to AI.
Rather, as the AAAI conference on "Issues Concerning AI Applications
To Battle Management" shows, AI *is* political.
-rich
------------------------------
Date: Sat, 28 Mar 87 13:52:49 EST
From: cross@nrl-css.arpa (Chuck Cross)
Subject: ad hominem arguments
Phil Marks' reply to Tetsuo Tomiyama begins: ``Very interesting...that we
should get such an opinion from a Japanese'' [the dots are his]. I can
think of nothing more offensive in a discussion than using a person's race
or national origin to ridicule his position. It is the worst kind of ad
hominem argumentation.
Chuck Cross
------------------------------
End of AIList Digest
********************
∂31-Mar-87 0057 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #92
Received: from SRI-STRIPE.ARPA by SAIL.STANFORD.EDU with TCP; 31 Mar 87 00:57:44 PST
Date: Mon 30 Mar 1987 22:34-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #92
To: AIList@SRI-STRIPE.ARPA
AIList Digest Tuesday, 31 Mar 1987 Volume 5 : Issue 92
Today's Topics:
AI Tools - How to FTP TMYCIN,
Policy - TMYCIN Code and Military AI,
Conference - Computing and Political and Social Issues,
Query & Replies - Daemons,
AI Tools - Genetic Algorithms,
CAD - Solid Modeling
----------------------------------------------------------------------
Date: Mon 30 Mar 87 10:42:04-CST
From: Gordon Novak Jr. <AI.NOVAK@R20.UTEXAS.EDU>
Subject: How to FTP TMYCIN
An earlier msg to this list offered TMYCIN, a small EMYCIN-like expert system
tool. Due to a policy of not distributing code on AILIST, the code was
excised by the editor.
The TMYCIN files are located on R20.UTEXAS.EDU ; Arpanet sites should be
able to get them, from directory <AI.NOVAK> , by anonymous FTP. If you
can't get them by FTP, let me know and I'll attempt to mail them.
The single file TMYCIN.ALL contains all the material appended together.
That may be the easiest to FTP. The individual files are TMYCIN.CL ,
TMDOC.DOC , TMTEST.CL . TMYCIN.CL is the largest, at about 22K chars.
Personally, I think AILIST should change its policy on distributing source
code; it would benefit a lot of people and be more valuable than much of the
material that appears on AILIST now. I have had poor luck in mailing code
to non-Arpanet sites. So long as code is identified as such so that people
can skip it if they don't want to see it, I don't see the objection to
including it. The bibliography lists are each as big as the TMYCIN code,
and lots of them are put on the AILIST.
If anyone wants to move the TMYCIN files to repositories of code where
people can get it more easily, that is fine with me. And let me add my
support to the idea of starting such a repository on the Arpanet.
Cheers, Gordon
------------------------------
Date: Mon, 30 Mar 87 10:08:31 pst
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: TMYCIN code and Military AI
The following should be regarded as opinion and commentary rather than
the expression of fact.
First, the dissemination of Tiny MYCIN sounds interesting.
I wish I had a convenient Common LISP machine to try it out.
I realize that TMYCIN is just a tool, but I wonder how good a tool
it really is. What is the value of learning about this tool
(to learn about ESs) when you don't have an expert around (rhetorical
question, obviously some value)? I ask this because I have a relative
who does research in pathology and got his PhD in bacteriology
at BYU (any connection with Dugway Proving Ground is not coincidence).
Anyway, anyone in the South SF Bay with a Common LISP machine which we
can try this code out on?
Second, I too am torn about the posting of military AI material.
My immediate response was against it. But Ken Laws (The voice of reason)
made some good points: similar to ones I made about why the UC should
keep the weapons labs (to prevent them from disappearing from public
view, but I don't like the idea of a U doing this work). The comments
by another reader (which had nothing to do with AI) just go to reinforce
certain observations of latent (?) rascism within military circles
and is a prejudice I occasionally get (when I get asked to attend certain
military meetings as an outside reviewer). For some people, WWII has
not ended, nor I guess has the Civil War for some.
Recent trade developments again have people talking about Economic
Pearl Harbors (Fujitsu-Fairchild and other chip agreements). I know a
decorated, one armed Senator and our local House Representative who
are watching developments very carefully. (The Rep is on the side of the
USA, but will defend against any and all attacks against a people who were
interned during a prior war.) Watch it people.
--eugene miya
------ Asian Italian ancestory(?)
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
Date: 30 Mar 87 16:58:04 GMT
From: jon@june.cs.washington.edu (Jon Jacky)
Subject: Battle Management at AAAI, mod.ai postings policy, "Militarism"
I think it is fine that you ran the AAAI Battle Management Workshop
announcement. I have grave reservations about a lot of that stuff;
nevertheless it is useful even for critics to be informed of what's going on
in the area.
Also, it is important to note the role of the military in
supporting so much AI research. If anything, there is too little rather than
too much acknowledgement of this fact in the AI community. The original
announcement noted the recent "order of magnitude increase in funding for
battle management AI projects," but that is only the tip of the iceberg --
a very large body of apparently more generic AI work is also funded by the
Department of Defense. Much of that is putatively basic research, but the
motivation for the funding, as described to Congress and the Secretaries of
Defense, emphasises potential weapons applications. This relationship
should be frankly acknowledged, rather than concealed or glossed over.
A very important question is, does this source of funding and this kind of
motivation for even "basic" AI research make any difference, either for the
content of the technical work, or for the larger matters of war and peace?
These issues will be addressed at another event (here comes the plug). On
Sunday, July 12 in Seattle, the day before the AAAI conference, the Seattle
Chapter of Computer Professionals for Social Responsibility is sponsoring
a one day-conference concerning computing and political and social
issues.
The keynote speakers will be Bob Kahn, who now heads the nonprofit
Corporaton for National Research Initiatives and who until 1985 was director
of the Information Processing Techniques Office at DARPA, and Terry
Winograd. We are accepting papers until April 1. (If you have something
you would like to submit but are worried about making the deadline, or would
just like to attend, call or write to me).
-Jonathan Jacky
University of Washington
jon@june.cs.washington.edu
(206)-548-4117
------------------------------
Date: 29 Mar 87 14:43:44 GMT
From: ihnp4!cord!gwr@ucbvax.Berkeley.EDU (GW Ryan)
Subject: daemons... where's the name from?
this came up in a class last week; we came up with a few interesting ideas but
no real answers. Why are "daemons" called "daemons"? that is, what is the
derivation of that name?
We got answers like "something to do with Maxwell's daemon" and "maybe if you
say the magic words (i.e. satisfy the conditions to fire the daemon) then the
daemon wakes up".
anybody know the right answer??
mail to me, and I'll summarize to the net.
thanks
jerry
allegra!cord!gwr
gwr@cord.garage.nj.att.com
------------------------------
Date: 29 Mar 87 22:20:49 GMT
From: flowers@locus.ucla.edu
Subject: Re: daemons... where's the name from?
>this came up in a class last week; we came up with a few interesting ideas but
>no real answers. Why are "daemons" called "daemons"? that is, what is the
>derivation of that name?
From "Pattern Recognition by Machine", by Selfridge and Neisser,
Scientific American 1960, in describing the Pandemonium model they proposed:
In parallel processing all the questions would be asked at once,
and all the answers presented simultaneously to the decision
maker. Different combinations identify the different letters.
One might think of all the various features as being inspected by
little demons, all of whom then shout the answers in concert to a
decision-making demon. From this conceit comes the name
"Pandemonium" for parallel processing.
This paper was reprinted in the seminal and still useful book
_Computers and Thought_, Feigenbaum and Feldman, eds., 1963. Anyway,
Selfridge and Neisser have some earlier publications about pattern
matching and the Pandemonium model which probably introduced the idea
of demons. I don't know if their use of the term was inspired by any
prior specific use.
Around 1970 demons were utilized and popularized by Charniak's Ph.D.
thesis.
Margot Flowers, Asst. Prof., UCLA AI Lab
Flowers@CS.UCLA.EDU [or Flowers@UCLA-CS for old host tables]
...!{ucbvax|ihnp4}!ucla-cs!flowers (uucp)
------------------------------
Date: 29 Mar 87 23:10:00 GMT
From: ihnp4!inuxc!iuvax!port@ucbvax.Berkeley.EDU
Subject: Re: daemons... where's the name from?
The use of daemon in Unix for a program that `wakes up' and
does some task whenever it is required is actually a
regular use of the word. It isnt one of those typical
computing terms that has an arcane history (one thinks
of the derivation of `nroff, grep, awk, winchester,' etc).
The word is classical Greek for any kind of spirit or
genie -- some kind of minor deity. In Latin they borrowed
the Greek word and spelled it daemon (for Greek daimon-ion),
to descdribe such spirits. For the Christians, of course,
all such deities were paganisms so, they were viewed
as evil. Thus the English word demon has the strong
flavor of evil about it.
But we also seem to have split the word in two,
so now the original pagan meaning has been restored in
modern English with a more classical spelling as daemon.
The use in `Maxwell's daemon' is in just this sense.
Similarly, in the 1950's Selfridge proposed a parallel model of
the perception of alphabetic letters that had `daemons'
for each letter. They were competing with each other
to `find themselves' in the incoming visual features.
The one that `shouted' the loudest was the one that
caused a `decision demon' to issue a conclusion.
The use of this word for independent procesess
that seem to have a `will of their own' as in operating
systems is very appropriate.
------------------------------
Date: 26 Mar 87 15:50:33 GMT
From: hpcea!hpfcdc!hpfclp!hillary@hplabs.hp.com (Hillary Davidson)
Subject: Re: Genetic Algorithms
Concerning GAs....
I am researching genetic algorithms for my Master's thesis work at CSU in
Ft. Collins, CO. I am doing this research under Dr. Darrell Whitley.
There is a conference on GAs this summer....it is the 2nd International
Conference on Genetic Algorithms an Their Applications, sponsored by AAAI
and the U.S. Navy Center for Applied Research in AI (NCARAI). It will be
on July 28-31, 1987 at MIT in Cambridge, Mass. John Holland is the
Conference Chairperson.
For more information contact:
Mrs. Gayle M. Fitzgerald
Conference Services Office
Room 7-111
MIT
77 Massachusetts Avenue
Cambridge, MA 02139
(617) 253-1703
The first of this conference was held on July 24-26, 1985 at Carnegie-Mellon
U. in Pittsburgh, PA. I obtained a copy of the proceedings by writing the
editor at the following address:
Dr. John J. Grefenstette
Navy Center for Applied Research in AI
Naval Research Laboratory
Washington, DC 20375-5000
gref@NRL-AIC.ARPA
(202) 767-2685
Holland's newest book "Induction: ...." is a well written book. It expands on
the chapter in "Machine Learning, Volume 2" that he wrote.
Hope this info is helpful.
Hillary Davidson :-) {hplabs,ihnp4}!hpfcla!hillary
------------------------------
Date: 30 Mar 87 19:52:10 GMT
From: puff!upl@rsch.wisc.edu (Future Unix Gurus)
Subject: Re: Solid Modeling
In article <798@ssc-bee.ssc-vax.UUCP> thornton@ssc-vax.UUCP
(Ken Thornton) writes:
>
>
>Unfortunately, there is no CAD/CAM, Robotics, or Automation newsgroups
>so I decided to post here.
>
>I am interested in hearing from people who know about solid modeling systems
>and have experience using them. Specific questions I'm interested in are:
I am doing a solid modeling based animation system as my senior's thesis
(on the Amiga1000. I also hope to eventually release it as a product, it
should beat the living daylights out of Caligari. (Modesty is not one of my
strong points)). In preperation for the thesis, I have spent the past year
and a half researching pertinient issues such as solid modeling techniques.
While I am not as informed as someone might be who has been working in the
field in the real world (i.e. not a student) I have learned a fair bit.
I am also VERY interested in discussing this topic with ANYONE out there!
>
>What is generally preferred, constructive solid geometry (CSG) representations
>or boundary represesentations (B-rep)?
The current trend seems to be toward CSG-BREP hybrid systems. BREP is very
good for generating wireframes, doing things like mass calculations, and
certain approaches to ray tracing. The big problem with BREP is the user
interface. We do not have a true 3d output device available yet, and
most of the systems for plotting 3d points on 2d displays are awkward,
confusing, and time consuming. BREP offers a system in which the user
can work with 3d primatives to begin with, on a more higher level and in
a manner more natural to most people. What most of the systems I've seen
do is take input as CSG from the user, and simultaneously perform
CSG operations on pre-defined BREP primatives that approximate the CSG
ones. There is a good article in the conference proceedings from
Siggraph '86 on one way to do these CSG ops on BREP objects.
>
>Of the available commercial systems, is CSG or B-rep more predominant?
>
See the above. Realize that I have seen more art intended systems than
CAD type systems, but they seem to be the same difference.
>
>More than anything, I'm interested in stimulating some discussion about
>solid modeling and related computer graphics algorithms. If such a
>discussion is considered inappropriate to this newsgroup, I might be
interested
>in forming another group or starting a mailing list, if anyone is
>interested.
GREAT! Lets discuss!
Jeff Kesselman
ihnp4!uwvax!puff!uhura!captain
(Captain @ Uhura in the Undergraduate Project Lab)
------------------------------
End of AIList Digest
********************
∂07-Apr-87 1158 LAWS@STRIPE.SRI.COM AIList Digest V5 #93
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 7 Apr 87 11:57:50 PDT
Date: Wed 1 Apr 1987 22:10-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #93
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 2 Apr 1987 Volume 5 : Issue 93
Today's Topics:
Seminars - AI, Mathematical Programming, and VLSI Design (Rutgers) &
Automating Theory Formation (Rutgers) &
Concept Learning (Ames) &
Argo: Analogical Reasoning for Design Problems (Rutgers) &
Decomposition for Hierarchical Problem Solving (Rutgers),
Conferences - Simulation & Protocol Specification
----------------------------------------------------------------------
Date: Wed, 25 Mar 87 18:17:55 EST
From: liew@aramis.rutgers.edu (Liew)
Subject: Seminar - AI, Mathematical Programming, and VLSI Design (Rutgers)
The next design colloquim will be held on Thursday (march 26th) at
1:30pm in TCB 103. Most of you are unfamiliar with the location of
TCB 103 so we will meet at Hill 423 at 1:15 and proceed from there.
The speaker will be Wayne Wolf of ATT Bell Laboratories and the title
of his talk is "Artificial Intelligence, Mathematical Programming and
VLSI Design". The suggested readings are:
Wolf, Kowalski, McFarland "Knowledge Engineering Issues in VLSI
Synthesis", AAAI-86.
Brayton, et al., "Multiple-Level Logic Optimization System",
ICCAD-86, pp. 356-360.
Gregory, et al., "SOCRATES: A System for Automatically Synthesizing
and Optimizing Combinational Logic", DAC-86, pp. 79-85.
Shin and Sangiovanni-Vincentelli, "MIGHTY: A Rip-Up and Reroute
Detailed Router", ICCAD-86, pp. 2-5.
Joobani, "WEAVER: A Knowledge-Based Routing Expert", PhD
dissertation, CMU, 1985.
----------------------------------------------------------------------
Abstract:
Title: Artificial Intelligence, Mathematical Programming, and VLSI Design
Speaker: Wayne Wolf, AT&T Bell Laboratories, Murray Hill
Artifical intelligence techniques have found their
greatest success in diagnosis and classification problems. The
application of AI to design problems is relatively new. In
this talk I want to consider how the intellectual tools that
AI brings to the design problem can best be used by contrasting
two paradigms: artificial intelligence and mathematical programming.
I will argue that mathematical programming is a more powerful
paradigm than AI for a lot of synthesis problems because
mathematical programming a) allows better application of
brute force; b) encourages us to formulate solvable problems.
I will argue that AI is a more powerful paradigm for
knowledge representation because it provides a lot of tools
for separating particular pieces of knowledge from the
engines used to maintain them.
The talk will be in three parts:
1) The VLSI design problem: what is hard about VLSI
design; what tools people need to make bigger, better designs;
what people would do with VLSI synthesis if they had it.
2) Synthesis and search: search in AI and mathematical
programming; problem formulation and search; results in
application of AI and mathematical programming techniques
to some design problems.
3) Synthesis and knowledge representation: why
knowledge representation is important; examples of KR
problems and solutions from Fred, the database; how
AI knowledge representation and mathematical programming
complement each other in Lucy, the controller designer.
------------------------------
Date: 26 Mar 87 17:01:17 EST
From: SOO@RED.RUTGERS.EDU
Subject: Seminar - Automating Theory Formation (Rutgers)
THE III, AN INFORMAL SEMINAR FOR AND BY STUDENTS,
--- INITIATES ITS SPRING SEASON ---
Title: Automating Theory Formation --
Postulation of Enzyme Kinetic Models
and Experimental Design
Date: April 7th, Tuesday
Time: 11:00 AM
Place: Hill 423
Speaker: Von-Wun Soo
This is a practice talk for my Ph. D. thesis defense. I would like to
present the work that I have been involved for the past five years.
I cordially invite you to come, support, and make comments before
my final defense.
Abstract:
In this talk I discuss how expert reasoning in scientific research such
as designing biochemical experiments or postulating kinetic mechanisms can
be modeled. Broadly speaking, designing an experiment, an important compoent
of scientific theory formation, can be viewed as a process of searching
and testing plausible decompositions of a hypothesis space.
In my thesis, I show how the results of qualitative reasoning and a
set partition method can be used to select experimental setups that
discriminate a set of plausible models. The interpretation of
experimental results, the critiques of previous experiments,
and comparisons of similarities and discrepancies among experiments
are all related issues that lead us to the automation of
scientific discovery.
------------------------------
Date: Thu, 26 Mar 87 21:31:07 PST
From: SIMS%PLU@ames-io.ARPA
Subject: Seminar - Concept Learning (Ames)
Title: LEARNING CONCEPTS TO IMPROVE PERFORMANCE:
The Role of Context
By: Dr. Richard Keller
(KELLER@RED.RUTGERS.EDU)
Computer Science Department
Rutgers University
Where: NASA AMES
When: Monday, April 6
Concept learning, like most intelligent behavior, should be
influenced by the context in which the behavior takes place. If
concept learning occurs in the context of improving the performance
of a problem solving system, then the type of concept learned and
the form of its description should depend on the goals and the
capabilities of the problem solver. Unfortunately, most current
inductive learning systems incorporate a set of fixed, implicit
assumptions about the problem solver being improved by learning.
This causes problems when the original problem solver changes over
time, and also makes it difficult to reuse the same inductive system
to improve a different problem solver.
As an alternative to the inductive framework, I describe a new
concept learning framework -- the concept operationalization
framework -- which makes contextual assumptions more explicit and
easier to change. To illustrate the new framework, I discuss how an
existing inductive system (the LEX system [Mitchell et al. 1981])
was converted to a concept operationalization system (the MetaLEX
system). In contrast with LEX, MetaLEX adapts more successfully to
certain changes in its learning context, learns contextually
suitable approximations of its target concept as necessary or
expedient, and has the potential to automatically generate its own
concept learning tasks to improve its problem solver.
------------------------------
Date: Mon, 30 Mar 87 15:22:26 EST
From: liew@aramis.rutgers.edu (Liew)
Subject: Seminar - Argo: Analogical Reasoning for Design Problems
(Rutgers)
There will be a design colloquim on Tuesday March 31st at 10:30 am in
Hill 423. The speaker will be Ramon Acosta of MCC and an abstract of
his talk is given below. A copy of his paper is in JoAnn Gabinelli's
office (Hill 408).
Argo: An Analogical Reasoning System for Solving Design Problems
Michael N. Huhns and Ramon D. Acosta
Microelectronics and Computer Technology Corporation
AI/KBS and VLSI CAD Programs
3500 West Balcones Center Drive
Austin, TX 78759
The static and predetermined capabilities of many knowledge-based design
systems prevent them from acquiring design experience for future use.
To overcome this limitation, techniques for reasoning and learning by
analogy that can aid the design process have been developed. These
techniques, along with a nonmonotonic reasoning capability, have been
incorporated into Argo, a tool for building knowledge-based systems.
Closely integrated into Argo's analogical reasoning facilities are
modules for the acquisition, storage, retrieval, evaluation, and
application of previous experience. Problem-solving experience is
acquired in the form of a problem-solving plan represented as a
rule-dependency graph. From this graph, Argo calculates a set of
macrorules, each based on an increasingly abstract version of the plan.
These macrorules are partially ordered according to an abstraction
relation for plans, from which the system can efficiently retrieve the
most specific plan applicable for solving a new problem. The use of
abstraction in a knowledge-based application of Argo allows the system
to solve problems that are not necessarily identical, but just analogous
to those it has solved previously. Experiments with an application for
designing VLSI digital circuits are yielding insights into how design
tools can improve their capabilities and extend their domains of
applicability as they are used.
------------------------------
Date: 31 Mar 87 10:36:22 EST
From: KAPLAN@RED.RUTGERS.EDU
Subject: Seminar - Decomposition for Hierarchical Problem Solving
(Rutgers)
PhD Oral Qualifying Examination for Mr. S. Mahadevan
Mr. Mahadevan's examination is scheduled for Wednesday, April 1 at 10:30 AM
in Hill 423. The examination committee is chaired by T. Mitchell, and includes
T. McCarty, J. Mostow, and L. Steinberg. DCS faculty are welcome to attend;
graduate students are invited to the public portion of the examination. Mr.
Mahadevan's dissertation proposal is abstracted below:
LEARNING DECOMPOSITION METHODS TO IMPROVE HIERARCHICAL
PROBLEM-SOLVING PERFORMANCE
Previous work in machine learning on improving problem-solving
performance has usually assumed a state-space or "flat"
problem-solving model. However, problem-solvers in complex domains,
such as design, usually employ a hierarchical or problem-reduction
strategy to avoid the combinatorial explosion of possible operator
sequences. Consequently, in order to apply machine learning to
complex domains, hierarchical problem-solvers that automatically
improve their performance need to designed. One general approach is
to design an interactive problem-solver -- a learning
apprentice -- that learns from the problem-solving activity of expert
users. In this talk we propose a technique, VBL, by which such a
system can learn new problem-reduction operators, or decomposition
methods, based on a verification of the correctness of example
decompositions. We also discuss two important limitations of the VBL
technique -- intractability of verification and specificity of
generalization -- and propose solutions to them. Finally, we present
a formalization of the problem of learning decomposition methods based
on viewing actions and problems as binary relations on states.
------------------------------
Date: Thu, 26 Mar 1987 19:05 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Conferences - Simulation & Protocol Specification
The Society for Computer Simulation Eastern Simulation Conferences
April 6-9, 1987, Orlando, Florida
AI and Simulation at Johnson Space Center, Robert Salvely (verbal presentation)
Flight Simulator Evaluation of Aircraft Systems Using AI Technology (verbal ..
Edward M. Huff, NASA Ames Research Center
An Expert System fo rManaging Multiple Cooperating Expert Systems (verbal ...
A. Gerstenfeld, Geoffrey Gosling, David S. Touretzky Worcester Polytechnic
The Simulation of Simple Analog and Discrete Circuits from a Knowledge Base
Representaiton of Structure and Function
NASA, Kennedy Space Center
Acknowledge2: A Knowledge Acquisition System
Pradip Dey, Kevin D. REilly, J. Todd Brown, University of Alabama at Birmingham
Knowledge Corpora Connectivities - Toward the Construction of a Thought
Simulator Testbed
Alhad M. Chande, Marti.n Marietta Baltimore Aerospace, Joe Clema, IIT
Research Institute
Qualitative Expert Systems: A Demographic Simulator with Heuristic Reasoning
Walt Conley, W. Lawrence, U. Sengupta, R. Hartley, M. Coombs, New Mexico
State University
Model Management in Knowledge Based Simulation
Hawa Singh, Alan Butcher, R. Reddy, West Virginia University
Constraint Directed Reasoning for Simulation Problem Formulation
Neena Sathi, Gary STrohm, Thomas Morton, Sean Winters, Carnegie Group Inc.
Knowledge-Based Resource Behavior
Allen Matsumoto, V. Baskaran, Beth Marvel, Carnegie Group
Sonar Plexus - Enhancing a Command and Control Simulation with Reasoning
Marc R. Halley, Thomas MIller, Craig Hougum, William Mosenthal
Analytic Sciences Corporation
Computer System Simulation in Scheme
Daniel B. Pliske The Analytical Sciences Corporation
Real Time Intelligent System Analysis by Dsicrete Event Simulation
J. M. Poole, T. M. McDermott, D. P. Glasson,
The Analytica Sciences Corporation
The Mobile Intercontinental Ballistic MIssible Simulation
Douglas Roberts, J. Darrell Morgeson, Jared S. Dreicer, Howard W. Egdorf
Los Alamos National Laboratory
SIMSMART: Dynamic Simulation fo rAutomated Control of Complex Industrial
Processes
Don Waye Applied High Technology Limited
Applicability of AI Techniques to Simulation Models
Norman R. Nielsen, SRI International, Victoria P. Gilbert, Intellicorp
Improving Effectivenes of Computer Simulation SModeling with Knowledge-
Based Problem-Solving Capability
Ronak Shodhan, J. J. Talavage, Purdue University
Expert Systems within Simulations
JohnPaul SanGiovanni, Jockey Holley Technologies
A Communication Network Model of the Brain
Ray Moses, Boeing Aerospace Company
An ARtificial Intelligence (AI) Simulation Based Approach for Aircraft
Maintenance Training
Lee Keskey, Dave Sykes, Honey Well Inc.
Knowledge Representation in Ada
Sumitra M. REddy, Francis L. VAn Scoy, West Virginia University
A Simulator of an Automatic Text Reading System
Nikolaos G. Bourbakis, George Mason University, Scott Schneider, IDA
Two-dimensional Image Scanning for Hierarchical Data Structures and Its
Simulation
Nikolaos G. Bourbakis, George Mason University
Cognitive Learning Theory: A Tool for Modelling and Simulation
Donald A. MacCuish, ICSD Corporation
A Computer Simulation Program of Animal Maze Learning
Roger Ingliss, Warren Marchioni, Montclair High School
+++++++++++++++++++++++++++++++++++++++++++++++++++++++
Protocol Specification, Testing and Verification: VII
May 5- 8, 1987, IFIP Protocol Symposium Interconventional Ltd.
c/o SWISSAIR CH-8058 Zurich-Airport, Switzerland
Communicati.ng Rule Systems
L. F. Mackert & I. Neumeier-Mackert
IBM European Network Center, Heidelberg
An Atomic Calculus of Communicati.ng Systems
L. Logrippo and A. Obaid
University of Ottawa
Fundamental Results for the Verification of Observational Equivalence:
A Survey
T. bolognesi, CNUCE, Pisa, S. A. Smolka, SUNY, STony Brook
Proof of Specification Properties by Using Finite State Machines and
Temporal Logic
A. R. Cavalli, F. Horn, CNET, Issy, Les Moulineaux
Translation of Formal Protocol Specifications to VLSI Designs
A. S. Krishankumar, B. Krishnamurthy, K. Sabnani
AT&T Bell Labs, Murray Hill
------------------------------
End of AIList Digest
********************
-------
∂07-Apr-87 1854 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #94
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 7 Apr 87 18:54:12 PDT
Date: Wed 1 Apr 1987 22:21-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #94
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 2 Apr 1987 Volume 5 : Issue 94
Today's Topics:
Queries - Intelligent Database Retrieval & Reliable AI Systems,
Humor - 7th Generation Computing Proposal: Basketball and AI,
Jargon - Daemons,
Comments - Military Sponsorship & Teaching Expert Systems &
Policy on Broadcasting Code,
Inference - What is the Color of Clyde?
----------------------------------------------------------------------
Date: Tue 31 Mar 87 09:51:26-PST
From: Kevin W. Whiting <Whiting@SRI-STRIPE.ARPA>
Subject: Wanted:Info. on Tools which intelligently facilitate db retrieval
All information about tools (PC based tools particularly), shells, products,
and/or projects aimed at adding intelligence to database retrieval would be
appreciated. Information on experiences with products such as Guru, Clout,
Savvy, Q & A, or software resulting from project work such as ZOG, GUIDON,
etc., is desired as well. I had thought there was a summary more or less on
this topic posted to the net last fall but can't find it now. If you can point
me to it or other summaries - it would be mucho appreciated.
Kevin Whiting
whiting@stripe.sri.com
------------------------------
Date: 29 Mar 87 17:18:32 EST (Sun)
From: dciem!mmt@seismo.CSS.GOV
Reply-to: mmt@dciem.UUCP (Martin Taylor)
Subject: Re: Oxymoron: Real-time Knowledge-Based Nurse/Nuclear Plant
Operator
>
>I strongly agree. Any safety-critical system should have certain
>characteristics: it should be rigorously specified (AT LEAST the safety
>aspects); it should be possible to reason rigorously about the
>implementation, to convince others that it matches the specification;
>it should be developed using QC/QA techniques that guarantee an audit trail
>so that any faults discovered after development can be traced to their
>cause.
>
>These considerations dictate the use of mathematically rigorous methods, and
>a certified Quality Assurance regime. Does anyone know of an AI system
>which measures up? Please reply by mail - I'll summarise.
>
Does anyone know of a human-controlled safety-critical system that measures
up to these criteria? Presumably not, but people don't expect them to do
so. To examine the reasons why not might be to get at the heart of what
"Artificial Intelligence" is and is not, in relation to human intelligence.
------------------------------
Date: Tue, 31 Mar 87 13:16:03 cst
From: lugowski%resbld%ti-csl.csnet@RELAY.CS.NET
Subject: 7th generation computing proposal: basketball and AI
In the wake of Indiana's capture of NCAA 1987 men's basketball championship
and in the wake of AIList discussions on militarism in AI and real-time
safety-critical AI, I propose that the emulation of basketball games would
be a good domain for developing all sorts of useful technology, starting with
multi-agent planning and ending in real-time control. For starters, one
could consider a bird's eye view of the basketball court with moving
circles representing the players and the ball. The robotics people could
work on the missed dunk. The vision people could work on recognizing
timeout signals. The naive physics crowd could model missed free throws.
And the speech-to-text and image-to-speech ("this game's so good it speaks
for itself") could zero-in on play-by-play. Analogies and metaphor folks
could distinguish zone defenses from man-to-man, as well as the eigen-cliches
of various color commentators. Reasoning under uncertainty could model the
referees' calls. And the AI-in-law effort could model Coach Knight's use of
the technical faul -- and the connectionist models of sentences -- of his
faul language.
This endeavor would be plenty difficult. It would offer abundant military
applications as well as civilian ones. Moreover, it would provide the AI
research community with a common performance yardstick while allowing
everyone to do their own thing, from neural networks to expert systems. It
would advance science and technology, not to mention the physical fitness
of AI experimentalists. It might even do something for Indiana's AI effort
and boost CMU's basketball standing. And we could anticipate hearing
Marvin Minsky or David Rumelhart from the TV booths of the NCAAs tournaments
to come -- "The Society of Swoosh", "Backpropagation of Missed Free Throws".
There's just one more thing...
Um, funding anyone?
-- Marek Lugowski (Indiana M.S. '84)
Neural Networks Project
Texas Instruments
Lugowski%CRL1@ti-csl.csnet P.O. Box 655936, M/S 154
(214) 995-4207 Dallas, Texas 75265
"basketball people and AI folks, unite!"
[Too late -- it's being done. The following seminar at SRI described
a system that tracks soccer players in down-looking imagery and reasons
about their actions and intentions. It then generates a play-by-play
commentary, being careful not to state anything that the listener could
infer from previous statements. -- KIL]
Prof. Wolfgang Wahlster of the Univeristy of Saarbruecken will
give a talk and demonstration of his systems on Friday February 20th
at 10 AM.
GENERATING NAUTRAL LANGUAGE DESCRIPTIONS FOR IMAGE SEQUENCES
Wolfgang Wahlster
Computer Science Department
Univerity of Saarbruecken
West Germany
The aim of the project VITRA (VIsual TRAnslator) is the
development of a computational theory of the relation between natural
language and vision. In this talk, we will focus on the semantics of
path prepositions (like "along" or "past") and their use for the
description of trajectories of moving objects, the intrinsic and deictic
use of spatial prepositions and the use of linguistic hedges to express
various degrees of applicability of spatial relations.
First, we describe the implementation of the system CITYTOUR,
a German question-answering system that simulates aspects of a
fictitious sightseeing tour through a city. Then we show how the
system was interfaced to an image sequence analysis system. From
the top of a 35m high building, a stationary TV camera recorded an
image sequence of a street crossing on video tape. In 130 selected
frames the moving objects were automatically recognized by analyzing
displacement vector fields. Our system then answers natural language
queries about the recognized events.
Finally, we discuss current extensions to the system for the
generation of a report on a soccer game that the system is watching.
Here we focus on the problem of incremental, real-time text generation
and the use of a re-representation component that models the assumed
imagination of the listener.
------------------------------
Date: Tue, 31 Mar 1987 09:58 EST
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #92
The term "demon" comes from Oliver Selfridge, via the paper,
"Pandemonium: A Paradigm for Learning", published in Symposium of the
mechanization of Thought Processes, November 1858. Selfridge's demons
were small feature-detecting agents, whose inputs were linearly
weighted sums of other signals, with autonomous hill-climbing learning
procedures for determining the weights. Selfridge's demons were
arranged in hierarchical networks; typical demons were constantly
active - and "shrieking" with intensities proportional to their
degrees of arousal; the nonlinear part was that certain "decision
demons" would "recognize" which of their inputs was most active.
------------------------------
Date: Tue 31 Mar 87 15:10:11-PST
From: Rich Alderson <ALDERSON@Score.Stanford.EDU>
Subject: Daemons (and others...)
The following definitions are from a file often distributed with Tops-20 EMACS,
known there as INFO:JARGON.TXT; its origins are the files GLS; JARGON > at
MIT-MC and AIWORD.RF[UP,DOC] at SAIL. This text is from the 1981 version;
later, expanded versions eventually were published as _The Hacker's Dictionary_
around 1984.
DAEMON (day'mun, dee'mun) [archaic form of "demon", which has slightly differ-
ent connotations (q.v.)] n. A program which is not invoked explicitly, but
which lays dormant waiting for some condition(s) to occur. The idea is that
the perpetrator of the condition need not be aware that a daemon is lurking
(though often a program will commit an action only because it knows that it
will implicitly invoke a daemon). For example, writing a file on the lpt
spooler's directory will invoke the spooling daemon, which prints the file.
The advantage is that programs which want (in this example) files printed need
not compete for access to the lpt. They simply enter their implicit requests
and let the daemon decide what to do with them. Daemons are usually spawned
automatically by the system, and may either live forever or be regenerated at
intervals. Usage: DAEMON and DEMON (q.v.) are often used interchangeably,
but seem to have distinct connotations. DAEMON was introduced to computing by
CTSS people (who pronounced it dee'mon) and used it to refer to what is now
called a DRAGON or PHANTOM (q.v.). The meaning and pronunciation have
drifted, and we think this glossary reflects current usage.
DEMON (dee'mun) n. A portion of a program which is not invoked explicitly, but
which lays dormant waiting for some condition(s) to occur. See DAEMON. The
distinction is that demons are usually processes within a program, while
daemons are usually programs running on an operating system. Demons are
particularly common in AI programs. For example, a knowledge manipulation
program might implement inference rules as demons. Whenever a new piece of
knowledge was added, various demons would activate (which demons depends on
the particular piece of data) and would create additional pieces of knowledge
by applying their respective inference rules to the original piece. These new
pieces could in turn activate more demons as the inferences filtered down
through chains of logic. Meanwhile the main program could continue with
whatever its primary task was.
DRAGON n. (MIT) A program similar to a "daemon" (q.v.), except that it is not
invoked at all, but is instead used by the system to perform various secondary
tasks. A typical example would be an accounting program, which keeps track of
who is logged in, accumulates load-average statistics, etc. At MIT, all free
TV's display a list of people logged in, where they are, what they're running,
etc. along with some random picture (such as a unicorn, Snoopy, or the
Enterprise) which is generated by the "NAME DRAGON". See PHANTOM.
PHANTOM n. (Stanford) The SAIL equivalent of a DRAGON (q.v.). Typical
phantoms include the accounting program, the news-wire monitor, and the lpt
and xgp spoolers.
SERVER n. A kind of DAEMON which performs a service for the requester, which
often runs on a computer other than the one on which the server runs.
Rich Alderson
A.Alderson@{Lear, Othello, Hamlet, Macbeth}.Stanford.EDU
------------------------------
Date: 31 Mar 1987 15:25-EST
From: DAVSMITH@A.ISI.EDU
Subject: Re: AIList Digest V5 #92
My two cents on the Military AI issue. I totally agree with
KIL's "voice of Reason" - the only reason for the existence
of Arpanet is military sponsorship. I am currently working
on the Pilot's Associate project - and am therefore biased in
my view. Military applications such as this are excellent for
"blowing the fluff away" and finding out which AI technologies
are ready for real applications where need has been demonstrated.
Perhaps a little later, we can digress on some of those findings.
Without the military applications, who in the commercial sector
would attempt to put together cooperating expert systems
in real-time? [ One could broaden the issue and ask
"Who in their right mind would..?"]
The sad fact is that a technology in the university lab can look
very good on viewgraphs, but you would be surprised at the
back-pedalling which occurs when you offer the opportunity to
plug into a real application.
David Smith DAVSMITH@a.isi.edu
------------------------------
Date: Wed, 1 Apr 87 11:03:56 PST
From: Ritchey Ruff <ruffwork%oregon-state.csnet@RELAY.CS.NET>
Subject: Teaching Expert Systems
>
> First, the dissemination of Tiny MYCIN sounds interesting.
> I wish I had a convenient Common LISP machine to try it out.
> I realize that TMYCIN is just a tool, but I wonder how good a tool
> it really is. What is the value of learning about this tool
> (to learn about ESs) when you don't have an expert around (rhetorical
> question, obviously some value)? I ask this because I have a relative
> who does research in pathology and got his PhD in bacteriology
> at BYU (any connection with Dugway Proving Ground is not coincidence).
>
> --eugene miya
> NASA Ames Research Center
> eugene@ames-aurora.ARPA
Well, 3 months ago I would have said that an expert system tool in vivo
is not much use, but now...I was a TA (teaching assistant) for an
expert systems course here at Oregon State last term taught by Tom
Dietterich. It was his first time around teaching this subject and
so he decided to go at it from a case study/theory viewpoint (if the
theory of expert systems isn't oxymorphic :-). Thus there was really
nothing said about how to implement systems. The term project though WAS
to implement a small expert system (4 or 5 weeks to do this, and we
DON'T have any expert systems tools - just LISP, PROLOG, and OPS5).
The projects were very impressive overall, but the style/organization/etc.
were generally dismall. Not in a traditional sense but more from
an expert systems sense. The code was documented, modular, etc. but
not in a way that made it easy to analyze as an expert system. It was
often hard to understand WHAT knowledge the system had from code reading.
What is needed is both sides of the coin - the theory/case study, and
a how-to-implement course. Having the proper tools is bound to help
here, but several project in the above languages WERE readable as
knowledge bases (style makes a difference).
IF the TMYCIN tool comes with some GOOD examples (no matter how
toy-ish) I think that a person could learn quite a bit about the
how-to-code end of expert systems - which is just as important
(in its own way) as the theory.
--ritchey ruff (reformed couch potato)
ruffwork%oregon-state@csnet-relay
(soon to be ruffwork@cs.orst.edu)
from the Home for the Artificially Intelligent
------------------------------
Date: 31 Mar 87 09:38 PST
From: ghenis.pasa@Xerox.COM
Subject: Special Postings and Digest Title
Regarding the issue of whether source code, bibliographies, etc should
be included in AIList... I realize this would create more work for
Moderator Ken Laws, but what if these special postings always went out
grouped in SEPARATE ISSUES and the "Subject:" line were made MORE
DESCRIPTIVE so readers could skip selectively?
Thus instead of getting
AIList Digest V5 #92
we could get messages titled:
AIList V5 #92 - Source
AIList V5 #92 - Bibliography
AIList V5 #92 - General
or something along those lines (you get the idea)
I would like to see source postings back in AIList, maybe the above
system can satisfy those who would rather skip them. Any comments?
Pablo Ghenis
Xerox Artificial Intelligence Systems
Educational Services
[I could add such a heading, but one result would be longer
delays for some material until enough arrived for a full
digest. Anyway, I'm not sure I see the savings. My mailer,
which is probably the used throughout the Arpanet, doesn't
display enough of the title for the keywords to be visible.
If I read enough of the message to get the full title, I only
have to scroll a few more lines to get the Topics listing.
A better solution is to have independent mailing lists for
different types of material. Even the Stanford bboard is
partitioned now, so why not AIList? The only difficulty
is that I don't want to maintain multiple mailing lists.
It wouldn't be so bad if I had a good database system for
converting request messages into additions and deletions,
but I have to do it by hand and I'm not eager to double or
triple the time this takes.
I've heard of a database server for code distributions that
might be open to the Arpanet; I will investigate. I am
beginning to think, though, that FTP and mail requests are
not such a bad thing. Gordon Novak tells me he has had over
thirty requests for his code, in addition to any FTPs (which
he wouldn't know about). Handling thirty requests is a bit
of a hassle, but also a bit of a thrill. It generates
professional contacts and keeps people in touch. Why, I
can imagine someone disallowing FTP altogether just to keep
track of who is getting the code. To go even further, a
separate interest list could be established. And if a code
author didn't want the hassle at all, s/he could use AIList to
find someone else willing to handle the distribution in
return for access to the code. Isn't this better than having
an impersonal central server stuffed with obsolete, unmaintained
code? Or a broadcast system like AIList? The only real
disadvantage is that code may become inaccesible if the author
leaves his current site, but copies should be available from
somewhere (perhaps via AIList query). -- KIL]
------------------------------
Date: 1 Apr 87 13:40:18 GMT
From: Dekang Lindek <mcvax!cs.strath.ac.uk!lindek@seismo.CSS.GOV>
Reply-to: lindek@cs.strath.ac.uk (Dekang Lin)
Subject: Re: What is the color of Clyde?
In article <8703021016.AA22995@stracs.cs.strath.ac.uk>
lindek@seismo.CSS.GOV@cs.strath.ac.uk (Dekang Lindek) writes:
>Look, WORLD, here is a little default reasoning exercise:
>
>95% of elephants have color grey.
>40% of Royal Elephants have color yellow.
>Clyde is a Royal Elephant.
>
>The color of Clyde is likely to be:
> a) Grey b) Yellow c) Red d) Unknown
>
There are several bugs here:
1) 'most likely' should be used in place of 'likely' to make the
question clear.
2) 'Unknown' should not be one of the choices because neither
'likely to be unknown' nor 'most likely to be unknown' makes
any sense. It is a fact that the color of Clyde is unknown,
otherwise we won't need to guess it.
3) 'elephants have color grey' sounds like Next-Generation-Database
English.
4) 'Lindek' is his E-name, not surname.
5) (This place is reserved for future use)
After fixing the first four bugs, we could make the following
inference:
#define confidence probability
proposition confidence
(1) A Royal Elephant is yellow. .40
(2) A Royal Elephant is not yellow .60
(3) (An elephant is not yellow) ==>
(The elephant is grey) .95~1.0
(4) (A Royal elephant is not yellow) ==>
(A Royal elephant is grey) .95~1.0
(5) A Royal Elephant is grey .57~.60
(6) Clyde is a Royal Elephant. 1.0
Conclusion(subject to change without notice):
Clyde is most likely to be GREY.[]
Discussion:
The decision becomes harder to make when the confidence of (1)
is inside the interval of (5).
Comments:
This problem seems too technical to be discussed on the net.
An opinion poll in Glasgow will definitely show that the
color of Clyde is green even though it is blue on the maps.
Dekang Lin
Dept. of CS
Univ. of StrathClyde
26 Richmond Street
Glasgow G1 1XH, U.K.
lindek%uk.ac.strath.cs@ucl-cs.arpa
....!seismo!mcvax!ukc!strath-cs!lindek
------------------------------
End of AIList Digest
********************
-------
∂07-Apr-87 2239 LAWS@SRI-STRIPE.ARPA AIList Digest V5 #95
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 7 Apr 87 22:39:38 PDT
Date: Wed 1 Apr 1987 22:38-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-STRIPE.ARPA>
Reply-to: AIList@SRI-STRIPE.ARPA
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #95
To: AIList@SRI-STRIPE.ARPA
AIList Digest Thursday, 2 Apr 1987 Volume 5 : Issue 95
Today's Topics:
Application - Text Critiquing
----------------------------------------------------------------------
Date: Wed 1 Apr 87 22:35:15-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Reply-to: AIList-Request@SRI-STRIPE.ARPA
Subject: Policy - Text Critiquing
The following messages are about a system that critiques English
prose. It could be argued whether this particular system is
within the realm of AI, but the application area does seem to
be of interest. This discussion really should be moved to
the AI-ED@SUMEX-AIM list (which has just distributed the text
grading query that started all this), or perhaps to the
NL-KR list. For now, I will continue to distribute to the
Arpanet discussions on this topic that have circulated on Usenet.
-- Ken
------------------------------
Date: 27 Mar 87 19:07:40 GMT
From: ritcv!rocksvax!rocksanne!sunybcs!colonel@CS.ROCHESTER.EDU
(Col. G. L. Sicherman)
Subject: Re: automatic checking
) But there is no reason to grade automatically, just let the students
) ↑<<* 23. SENTENCE BEGINS WITH BUT *>>
) work on their papers (with the automatic checker) until they are satisfied.
) <<* 21. PASSIVE VOICE: are satisfied. *>>↑
) <<* 17. LONG SENTENCE: 24 WORDS *>>↑
"They are satisfied" is in the passive voice? That's what comes of letting
computers run things....
"Hey, Rocky! Watch me pull a UNIX program outa m'
source directory!"
"AGAIN?"
"Nothin' up my sleeve ... PRESTO!"
IDENTIFICATION DIVISION.
PROGRAM-ID. PROCESS-DATA.
AUTHOR-NAME. B. J. MOOSE, FROSTBYTE DATA SYS.
SOURCE-COMPUTER. IBM-7044.
OBJECT-COMPUTER. IBM-7044.
. . .
"No doubt about it--I gotta get a new source directory!"
--
Col. G. L. Sicherman
UU: ...{rocksvax|decvax}!sunybcs!colonel
CS: colonel@buffalo-cs
BI: colonel@sunybcs, csdsiche@ubvms
------------------------------
Date: 30 Mar 87 00:24:00 GMT
From: kadie@b.cs.uiuc.edu
Subject: Re: AI Project Information Request
Several people have ask if the grammar checker I used was real. It
is. It is a commercial product for the IBM PC. Here is some more
information and an example.
I own a spelling checker that I always use. And a grammar and style checker
that I sometimes use. I have a lot of confidence in the spelling checker; I
take virtually all of its advice. The style checker is not as good. I always
consider it's suggestions, but I know that it has missed many grammar
and style errors and that not everything it flags is really wrong.
Enclosed find its critique of a draft report.
This gives a pretty good indication of how well the program works.
The program is RIGHTWRITER version 2.0, a Right Soft product by
Decisionware, Inc.
of 2033 Wood Street, Suite 218, Sarasota, Florida 33577. It runs on
IBM PC's and compatible computers. It costs about $100.00.
Carl Kadie
University of Illinois at Urbana-Champaign
UUCP: {ihnp4,pur-ee,convex}!uiucdcs!kadie
CSNET: kadie@UIUC.CSNET
ARPA: kadie@M.CS.UIUC.EDU (kadie@UIUC.ARPA)
(I disclaim any ulterior relationship to Decisionware.)
.+c "A Program To Compute Moore's Stable Expansions"
.pp
Moore has recently proposed a possible-world semantics for autoepistemic logic.
His method has the intriguing property of producing multiple expansions, that
<<* 16. UNNECESSARY COMMA *>>↑
is it list the (finite) theories of what you believe about the world, given
the axioms.
↑<<* 17. LONG SENTENCE: 27 WORDS *>>
For example, if your unbelief in proposition $P$ implies $Q$, and your unbelief
in proposition $Q$ implies $P$, then we can theorize that either
$P$ is true or alternatively $Q$ true.
<<* 17. LONG SENTENCE: 31 WORDS *>>↑
<<* 31. COMPLEX SENTENCE *>>↑
.pp
In Lisp notation the axioms are expressed:
.(L
(and (imp (not (l 'p)) q) (imp (not (l 'q)) p))
.)L
and the conclusion is expressed:
.(L
(Q) (P)
.)L
.pp
I have written a program that finds the stable expansions of
formula in Moore's autoepistemic logic. As might be expected
<<* 21. PASSIVE VOICE: be expected *>>↑
the program run in time exponential to the number of variables.
<<* 32. INCOMPLETE SENTENCE OR MISSING COMMA *>>↑
Let's look at some runs:
.(L
A non-autoepistemic sentence:
(expand
'(and p (imp p (not q)) (imp (not q) r)) ;; axioms
'(p q r) ;; propositions
0) ;; trace level
returns:
((P (NOT Q) R))
.)L
In other words, the axioms entail that $P$ is true, $Q$ is false, and $R$ is
true. This is of course just what we expect for this propositional sentence.
.pp
Here is a trace of the run of the example we saw before:
.(L
[Figure goes here. -- CMK]
.)L
.pp
The program also identifies cases where no stable expansion exists:
.(L
[Figure goes here. -- CMK]
.)L
.pp
At higher trace levels, the program provides counter-models
to non-grounded theories. For example:
.(L
(expand
'(and (imp (not (l 'p1)) p2)
(imp (not (l 'p2)) p3)
(imp (not (l 'p3)) p4)
(imp (not (l 'p4)) p1))
'(p1 p2 p3 p4)
2)
...
(P1 P2 P3 P4) in theory is stable w.r.t. the axioms.
S5 is ((P1 P2 P3 P4))
(s5:((P1 P2 P3 P4)) , V:((NOT P1) P2 (NOT P3) P4)) is a model of A
Counter-model: (s5:((P1 P2 P3 P4)), V:((NOT P1) P2 (NOT P3) P4))
Theory (P1 P2 P3 P4) is NOT a stable expansion of the axioms
...
((P2 P4) (P1 P3))
.)L
.pp
In fact it is just this test of groundness that makes Moore's logic
different from the logic of Shoham that we will see later.
<<* 17. LONG SENTENCE: 24 WORDS *>>↑
For example when we give Shoham's gun
example to the program it replies that there are no stable
<<* 1. REPLACE: that there BY there *>>↑
expansions. This is because it does not have Shoham's
chronological ignorance criteria with which to choose ungrounded
theories. Here is the trace:
.(L
[Figure goes here. -- CMK]
.)L
.pp
Having no stable expansion and believing nothing are two separate case.
Here is a case where the only stable expansion is the theory
where nothing is believed.
↑<<* 21. PASSIVE VOICE: is believed. *>>
.(L
[Figure goes here. -- CMK]
.)L
.pp
The program works by enumerating every theory, then constructing
the corresponding S5 structure. Next, it tests every world
of the S5, if any world fails to support the axioms then
it is unstable and the theory is removed from consideration.
<<* 21. PASSIVE VOICE: is removed *>>↑
<<* 17. LONG SENTENCE: 27 WORDS *>>↑
Stable theories are next tested for groundness. This is done
<<* 21. PASSIVE VOICE: are next tested *>>
<<* 21. PASSIVE VOICE: is done *>>↑
by trying every variable assignment $V$. If an assignment
makes the axioms true then $V$ must correspond to a world
in the S5, or else the theory is not grounded. A theory
<<* 21. PASSIVE VOICE: is not grounded. *>>↑
<<* 17. LONG SENTENCE: 33 WORDS *>>↑
that is both stable and grounded is added to the stable
<<* 21. PASSIVE VOICE: is added *>>↑
expansion list to be returned at the end of the program.
<<* 21. PASSIVE VOICE: be returned *>>
<<* 17. LONG SENTENCE: 24 WORDS *>>↑
.pp
Overall, the program works very well on small problems (four
variable problems take only seconds on a SUN). The program
accepts any formula that Lisp can evaluate;
so very complex formula may be input. However, since
the program relies on enumeration, it can not be expanded
<<* 21. PASSIVE VOICE: be expanded *>>↑
to first-order logic, nor can it be considered practical
<<* 21. PASSIVE VOICE: be considered *>>↑
unless the problems can be guaranteed to be small.
<<* 21. PASSIVE VOICE: be guaranteed *>>
<<* 17. LONG SENTENCE: 31 WORDS *>>↑
<<* 31. COMPLEX SENTENCE *>>↑
<<** SUMMARY **>>
READABILITY INDEX: 7.63
Readers need an 8th grade level of education to understand.
STRENGTH INDEX: 0.19
The writing can be made more direct by using:
- the active voice
- shorter sentences
- more common words
- fewer abbreviations
DESCRIPTIVE INDEX: 0.74
The use of adjectives and adverbs is within the normal range.
JARGON INDEX: 0.25
SENTENCE STRUCTURE RECOMMENDATIONS:
15. No Recommendations.
<< UNCOMMON WORD LIST >>
The following words are not widely understood.
Will any of these words confuse the intended audience?
AUTOEPISTEMIC 3 AXIOM 2 AXIOMS 40
CHRONOLOGICAL 1 CRITERIA 1 DRIBBLE 1
ENTAIL 1 ENUMERATING 1 ENUMERATION 1
EXPONENTIAL 1 FINITE 1 FIRE4 20
GROUNDNESS 2 IMP 24 INTRIGUING 1
LISP 2 LOAD1 20 MOORE 1
MOORE'S 3 NIL 5 NOISE6 17
P 4 PROPOSITION 2 PROPOSITIONAL 1
PROPOSITIONS 2 Q 4 R 1
SEMANTICS 1 SHOHAM 1 SHOHAM'S 2
THEORIZE 1 UNBELIEF 2 UNGROUNDED 1
V 2 VACUUM5 17 WRT 19
<< END OF UNCOMMON WORD LIST >>
<<** WORD FREQUENCY LIST **>>
A 31 ABOUT 1 ACCEPTS 1
ADD 1 ALSO 1 ALTERNATIVELY 1
AN 1 AND 18 ANY 2
ARE 4 AS 1 ASSIGNMENT 3
AT 3 AUTOEPISTEMIC 3 AXIOM 2
AXIOMS 40 BE 7 BECAUSE 1
BEFORE 1 BELIEVE 3 BOTH 1
[Rest of word frequency list goes here -- CMK]
<<END OF WORD FREQUENCY LIST>>
------------------------------
Date: Mon, 30 Mar 87 11:31 EST
From: "Linda G. Means" <MEANS%gmr.com@RELAY.CS.NET>
Subject: Re: AI Project Information Request
means%gmr.com@relay.cs.net >Date: 25 Mar 87 01:44:00 GMT
>From: kadie@b.cs.uiuc.edu
>Subject: Re: AI Project Information Request
>
>
>Automatic checking and automatic grading are different things. I think
> <<* 3. WEAK: I think *>>↑
>automatic computer checking is a good thing, especially for spelling
>and simpler grammar.
>
>But there is no reason to grade automatically, just let the students
> ↑<<* 23. SENTENCE BEGINS WITH BUT *>>
>work on their papers (with the automatic checker) until they are satisfied.
> <<* 21. PASSIVE VOICE: are satisfied. *>>↑
> <<* 17. LONG SENTENCE: 24 WORDS *>>↑
>Then have them turn in their work and the final computer critique to a human
>grader.
>
>The situation is similar to programming, where the compiler
>automatically checks the syntax. It would be unthinkable to make people turn
>in programs without letting them compile the programs first. On
>the other hand it would unthinkable to leave a syntax error in
>when the compiler tells you right were it is.
>
>
> <<** SUMMARY **>>
>
> READABILITY INDEX: 10.42
> Readers need a 10th grade level of education to understand.
>
> STRENGTH INDEX: 0.41
> The writing can be made more direct by using:
> - the active voice
> - shorter sentences
>
> DESCRIPTIVE INDEX: 0.65
> The use of adjectives and adverbs is within the normal range.
>
> JARGON INDEX: 0.00
>
> SENTENCE STRUCTURE RECOMMENDATIONS:
> 1. Most sentences contain multiple clauses.
> Try to use more simple sentences.
>
> << UNCOMMON WORD LIST >>
>The following words are not widely understood.
>Will any of these words confuse the intended audience?
> CRITIQUE 1 SYNTAX 2 UNTHINKABLE 2
> << END OF UNCOMMON WORD LIST >>
>
>
>Carl Kadie
>University of Illinois at Urbana-Champaign
>UUCP: {ihnp4,pur-ee,convex}!uiucdcs!kadie
>CSNET: kadie@UIUC.CSNET
>ARPA: kadie@M.CS.UIUC.EDU (kadie@UIUC.ARPA)
Carl,
Your submission regarding grammar/style checkers sends a mixed
message to me. The content appears to advocate the use of such
systems as tutoring tools. The automatic critique interspersed
throughout the text, however, seems to belie your intention.
First of all, it failed to point out three blatant errors in the text:
> But there is no reason to grade automatically, just let the students work
on their papers (with the automatic checker) until they are satisfied.
- a comma is an inappropriate conjuntion for the two independent clauses
here; a semi-colon would be more appropriate.
> On the other hand it would unthinkable to leave a syntax error in when
the compiler tells you right were it is.
- 'where' is misspelled as "were".
- 'be' was omitted before 'unthinkable'.
Second, I have a number of objections to the types of criticisms the
program does make. You characterize automatic style checking as
"... a good thing, especially for spelling and simpler grammar".
I would call it simple-minded, not simple. The complaint about
the use of passive voice in "until they are satisfied" is ridiculous.
This is not an example of passive voice at all; it's a predicate
adjective. And even if passive voice had been used there, so what?
The strength index in the summary gives the text a low grade on the
basis of two supposed weaknesses: one occurrance of passive voice,
and one sentence which is overly long (24 words). This evaluation
is quite misleading to a student, who will subsequently comb his
papers for constructions like "they are satisfied" to be purged, and
will frantically count words in sentences. No machine or human
critic should object to the use of "they are satisfied" in this
context (or probably any other). And if you want to evaluate
sentence length as an index of readability, number of words is
too superficial an index to use. The readability of a sentence
is better judged by the embedding of clauses, or syntactic complexity.
I think it would be dangerous to have students become obsessed with
counting words in sentences while ignoring sentence structure, just
because the teacher requires them to use an inadequate computer program
as a teaching aid.
I could go on and on. And I think I will, because I get so angered
by the commercial crap which is passed off to gullible teachers and
parents as computer-aided instruction! I don't want my child to
learn how to write with a program that scolds him every time he
begins a sentence with the word 'but', and tells him that he should
"try to use more simple sentences" because "most [of his] sentences
contain multiple clauses". There's nothing wrong with multiple clauses,
even in most of your sentences. Try writing most sentences with
single clauses. The technique will not enhance your writing style,
I assure you. Granted, you don't want to embed clauses in your
sentences to the depths of Hell. But the difficulty in comprehending
sentences with a lot of embedding stems from the syntactic structure,
and not simply the number of clauses. (Nyaaa nyaaa, I just started a
sentence with 'but'. Did it make your skin crawl as you read it? No,
of course not. Some sentences just cry out to begin with 'but', although
not ALL your sentences should.) Which sentence do you find more
readable: the sentence criticized for its length in your text (number 1
below), or my utterly grammatical and very short sentence number 2?
1. But there is no reason to grade automatically, just let the
students work on their papers (with the automatic checker) until
they are satisfied.
2. The man the girl the boy loved kissed died.
I don't want my child's creativity and personality in his writing to
be stifled by a computer program which performs such rigid and
superficial analysis. Nor do I want his writing to be limited to
an average 10th grade level when he's in 10th grade if his writing
ability goes beyond the level of the average 10th grader. Thanks
for including your style checker's criticisms in your message. It
serves as evidence that those programs may do more harm than good
to a child's developing literary talents.
Linda Means
means%gmr.com@relay.cs.net
------------------------------
End of AIList Digest
********************
-------
-------
∂10-Apr-87 2156 LAWS@STRIPE.SRI.COM AIList Digest V5 #96
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Apr 87 21:55:54 PDT
Date: Sun 5 Apr 1987 23:33-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #96
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 6 Apr 1987 Volume 5 : Issue 96
Today's Topics:
Code Source - BBS for Micro AI and Geotechnical Applications,
Queries - Fuzzy Logic Implementation & OPS5 Examples &
Knowledge Representation Languages,
Comments - Demons and Censorship,
Application - Police Computer Detects Suspects
----------------------------------------------------------------------
Date: 1 Apr 87 23:38:22 GMT
From: nbires!isis!csm9a!japplega@ucbvax.Berkeley.EDU (Joe Applegate)
Subject: New AI BBS for Micro AI Applications
The Colorado School of Mines Consortium for AI Research is sponsoring a
public BBS for AI and geotechnical discussions and public domain software.
This forum features areas for AI and conventional language development as
well as the geologic and geophysical disciplines. Currently 6 meg. of
PC based public domain applications are on line (most with source).
You can reach this forum at (303) 273-3989 300/1200/2400 baud 8-N-1 24 hrs.
Supports XMODEM, TELINK, and YMODEM transfer protocols.
Joe Applegate - Colorado School of Mines Computing Center
{seismo, hplabs}!hao!isis!csm9a!japplega
*** UNIX is a philosophy, not an operating system! ***
------------------------------
Date: Thu, 2 Apr 87 14:06:08 PST
From: jain%newton.Berkeley.EDU@berkeley.edu (Pramod Jain)
Subject: Information on Fuzzy Logic Implementation wanted
We are interested in information on research and development
issues in implementation of fuzzy logic, computer architecture
based on fuzzy logic, hardware issues in fuzzy control, the fuzzy
chip and the like.
Any leads, pointers, references. will be greatly appreciated.
Reply to jain@newton, or call 415-642-8255.
Pramod Jain.
------------------------------
Date: Wed, 1 Apr 87 23:08:00 WET
From: John Fitch (Bath Univ.) <fitch@Cs.Ucl.AC.UK>
Subject: OPS5 Examples
Does anyone have any example s of OPS5 programs? I have the Monkeys and
Bananas, and also the Manhattan mapper. What I want is examples so we can test
alternative matching algorithms. Any help or pointers would be appreciated
==John Fitch
University of Bath
------------------------------
Date: Thu, 2 Apr 87 16:46:57 EST
From: weltyc@csv.rpi.edu (Christopher A. Welty)
Subject: Knowledge Representation Languages
Pardons if this has been done recently, I've been off ailist for
the past month (doctors orders :-). I'm working on some KR tools -
specifically, designing a new representation language - and I am
currently discussing with colleagues and students in the project the
issues involved. We are looking at various existing KR languages and
their merits/faults, but only I and one other person in the project have
any real experience with any of these (SRL, KRL, CRL, FRL ...).
I thought it would be interesting (and hopefully enlightening
for me) to get some input from the net here. I'd like to discuss what
other people who are actually using/have used KR systems (like Knowledge
Craft, KEE, etc.), think of these systems.
It seems to start an interesting discussion (I thought the
conciousness stuff was interesting) you have to make a bold statement
that you know people will disagree with and get riled - or you have to
be Marvin Minsky and just post a simple message, so maybe I'm going
about this the wrong way...but I'll give the soft approach a shot first.
-Chris Welty, RPI
weltyc@csv.rpi.edu
[I have forwarded a copy of this query to the NL-KR@ROCHESTER.ARPA
list, and would expect the main discussion to occur there. -- KIL]
------------------------------
Date: Fri, 3 Apr 87 18:29 PST
From: Tom Garvey <GARVEY@SRI-STRIPE.ARPA>
Subject: Demons and censorship
One of the first places I saw "demons" used in the manner that
they now exist (as "daemons," a sexier, more classical sounding spelling
and a "subordinate deity" into the bargain) was in Carl Hewitt's Planner
system/language (actually, I don't know whether there ever was a real
implementation of Planner, but Winograd & Sussman (and al, too, I
suspect) implemented a version in Lisp called Microplanner). Anyway,
demons (as in the Maxwell's Demon sense) were the little processes with
associated patterns that watched the "data base," and when an assertion
was made, any demon with a pattern that matched the assertion would be
activated to do something interesting. These were also known as
"antecedent theorems," but that isn't nearly as catchy, and most people
referred to them as "demons." All this took place in the early '70s,
and I suspect their use predated the "daemon" processes that today screw
up our mail, hardcopies, and network access on a wide variety of
machines.
By the way, I feel that it is an incredible expression of
arrogance to assume that we can ever produce a machine intelligence, and
I continue to be astounded that you allow messages dealing with that
topic. From now on, I would like to request that you filter these
messages from the list; if you feel that this approach is too draconian
or possibly controversial, perhaps you could just insist that anyone
writing a note dealing with intelligence in any form so indicate in the
header, and the rest of us (who are, of course, better and more socially
conscious than the rest of you) can just skip over them.
This note has nothing to do with intelligence in any form.
And, of course, "Everything you know is wrong!"
Cheers,
Tom
[I have faith that only half of what I know is wrong. I'll
let you know when I find out which half. -- KIL]
------------------------------
Date: Sat, 4 Apr 1987 16:27 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Police Computer Detects Suspects
From the Daily Campus, Thursday, April 2, 1987,
Original Source: Associated Press
Grand Prairie, Texas - A Computer used by police to
detect likeley locations for crime pinpointed the
likely time and location for a burglar enabling the
police to stake out the area and make the arrest. The
computer predicted the time to an accuracy of four
hours and the place to within a few blocks.
------------------------------
End of AIList Digest
********************
∂13-Apr-87 2329 LAWS@STRIPE.SRI.COM AIList Digest V5 #97
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 Apr 87 23:28:53 PDT
Date: Mon 13 Apr 1987 20:49-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #97
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 14 Apr 1987 Volume 5 : Issue 97
Today's Topics:
Administrivia - Recent Delivery Problems,
Policy - Source Code Postings,
Seminars - The Anatomy of AI Tarpits (CMU) &
Analogical Transformation Extension (CMU) &
Leaning on the World (CMU) &
Parallelism for KR Languages (SRI) &
Understanding and Personality (SUNY Buffalo) &
An Integrated Framework for Factory Scheduling (CMU)
----------------------------------------------------------------------
Date: Mon 13 Apr 87 10:28:38-PDT
From: Ken Laws <Laws@STRIPE.SRI.COM>
Subject: Recent Delivery Problems
AIList distribution has been delayed for about a week due to 1) mailer
problems caused by the recent change in Arpanet host names, 2) the time
it has taken me to put in a garden, and 3) the birth of my third child,
Devon Lee Laws. The mailer and garden problems seem to be fixed now,
but please excuse my continued poor response time -- I have to spend a
greater percentage of my evenings and weekends looking after my family now.
-- Ken
------------------------------
From: "Norbert E. Fuchs" <fuchs%ifi.unizh.chunet@RELAY.CS.NET>
Subject: Source Code Postings
Using FTP for source code downloading may be fine for those on the Arpanet, but
there are others like myself outside the USA who have no access to an Arpanet
site. I support posting source code in AIList - or an equivalent solution - so
that everybody has the possibility of downloading.
--- nef
------------------------------
Date: 1 Apr 87 15:01:35 EST
From: Patricia.Mackiewicz@isl1.ri.cmu.edu
Subject: Seminar - The Anatomy of AI Tarpits (CMU)
SPECIAL AI SEMINAR
TOPIC: "The Anatomy of AI Tarpits"
SPEAKER: Phil Agre, MIT
WHEN: Monday, April 6, 1987, 1:00 pm
WHERE: Doherty Hall 3313
ABSTRACT
This is a talk I gave at a recent workshop on Meta-Level Architectures.
I originally wrote it to blow off steam at the last dozen AI papers I
had read, but I have come to think that it provides a clean, simple
explanation of why AI (among other fields) is wedged.
My thesis is that AI, as a field, has a pathological attitude toward
language. AI repeatedly gets itself into tarpits based on
pseudo-technical words like, for example, "planning." The community
(or, lately, some sub-field of it) cultivates a habit of seeing "planning"
in an activity's slightest intentionality, regularity, deliberateness,
or planfulness -- and marginalizing or ignoring anything else. Then it
writes (destruct plan ...). I will describe an anatomy of tarpits that
lets us predict in remarkable detail how their victims will get stuck.
Then I will discuss five examples: the mind, planning, knowledge,
variables, and the meta level. Along the way I will suggest some ways out.
**************************************************************************
If you are interested in an appointment with Phil Agre please contact
Patty at extension 8818 or pah@d.
**************************************************************************
------------------------------
Date: 1 Apr 87 19:51:18 EST
From: Steven.Minton@cad.cs.cmu.edu
Subject: Seminar - Analogical Transformation Extension (CMU)
Wei-Min Shen is giving this week's seminar. As usual, we will meet
in 7220 at 3:15 on Friday. Here's the abstract:
Analogical Transformation Extention
and its Applications
One of the aspects of learning by analogy is concerned with constructing and
generalizing a transformation in the source domain and productively using it
in the target domain. In this talk, we will discuss a preliminary approach,
ATE, to the problem and its applications to: (1) creating new operators
(more general than Macro-Operators) in AI discovery systems; and (2) solving
problems in Geometric-Analogy Intelligence-Tests.
For the first application, we will discuss in detail an implemented system,
ARE. It starts with a small set of creative operations and a small set of
heuristics, and uses ATE to create all the concepts attained by Lenat's AM
system, and others as well. Besides showing a way to meet the criticisms of
lack of parsimony that have been leveled against AM, the ARE system provides
a route to discovery systems that are capable of "refreshing" themselves
indefinitely by continually creating new operators.
For the second application, we will compare the ATE approach with the method
used by Evans in his program for solving problems in Geometric-Analogy
Intelligence-Tests, and show that the ATE approach can solve the problems
more efficiently.
This discussion is a report on an ongoing project. We will appreciate any
suggestions and comments. In case I cannot answer your hard questions, I
will bring some delicious chinese rice pudding as my defence.
------------------------------
Date: 3 Apr 87 08:36:22 EST
From: Patricia.Mackiewicz@isl1.ri.cmu.edu
Subject: Seminar - Leaning on the World (CMU)
TOPIC: "Leaning on the World"
SPEAKER: Phil Agre, MIT
WHEN: Tuesday, April 7, 1987, 3:30pm
WHERE: Wean Hall 5409
David Chapman and I have been studying the organization of everyday
routine activity (things like making breakfast and driving to work)
with an eye to understanding the human cognitive architecture.
In trying to explain what we've observed, we've been lead away from
mentalistic metaphors emphasizing containment and boundary (perception,
behavior, programs and processes, content-bearing datastructure-like
representations) and toward metaphors emphasizing agents' interactions
with their worlds.
Our central distinction is between an agent's "machinery" and the
"dynamics" of its activity. We have found that, for the broad range of
routine activity we have studied, a very simple architecture suffices.
It consists of an innate "periphery" (along the lines of Marr and
Ullman) and a constructed "center". Careful analysis of the reliable
patterns of interaction in the agent's world allows the center to be
made out of very simple hardware, in fact combinational logic.
This simplicity derives largely from a new theory of representation.
Where traditional representation schemes posit objectively defined
"individuals" in the world, our scheme of "indexical-functional
aspects" (or "aspects" for short) parses the nearby materials
according to their relationship to the agent's person (i.e.,
indexically) and purposes (i.e., functionally). Such a scheme
generalizes its understanding without putting variables in for
constants, so it does not need any hardware for matching, binding, and
substitution.
Chapman is almost done implementing an instance of this architecture.
Pengi is a program that plays the video game Pengo. Pengi's periphery
simulates a person looking at a video game monitor. Its center is a
fixed combinational network derived from a specification of the salient
aspects of the recurring game situations. With luck, a demo will be
available.
Strongly suggested reading (copies may be available):
Chapman and Agre, Penti: An Implementation of a Theory of Situated
Activity, submitted to AAAI-87.
Chapman and Agre, Abstract Reasoning as Emergent from Concrete
Activity, Workshop on Reasoning About Action, 1986.
Shimon Ullman, Visual Routines, MIT AI Lab Memo 723, June 1983.
**************************************************************************
If you are interested in an appointment with Phil Agre please contact
Patty at extension 8818 or pah@d.
**************************************************************************
------------------------------
Date: Fri, 10 Apr 87 12:23:48 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Parallelism for KR Languages (SRI)
PARALLELISM IN INTERPRETERS FOR KNOWLEDGE REPRESENTATION LANGUAGES
Henry Lieberman (HENRY@OZ.AI.MIT.EDU)
MIT
11:00 AM, MONDAY, April 13
SRI International, Building E, Room EJ228
While there has been considerable interest in applying parallelism to
problems of search in knowledge representation languages, lingering
assumptions of sequentiality in the interpreters for such languages still
stand in the way of making effective use of parallelism. Most knowledge
representation languages have a sequential QUERY-SEARCH-ANSWER loop, the
analog of the READ-EVAL-PRINT loop of Lisp, and employ parallelism only in
the SEARCH phase, if at all. I will discuss parallel alternatives to
sequential interpreters for knowledge representation languages, and new
approaches to constructing user interfaces for these languages. These
observations arise out of experience with the representation language Omega
of Attardi, Simi, and Hewitt. The approach is motivated by a desire to
respond to Hewitt's "open systems" critique of logic-based systems, which
strives for systems that can deal with inconsistent beliefs, dynamically
revise beliefs, and are sensitive to allocation of resources.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: 10 Apr 87 22:24:44 GMT
From: rocksvax!rocksanne!sunybcs!rapaport@CS.ROCHESTER.EDU (William
J. Rapaport)
Subject: Seminar - Understanding and Personality (SUNY Buffalo)
philosophy of science
STATE UNIVERSITY OF NEW YORK AT BUFFALO
GRADUATE GROUP IN COGNITIVE SCIENCE
JOHN HAUGELAND
Department of Philosophy
University of Pittsburgh
UNDERSTANDING AND PERSONALITY
Artificial Intelligence (AI) has inherited a conception of pure under-
standing from modern philosophy, especially Descartes and Kant. How-
ever, developments within AI, specifically with regard to knowledge
representation, have partially undermined this conception. It will be
argued that they have not gone far enough in this. In particular,
``impurities'' like ego and affects must be included as well.
Thursday, April 23, 1987
4:00 P.M.
Knox 4, Amherst Campus
Co-sponsored by:
Department of Computer Science
and
Colloquium in the History and Philosophy of Science
Informal discussion at 8:00 P.M. at Stuart Shapiro's house, 112 Park-
ledge Drive, Snyder, NY. Call Bill Rapaport (Dept. of Computer Science,
636-3181), Gail Bruder (Dept. of Psychology, 636-3676), or Zeno Swijtink
(Dept. of Philosophy, 636-2444) for further information.
------------------------------
Date: 10 Apr 87 13:05:44 EDT
From: Patricia.Mackiewicz@isl1.ri.cmu.edu
Subject: Seminar - An Integrated Framework for Factory Scheduling
(CMU)
AI SEMINAR
TOPIC: Toward An Integrated Framework For Factory Scheduling
SPEAKER: Steve Smith, CMU
WHEN: Tuesday, April 14, 1987, 3:30 p.m.
WHERE: Wean Hall 5409
ABSTRACT:
In this talk we present work aimed at providing an integrated framework for
coordinating factory production. An integrated framework is defined as one
that merges predictive generation/expansion of the production schedule with
reactive schedule management in response to the dynamics of factory
operation. We describe OPIS, a knowledge-based scheduling system that
advocates a common view of predictive and reactive scheduling as an
opportunistic problem solving process. This view is realized by a system
architecture that combines constraint propagation and consistency
maintenance techniques with heuristics for dynamically focusing the
scheduler according to characteristics of current solution constraints. A
collection of scheduling methods, varying in the decomposition of the
problem that is assumed and the types of constraints and objectives that are
emphasized, are defined to provide strategic alternatives. We present
experimental evidence of the effectiveness of this approach in generating
schedules and give examples of its use in reactively revising them as the
situation warrants. We then turn attention to the central assumption of an
incrementally maintained schedule as the basis for factory floor
decision-making and consider its computational implications. Current work
directed toward improving the robustness of predictive schedules and
hierarchically distributing the scheduling effort is described.
------------------------------
End of AIList Digest
********************
∂14-Apr-87 0129 LAWS@STRIPE.SRI.COM AIList Digest V5 #98
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 14 Apr 87 01:29:42 PDT
Date: Mon 13 Apr 1987 21:08-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #98
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 14 Apr 1987 Volume 5 : Issue 98
Today's Topics:
Conference Session - 11th Annual Computer Science Conference,
Conferences - Midwest AI and CogSci Society &
Philosophy/Psychology Conference
----------------------------------------------------------------------
Date: Sat, 11 Apr 1987 01:47 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Conference Session - 11th Annual Computer Science Conference
Eleventh Annual Computer Science Conference
Texas Woman's University, Denton Texas, Thursday, April 23, 1987
9:00AM, Steve Krueger, Topic: The Texas Instrument AI/LISP Chip -- Its
Functional Architecture
10:45AM Embedding Parallelism into an Expert System, L. Haerim
11:15 Topics in the Applications of Prolog, D. Scott Thorp
11:45 A Program to Learn and Play Bridge, S. Starmer, T. Nabors, t. Nute,
J. R. Rinewalt
Speech Recognition Perspective, D. H. Lin
1:30 Pattern Recognition for Analysis of Inexact Data
2:00 Analysies of Some Strategies for Playing Mastermind
Kwok-bun Yue
3:00 Developing an Expert System for Process Planning
G. N. Black, East Texas State University
4:00 PM, Using a Two Camera System to Computer 3-D Positons by Silvia Monroe
------------------------------
Date: Mon, 6 Apr 87 13:18:29 cdt
From: Kris Hammond <kris@ANUBIS.UCHICAGO.EDU>
Subject: Conference - Midwest AI and CogSci Society
The First Annual Meeting
of
The Midwest Artificial Intelligence and Cognitive
Science Society
The University of Chicago
April 24th and 25th
The Enrico Fermi Research Institute
5640 Ellis Ave - Room 480
We now have a schedule for the first meeting of Midwest Artificial
Intelligence and Cognitive Science Society (MAICSS):
Friday, April 24th.
7:00 Welcome to MAICSS
7:15 Keynote Address -
Gerald DeJong: Machine Learning at UIUC
8:15 MAICSS reception/dinner
Saturday, April 25th.
9:00 AI at Ohio - Ashok Goel
9:30 Ohio Student Talks
10:30 AI at Michigan - Steve Lytinen
11:00 Michigan Student Talks
11:20 The Organization of Natural Movement - Peter Greene: IIT
11:50 IIT Student Talks
12:30 Lunch
1:30 AI at Wisconsin
2:00 AI at Chicago - Kristian Hammond
2:30 Adaptive Feedback Testing System - Ming Rao: UI Circle
2:50 Break
3:20 UIUC Student Talks
4:20 Northwestern Student Talks
5:30 MAICSS Business meeting
If you plan on attending, please get in touch with us now. We need to
have an accurate head count so we can order food and print up the right
number of proceedings. There is no registration fee but we would prefer
that people don't just show up at the door without notice. So, if you
have not been in touch with us yet, please call (312) 702-8070 and talk
to Andrea. If you are planning on coming, DO THIS NOW.
We still have space to put up out-of-town graduate students on Friday
and Saturday night. But, here again, we need to know before hand who
needs space. There is also a definite limit on how much space we have.
For non-students, we have arranged for housing at the Hyde-Park Hilton.
The number there is (312) 288-5800. They are holding a block of reduced
rate rooms for the conference.
If you have any other questions concerning the conference, call Kris
Hammond at (312) 702-1571 or send mail to kris@gargoyle.uchicago.csnet -
for CSnet mail or kris%gargoyle.uchicago.csnet-relay.arpa - for ARPA
mail.
Thanks and we'll see you there.
------------------------------
Date: 4 Apr 87 05:55:03 GMT
From: princeton!mind!harnad@RUTGERS.EDU (Stevan Harnad)
Subject: Conference - Philosophy/Psychology Conference
Program of the 13th Annual Meeting of the Society for Philosophy and Psychology
June 21 -23, University of California, San Diego
For program information: William Bechtel (SPP Program Chairman),
Philosophy Department, Georgia State University, Atlanta GA 30303-3083
phone: (404)-658-2277 bitnet address: psuvax1!phlpwb%GSUMVS1.BITNET
For membership information: Patricia Kitcher, Philosophy Department,
University of California-San Diego, La Jolla CA 92093
arpanet address: sdcsvax!ir205%sdcc6
-------- SUNDAY, JUNE 21, 1987 --------
9:00 - 11:00am SYMPOSIUM: DEPRESSION, COGNITION, AND RATIONALITY
Chair: Evalyn Segal, Psychology, San Diego State University
Speakers: George Graham, Philosophy, University of Alabama at Birmingham
Christopher Peterson, Psychology, University of Michigan
Lynn Rehm, Psychology, University of Houston
Commentator: Richard Garrett, Philosophy, Bentley College
1:00 - 3:15pm CONCURRENT CONTRIBUTED PAPERS SESSIONS I AND II
SESSION I: Behavior and Belief
Chair: James Pate, Psychology, Georgia State Unviersity
Speaker: Ruth Garrett Millikan, Philosophy, University of Connecticut
"What is Behavior? or Why Narrow Psychology/Ethology
is Impossible"
Commentator: John Biro, Philosophy, University of Oklahoma
Speaker: David Martel Johnson, Philosophy, York University
"'Brutes Believe Not': Why Non-Human Animals Have No Beliefs"
Commentator: Carolyn Ristau, Psychology, Vassar
SESSION II: Computational Theories of Mind
Chair: Owen Flanagan, Philosophy, Wellesley
Speaker: David Kirsch, Artificial Intelligence, MIT
"The Concept of Computation in Connectionist Systems"
Commentator: Brian Cantwell Smith, Computer Science, Xerox PARC
Speaker: Joseph Levine, Philosophy, North Carolina State University
"Demonstrative Thought"
Commentator: La Verne Shelton, Educational Testing Service, Princeton
3:30-5:00pm INVITED LECTURE: LANGUAGES OF THE DEAF
Chair: Adele Abrahamsen, Language Research Center, Georgia State
Speaker: Howard Poizner, Salk Institute, San Diego
"Brain Function for Language: Perspectives from Another Modality"
7:00-10:00pm SYMPOSIUM: ANALOGY AND LEARNING
Chair: Paul Thagard, Cognitive Science, Princeton
Speakers: Dedre Gentner, Psychology, University of Illinois
Doug Medin, Psychology, University of Illinois
Keith Holyoak, Psychology, University of California, Los Angeles
Commentator: Eva Kittay, Philosophy, SUNY, Stony Brook
----- MONDAY, JUNE 22, 1987 --------
9:00-11:30am SYMPOSIUM: CONNECTIONISM AND IMAGE SCHEMATIC STRUCTURES
Chair: Patricia Churchland, Philosophy, University California, San Diego
Speakers: David Rumelhart, Psychology, University of California, San Diego
George Lakoff, Linguistics, University of California, Berkeley
Mark Johnson, Philosophy, Southern Illinois University
Terrence Sejnowski, Biophysics, Johns Hopkins University
12:30-2:45pm CONCURRENT CONTRIBUTED PAPERS SESSIONS III, IV, AND V
Session III: Logic and Reasoning
Chair: Ralph Kennedy, Philosophy, Wake Forest
Speaker: David Sanford, Philosophy, Duke University
"Circumstantial Validity"
Commentator: John Rust, Psychology, London School of Education
Speaker: Howard Margolis, Committee on Public Policy,
University of Chicago
"Habits of Mind"
Commentator: Stuart Silvers, Philosophy, Tilburg University
Session IV: Mentalistic Explanations
Chair:
Speaker: Joseph Thomas Tolliver, Philosophy, University of Maryland
"Knowledge Without Truth"
Commentator: Kent Bach, Philosophy, San Fransciso State University
Speaker: Louise M. Antony, Philosophy, North Carolina State University
"Anomalous Monism and the Problem of Explanatory Force"
Commentator: Ken Presting, Philosophy, San Francisco State University
Session V: Subjective Experience
Chair: Hilary Kornblith, Philosophy, Vermont
Speaker: James S. Kelly, Philosophy, Miami University
"On Quining Qualia"
Commentator: Henry Jacoby, Philosophy, East Carolina University
Speaker: Richard J. Hall, Philosophy, Michigan State University
"Is An Inverted Pain-Pleasure Spectrum Possible?"
Commentator:
3:00-5:30pm SYMPOSIUM: CONCEPTUAL AND SEMANTIC CHANGE IN CHILDHOOD AND SCIENCE
Chair:
Speakers: Annette Karmiloff-Smith, MRC, Cognitive Development Unit
Alison Gopnik, Psychology, University of Toronto
Susan Carey, Psychology, Massachusetts Institute of Technology
Philip Kitcher, Philosophy, University of California, San Diego
8:00-9:00pm PRESIDENTIAL ADDRESS
Chair: Alvin Goldman, Philosophy, Arizona
Speaker: Stevan Harnad, Behavioral and Brain Sciences
"Uncomplemented Categories, or, What Is It Like To Be
a Bachelor?"
------ TUESDAY, JUNE 23, 1987 ------
9:00-11:00am SYMPOSIUM: SEMANTICS
Chair: Richard Jeffrey, Philosophy, Princeton
Speakers: Mark Johnston, Philosophy, Princeton
Barbara Hall Partee, Linguistics, U. Massachusetts, Amherst
Norbert Hornstein, Linguistic, University of Maryland
Commentator: Stephen Schiffer, Philosophy, University of Southern California
11:15-12:30pm INVITED LECTURE: Memory and Brain
Chair:
Speaker: Larry R. Squire, Psychiatry, University of California, San Diego
"Memory and Brain: Neural Systems and Behavior"
1:30-3:45pm CONCURRENT CONTRIBUTED PAPER SESSIONS VI AND VII
SESSION VI: CONCEPTS
Chair: Bernard Kobes, Philosophy, Arizona State University
Speaker: Kenneth R. Livingston & Janet Andrews, Psychology, Vassar College
"Reflections on the Relationship Between Philosophy and Psychol-
ogy in the Study of Concepts?: Is there Madness in our Methods?"
Commentator: Robert McCauley, Philosophy, Emory University
Speaker: Andrew Woodfield, Philosophy, Bristol
"A Two-Tiered Model of Concept Formation"
Commentator:
SESSION VII: INTENTIONALITY
Chair: Douglas G. Winblad, Philosophy, Georgia State University
Speaker: Ron Amundson, Philosophy, University of Hawaii at Hilo
"Doctor Dennett and Doctor Pangloss"
Commentator: Justin Leiber, Philosophy, University of Houston
Speaker: Robert Van Gulick, Philosophy, Syracuse
"Consciousness, Intrinsic Intentionality,
and Self- Understanding Machines"
Commentator: Nick Georgalis, Philosophy, East Carolina University
4:00-5:30pm INVITED LECTURE: CONSCIOUSNESS
Chair:
Speakers: Daniel Dennett, Philosophy, Tufts University
Kathleen Akins, Philosophy, Tufts University
BEACH PARTY
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@princeton.ARPA harnad@mind.Princeton.EDU
------------------------------
End of AIList Digest
********************
∂14-Apr-87 0325 LAWS@STRIPE.SRI.COM AIList Digest V5 #99
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 14 Apr 87 03:24:59 PDT
Date: Mon 13 Apr 1987 21:15-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #99
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 14 Apr 1987 Volume 5 : Issue 99
Today's Topics:
Queries - Statistical Expert Systems & Prolog for UNIX System V.2 &
Cog Sci Conference & Cog. Psych. Grad. Schools,
AI Tools - MS-DOS Expert System Tools,
Application - AI in Network Protocols,
Funding - Military Funding,
Humor - Demon Error & Which Half is Right?,
Inference - Clyde the Elephant
----------------------------------------------------------------------
Date: Mon 13 Apr 87 16:19:12-PST
From: Ken Laws <LAWS@IU.AI.SRI.COM>
Subject: Statistical Expert Systems
I have received a letter from Dr. D.J. Hand, Institute of Psychiatry,
De Crespigny Park, Denmark Hill, London, SE5 8AF. He (or she?) is
trying to compile a list of researchers working in statistical expert
systems, for use by researchers and conference organizers. If you
would like to be listed, and to receive a copy, send your name,
address, and a brief description of your work.
-- Ken
------------------------------
Date: 13 Apr 87 16:15:39 GMT
From: husc8!edwards@husc6.harvard.edu (Bill Edwards)
Subject: Good Prolog Interpreter/Compiler for UNIX System V.2
Wanted: Good Prolog Interpreter/Compiler for UNIX System V.2
Please respond by email-thanks. -- Bill Edwards
Bill Edwards edwards@harvard.harvard.edu (ARPA)
UNIX Systems Programmer/Analyst ...!harvard!edwards (UUCP)
Harvard Science Center edwards@harvunxu (BITNET)
1 Oxford Street hucsc::edwards (DECNET)
Cambridge, MA 02138
------------------------------
Date: Mon 13 Apr 87 16:53:40-EDT
From: John C. Akbari <AKBARI@cs.columbia.edu>
Subject: cog sci conference
anyone have an email address to inquire about attending the cognitive science
conference in july (just after aaai-87).
john c akbari
ARPANET & Internet akbari@CS.COLUMBIA.EDU
BITnet akbari%CS.COLUMBIA.EDU@WISCVM.WISC.EDU
uucp & usenet ...!seismo!columbia!cs!akbari
DECnet akbari@cs
PaperNet 380 riverside drive, no. 7d
new york, new york 10025 usa
SoundNet 212.662.2476
------------------------------
Date: 10 Apr 87 17:19:04 GMT
From: seger@husc4.harvard.edu (carol seger)
Subject: Cog. Psych. Grad. School advice sought.
I am planning to apply to graduate schools in cognitive psychology /
cognitive science in the fall. However, I will be teaching
high school in Kenya for a year beginning in July, so I
have to decide where I want to apply soon so I can visit places before
I leave. I am seeking three sorts of advice:
a. Other schools that might be worthwhile but that I have overlooked
b. Any information from current students in any of the programs I
am considering.
c. General advice on the applications process. As far as I am aware,
none of the programs I am applying to require interviews. Is
there any reason I cannot apply from overseas?
I am interested in high-level perception, natural reasoning,
categorization, spatial cognition, cognitive development and cognitive
neuropsychology. I am not interested in psycholinguistics (at least at
the moment) or low-level perception. I prefer to concentrate on
experimental psychology -- while I find computer modeling to be
interesting, I don't want to do it myself.
I am currently a senior in the cognitive science option of the
Psychology concentration at Harvard Univeristy. I wrote my senior
thesis on intermodality realtions in shape perception, and have worked
on a naturalistc study of mental imagery.
So far, in order of preference, I am applying to
Stanford
UC Berkeley
UC San Diego
UCLA / University of Pennsylvania (tie, so far).
I prefer to live in California, but, of course, I'll go to the best
program I can get into.
If you have any advice, please mail it to me. Many thanks.
Carol Seger.
carol@borax.lcs.mit.edu
seger@wjh12.harvard.edu
------------------------------
Date: 5 Apr 87 04:46:06 GMT
From: nbires!isis!csm9a!japplega@ucbvax.Berkeley.EDU (Joe Applegate)
Subject: Re: MS-DOS expert system tools?
>
>I'm looking for expert-systems tools that can be run on PC-class machines
>
>So far I have looked at GURU, EXSYS, VP-Expert, and KDS. None of these
>systems comes close to my needs; most of them are question/answer menu-based
>tools best suited for very simple interactive diagnostic or recommendation
>ES's. Some of them allow access to external databases, but none of them
>(as far as I can tell) allow general user routines to be linked in.
>
>I have access to TI's PC-Plus and will be looking at it soon. I have read the
>advertising blurb on Level Five's Insight-2+, and it sounds very interesting.
>But then, the blurbs on some of the other tools sounded good, too.
>
>Has anyone used these systems, or any others that meet my needs? I would
>really appreciate it if you would contact me with any suggestions.
>
Most PC based Expert Systems shells are oriented towards database type
type queries of their knowledge. Though it is possible to acces both ports
and the bios from TI's Personal Consultant Plus, I doubt if that or any shell
will give the response needed for real time processing.
A more feasible method for this type of development is to do it from scratch
in an acceptable language... most probably Lisp or Prolog, though C and
Pascal can be used in such an environment and have been in the past!
At the risk of getting lynched I would recommend you take a look at Turbo
Prolog... if your rule base is not dynamic, Turbo Prolog provides a powerful
yet inexpensive development engine with graphic primitives and direct access
to DOS and BIOS functions as well as the I/O ports of a PC.
Joe Applegate - Colorado School of Mines Computing Center
{seismo, hplabs}!hao!isis!csm9a!japplega
or
SYSOP @ (303) 273-3989 300/1200/2400 8-N-1
Minds of Mines AI BBS
------------------------------
Date: 7 Apr 87 13:21:24 GMT
From: sundc!cos!duc@seismo.CSS.GOV (Duc Kim Nguyen)
Subject: Re: AI in Network Protocols.
I think this is a very interesting topic for discussion.
Typically a protocol specification contains some BNF notation
for the syntactical definition (e.g., X.400, etc...) and the binding
(or usage/meaning) of the components' values is burried in the 'english'
text of the spec. The effect of this is the lack of a more 'complete'
and/or formal notation to capture both the syntax and semantic in order
for automating a testing system (to test the protocol) and/or
determining a set of test cases to be 'partially' (or even wholly)
complete to test a set of functionalities of the protocol (and
therefore a result analysis system can be automated).
Maybe, a knowledge-based system will solve this, but I
prefer not to think about a database-driven approach until no can-do.
Duc Kim Nguyen
Corporation for Open Systems
------------------------------
Date: 5 Apr 87 06:28:07 GMT
From: ubc-vision!calgary!vuwcomp!steve@seismo.CSS.GOV (Steve Cassidy)
Reply-to: steve@vuwcomp.UUCP (Steve Cassidy)
Subject: Military Funding
In article <[A.ISI.EDU]31-Mar-87.15:25:11.DAVSMITH> DAVSMITH@A.ISI.EDU writes:
>Without the military applications, who in the commercial sector
>would attempt to put together cooperating expert systems
>in real-time? [ One could broaden the issue and ask
>"Who in their right mind would..?"]
Here we assume that the only *possible* applications of real-time cooperating
ES are military ones. What is the major difference between a system which sits
in a fighter plane monitoring the pilots actions and one which sits in some
complex manufacturing plant monitoring the processes there?
Too often military research is justified as the only way new ideas can
develop, the truth is that they are the only research programmes given
sufficient funds to develop new ideas. If research groups had the same level of
funding available for civil projects then they would be able to develop
real-time cooperative expert systems in domains which may actually be *useful*
to mankind.
Steve
ACSnet: steve@vuwcomp.nz
UUCP: {ubc-vision,alberta}!calgary!vuwcomp!steve
------------------------------
Date: Mon, 13 Apr 87 01:33:15 pst
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Feigenbaum Comment about SDI
Last week, Computer Literacy bookstore completed a kick off opening
lecture series, some very noted computers scientists spoke over the
course of two weeks. I think comments by two speakers would interest
recent discussions on both Arms-d and AIlist. In particular,
Dr. Ed. Feigenbaum made mention in his words that the SDIO has
dropped funding of AI from its budget. His implication appeared
to be more software engineering oriented rather than battle
management oriented. I don't know if they have or not, but I personally
do not get the impression that they have, especially for battle
management.
>From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
Date: 6 Apr 87 17:48:27 GMT
From: "Col. G. L. Sicherman"
<colonel%sunybcs%math.waterloo.edu@RELAY.CS.NET>
Subject: Re: AIList Digest V5 #92
In article <MINSKY.12290784989.BABYL@MIT-OZ>, MINSKY@OZ.AI.MIT.EDU writes:
> The term "demon" comes from Oliver Selfridge, via the paper,
> "Pandemonium: A Paradigm for Learning", published in Symposium of the
> mechanization of Thought Processes, November 1858.
Then we can certainly concede priority to Selfridge. I wonder how much
influence he had on the work of Babbage? (Ken, you should have caught this!)
--
Col. G. L. Sicherman
UU: ...{rocksvax|decvax}!sunybcs!colonel
CS: colonel@buffalo-cs
BI: colonel@sunybcs, csdsiche@ubvms
------------------------------
Date: 13-Apr-1987 0938
From: kevin%bizet.DEC@decwrl.DEC.COM (Now, if it sounds good, you
don't worry what it is: you just go and enjoy it.)
Subject: Which half is right?
> [I have faith that only half of what I know is wrong. I'll
> let you know when I find out which half. -- KIL]
Merely determining the halves, let alone figuring out which half is right, would
be an astonishing accomplishment!
Kevin LaRue
------------------------------
Date: 5 Apr 87 20:36:23 GMT
From: "Col. G. L. Sicherman"
<colonel%sunybcs%math.waterloo.edu@RELAY.CS.NET>
Subject: Re: Clyde the elephant
The problem of Clyde the elephant brings up one of the biggest
controversies in statistics, one which is starting to spill over
into A.I. To recapitulate:
1. 95% of elephants are grey;
2. 40% of royal elephants are yellow;
3. Clyde is a royal elephant.
But we know nothing about what percentage of elephants are royal.
The distribution could look like this:
| royal common
------+---------------
grey | 15 175
yellow| 10 0
or like this:
| royal common
------+---------------
grey | 0 95000
yellow| 2 0
red | 3 4995
Can we assign a valid probability to "Clyde is grey" without knowing
the likelihood of either distribution (or any other)? One school of
thought says no--the best we can do is follow Boole's suggestion of
computing upper and lower bounds for the probability. Other schools,
notably that led by A. P. Dempster, say yes.
And this topic is all too philosophical enough to be discussed here
in mod.ai!
--
Col. G. L. Sicherman
UU: ...{rocksvax|decvax}!sunybcs!colonel
CS: colonel@buffalo-cs
BI: colonel@sunybcs, csdsiche@ubvms
[SRI is a hotbed of Dempster-Shaferism, so I'll take a chance on
clarifying this. Tom Garvey or other readers can correct me if
I'm off base. The Dempster-Shafer (D-S) is to track upper and
lower bounds for probability. This is controversial in two ways:
Dempster's rule for combining contradictory evidence, and the
power/appropriateness/usefulness of the interval approach in general.
(Conflicting evidence really doesn't enter into the Clyde problem.)
It is the Bayesians who generally assign probabilities, although
they don't do it is blindly as their "loyal opposition" would
imply -- while underlying uniform or even Gaussian distributions
are typically assumed for predictive power under random sampling,
Bayesians might choose a "pessimal" a priori distribution to model
tricky situations such as this one. They can also do symbolic Bayesian
analysis with free parameters in order to derive formulas that are
valid for any state of the world. Fuzzy logicians use a very similar
theory, but are likely to assume that the underlying distributions
are typically implied by the manner in which the problem is stated.
A fourth group, perhaps led by Tversky and Kahneman, are more interested
in the analogy-based reasoning of humans than in optimal decision
theory. And others, e.g. Cohen and various expert systems researchers,
are willing to consider any type of estimate as long as the justification
is given (for use in further reasoning).
Intervals are nice because they make no unwarranted statements.
(Disclaimer: The endpoints may themselves by subject to sampling
errors. Logic-based methods, including D-S, can be very sensitive
to errors in the intial evidence -- as can methods based on tightly
constrained a priori distributions.) Upper and lower probabilities
are also more informative than single point estimates, and can
be interpreted as recording what is unknown as well as what is
known. In cases where a parametric distribution is appropriate,
however, the parameters of that distribution (or optimal estimates
thereof) are the most powerful estimates of the state of the world.
Intervals are not convenient for representing true Gaussian distributions,
for instance, since the intervals must be infinite in extent. (One
might want to use intervals for the mean and standard deviation, though.)
I tend to believe that all sampled data is Gaussian unless there is
evidence to the contrary (either a priori or from examination of the
data), partly because that leads to points estimates and distributions
thereof that are useful. I would not attempt to impose this assumption
on Clyde, however, and there are many situations calling for non-Bayesian
reasoning. -- KIL]
------------------------------
End of AIList Digest
********************
∂23-Apr-87 1228 LAWS@Stripe.SRI.COM AIList Digest V5 #100
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 23 Apr 87 12:27:45 PDT
Date: Sun 19 Apr 1987 19:40-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #100
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 20 Apr 1987 Volume 5 : Issue 100
Today's Topics:
Queries - Legal Modelling & Embedded Lisp and Ada on 68000 &
Request for a Rule Base & OPS5 Programs &
Benchmarking Production Systems & Tough Speech Recognition Examples &
Training Applications of Expert System Shells &
Efficient Implementation of Knowledge Representations &
Cognitive Science Grad Schools,
News - LMI Bankruptcy & Travel Grant Support for IJCAI-87 &
Canadian Artificial Intelligence, April 1987, No. 11
----------------------------------------------------------------------
Date: 7 Apr 87 16:29:25 EST
From: Roger Jagoda Sibley FTOP <FQOJ%CORNELLA.BITNET@wiscvm.wisc.edu>
Subject: Legal Modelling
For a change of pace on this net I'd like to ask if anyone out there has
any information or experience with Legal (as in LAW not lawful)
expert systems. I myself am from the engineering disciplines, but
the Law School here is interested in developing a learning tool with a
bank of legal precedences as the rule set. The inference engine will be
designed by the students as part of the legal argument entered to the
computer "judge". The concept sounded so interesting I thought I'd probe
the nets and see if there were any of you out there that had some ideas
for starting points. If there's enough interest/response I'll summarize
the responses back to the list. Thanks in advance.
Roger Jagoda
Cornell University/CCS
Internet: FQOJ%CORNELLA.BITNET@WISCVM.WISC.EDU
------------------------------
Date: 9 Apr 1987 20:43-EDT
From: LCELEC@A.ISI.EDU
Subject: Embedded Lisp & Ada on 68000
Does anyone know of:
1. An embedded Lisp system, or
2. A 68000-based system that supports Lisp and Ada?
We are trying to implement a small real-time program, originally
written in 68000, in both Lisp and Ada. Since we would eventually
like to do some benchmarking, we would like to keep the Ada and
Lisp on the same 68000 machine. Telesoft Ada supports an
embedded Ada but there does not seem to be any embedded Lisp.
Due to cost constraints, our next alternative is to use some kind
of PC. IBM PC supports both Lisp and Ada but is not 68000 based.
Any information would be helpful.
-- Tracy Mullen
(Please respond directly to LCELEC@A.ISI.EDU)
------------------------------
Date: 10 Apr 87 08:05:10 EDT
From: ABBOTT@RED.RUTGERS.EDU
Subject: request for a rule base
A colleague of mine is doing some work on optimization of production systems
and needs a rule base or two to test his system. Can anyone provide a
reference to a rule base of 50 or more rules? A backward-chaining
system is preferred, but not absolutely necessary. All he needs is a
listing of the rules themselves, not source code (although source code
would certainly be acceptable). Any help would be greatly appreciated.
Kathy Abbott
abbott@red.rutgers.edu
Mail Stop 156A
NASA Langley Research Center
Hampton, Va. 23665
(804) 865-3621
------------------------------
Date: 15 Apr 87 21:26:25 GMT
From: columbia!cheshire.columbia.edu!al@seismo.css.gov (Alexander
Pasik)
Subject: OPS5 programs
Here at Columbia, we are doing extensive research on production
systems especially in the realm of parallel processing. We are in the
process of building a public service library of OPS5 programs for use
in research and benchmarking. Once installed, anyone will be able to
retrieve the systems stored there anonymously through FTP.
We are requesting contributions to this library. Any contibutions
would be most helpful both to our research and to others in the
future.
If you have an interesting OPS5 system, place it in a directory with
all necessary files and a README file describing the system and how it
is used. Then send me (al@cheshire.columbia.edu) the location of the
UNPROTECTED files and I will copy them into the library. When the
library is in place, I will post its location and instructions for
access.
Thanks,
Alexander Pasik (al@cheshire.columbia.edu).
------------------------------
Date: 9 Apr 87 22:14:18 GMT
From: cadre!pitt!wvucsb!rsr@pt.cs.cmu.edu (Ravi S Raman)
Subject: Wanted: Benchmarking Production Systems
Has anybody seen any benchmark or comparative study of the various production
system engines? I am specifically interested in information regarding:
* the implementation language/environment (lisp/ops5/loops/psrl/kee/emycin...)
* the benchmark program
* the number of rules they fire/minute,
* the size and complexity of the rules that were employed,
* the size and complexity of the knowledge-base that was employed,
* the match algorithm employed by the system (Rete...) as well as
its speed/limitations.
I am aware that CMU's Anoop Gupta did quite a bit of comparasion studies;
however they were primarily on CMU systems employing OPS5. I'd like to hear
from other researchers/users in the field.
Please E-mail directly to me. If there is sufficient interest/response
I'll post a summary.
- ravi -
Ravi S. Raman
Department of Statistics and Computer Science
West Virginia University
Morgantown, WV 26506
(304)-293-3607
NET ADDRESS: pitt!wvucsb!wvucswv!rsr@cadre
------------------------------
Date: 17 Apr 87 07:19:20 GMT
From: pioneer!eugene@ames.arpa (Eugene Miya N.)
Subject: Tough speech recognition examples
I am looking for tough speech generation and recognition examples:
discriminating tests. I've seen people present examples to training
systems, and things like DECtalk.
For instance, one example I've heard and seen given is:
How to recognize speech.
How to wreck a nice beach.
I would like to find others. As tests of discrimination. I will not
only collect to summarize, I will maintain the list electronically.
Sort of reminds me of the Ishihara Color Blindness test.
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
Date: 16 Apr 87 07:40:07 GMT
From: mcvax!ukc!its63b!epistemi!rda@seismo.css.gov (Robert Dale)
Subject: Training Applications of Expert System Shells
Can anyone give me pointers to case studies where PC-based expert system
shells have been used in training applications?
If there is sufficient interest, I will post a summary of what I receive to
the net.
Thanks in advance
R
--
Robert Dale University of Edinburgh, Centre for Cognitive Science,
2 Buccleuch Place, Edinburgh, EH8 9LW, Scotland.
UUCP: ...!ukc!cstvax!epistemi!rda
ARPA: rda%epistemi.ed.ac.uk@ucl.cs
JANET: rda@uk.ac.ed.epistemi
------------------------------
Date: Tue, 14 Apr 87 14:32:54 GMT
From: unido!tadam!michael@seismo.CSS.GOV (Michael Beetz)
Subject: Efficient implementation of knowledge representations
We are interested in information on implementation techniques
for object oriented knowledge representation languages on SYMBOLICS
Lisp machines/Genera 7.0. We need an efficient implementation for
maintaining and interpreting large amounts of objects.
Does anybody have comparisons of efficiency for various implementation
techniques like Flavors, Defstructs, generic functions ....??
Or does anybody have experience in implementing such languages.
Any hints, pointers, references will be greatly appreciated !
Reply to stripe.sri.com!unido!taeva!tadam!michael
Michael Beetz
Gaby Streck
------------------------------
Date: Tue, 14 Apr 87 13:15:26 est
From: Amy Winarske <winarske%wellesley.edu@RELAY.CS.NET>
Subject: Cognitive Science Grad Schools
I was very glad to see Carol Seger's letter, as I'm a junior at
Wellesley College in a similar position. Although I'm not going to
Kenya next year and I'm not quite sure what I want to study, (something
to do with language and cognitive science at this point), I would LOVE
to know which schools are doing what, and hear what the people there think
of their programs. It is rather difficult to get information on this field
without knowing who has such programs, since it isn't listed in any of the
"guide books" and is a relatively unknown field to people not involved in
it. (I'm really tired of people asking me "You're majoring in WHAT?")
If you have any words of wisdom or think anybody on the net might,
my address is: winarske@wellesley.edu
Thanks!
-Amy Winarske
------------------------------
Date: Mon, 13 Apr 1987 03:49 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: NEWS FLASH!
Lisp Machine Inc. filed for Chapter 11 Bankruptcy.
Source: Computerworld, April 6, 1987, page 110.
------------------------------
Date: Thu, 16 Apr 87 13:29:58 est
From: walker@flash.bellcore.com (Don Walker)
Subject: Travel Grant support for IJCAI-87
TRAVEL GRANTS FOR IJCAI-87
IJCAII has submitted a proposal to NSF to provide travel allowances
for U.S. participants attending IJCAI-87 in Milan. It also plans to
provide an equal amount of IJCAII funds to support participants from
other countries. The amounts awarded would probably cover no more than
discount air fares and would vary depending on location and on the
number of persons applying. The intent is to help about 100 people.
Priority will be given to younger members of the AI community who
are presenting papers or are on panels and who would not otherwise be
able to attend because of lack of travel funds. Note that U.S.
applicants must use U.S. air carriers.
Applications should be submitted as soon as possible, even though we
have not received confirmation from NSF about a grant award. The
application should briefly describe benefits expected from attendance;
identify expected form of conference participation (e.g., presenting
paper); state current sources of research funding; and list travel
support from other sources. A brief resume should be attached, and
students should include a letter of recommendation from a faculty
member.
Five copies of the application should be sent, no later than 1 June
1987, to:
Priscilla Rasmussen
IJCAI-87 Travel Grants
Laboratory for Computer Science Research
Hill Center, Busch Campus
Rutgers, the State University
New Brunswick, NJ 08903, USA
------------------------------
Date: Sat, 11 Apr 1987 20:43 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Summary of Canadian Artificial Intelligence, April 1987, NO. 11
Discussion of the "Canadian Working Group on Prolog Standardization"
first meeting.
There is a newsletter available on LISP called "Lisp Pointers" available
free from:
Mary S. Van Deusen, Editor
IBM Research
P. O. Box 704
Yorktown Hieghts, NY 10598, USA
maida@ibm.com
A new consulting firm in expert systems: Expert Solutions, 8 Olympus
Avenue, Toronto (Dr. Peter Davies)
Article on expert system activities of the Canadian railways.
Report from the first Workshop on Knowledge Acquisition for Knowledge-
Based Systems was sponsored by the American Association of ARtificial Intelligen
ce
James Bradford of Brock University is developing AI based tools to
offer spontaneous advise to those using commercial packages on PC's.
This will include evaluation of user productivity and satisfaction in
field trials. He is also developing a natural language student
advisor.
At University of Alberta, the Schubert and Pelletier natural language system
is being modified to handle quantifiers such as "some" and "every" combined
with "and" and "not". Also a Generalized Phrase Structure Grammar
with a left-corner parser is being developed which generates something close
to first-order logic with identity.
Other work at University of Alberta:
THINKER, a natural deduction system for first-order predicate logic with
identity.
qualitative physics including liquid flow
system for handling shared logic databases including consistency and
completeness and concurrency issues
robot planning using first-order logic
new search algorithms including a parallel alpha-beta algorithm which was used
in the first place World Computer Chess Championship (on 20 Sun workstations)
incremental learning of conjunctive ocnepts by example
genetic learning algoirthms
List of papers on the workshop "The Challenge of Commonsense Knowledge
Representation in Artificial Intelligence"
Expert Systems and Common Sense
R. Narasimhan, Tata Institute of Fundamental Research in Bombay
Knowledge Reprentation: What is it?
N. Circone, University of Victoria
Some Uncommon Sense About Commonsense
A. Kelkar, Deccan College in Pune
Contributions of Semioptics to the Issue of Commonsense Knowledge
Representation
P. Bouissac of Victoria College at the University of Toronto
Commonsense and the Interpretation of Human Phenomena
J. C. Gardin, CNRS at Paris
Knowledge Representation Issues in Automated Tutoring
G. McCallas of the University of Saskatchawan
Markovian Connotation Models for the Exploration of Commonsense Knowledge
P. Miranda of Laval University
From Meaning to Text: Semantic Representation in the Meaning Text
Linguistic Theory
I. Melcuk of l'Universite de Montreal
Neurollinguistics: From Static Representational STructures to Dynamic
Processes
J. L. Nespoulous
Biology of Natural Language
A. R. Lecours of Centre Hospitalier de la Reine Marie in Montreal
Concluding Paper
S. Ramani of the Tata Institute in Bombay
Reviews of
Roy Davies, Intelligent Information Systems: Progress and Prospects
Kokichi Sugihara, Machine Interpretation of Line Drawing
Michael L. Brodie and John Mylopoulos, On Knowledge Base Management
Systems: Integrating Artificial Intelligence and Database Technologies
------------------------------
End of AIList Digest
********************
∂23-Apr-87 1544 LAWS@Stripe.SRI.COM AIList Digest V5 #101
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 23 Apr 87 15:43:41 PDT
Date: Sun 19 Apr 1987 19:49-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #101
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 20 Apr 1987 Volume 5 : Issue 101
Today's Topics:
Comments - Text Critiques & Statistical Expert Systems & Demons,
AI Tools - Demons in Simulated Annealing Optimization &
Neural Networks Survey Paper & Multilayer Connectionist Theory
----------------------------------------------------------------------
Date: Thu 16 Apr 87 17:45:55-PDT
From: PAT <HAYES@SPAR-20.ARPA>
Reply-to: HAYES@[128.58.1.2]
Subject: Re: AIList Digest V5 #95
Let me briefly add a seconding voice to Linda Means comments on the horrible
output of the style-criticising programs illustrated a while ago. That
people should suggest using such things to influence children almost makes
me agree with Weizenbaum. The thesis behind AI is that intelligence is
computation, but not TRIVIAL computation. Obviously nothing that could run
on a PC could possibly do a good job of such a very subtle and information-
-rich task as critiquing English style, and these things do a TERRIBLE job.
But perhaps the worst aspect of them used as pedagogical tools is not how
well they do the job, but that they so obviously work by applying some simple
and superficial rules in a context-insensitive fashion. Any kid who was
'taught' by one of these would quickly learn these rules. A few experiences
like this, though, and (s)he would learn that most problems are solved by
applying a few superficial rules without any need for deeper thinking, which is
a worse and more dangerous lesson. Im all for the application of AI to
education, but lets not get it confused with the thoughtless use of mediocre
code to subvert education.
Pat Hayes
------------------------------
Date: Fri, 17 Apr 87 00:52:10 EDT
From: lubinsky@topaz.rutgers.edu (David Lubinsky)
Subject: Re: Statistical Expert Systems
I have been working in approximately this field for the last year
at Bell Labs in Murray Hill with Bill Gale and Daryl Pregibon, two of the
most active researchers in the field. Hand is probably aware of Bill's recent
book 'AI in Statistics', where you can find a whole host of people working
in this area.
Personally, I have been working on a system called TESS, (Tree based
Environemnt for Statistical Strategy). TESS allows an expert statistician
to define, implement and critique strategies for particular data analysis
tasks. So far we have implemented two strategies, one for analysing
univariate batches, and one for bivariate analysis.
I can send copies of Tech. Reports, if you want or if you can wait, look
out for a paper called "Data Analysis as Search" in a special statistical
computing edition of Technometrics in the fall.
David
------------------------------
Date: Sat 18 Apr 87 08:46:45-PST
From: Oscar Firschein <FIRSCHEIN@IU.AI.SRI.COM>
Subject: re demons
The Selfridge citation should be 1958 not 1858.
Oscar
------------------------------
Date: Mon 13 Apr 87 10:03:12-PST
From: Stephen Barnard <BARNARD@IU.AI.SRI.COM>
Subject: demons
Everyone is familiar with Maxwell's demon, the tiny sprite that
reverses the increase of entropy dictated by the 2nd Law of
Thermodynamics. He sits at a trapdoor between two chambers containing
a gas in equilibrium (i.e., with maximum entropy) and segregates the
molecules into low- and high-energy populations, thereby moving the
system away from equilibrium and *decreasing* its entropy. If
Maxwell's demon could exist (and be tamed), we could build perpetual
motion machines. The thermal gradient between the chambers could
drive a heat engine.
Brillouin killed the demon by considering the connection between
thermodynamics and information theory. The demon would have to
acquire information about the position and velocity of the molecules
(for example, by bouncing photons off them), but this information would
be gained only at a cost that would balance the decrease in entropy
due to its actions.
Demons of another kind are still alive and well in physics, however.
Creutz described a Monte Carlo algorithm that simulates a system in
thermal equilibrium, much like the Metropolis algorithm used in
simulated annealing. The difference is that Creutz samples from the
*microcanonical ensemble*, in which the system is considered to be
thermally insulated (constant energy). When the state of the system
changes randomly, its potential energy usually changes, and this
difference is absorbed or emitted by a demon, which carries kinetic
energy.
What does this have to do with AI? Simulated annealing is an
effective optimization technique. It's been used for several vision
problems. Creutz's algorithm can be used in a new variant of
simulated annealing that is simpler, more efficient, and more easily
controlled than the standard Metropolis version.
references:
Brillouin, L., Science and Information Theory, Academic Press, New
York, 1962.
Creutz,M., Microcanonical Monte Carlo simulation, Physical Review
Letters, vol. 50, no. 19, May 9, 1983, pp. 363-373.
Barnard, S., Stereo matching by hierarchical, microcanonical
annealing, SRI technical note 414 (to appear in Proc. IJCAI87).
------------------------------
Date: 13-APR-1987 15:46
From: SIMPSONP@COD.NOSC.MIL
Subject: ANS Survey Paper
[Forwarded from the Neuron Digest by Laws@STRIPE.SRI.COM.]
A Survey of Artificial Neural Systems
Patrick K. Simpson
Unisys
San Diego Systems Engineering Center
4455 Morena Boulevard
San Diego, CA 92117
619/483-0900
Abstract
This paper is a survey of the field of Artificial
Neural Systems (ANSs). ANSs have a large number of highly
interconnected processing elements that demonstrate the
ability to learn and generalize from presented patterns.
ANSs represent a possible solution to previously difficult
problems in areas such as speech processing and natural
language understanding. This paper presents a brief history
of ANSs, examples of ANS models and areas where the technol-
ogy has been applied. Also discussed is the connection
between Artificial Intelligence (AI) and ANS, computer
architectures that are evolving from this field, and two ANS
algorithms.
[Copies are available from simpson@cod.nosc.mil or the address
listed above - MTG]
------------------------------
Date: 3-APR-1987 14:46
From: @C.CS.CMU.EDU:JOSE@LATOUR.ARPA
Subject: Multilayer Connectionist Theory
[Forwarded from the Neuron Digest by Laws@STRIPE.SRI.COM.]
Knowledge Representation in Connectionist Networks
Stephen Jose Hanson and David J. Burr
Bell Communications Research
Morristown, New Jersey 07960
Abstract
Much of the recent activity in connectionist models stems
from two important innovations. First, a layer of
independent, modifiable units (hidden layer) that can model
the statistics of the domain and in turn perform significant
associative mapping between stimulus pairs. Second, a
learning rule that dynamically creates representation in the
hidden layer based upon constraints from a teacher
signal. Both Boltzmann machine and back-propagation models
share these two innovations and interestingly ones that
were apparently well known by Rosenblatt[14]. Although
presently, many complex perceptual and cognitive models
have been constructed using these methods the exact
computational nature of the networks in terms of their
clustering, partitioning, and generalization behavior is not
well understood.
In this paper we present a uniform view of the
computational power of multi-layered learning (MLL)
models. We show that MLL models represent knowledge by
applying Boolean combination rules to partition the problem
space into regions. A by-product of these rules is that
knowledge is represented as distributed patterns of
activation in the hidden layers. Their partitioning
capability is related to both the neural device model and
the network complexity in terms of numbers and layers of
neurons. The device model determines the shape of an
elementary boundary segment and the network determines how
to combine the segments into region boundaries.
For continuous problem spaces two hidden layers are
sufficient to form arbitrary regions (or Boolean functions)
in the space, and for binary-valued spaces a single layer
suffices. Finally we show that networks can produce
probabilistic combination rules which closely approximate
the Bayes risk.
You can get a copy of this paper by replying to this message
or writing to jose@bellcore or djb@bellcore, comments
appreciated.
------------------------------
End of AIList Digest
********************
∂23-Apr-87 1803 LAWS@Stripe.SRI.COM AIList Digest V5 #102
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 23 Apr 87 18:02:55 PDT
Date: Mon 20 Apr 1987 22:47-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #102
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 21 Apr 1987 Volume 5 : Issue 102
Today's Topics:
Seminars - Problems in Nonmonotonic Reasoning (MCC) &
Constraints, Planning, and Design (TI) &
Order-Sorted Unification (SRI) &
Conceptual Thinking for Restructuring and Insight (CMU) &
A Synthesis of Higher-Order Unification (CMU) &
Graphical Access to an Expert System (Rutgers) &
Reactive Learning (CMU) &
Equivalences of Logic Programs (Rutgers)
----------------------------------------------------------------------
Date: Tue 14 Apr 87 15:24:13-CDT
From: Charles Petrie <AI.PETRIE@MCC.COM>
Reply-to: Petrie@MCC
Subject: Seminar - Problems in Nonmonotonic Reasoning (MCC)
Michael Reinfrank
NML/RMS-Group, Dept. of CS, Univ. of Linkoeping
XPSLAB ZTI INF 31, SIEMENS AG, Munich
PROBLEMS IN NONMONOTONIC REASONING
MCC Auditorium
10:30 April 16
Nonmonotonic reasoning now has been a topic of interest for more than
fifteen years, although substantial research into its theoretical
foundations did not begin until the late seventies. Recently, some doubts
arose concerning the achievements in this field, in particular concerning
the question whether the techniques developed so far can solve those
problems they are intended to solve. A survey of the history of nonmonotonic
reasoning will be given and major unresolved issues in the current theories
identified.
------------------------------
Date: Wed, 15 Apr 87 13:27:12 cdt
From: "Michael T. Gately" <gately%resbld%ti-csl.csnet@RELAY.CS.NET>
Subject: Seminar - Constraints, Planning, and Design (TI)
From: NGSTL1::LINDAHL "Multihack -- lindahl%ngstl1@ti-eg.csnet"
From: TILDE::"BEF@HOME"
Texas Instruments Computer Science Center Lecture Series
CONSTRAINTS, PLANNING, AND DESIGN:
THERE IS A REASON FOR EVERYTHING UNDER THE SUN
PROF. DANIEL WEISE (STANFORD UNIVERSITY)
10:00 am, Friday, 1 May 1987
Semiconductor Building Main Auditorium
Every design decision has a set of rationales and a set of
ramifications. These ramifications affect other design decisions. I
believe that algorithms and expert systems fail for automatic design
synthesis because they do not explicitly reason about rationales or
ramifications. They also fail because they do not react to the design
being built. In this talk I will outline the problems of
automatically designing hardware, show why current approaches must
fail, and describe a new methodology, based on communicating
constraint based problem solvers, which might succeed.
BIOGRAPHY
Daniel Weise received both his Masters and Ph.D. degrees at the MIT
Artificial Intelligence Laboratory. He did his dissertation on
verifying MOS circuits. He is now an assistant professor at Stanford
University working on design automation and silicon compilation.
----------------------------------------------------------------------
The lecture will be given in the Semiconductor Building Main
Auditorium at the Dallas Expressway site. Visitors to TI should
contact Dr. Bruce Flinchbaugh (214-995-0349) in advance and meet in
the north entrance lobby of the Semiconductor Building by 9:45am.
------------------------------
Date: Thu, 16 Apr 87 10:27:48 PDT
From: lunt@april.csl.sri.com (Teresa Lunt)
Subject: Seminar - Order-Sorted Unification (SRI)
ORDER-SORTED UNIFICATION
Jose Meseguer
SRI International Computer Science Laboratory
Monday, April 27 at 4:00 pm
SRI International, Computer Science Laboratory, BN182
Jose Meseguer will speak on his work with Joseph Goguen of
SRI International and Gert Smolka of Universitat Kaiserslautern.
Order-sorted logic is the logic of multiple inheritance and
overloading polymorphism. It provides a rich type theory
that permits easy and natural expression of many problems in
knowledge representation, natural language processing,
theorem proving, etc. Order-sorted logic is also the basis
for the logical languages OBJ3 and Eqlog. Despite its
considerable expressive power, all the usual results of
equational and first-order logic generalize to order-sorted
logic. The present work develops a general theory of
order-sorted E-unification, and characterizes the cases
where there is a minimal family of unifiers, a finite family
of unifiers, and a unique most general unifier. The latter
case has a simple syntactic characterization and also a
quasi-linear unification algorithm a la Martelli-Montanari
that is in fact more efficient than ordinary unification,
due to its type-checking.
------------------------------
Date: 16 Apr 1987 1049-EDT
From: Elaine Atkinson <EDA@C.CS.CMU.EDU>
Subject: Seminar - Conceptual Thinking for Restructuring and Insight
(CMU)
SPEAKER: Dr. Stellan Ohlsson, LRDC, University of Pittsburgh
TITLE: "A theory of conceptual thinking applied to the phenomena of
restructuring and insight"
DATE: Tuesday, April 21
TIME: 12:00 - 1:20 p.m.
PLACE: Adamson Wing, Baker Hall
ABSTRACT: Current theories of problem solving focus on the nature and function
of problem solving strategies. However, novel problems cannot, by definition,
be solved by applying a pre-existing strategy; rather, they are solved by
trying to understand the problem situation, a process to be called "conceptual
thinking". According to studies by the Gestalt psychologists, conceptual
thinking exhibits the phenomena of restructuring and insight. A first
approximation theory of restructuring and insight and some relevant data
will be discussed.
------------------------------
Date: 15 Apr 87 10:08:23 EDT
From: Conal.Elliott@theory.cs.cmu.edu
Subject: Seminar - A Synthesis of Higher-Order Unification (CMU)
Area Qualifier Talk
Speaker: Conal Elliott
Date: April 21
Time: 10:00-11:30
Place: WeH 7220
Topic: A Synthesis of Higher-Order Unification
Program synthesis is the derivation of implementations from noneffective
specifications.
Higher-order unification is unification in the typed lambda calculus with
alpha, beta, and eta conversion. It has been used in
- program manipulation,
- theorem proving in higher-order logic,
- logic programming, and
- mechanizing natural deduction.
In this talk, we
- give a new, useful conceptualization of the unification problem,
- synthesize a family of ``pre-algorithms'' for unification, unifiablity,
matching, matchability, with some efficiency improvements, and
- present a new synthesis methodology, which may be viewed as a new
interpretation, justification, and generalization of Burstall &
Darlington's methodology.
------------------------------
Date: 16 Apr 87 14:14:26 EDT
From: KALANTARI@RED.RUTGERS.EDU
Subject: Seminar - Graphical Access to an Expert System (Rutgers)
RUTGERS COMPUTER SCIENCE COLLOQUIUM SCHEDULE - SPRING 1987
DATE: Thursday, April 23, 1987
SPEAKER: Ted Shortliffe
AFFILIATION:
Visiting Professor of Computer and Information Science
University of Pennsylvania
and
Associate Professor of Medicine and Computer Science
Medical Computer Science Group
Knowledge Systems Laboratory
Stanford Medical School
TITLE: GRAPHICAL ACCESS TO AN EXPERT SYSTEM: THE EVOLUTION OF THE ONCOCIN
PROJECT
TIME: 2:50 (Coffee and Cookies will be setup at 2:30)
PLACE: Hill Center, Room 705
ABSTRACT
The research goals of Stanford's Medical Computer Science group are directed
both toward the basic science of artificial intelligence and toward the
development of clinically useful consultation tools. Our approach has been
eclectic, drawing on fields such as decision analysis, interactive graphics,
and both qualitative and probabilistic simulation as well as AI. In this
presentation I will discuss ONCOCIN, an advice system designed to suggest
optimal therapy for patients undergoing cancer treatment, as well as to
assist in the data management tasks required to support research treatment
plans (protocols). A prototype version, developed in Interlisp and SAIL
on a DEC-20, was used between May 1981 and May 1985 by oncology faculty and
fellows in the Debbie Probst Oncology Day Care Center at the Stanford
University Medical Center. In recent years, however, we have spent much
of our time reimplementing ONCOCIN to run on Xerox 1100 series workstations
and to take advantage of the graphics environment provided on those
machines. The physician's interface has been redesigned to approximate the
appearance and functionality of the paper forms traditionally used for
recording patient status. The Lisp machine version of ONCOCIN was introduced
for use by Stanford physicians earlier this year.
In response to the need for an improved method for entering and maintaining
the rapidly expanding ONCOCIN protocol knowledge base, we have also developed
a graphical knowledge acquisition environment known as OPAL. This system
allows expert oncologists to directly enter their knowledge of protocol-
directed cancer therapy using graphics-based forms developed in the
Interlisp-D environment. The development of OPAL's graphical interface led
to a new understanding of the natural structure of knowledge in this domain.
ONCOCIN's knowledge representation was accordingly redesigned for the Lisp
machine environment. This has involved adopting an object-centered knowledge
base design which has provided an increase in the speed of the program while
providing more flexible access to system knowledge.
------------------------------
Date: 17 Apr 87 15:59:21 EDT
From: Patricia.Mackiewicz@isl1.ri.cmu.edu
Subject: Seminar - Reactive Learning (CMU)
TOPIC: Reactive Learning: Experimentation and Decompilation
SPEAKER: Jaime Carbonell, CMU
WHEN: Tuesday, April 21, 1987, 3:30 p.m.
WHERE: Wean Hall 5409
Most symbolic learning approaches have been purely empirical (inductive)
or purely analytical. The former extracts a general concept from a set of
empirical observations, whereas the latter composes primitive concepts
into larger units (chunks, macro-operators, "explanations", etc.).
Analytical methods include explanation-based learning, capable of
exploiting a complete domain theory to learn complex concepts from very few
instances. However, the domain theory may be partial, and judicious
integration of empirical and analytical methods may prove far superior
to either method alone. Reactive experimentation is a case in point:
partial domain knowledge is used to formulate hypotheses, and empirical
data from the experiments is used to formulate new concepts or modify
existing ones. Decompilation maps complex empirical observations into
comprehensible operational units using analytical techniques. Both
methods for combining analytical and empirical approaches are
explored with the objective of creating robust learning systems.
------------------------------
Date: 19 Apr 87 04:18:08 EDT
From: KALANTARI@RED.RUTGERS.EDU
Subject: Seminar - Equivalences of Logic Programs (Rutgers)
SPECIAL RUTGERS COMPUTER SCIENCE COLLOQUIUM
DATE : Tuesday, April 21st
SPEAKER: Michael J. Maher
TITLE: Equivalences of Logic Programs
AFFILIATION: IBM T.J. Watson Center
TIME: 1:30 pm
PLACE: Hill 423
One of the most important relationships between programs in any
programming language is the equivalence of such programs. This
relationship is at the basis of most, if not all, programming
methodologies. This talk provides a systematic comparison of
the relative strengths of various formulations of equivalence
for logic programs. These formulations arise naturally from
several well-known formal semantics. These comparisons are
useful in reasoning about program behavior, verification of
correctness and termination of programs, the correctness of ad
hoc source-to-source transformations such as occur in program
development, and, at a more abstract level, the establishment of
the correctness and other properties of automated transformation
systems which can be used both in program development and as a
pre-compilation optimization.
---------------------------------------------------------------------------
DATE : Friday, April 24
SPEAKER: Dr. Susan Epstein
TITLE: An Introduction to GT, the Graph Theorist
AFFILIATION: Hunter College (CUNY)
TIME: 1:30 (Coffee and Cookies will be setup after the talk at 2:30)
PLACE: Hill 705
ABSTRACT
GT, the Graph Theorist, is a knowledge-intensive, domain-specific
learning system which uses algorithmic class descriptions to
discover new mathematical concepts and relations among them.
GT is based upon a set of powerful
representation languages for object classes. The definition of a graph theory
concept is an expression in one of these languages.
GT generates correct examples of any of its concepts, constructs new
concepts, and conjectures and proves relations among concepts. Beginning
from only the concept of "graph," GT has developed its own version of graph
theory and discovered such concepts as "tree," "acyclic," "connected,"
and "bipartite." GT has also conjectured and then proved such theorems as
"The set of acyclic, connected graphs is precisely the set of trees" and
"There is no odd-regular graph on an odd number of vertices."
This talk presents initial results and outlines the theoretical
foundations for this work.
------------------------------
End of AIList Digest
********************
∂23-Apr-87 2044 LAWS@Stripe.SRI.COM AIList Digest V5 #103
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 23 Apr 87 20:44:40 PDT
Date: Mon 20 Apr 1987 22:51-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #103
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 21 Apr 1987 Volume 5 : Issue 103
Today's Topics:
Conferences - A typo and an addition to the MAICSS schedule &
Theoretical Aspects of Reasoning about Knowledge &
Third Institute, UT Year of Programming &
Second Workshop on Large Grained Parallelism
----------------------------------------------------------------------
Date: Fri, 17 Apr 87 13:05:26 cdt
From: Kris Hammond <kris@ANUBIS.UCHICAGO.EDU>
Subject: Conference - A typo and an addition to the MAICSS schedule
A slight change of venue for the MAICSS conference and an additional
speaker -
The First Annual Meeting
of
The Midwest Artificial Intelligence and Cognitive
Science Society
The University of Chicago
April 24th and 25th
----> Ryerson 251
----> 1100 58th Street
----> Chicago, Illinois
Also, Professor Larry Travis will be giving an overview talk on the AI
work at the University of Wisonsin.
And, if you haven't called us yet, do so now. (312) 702-8070.
Kris Hammond
CS Department
University of Chicago
------------------------------
Date: 17 April 87 14:41-PDT
From: VARDI%ALMVMA.BITNET@wiscvm.wisc.edu
Subject: Conference - Theoretical Aspects of Reasoning about Knowledge
Call for Papers
The Second Conference on
THEORETICAL ASPECTS OF REASONING ABOUT KNOWLEDGE
March 6-9, 1988, Monterey, California
The 2nd Conference on Theoretical Aspects of Reasoning about
Knowledge, sponsored by the International Business Machines
Corporation and the American Association for Artificial
Intelligence, will be held March 6-9, 1988, at the Asilomar
Conference Center in Monterey, California. While traditionally
research in this area was mainly done by philosophers and
linguists, reasoning about knowledge has been shown recently to
be of great relevance to computer science and economics. The aim
of the conference is to bring together researchers from these
various disciplines with the intent of furthering our theoretical
understanding of reasoning about knowledge.
Some suggested, although not exclusive, topics of interest are:
Semantic models for knowledge and belief
Resource-bounded reasoning
Minimal knowledge proof systems
Analyzing distributed systems via knowledge
Knowledge acquisition and learning
Knowledge and commonsense reasoning
Knowledge, planning, and action
Knowledge in economic models
You are invited to submit ten copies of a detailed abstract (not
a complete paper) to the program chair:
Moshe Y. Vardi
IBM Research
Almaden Research Center K53-802
650 Harry Rd.
San Jose, CA 95120-6099, USA
Telephone: (408) 927-1784
Electronic address: vardi@ibm.com, vardi@almvma.bitnet
Submissions will be evaluated on the basis of significance,
originality, and overall quality. Each abstract should 1)
contain enough information to enable the program committee to
identify the main contribution of the work; 2) explain the
importance of the work - its novelty and its practical or
theoretical implications; and 3) include comparisons with and
references to relevant literature. Abstracts should be no longer
than ten double-spaced pages.
Program Committee:
J. Barwise (Stanford University)
P. van Emde Boas (University of Amsterdam)
H. Kamp (University of Texas at Austin)
K. Konolige (SRI International)
Y. Moses (Weizmann Institute of Science)
S. Rosenschein (SRI International)
T. Tan (University of Chicago)
M. Vardi (IBM Almaden Research Center)
The deadline for submission of abstracts is August 31, 1987.
Authors will be notified of acceptance by November 1, 1987
(authors who supply an electronic address might be notified
earlier). The accepted papers will be due by December 15, 1987.
Proceedings will be distributed at the conference, and will be
subsequently available for purchase through the publisher.
We hope to allow enough time between the talks for private
discussions and small group meetings. In order to ensure that
the conference remains relatively small, attendance will be
limited to invited participants and authors of accepted papers.
Support for the conference has been received from IBM and AAAI
for partial subsidy of participants' expenses; applications for
further support are pending.
------------------------------
Date: Wed 1 Apr 87 16:38:24-CST
From: Hamilton Richards <CS.HAM@R20.UTEXAS.EDU>
Subject: Conference - Third Institute, UT Year of Programming
Preliminary Announcement
The 1987 UT Year of Programming
with the support of the
U. S. Office of Naval Research
announces
The Institute on Logical Foundations of Functional Programming
Scientific Director: Dr. Gerard Huet, INRIA
Austin, Texas
8-12 June 1987
There is a growing realization that mathematical logic provides a foundation on
which programming languages and environments for software engineering can be
soundly based. Such a foundation should include a highly expressive notation
for formalisation of requirements, an efficiently implementable language for
coding programs, and a means of systematically deriving each program from its
specification, together with such proofs of correctness as are needed.
This Institute concentrates on a particularly simple paradigm. The type
verification rules of a programming language such as PASCAL or ADA may be
seen as a logical inference system. The rules of inference can be extended in
a uniform manner to check the validity of a program with respect to more
general formalized comments, assertions, and specifications. A powerful
constructive logic may thus be considered as the backbone of a pure, strongly
typed, functional programming language. We may thus envision programming
environments for such languages in which programs are designed consistently
with formal specifications. In such a system, a well-typed program serves as
its own proof of correctness, which may be checked by type-checking throughout
the period of program development. There is hope that in the future some of
the more routine parts of programs can be generated with machine assistance.
This approach to software engineering is currently the subject of much
speculation and research, involving both theory and practical implementation.
One of the leading research projects is Project Formel, which is jointly
sponsored by INRIA (Rocquencourt, France) and Ecole Normale Superieure (Paris)
and led by Dr. Gerard Huet of INRIA and Prof. Guy Cousineau of ENS. The Year
of Programming has invited Dr. Huet and his senior colleagues to present
their work in the Institute on the Foundations of Functional Programming.
The first three days of the Institute will be a tutorial on type theory,
functional programming, and their relationship to one another. It will prepare
students with some background in theoretical computer science for the more
advanced Research Seminar on Thursday and Friday, at which presentations will
be made of research in progress in several countries around the world.
The tutorial on functional programming and type theory will present a unified
view of computational structures described by categorical combinators. These
combinators may be seen as proof combinators from a sequent formulation of
intuitionistic logic, or alternatively as the building blocks of an
environment-manipulating machine well suited for executing lambda-calculus and
other functional programming languages. This introduces the Categorical
Abstract Machine (CAM) (a simplification of Landin's SECD machine) for
executing call-by-value lambda-calculus. The language CAML (Categorical
Abstract Machine Language) is closely derived from languages such as ML and
Hope. The compilation of CAML on the CAM will be discussed and compared with
related projects (ML on the FAM and the G-machine, Amber on the Amber machine).
Polymorphic types and the problems of type synthesis will be discussed at two
levels: ML's parametric polymorphism, and full polymorphism in Girard's
second-order lambda-calculus. A very general logical framework, the Calculus
of Constructions, will be described. It will be shown how this formalism
combines the expressive power of Girard's higher-order polymorphic
lambda-calculus, Martin-Lof's theory of types, and de Bruijn's AUTOMATH. The
tutorial will be taught by Prof. Cousineau and Dr. Huet, the scientific leaders
of Project Formel where CAM, CAML, and the Calculus of Constructions have
been designed and implemented. An implementation of CAML on SUN workstations
will be available for demonstrations and practical exercise sessions.
The Research Seminar will present research topics in Linear Logic and
Constructive Semantics. Linear Logic, a new formalism designed to serve as a
logical foundation for parallel programming, will be presented by its inventor,
Prof. Jean-Yves Girard, Groupe de Logique Mathematique, Universite Paris 7.
Under the general title of Constructive Semantics, recent research in Type
Theory under way at various centres in the USA and in Japan will be presented
by four research leaders in the field: Prof. Albert Meyer (MIT), Dr. John
Mitchell (AT&T Bell Laboratories), Dr. Susumu Hayashi (RIMS, Kyoto University),
and Prof. Andre Scedrov (U. of Pennsylvania). The Seminar program will be
augmented by short communications of research work in progress by the seminar
participants.
It is recommended that potential participants in the seminar register early.
In order to facilitate interaction, the number of participants will be limited.
Tentative schedule.
1. Tutorial on Functional Programming and Type Theory (June 8-10)
Monday.
8-10 Elements of category theory (GH)
10-12 Introduction to the ML language (GC)
2-4 A tutorial on lambda-calculus (GH)
4-5 Programming session: CAML
Tuesday.
8-10 Polymorphic type-checking (GC)
10-12 Natural deduction, the Propositions as Types principle (GH)
2-4 The Categorical Abstract Machine (GC)
4-5 Programming session: CAM
Wednesday.
8-10 The polymorphic lambda-calculus (GH)
10-12 Compiling functional languages; CAML Implementation (GC)
2-4 Type theory, the Calculus of Constructions (GH)
4-5 Programming session: Constructions
2. Research Seminar on Linear Logic and Constructive Semantics (June 11-12)
Thursday.
8-12 Qualitative domains, Coherent spaces. (J.Y. Girard)
2-330 Guest Lecture 1 (A. Meyer)
330-5 Guest Lecture 2 (J. Mitchell)
Friday.
8-12 Linear Logic. (J.Y. Girard)
2-330 Guest Lecture 3 (S. Hayashi)
330-5 Guest Lecture 4 (A. Scedrov)
Prerequisites: same as for graduate-level course in theoretical computer
science; programming experience is recommended.
Recommended readings:
G. Cousineau, P.L. Curien and B. Robinet, eds., Combinators and Functional
Programming Languages. Springer-Verlag, Lecture Notes in Computer Science 242,
1986.
L. Cardelli and P. Wegner. "On Understanding Types, Data abstraction, and
Polymorphism". ACM Computing Surveys 17, 4 (Dec. 1985): 471-522.
J. R. Hindley and J. P. Seldin. Introduction to combinatory logic and lambda
calculus. Cambridge University Press, 1986.
H. Abelson and G. J. Sussman. Structure and Interpretation of Computer
Programs. MIT Press 1985.
J. Lambek and P. J. Scott. Introduction to higher order categorical logic.
Cambridge University Press, 1986.
The U. T. Year of Programming
The Institute on Logical Foundations of Functional Programming is the third in
a series of Programming Institutes comprising the 1987 U. T. Year of
Programming, which is underwritten principally by the U.S. Office of Naval
Research, with supplementary funding from the University of Texas, Lockheed
Missiles and Space Company, and other sponsors. The other Institutes in the
series are:
Concurrent Programming (23 February - 6 March)
C.A.R. Hoare (Texas and Oxford)
Encapsulation, Modularization, and Reusability (1-10 April)
D. Gries (Cornell)
Formal Specification and Verification of Hardware (29 June - 3 July)
M.J.C. Gordon (Cambridge)
Declarative Programming (24-29 August ) D.A. Turner (Kent)
Specification and Design (14-25 September) J.R. Abrial (Paris)
Formal Development of Programs and Proofs (autumn) E.W. Dijkstra (Texas)
FOR FURTHER INFORMATION
To receive announcements and application forms for individual Programming
Institutes (this one or any of the others), please contact the Year of
Programming Office at one of the following addresses:
U. T. Year of Programming INTERNET: cs.ham@R20.UTEXAS.EDU
Department of Computer Sciences INTERNET: ham@SALLY.UTEXAS.EDU
Taylor Hall 2.124
The University of Texas at Austin telephone: 512-471-9526
Austin, Texas 78712-1188
------------------------------
Date: Friday, 17 April 1987 10:18:22 EST
From: Mario.Barbacci@sei.cmu.edu
Subject: Conference - Second Workshop on Large Grained Parallelism
PRELIMINARY CALL FOR ABSTRACTS
SECOND WORKSHOP ON LARGE GRAINED PARALLELISM
OCTOBER 11-14, 1987
HIDDEN VALLEY, PENNSYLVANIA
Organized by the Software Engineering Institute and the Department of
Computer Science, Carnegie Mellon University, with the cooperation of
the Computer Society of the IEEE (pending approval).
The Second Workshop on Large Grained Parallelism is being organized to
bring together researchers in the areas of programming languages,
methodologies, and formalisms for loosely-coupled computer
networks, and developers of applications who would benefit from such
work. Issues of interest within these areas include, but are not limited
to, performance, fault tolerance, real-time execution, and heterogeneity of
the environment.
Attendance is by invitation only. Researchers interested in participating
must submit five (5) copies of a short (1 or 2 pages long) abstract
describing their activities in the areas of interest outlined above.
The workshop technical sessions will consist of a combination of
formal presentations, panel sessions, and working group meetings. Only a
subset of the participants will address the audience in the formal
sessions. All of the abstracts will be published as conference
proceedings and will be available to the participants upon arrival. The
participants will have the option of submitting a revised version
of their abstracts a few weeks prior to the meeting.
Submit abstracts to: Relevant dates:
Professor Jeannette M. Wing Deadline for Abstracts: July 15, 1987
Department of Computer Science Invitation to Authors: August 14, 1987
Carnegie Mellon University Deadline for Registration and
Pittsburgh, PA 15213-3890 Revised Abstracts: September 11, 1987
Telephone: (412) 268-3068
ArpaNet: WING@K.CS.CMU.EDU
Workshop Committee: Mario Barbacci (Carnegie Mellon University),
Maurice Herlihy (Carnegie Mellon University), Paul Leach (Apollo
Computer), Jack Stankovic (University of Massachusetts), and Jeannette Wing
(Carnegie Mellon University)
Location: The Hidden Valley Resort Community and Conference Center is
located in the scenic Allegheny mountains, 60 miles east of Pittsburgh, and
is easily reachable via the Pennsylvania Turnpike.
The Software Engineering Institute is a Federally Funded Research and
Development Center, sponsored by the Department of Defense.
------------------------------
End of AIList Digest
********************
∂23-Apr-87 2309 LAWS@Stripe.SRI.COM AIList Digest V5 #104
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 23 Apr 87 23:09:05 PDT
Date: Mon 20 Apr 1987 22:57-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #104
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 21 Apr 1987 Volume 5 : Issue 104
Today's Topics:
Conference - The Brain: Philosophy, Neurology, and AI
----------------------------------------------------------------------
Date: Sat, 11 Apr 87 14:32:14 PDT
From: Kenneth Schaffner <SCHAFFNER@SUMEX-AIM.STANFORD.EDU>
Subject: Conference - The Brain: Philosophy, Neurology, and AI
Bruce Buchanan suggested that I send you the following for posting on the AI
LIST Bulletin Board. If you have any questions, you may contact me at
SCAHFFNER@SUMEX-AIM.ARPA, though inquiries about the Conference should go to
the Special Events Office as listed below. Thanks.
---Ken Schaffner
A CONFERENCE ON
THE BRAIN: PHILOSOPHY, NEUROLOGY, AND ARTIFICIAL INTELLIGENCE
In Commemoration of the Bicentennial of the University of
Pittsburgh and the Centennial of the School of Medicine
The nature of the relationship of the mind to the human brain and the
process by which thinking occurs have been perennial philosophical problems.
Attempts to understand these issues through the centuries have progressively
involved new sciences and new ways of approaching these classic questions.
Psychology, neurology, and the neurosciences are relatively new recruits to
the interdisciplinary company whose mission is to comprehend the mind and
the brain, and they have been even more recently joined by computer science
and artificial intelligence.
The past five years has seen the rapid emergence of a revolutionary
computational framework which suggests a new and exciting approach to mind-
brain relations and to thought itself. This approach, which goes by the
various names of "connectionism," "parallel distributed processing," and
"neural network theory" has been described as a paradigm shift in the
cognitive sciences. Problems in perception, memory, language, and thought
that were recalcitrant to previous approaches have yielded startling
solutions when pursued from the perspective of connectionism. This new
viewpoint, which adopts an explicitly parallel architecture on which to base
its models, is also consistent with developments occurring in the design of
so called "supercomputers." Both connectionism and supercomputer design
studies are critical of traditional "von Neumann style" computer
architecture and processing, and have proposed novel human brain-like models
which already offer extraordinary promise in the areas of speech recognition
and pattern detection.
This Conference, which is being held as part of the celebration of the
University of Pittsburgh's bicentennial and its School of Medicine's
centennial, is designed to critically examine this developing revolution in
our comprehension of thought and the brain from an interdisciplinary
perspective. The implications of the revolution for our understanding of
consciousness, learning, memory, language, and knowledge in general will be
examined by psychologists, computer scientists, physicians, and
philosophers. The extent to which neurological data and theories can suggest
novel directions for both psychological and computer-based research, and
vice versa, will be a recurrent theme of the Conference. Possible though as
yet futuristic therapeutic implications such as partial brain reconstitution
with the aid of "neural chips" will be considered. Ethical and legal issues
associated with both current brain research and such possible futuristic
advances will be examined as well.
The Conference brings together a group of scholars who have
collectively had a phenomenal impact on our current understanding of the
mind and its relations to the brain. Dr. Minsky who will lead off the
Conference with a Keynote address is generally recognized as the preeminent
theoretician of artificial intelligence and its application to theories of
the mind. Drs. Rumelhart and McClelland are cognitive psychologists whose
recently edited two volume collection of papers on Parallel distributed
Processing is already recognized as the "bible" of connectionism. Dr. Joynt
is a distinguished neurologist who brings extensive clinical experience to
the Conference's interdisciplinary subject matter. Drs. Paul and Patricia
Churchland, Dennett, and Haugland are all nationally recognized philosophers
of science and of mind who have made major contributions to these areas. Dr.
Hinton has been one of the major developers of parallel distributed
processing theory, and Dr. Reggia is a neurologist and computer scientist
who has developed pioneering applications of neurological data to artificial
intelligence models of the brain. Dr. Miller is a nationally prominent
medical ethicist, and Prof. Meisel is a leading figure in both health law
and bioethics. These major speakers will also be joined by nationally
prominent University of Pittsburgh faculty from philosophy, psychology,
neuroscience, neurology, neurosurgery, and computer science who will serve
as commentators on the Conference material.
PROGRAM
THE BRAIN: PHILOSOPHY, NEUROLOGY, AND ARTIFICIAL INTELLIGENCE
ALL SESSIONS WILL BE HELD IN THE WESTERN PSYCHIATRIC INSTITUTE AND CLINIC
AUDITORIUM, 2ND FLOOR, 3811 O'HARA STREET, UNIVERSITY OF PITTSBURGH
Tuesday, May 5, 1987:
8:30 a.m. REGISTRATION
Morning - Session I
9:00 a.m. INTRODUCTION....................Thomas Detre, M.D.
Senior Vice President for Health
Sciences, University of
Pittsburgh
WELCOME.........................Wesley W. Posvar, Ph.D.
President
University of Pittsburgh
9:15 a.m. INTRODUCTION TO THEMES..........Kenneth F. Schaffner, M.D.,Ph.D.
Professor, Department of History
and Philosophy of Science
9:30 a.m. Keynote address:
THE SOCIETY OF MIND..............Marvin Minsky, Ph.D.
Donner Professor of Science
Department of Electrical
Engineering
and Computer Science
Massachusetts Institute of
Technology
10:30 a.m. Coffee Break
10:45 a.m. PARALLEL DISTRIBUTED
PROCESSING IN COGNITIVE
SCIENCE..........................David Rumelhart, Ph.D.
Co-Director, Institute of
Cognitive Science
University of California,
San Diego
Afternoon - SESSION II:
Chairperson - John Moossy, M.D.
Professor of Pathology and Neurology
Chief, Division of Neuropathology
University of Pittsburgh
1:00 p.m. REPRESENTATION AND COMPUTATION:
BIOLOGICAL VARIETIES AND
PHILOSOPHICAL CONSEQUENCES........Paul Churchland, Ph.D.
Professor
Department of Philosophy
and Cognitive Science Program
University of California,
San Diego
2:00 p.m. THINKING ABOUT THINKING...........Robert J. Joynt, M.D., Ph.D.
Dean and Vice-President
Professor of Neurology
University of Rochester
School of Medicine and
Dentistry
3:30 p.m. Coffee Break
3:45 p.m. HUMAN CONSCIOUSNESS AS A VIRTUAL
VON NEUMANN MACHINE...............Daniel Dennett, Ph.D.
Director, Center for
Cognitive Studies
Tufts University
4:45 p.m. General Discussion
5:15 p.m. Adjournment
6:00 p.m. Cocktails (location to be announced)
Wednesday, May 6, 1987
Morning - Session III
Chairperson - S.K. Chang, Ph.D.
Chairperson, Computer Science Department
University of Pittsburgh
9:00 a.m. LEARNING REPRESENTATIONS IN
A PARALLEL NETWORK................Geoffrey Hinton, Ph.D.
Associate Professor
Department of Computer
Science
Carnegie-Mellon University
9:45 a.m. UNDERSTANDING NATURAL LANGUAGE
THROUGH PARALLEL DISTRIBUTED
PROCESSING........................James. L. McClelland, Ph.D.
Professor
Department of Psychology
Carnegie-Mellon University
10:30 a.m. COOPERATION THROUGH COMPETITION
IN ASSOCIATED MEMORY MODELS.......James Reggia, M.D., Ph.D.
Departments of Neurology
and Computer Science
University of Maryland
11:15 a.m. Coffee Break
11:30 a.m. UNIVERSITY OF PITTSBURGH PANEL DISCUSSION
Panelists:
Gordon Banks, M.D., Ph.D.(Neurology)
Eric Frank, Ph.D.(Neurobiology, Anatomy and Cell Science)
Alan Lesgold, Ph.D.(Psychology)
Harry E. Pople, Ph.D. (Decision Systems Laboratory)
John Vries, M.D. (Neurosurgery)
Richmond Thomason, Ph.D. (Linguistics and Philosophy)
Afternoon - Session IV
Chairperson Kurt Baier, D. Phil.
Distinguished Service Professor of Philosophy
University of Pittsburgh
1:30 p.m. KNOWLEDGE, BENEFITS, AND RIGHTS:
ETHICAL ISSUES IN BRAIN RESEARCH..Bruce Miller, Ph.D.
Professor and Chairman
Department of Philosophy
Michigan State University
2:15 p.m. ON THE OBLIGATION TO "VOLUNTEER"
FOR BRAIN RESEARCH................Alan Meisel, J.D.
Professor of Law
and Psychiatry
University of Pittsburgh
3:00 p.m. Coffee Break
3:15 p.m. EPISTEMOLOGY IN THE AGE OF
NEUROSCIENCE.....................Patricia Churchland, Ph.D.
Professor of Philosophy
and Cognitive Science Program
University of California,
San Diego
4:00 p.m. TWO MODELS OF INTELLIGENCE.......John Haugeland, Ph.D.
Professor
Department of Philosophy
University of Pittsburgh
5:00 p.m. Adjournment
All individuals who wish to attend should register for the Conference.
There is no Registration Fee for the Conference, but a form containing
the following information should be received by the University of Pittsburgh
Health Sciences Office of Special Events, M-211 Scaife Hall, Pittsburgh PA
15261, no later than April 20th, 1987. Space is limited and early registration
is advised. A block of rooms has been reserved for registrants at the
University Inn in the Oakland section near the University of Pittsburgh;
telephone 800-245-6675 (in Pennsylvania 800-242-1498). When registering,
please identify yourself as being with this Conference. For individuals
attending the Conference, a 20% reduced air fare is available from U.S.
Air; contact the Special Events Office below for information. This Conference
meets the criteria for twelve credit hours in Category 1 of the Physician's
Recognition Award of the American Medical Association. (1.2 CEUs are awarded
to health professionals.)
REGISTRATION FORM:
(Please Print)
Name: Degree:
Office Address:
Home Address:
Telephone: (Home) (Office)
Affiliation:
For further information contact the Special Events Office: (412) 648-9006.
------------------------------
End of AIList Digest
********************
∂24-Apr-87 0809 LAWS@Stripe.SRI.COM AIList Digest V5 #105
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 24 Apr 87 08:08:45 PDT
Date: Tue 21 Apr 1987 21:03-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #105
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 22 Apr 1987 Volume 5 : Issue 105
Today's Topics:
Bibliography - Leff ai.bib52AB
----------------------------------------------------------------------
Date: Sat, 11 Apr 1987 20:43 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: ai.bib52AB
%A Luis Pastor
%A Jose Maria Sebastian
%T A Least-Squares Algorithm for Interframe Displacement Estimation.
Application to Stereo Vision
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 101-108
%K O06 AI06
%X ISBN 0931215129
%A Zhong-Rong Li
%A Da-peng Zhang
%T An Intelligent Vision System for Robot
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 119-128
%K AA27 AI07 AI06 satellite landsat geosensing
%X ISBN 0931215129
.br
br
Describes having a satellite for landsat type applications only send relevant
material rather than transmit all the data for the purpose of reducing use
of bandwidth in communication between ground and satellite.
The proposed system uses region growing as well as a variety of convolution
operators as well as special purpose hardware. The system achieved 97%
accuracy in recognition of type of area (farmfield, mountain, shadow, etc.)
%A K. K. Ong
%A R. E. Seviora
%A P. Dasiewicz
%T Knowledge-Based Position Estimation for a Multisensor House Robot
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 119-130
%K AI06 AI07 AA19 blackboard
%X ISBN 0931215129
.br
br
A Hero-I robot containing a cheap light sensor and a sonar sensor was
interfaced to an IBM-PC containing a Hearsay-like system for determining
which room the robot was in. This system achieved an 87% success rate.
%A W. L. Whitaker
%A B. Motazed
%T Interpretation of Pipe Networks by Magnetic Sensing
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 131-139
%K AA05 AI06
%X ISBN 0931215129
.br
br
Describes system to interpret magnetic sensor readings for such as
evaluating the position of iron reinforcements within concrete
and locating underground pipes.
%A W. T. Keirouz
%A D. R. Rehak
%A I. J. Oppenheim
%T Object-Oriented Domain Modelling of Constructed Facilities for Robotic
Operations
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 141-150
%K AI07 AI16 AA05
%X ISBN 0931215129
.br
br
describes goals and methods for organizing data structures to manage
robots in a construction site.
%A Nancy E. Orlando
%T Interfacing Intelligent Software to Robotic Peripherals
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 151-162
%K AA10 AA27 AI07 satellite Langley
%X ISBN 0931215129
.br
br
draws analogies between animal behavior and robotic systems. Also discusses
research at Nasa Langley Research Center which include simulation systems
and attempts to get robots to perform removal and replacement of a module
on a satellite as well as refueling of satellites.
%A Michel Bidoit
%A Francesca Losavia
%T Automatic Programming Techniques Applied to Software Development An
Approach Based on Exception Handling
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 165-178
%K AA08 digital telephony
%X ISBN 0931215129
.br
br
Describes a system for generation of ADA program in telephony systems.
%A Hirooaki Saito
%A Masaru Tomita
%T On Automatic Composition of Stereotypic Documents in Foreign Languages
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 179-192
%K AI02
%X ISBN 0931215129
.br
br
Describes a system that will take input for various standard situations
such as a move and prepare a letter in the appropriate language including
all politeness type sentences appropriate for the target language.
%A Meng Li-Ming
%T Natural Language Interface to Relational Data Base Systems
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 193-200
%K AI02 AA09
%X ISBN 0931215129
.br
br
Description of the overall architecture of a system that they built.
%A J. Korn
%A J. D. Cumbers
%A F. Huss
%T Computer Aided Systems Modelling
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 202-213
%K AI02 T02
%X ISBN 0931215129
.br
br
discusses the design of a system to read text with an example given
from an newspaper article about the sale of public woodlands to private
investors in Britain.
%A Kingsley Harrop-Williams
%T Artificial Intelligence in Soil Exploration
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 229-237
%K AA05 AI04 O04 AI06
%X ISBN 0931215129
.br
br
This system interprets cone penetrometer data in a geotechnical survey.
It uses learning techniques and interprets information as readings
are taken so as to allow decisions on which readings to take next to be
influenced by the interpretation of those already taken in the past.
Pattern recognition techniques are used to separate the M soil types
from the observed measurement vectors and fuzzy techniques are used
to represent various beliefs about the characteristics of the site.
%A Rense Lange
%T Stat: A Probabilistic Knowledge Based Induction Program for Building
Expert Systems
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 239-246
%K AI04 AI01
%X ISBN 0931215129
.br
br
Describes a clustering system of the Michalski type with applications
to expert systems.
%A Felix S. Wong
%A Weimin Dong
%T Fuzzy Information Processing in Engineering Analysis
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 247-260
%K O04 AI01 AA05 AT08
%X ISBN 0931215129
.br
br
discussion of fuzzy logic techniques
%A John J. Granacki
%A Alice C. Parker
%T A Natural Language Interface for Specifying Digital Systems
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 215-226
%K AA04 AI02
%X an interface to the VLSI design system ADAM using Conceptual
Dependencies. New Conceptual Dependencie classes were created
for digital design in such a manner that the system developed will
work with any CD based Natural Language design system.
%A W. M. Dong
%A H. C. Shah
%A A. C. Boissonnade
%T Treatment of Vague Information in the Development of a Risk
Evaluatin System - Application to Seismic Risk Analysis
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 247-260
%K O04 AA05 AI01
%X Fuzzy rules are used to represent various socio-economic considerations
in measuring the impact of an earthquake while more structured rules
are used to represent various analysis tools for earthquake engineering.
%A C. C. Thiel
%A A. C. Boissonnade
%T System Identification and Information Processing in Seismic Vulnerability
Analysis of Structures
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 277-285
%K AA05 O04
%X The use of fuzzy modelling and cascading models in generating earthquake
vulnerability assessments
%A Adele Howe
%A Paul Cohen
%A John Dixon
%A Melvin Simmons
%T Dominic: A Domain-Independent Program for Mechanical Engineering Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 289-299
%K AA05
%X an optimization system for evaluate and redesign engineering.
The emphasis is on "parameter selection" for a system whose basic configuration
is known. I. E. in a belt and pulley system, the exact sizes and locations
of the pulleys would be chosen when the configuration of what belt is
attached to which pulley has been predetermined.
%A Farrokh Mistree
%A H. M. Karandikar
%A Saiyid Kamal
%T Rule-Based Post Solution Analysis of Decision Support Problems: Some
Preliminary Results
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 302-315
%K linear programming sensitivity analysis optimization AI01
%X describes methods for assisting the user in analyzing the results
of a linear programming run. Examples of changes that can be examined
are changes in the coefficients of the constraints or the inclusion
of a new variable.
%A Bertrand Neveu
%A Pierre Haren
%T SMECI: An Expert System for Civil Engineering Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 317-325
%K AA05 AI01
%X an expert system for harbor and breakwater design.
%A Michael G. Dyer
%A Margot Flowers
%A Jack Hodges
%T Edison: An Engineering Design Invention System Operating Naively
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 327-342
%K AI03 AA05 AI01
%X A system to handle naive physical reasoning in connection with simple
physical objects such as can openers and transmission systems.
The system works in brainstorming mode (to discover new devices ala Lenat)
and problem solving mode.
%A J. S. Gero
%A M. Balachandran
%T Knowledge and Design Decision Processes
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 343-352
%K Pareto optimality optimization NISE
%X design under conditions of Pareto optimality, that is with multiple
items that need to be "optimized." Rules are used to reduce the time
to compute the Pareto optimal set and to determine the shape of the
optimal set qualitatively.
%A D. Sriram
%A M. L. Maher
%T The Representation and Use of Constraints in Structural Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 355-368
%K AA05 AI01 AI16
%X discussion of some of the knowledge engineering and constraint
representation issues in the HI-RISE and ALL-RISE building design
systems
%A Navin Chandra
%A David H. Marks
%T Intelligent Use of Constraints for Activity Scheduling
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 369-382
%K operations research scheduling AI01 AI03
%X A rule-based scheduling system and a language for representing
constraints in a scheduling system
%A David C. Brown
%A Robert Breau
%T Types of Constraints in Routine Design Problem-Solving
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 383-390
%K AA05 package design AI16 AI01
%X discusses the work of those designing packaging for computer terminals
and other equipment. Reviews observations on real engineers doing this
work, various types of constraints that exist and methods used in
failure handling to backtrack.
%A Robert Milne
%T Constraint Drive Distribution Scheduling
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 391-399
%K AI01 AA18
%X describes expert systems
to handle the fielding of equipment to large organizations including the
handling of priorities of which group gets which equipment first and
the disposition of old equipment being replaced.
%A Bernt A. Bremdel
%A Svein Kristiansen
%T Concept Definition in Marine System Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 403-421
%K AA03 AI01 AA05
%X describes goals of expert systems for the overall design of offshore
oil drilling systems and the systems and plans to lift equipment onto
an offshore structure being constructed.
%A S. C. Y. Lu
%A C. R. Blattner
%T A Knowledge-Based Expert System for Drilling Station Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 423-443
%K IDRILL AI01 AA26
%X An expert system for the design of drilling stations in large
scale manufacturing transfer lines is described.
%A Jack Aldridge
%A John Cerutti
%A Willard Draisin
%A Michael Steuerwalt
%T Expert Assistants for Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 445-455
%K AI01 nuclear weopon AA05 AA26 AA18 AA28 PROCON APPRENTICE
%X these systems provide an interface to simulation systems and although
of general use, have been applied to nuclear warhead design. APPRENTICE
provides graphical input and assists the engineer in designing.
%A K. G. Swift
%A A. Matthews
%A C. Syan
%T The Application of IKBS in Design for Assembly and Surface Treatment
Selection
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 459-471
%K AA26 AA05 AI01
%X The coating system chooses polymeric coatings for objects.
It has achieved an error rate of 5% compared to human error rate of 3%.
.br
br
The assembly system is resident
in the CAD workstation and presents its data as annotations and proposed
revisions
%A Paul J. Nolan
%T An Intelligent Assistant for Control System Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 473-481
%K AA05 AI01
%X This expert system designs linear time-invariant control systems
and includes the simplification into block diagrams or signal flow
graphs to canonical form, selection of compensator type and analysis/
synthesis approach.
%A B. S. Lim
%A J. A. G. Knight
%T Holdex - Holding Device Expert System
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 483-493
%K AA26 AA05 AI01
%X A system for tooling design in manufacturing. The discussion emphasizes
the type of drilling to be used. It also appears that there is an interface
to PADL for getting geometric information about the part to be manufactured.
%A Jacques Calmet
%A Denis Lugiez
%T A Knowledge-Based System for Computer Algebra
%J SIGSAM Bulletin
%V 21
%N 1
%D FEB 1987
%P 7-13
%K AA15 AI14
%X outline of such a system, includes a description of software engineering
aspects as well.
%A Monique Grandbastien
%A Jean Maroldt
%T Towards an Expert System for Troubleshooting Diagnosis in Large Industrial
Plants
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 503-511
%K AA20 AA21 AA05 AI01
%X A demonstration expert system for a gas blast furnace was developed
with emphasis on the gas analysis aspects. A complete expert system
is being prototyped.
%A A. DiLeva
%A P. Giolito
%T Data Models and Process Models for Computer Integrated Manufacturing
Systems
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 513-526
%K AA26 AA21 AA05 AI01 AA09 AI16 petri net entity relation model
%X The Entity Relation Model for Databases and a Transaction Definition
Language as well as Petri Nets are used to represent manufacturing systems.
%A P. J. Nolan
%A M. A. McCarthy
%T AI Frame-Based Simulation in System Dynamics
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 527-538
%K AA11 AA28 continuous system simulation CSMP dynamo frame
%X This system provides a representation for common components of
social and biological
continuous system simulations such as simple inventory system, time delay
population model, and summing junction. This provides a way for
the user to specify DYNAMO and CSMP simulations at a higher level.
%A D. L. Crandall
%T Automated Valve Expertise Capture
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 539-544
%K AI01 AA05 component selection
%X This system is used in experimental energy production equipment
design for the selection of valves. In addition to comparing the
valve request with a data base, it invokes special features for
special problems in valve selection such as high temperature requirements.
%A W. A. Taylor
%T Development of a Knowledge Based System for Process Planning in
Welding
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 545-562
%K metallurgy hardenability steel AI01 AA05 AA26 offshore oil wells
%X This rule based expert system develops appropriate welding
procedures for arc welding a specific range of steel grades.
%A H. C. Brockelsby
%A D. L. Crandall
%T Information Processing in the Non-Homogenous Environment
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 563-572
%K AA05
%X describes the engineering functions at Idaho National
Engineering Laboratory and how they can be served by an integrated
engineering automation system which would probably include AI
components.
%A D. E. Reynolds
%A C. B. Boulton
%A S. C. Martin
%T AI Applied to Real Time Control: A Case Study
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 573-583
%K AI01 AI09 AI06 AA19 AA18
%X Applications to the control of a mine hunting surface ship
which typifies problems
in which standard multi-variable control theory can be used but
different control strategies must be used at various times while
the system is running. The system uses "plan scripts" to structure
the database of actions and uses signal interpretation to determine
what state it is in.
------------------------------
End of AIList Digest
********************
∂03-May-87 1609 LAWS@Stripe.SRI.COM AIList Digest V5 #106
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 May 87 16:09:24 PDT
Date: Sun 3 May 1987 13:54-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #106
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 4 May 1987 Volume 5 : Issue 106
Today's Topics:
Administrivia - AIList Interruption & MDee Mailer Troubles,
Queries - Robot Planning & LISP Engine Speed &
Canonical List of Commercial AI Products under UNIX &
Tech Report Contact Info & Performance of Rule-Based Systems &
Singapore KEE Users Seeking Other KEE Users &
Flavors & XENIX Expert Shells & HEX & Go &
Theorem Proving Text & Sun/Lucid Environment &
Meta-Level Architectures for Rule Systems
----------------------------------------------------------------------
Date: Thu 30 Apr 87 09:48:17-PDT
From: Ken Laws <Laws@Stripe.SRI.COM>
Subject: AIList Interruption
Sorry for the delay in getting the digest out. An unbalanced quote
in my distribution list took four days to discover and fix; then I
came down with a case of flu so bad that I couldn't bear to read
for several days. I'm nearly recovered, and I also have my home
terminal back from the repair shop, so I should be able to get the
digest going again.
-- Ken
------------------------------
Date: 30 Apr 87 23:15:00 GMT
From: mdee!md@eddie.mit.edu
Subject: Mailer Troubles
Would anyone who sent us electronic mail between April 26th and April 30th
please resend -- our incoming mailer was broken. Sorry for the inconvenience.
Marilyn Dee Associates, Inc.
"Specialists in Artificial Intelligence"
One Kendall Square, Suite 2200
Cambridge, Massachusetts 02139
(617) 577 8881
{seismo, genrad, allegra}!mit-eddie!mdee!md
------------------------------
Date: 20 Apr 87 04:31:36 GMT
From: friedman@topaz.rutgers.edu (Gadi )
Subject: robot planning papers request.
I am writing a paper on current work in Robot planning. I would like
stuff from the '80s.. I already have some from the early seventies.
(72,73,74). Any references would be appreciated.
Gadi
--
ARPA: friedman@topaz.rutgers.edu
UUCP: {harvard, seismo, ut-sally, sri-iu, ihnp4!packard}!rutgers!topaz!friedman
CMS: RUTGERS!SYSOP (CMS is DOWN. Long live CMS)
------------------------------
Date: Mon, 20 Apr 87 13:26:50+0900
From: "Jin H. Kim" <jkim%csd.kaist.ac.kr@RELAY.CS.NET>
Subject: LISP Engine Speed
I am writing an introductory paper about Lisp Workstations such as
Symbolics 3600, TI's Explorer, and Lambda machine. Does anybody have
speed comparisions between the Lisp Engines and conventional
workstations such as Sun and Apollo in executing LISP programs.
Jin H. Kim
Korea Advanced Institute of Science and Technology
Computer Science Department
------------------------------
Date: 21 Apr 87 20:56:54 GMT
From: bagwill@decuac.dec.com (Bob Bagwill)
Subject: canonical list of commercial AI products under UNIX
Has anyone compiled such a list? Thanks.
--
-------------------------------------------------------------------------------
Bob Bagwill Are we not men?
UUCP: {decvax,seismo,cbosgd}!decuac!bagwill INET: bagwill@decuac.DEC.COM
------------------------------
Date: Wed, 22 Apr 87 18:00:24 AST
From: brant@linc.cis.upenn.edu (Brant Cheikes)
Subject: Call for Tech Report Contact Info
Every time I need a technical report published at another institution,
I always find myself going through the same hassle, usually involving
several phone calls and transfers, until the "right person" is found.
Is there any list or "lookup service" where one can, given an
institution, find out the name (and perhaps network address) of the
person to whom requests for technical reports can be addressed?
If anyone knows of such a thing, please let me know. If I hear
anything useful, I'll pass it on to the community. Thanks.
-----------------------------------------------------------------------------
Brant Cheikes University of Pennsylvania
ARPA: brant@linc.cis.upenn.edu Computer and Information Science
=============================================================================
[Lawrence Leff maintains such a list of report sources.
Write to him as Leff%smu.csnet@relay.cs.net, or as
E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU. -- KIL ]
------------------------------
Date: Thu, 23 Apr 87 11:14:24 WUT
From: ADELSBER%AWIWUW11.BITNET@wiscvm.wisc.edu
Subject: performance of rule-based systems
subject: performance of rule-based systems
I am currently working on a methodology for defining the performance of
rule-based expert systems. I would like to discuss and to compare the
performance of different inference-strategies. To get comparable results
it seems to me important to classify and to evaluate different rule-
representations and to find a measure for specific rule-bases.
This measure should include attributes like complexity, granularity,
depth etc. A main goal of this work is to find a method for the
selection of the best representation and inference strategy for
a specific kind of rule-based knowledge. Is there anybody working on the
same object ? I would be thankful for hints, information and (or)
references.
Marcus Oppitz, Technical University Vienna
Please send your answer to
vipvax!marcus%tuvie.uucp@cernvax (marcus oppitz)
or
adelsber at awiwuw11 (bitnet)
------------------------------
Date: Fri, 24 Apr 87 08:23:54 cdt
From: "Michael T. Gately" <gately%resbld%ti-csl.csnet@RELAY.CS.NET>
Subject: KEE users seeking other KEE users
From: TILDE::"UCBCAD!AMES!SEISMO!ROCHESTER!RITCV!SPW2562@UCBVAX.BERKELEY.EDU"
Posted for a friend without access to netnews...
Pls respond to iss@tataelxsi, NOT to me.
==============================================================================
In space no one hears you scream! Loneliness got to me finally.
We are an isolated group of KEE users in Singapore (South East
Asia), feeling lonely and chilly due to the thousands of miles
of empty space to the nearest the KEE civilization. We need
someone to talk to, please respond! We face lots of technical
problems and once in a while feeling that we are reinventing
some tools.
Our site is running a TI Explorer with KEE version 3.0. We have
something to offer too: tools for compact bitmap storage and
displaying, and bitmap cutting from screen.
plse e-mail to..
...sun!elxsi!tataelxsi!iss or
ISSAD@NUSVM (bitnet)
looking forward to hearing from all of you 8-)
Loo Peing Ling
Institute of Systems Science
==============================================================================
Steve Wall @ Rochester Institute of Technology
UUCP: ..{allegra|seismo}!rochester!ritcv!spw2562 Unix 4.3 BSD
BITNET: SPW2562@RITVAXC VAX/VMS 4.4
------------------------------
Date: 24 Apr 87 15:41:48 GMT
From: rochester!kodak!murthy%svax.cs.cornell.edu@seismo.CSS.GOV (Chet
Murthy)
Reply-to: murthy@svax.cs.cornell.edu (Chet Murthy)
Subject: Flavors anyone?
Hi. I am looking for a copy of flavors that will run on Franz LIsp
under 4.3. (Opus 38.92). The version of flavors that comes with Franz is
a bit (putting it lightly) broken. Anybody out there have anything?
(Please reply to me, since I figure most people have real lisps to work with.
Thanks in advance,
--chet--
In Real Life: Chet Murthy
ARPA: murthy@svax.cs.cornell.edu
SnailMail: Chet Murthy
Gaslight Village Apts 21-B
Uptown Road
Ithaca, NY 14850
Office: 4162 Upson (607) 255-2219
MaBellNet: (607)-257-5709
--
--chet--
In Real Life: Chet Murthy
ARPA: murthy@svax.cs.cornell.edu
SnailMail: Chet Murthy
Gaslight Village Apts 21-B
Uptown Road
Ithaca, NY 14850
Office: 4162 Upson (607) 255-2219
MaBellNet: (607)-257-5709
------------------------------
Date: 26 Apr 87 00:21:14 GMT
From: jsrobin@ra.ee.umd.edu (John S. Robinson)
Reply-to: jsrobin@ra.UUCP ()
Subject: Expert Shells for PC/AT XENIX - what's good, what's bad?
I am posting this for a friend:
I am in the process of developing an expert system on an IBM PC/AT under
the XENIX operating system.
I would like to find out people's views on expert system shells that run
under XENIX on IBM PC/AT's. Any information about these tools (pros and cons)
would be greatly appreciated. Thank you.
Please reply to jsrobin@ra.UUCP, or jsrobin@eneevax.umd.edu, or post responses
to the appropriate newsgroups. Thanks in advance for your responses.
------------------------------
Date: 27 Apr 87 15:47:03 GMT
From: mcvax!cernvax!bcfl@seismo.css.gov (bcfl)
Subject: asking infos on HEX game
Hi there.I hope that somebody on the net knows a board game called HEX,
consisting of a 11 x 11 board of hexagonal cases.The winner is the first one
who completes a chain joining two parallel sides.I used to play some years
ago,but have not kept in touch with the players community.I was told that
the game is played in the US,so I would appreciate infos about the
following points:
1)What about the mathematical researach?Did anybody find a winning strategy
for the first player?
2)Do intelligent probgrams exist?What sort of algorithm do they use?Are
they commercially available?
3)Do dedicated playing machines exist?
I gratefully thank in advancec anyone who will provide me with infos
on any of the points above.
Giulio Prisco. CERN EP Division.
------------------------------
Date: 28 Apr 87 22:13:34 GMT
From: andrew.cmu.edu!lord#@pt.cs.cmu.edu (Tom Lord)
Subject: recorded go games
<>
Does anyone out there have a library of go games, played by humans, in a
machine readable format? I would like to use such a library to test some
notions I have about how to build a selective search for the game. Machine
readable libraries of joseki, tesuji problems and the like would also be of
use.
Thanks,
Thomas Lord
lord@andrew.cmu.edu
or
tbl@k.cs.cmu.edu
------------------------------
Date: Tue, 28 Apr 87 16:05 EDT
From: DON%atc.bendix.com@RELAY.CS.NET
Subject: Theorem Proving Text recommendation
What is a good, up-to-date, intermediate or advanced automated theorem
proving book? If there isn't a list which someone can send me from the
archives, I'll collect responses and post.
Don Mitchell Don@atc.bendix.com
Bendix Aero. Tech. Ctr. Don%atc.bendix.com@relay.cs.net
9140 Old Annapolis Rd. (301)964-4156
Columbia, MD 21045
------------------------------
Date: 29 Apr 1987 12:23-EDT
From: VERACSD@A.ISI.EDU
Subject: Symbolics & Sun-3 + Lucid Dev Envs
I'm interested in the viability of the Sun-3/160 running Lucid Common Lisp
(with Lucid's version of Flavors) as a Lisp development environment.
My standard for the comparison are Symbolics 36xx's, which I have a
strong predilection toward.
I'm especially interested in opinions/remarks by experienced Symbolics
programmers who have used Sun-3's with Lucid for more than a few hours.
Some specific areas I would like to see addressed are:
o the completeness is Lucid's Flavors
o the quality of editing and debugging tools
o gc
o major wins/losses vis-a-vis Symbolics
o rough estimate of development time vis-a-vis Symbolics
I will be glad to summarize and post if the response warrants it.
-- Cris Kobryn
----------------------------------------------------------------------------
Cris Kobryn ARPA: VERACSD.CK@A.ISI.EDU
Advanced Systems Development BELL: (619)457-5550
VERAC, Inc.
9605 Scranton Rd., Suite 500
San Diego, CA 92121
------------------------------
Date: Tue, 28 Apr 87 17:36:01 GMT
From: unido!tadam!michael@seismo.CSS.GOV (Michael Beetz)
Subject: efficient implementation of meta-level architectures for
rule-systems
We are currently developing a production rule interpreter that processes
explicit and declarative representations of control knowledge. Therefore,
we are interested to get contact to people working at the same topics.
Our interpreter processes rules like rules in OPS5, meta rules
like the rules of the TEIRESIAS system. Rules are partitioned in rule
sets and the user can specify phase sequences describing the order
in which rule sets are applied within an interpretation process. Or
the user can specify conflict resolution rules if more than one rule set
is applicable (with each rule set a precondition is associated).
We are working at the following topics:
1. Extending the RETE algorithm such that
- it can process objects (inheritance!)
- it can increase the efficiency of matching by exploiting the
partitioning of rule bases in rule sets
- can match meta rules (rules that contain patterns of object rules
in their condition part)
2. languages for specifying meta-level architectures for rule-based
systems.
3. Efficient implementations of RETE algorithms on a SYMBOLICS LISP
machine Genera 7.0.
Thanks in advance
Michael
Michael Beetz
c/o Gerhard Kraetzschmar
Schweppermannstr 5
8500 Nuernberg 10
Federal Republic of Germany
------------------------------
End of AIList Digest
********************
∂03-May-87 1809 LAWS@Stripe.SRI.COM AIList Digest V5 #107
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 May 87 18:09:03 PDT
Date: Sun 3 May 1987 15:31-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #107
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 4 May 1987 Volume 5 : Issue 107
Today's Topics:
AI Tools - Kyoto Common Lisp Distribution,
Review - Spang Robinson Report, Vol. 3, No. 4,
Applications - Tough Speech Recognition Examples (Summary) &
Checking Rule-Based Expert Systems
----------------------------------------------------------------------
Date: Thu, 30 Apr 1987 16:57 EDT
From: "Scott E. Fahlman" <Fahlman@C.CS.CMU.EDU>
Subject: Notice on Kyoto Common Lisp distribution
Mr. Yuasa asked me to pass the following announcement along to the
appropriate mailing lists in the U.S.:
We, the Kyoto Common Lisp people have decided to distribute KCL
through channels other than a commercial company,
free of charge out of Japan.
We are looking for a best possible channel but it may take some time.
Please note the following:
1. We always claimed that no fee is charged for the source of KCL, and
if any fee is charged, it is exclusively for the service of distribution,
maintenance, etc. of the software.
2. We never received any kind of royalty out of the software or service for
it up to present.
Research Institute for Mathematical Sciences
Kyoto University
Reiji Nakajima
Taiichi Yuasa
Masami Hagiya
------------------------------
Date: Sat, 2 May 1987 19:29 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Spang Robinson Report, Vol. 3, No. 4
Summary of Spang Robinson Report
April 1987, Volume 3 No. 4
The lead article of the issue is Expert Systems in Japan.
A recent survey of Japanese companies indicated that half of them are actively
involved in expert systems use or development. They found 50 in prototype
stage, 31 being field tested, 19 operating and 5 in commercial use.
The majority of Japanese expert systems are on mainframes. BRAINNS (from
Toyo Information Systems) and ESHELL are popular tools for expert system
development.
Japanese AI development is estimated at
$170 million/year with fourty percent coming from US
imports. [I reported in AILIST elsewhere that U. S. AI revenues were about
two hundred million.- LEFF]
ADL reports that large Japanese companies are becoming discouraged with
ICOT for being out of schedule and insufficient ROI. There is a new
joint development project involving 200 companies called SIGMA for automating
software generation. It will take natural language input in Japanese and
English and generate code automatically. Funding is 160 million over four
years.
Marty Tenenbaum states that the Japanese are not behind the US in expert systems
develop[ment and they are emphasizing applications to real problems.
+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_
An article on the new TI Compact Lisp Machine
Some of the information in this article that I have not seen in articles on
the CLM that have been reported in AILIST elsewhere is
- There are discussions of integrating the TI Explorer Chip into Apple's
new machine.
- TI may be selling boards to be integrated into commercial as well
as military products
_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+
An article on commercial implications of AI
Hundreds of expert systems have been "fielded"
Dramatic Successes:
Hitachi's expert system for floor planning main frame installations has
reduced the task from eight hours to fifteen minutes.
Canon's expert system for lens design has reduced design time from eight
man-months to two man-weeks
IBM's storage system saves five million a year (it was developed in six
man months)
DEC's XCON saves eighteen million a year while costing two million a year
to maintain.
Most expert systems are small (<300 rules) and are running on micros.
_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+
Applications of expert Systems
Nisssan Auto - engine control system diagnosis (fielded)
Sanwa Bank - investment consultation system for clients (in use at six
branch offices)
Tokyo Electric - substation design (in field test), design time reduced by
a factor of ten
Nihon Steel - blast furnace diagnosis (80 percent accuracy)
Seibu Saison - diet consultation
gift selection
-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+SHORTS-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
The expert system, ACORN, from Gold Hill Computers will now be called
GOLDWORKS due to a conflict with Acorn Computers.
Inference Corporation's ART is now available under VMS.
Intellicorp's KEE is now available on the SUN. They are committed to
developing a Japanese version. They have already sold 90 copies in Japan.
MAD intelligent systems is bundling a Relational Lisp which supports both
classical relational operators and functions for complex and recursive
relations.
ExperTelligence's Common Lisp on a Macintosh II runs 53 percent faster
than a Symbolics Lisp machine (as indicated by the Gabriel DDERIV benchmark)
Arthur D. Little is involved in a research project for the Post Office
for applying AI to several areas.
Intelligent Applications will be selling in the US, a machine-health
monitoring system based on vibrations, a tool kit, an Analogue Interface
Expert and a Fault Diagnosis and Schematic Capture System.
Teknowledge has named Peter Weber President and Chief Operation Officer.
He comes from FMC Corporation where he established their AI system.
Symbolics has appointed Annie Brooking as marketing director.
++++++++++++++++++++++++++++++++++++++++++++++++++
Also a listing of some papers reporting on Japan's AI research.
------------------------------
Date: 29 Apr 1987 1435-PDT (Wednesday)
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Tough speech recognition examples (summary)
Attached are my so far collected examples of tough speech
problems (synthesis and recognition). I am a bit disappointed
with the list: smaller, poorer quality, and have not heard from
people who are really doing lots of this work. {messages were sent to
ailist, comp.ai on the usenet, nihongo on the ARPAnet [Japanese being a
significantly difficult language and the NGCProj]}.
My plan is to keep this list {collective ailist memory} and ask for
new contributions every year (along with my other lists). It will
be ftpable from a machine at Ames, as soon as I decide where to put
it probably (aurora). My hope is to have a ready list of tests for
speech processing naive people to gain some understanding of the problems.
I am posting this summary now in hopes of getting a few last examples.
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
=============================================================
From: elman@amos.ling.ucsd.edu (Jeff Elman)
Subject: Re: Tough speech recognition examples
Raj Reddy (at CMU) has a couple of examples of difficult
utterances they gave to HEARSAY and HARPY. One of these was
"In mud eels are, in tar none are".
The lack of semantic support, plus the ambiguity of segmentation
make it almost impossible for someone to understand this sentence
when you read it to them at a normal rate of speech.
I'd like to hear what responses you get. Would you let me know?
Thanks,
Jeff Elman
Phonetics Lab, C-008
Univ. of Calif., San Diego
La Jolla, CA 92093
Internet: elman@amos.ling.ucsd.edu
==================================================================
From: mcguire@aero2.aero.org
>From my days many years ago in a linguistics laboratory I remember
some examples showing the importance of phonetic juncture:
grey day / grade A
euthanasia / youth in Asia
"Whats that up in the road" ahead / a head?
Happy collecting
Another cute example (though it may not what you are looking for) is to
say to somebody:
"Take off your hat and dloves"
and then ask them what you said. 99% of all people will insist that
you said the word "gloves".
==================================================================
From: minow%thundr.DEC@decwrl.DEC.COM (Martin Minow THUNDR::MINOW
ML3-5/U26 223-9922)
I'd be happy if you could do the digits, including "Oh", and Yes/No.
Continuous digits, telephone quality, no training, male and female voice.
DECtalk should be very easy, as it's predictable.
Martin Minow
(ex-DECtalk developer)
The problem is in distinguishing "oh" from "no".
Getting the alphabet (not "alpha", "bravo", but "aye", "bee") would
be nice, too.
Martin.
==================================================================
From: Marc Majka <ames!seismo!ubc-vision!vision.ubc.cdn!majka>
Here one that my office mate Nou Dadoun came up with:
I love you
Isle of View
==================================================================
From Joseph_D._Becker.osbunorth@Xerox.COM Fri Apr 24 10:06:44 1987
I think you need at least one example in Chinese, and here's my favorite
(because I actually said it by mistake). The numbers after the words
are phonic "tones". What I meant to say was:
Wo(3) hen(3) xiang(3) shui(4)-jiao(4) -- I want to go to sleep
... but what I actually ended up saying was:
Wo(3) hen(3) xiang(4) shui(3)-jiao(3) -- I am like a boiled ravioli
Joe
==================================================================
"ice cream"/"I scream"
"beginning"/"big inning"
"soccer"/"sock her"
"its hardware problems are intermittent"/"it's hard where problems ..."
from Mark Twain:
"Good-bye God, I'm going to Missouri."/"Good, by God, I'm going to
Missouri."
--Stephen Slade
Slade@Yale.Arpa
Came across this last night
"attacks"/"a tax"
--Stephen
------------------------------
Date: Wed, 22 Apr 87 14:29:14 WET
From: "G. Joly" (Birkbeck) <gjoly@Cs.Ucl.AC.UK>
Subject: Checking Rule-Based Expert Systems (Response to Info Request).
Below is a list of the references I have received to date on
the various aspects of checking rule-based systems, together
with some related items.
Gordon Joly,
Dept. of Computer Science,
Birkbeck College,
University of London.
ARPA: gjoly@cs.ucl.ac.uk
BITNET: UBACW59%uk.ac.bbk.cu@AC.UK
UUCP: ...{seismo,decvax,ucbvax}!mcvax!ukc!bbk-cs!gordon
%A F. Barachini
%T Konsistenzprufung von Wissensbasen medizinischer Expertensysteme
(Consistency checking of knowledge bases of medical expert systems)
%I thesis, Tech. Univ. Vienna, Austria
%D Feb 1984
%P 153 (in German)
%K consistency
%A Blum, R.L.
%T Computer-Assisted Design of Studies Using Routine Clinical Data:
Analyzing the Association of Prednisone and Serum Cholesterol
%J Annals of Internal Medicine
%V 104
%N 6
%P 858-868
%D June, 1986
%A Boose, John H
%A Bradshaw, Jeffrey M
%T A Knowledge Acquisition Workbench for Eliciting Decision Knowledge
%B Proceedings of the Twentieth Annual International Conference
on System Sciences
%P 450-459
%D 1987
%A Robert S Boyer (ed)
%A J Strother Moore (ed)
%T The Correctness Problem in Computer Science
%I Academic Press
%D 1981
%A Manfred Broy
%A Bernhard Moller
%A Peter Pepper
%A Martin Wirsing
%T Algebraic Implementations Preserve Program Correctness
%J Sci Comput. Programming
%V 7
%D 1986
%N 1
%P 35-53
%A W. Chehire
%T SYPRUC: a knowledge representation and manipulation system
%B 6th International Workshop on Expert Systems and their Applications
%C Avignon, France
%D April 1986
%P 933-946 (in French)
%K consistency
%A Eshelman, Larry
%A McDermott, John
%T MOLE: A Knowledge Acquisition Tool That Uses Its Head
%J Proceedings of the American Association of Artificial Intelligence
%P 950-955
%D 1986.
%A D. W. Etherington
%T Formalizing Nonmonotonic Reasoning Systems
%J Artificial Intelligence
%V 31
%N 1
%D 1987
%P 41-86
%A Ginsberg, Allen
%T A Metalinguistic Approach to the Construction of Knowledge
Base Refinement Systems
%B Proceedings of the American Association of Artificial Intelligence
%P 436-441
%D 1986
%A Ginsberg, Allen
%A Weiss, Sholom
%A Politakis, Peter
%T SEEK2: A Generalized Approach to Automatic Knowledge Base Refinement
%B Proceedings of the Ninth International Joint Conference on Artificial
Intelligence
%P 367-374
%D 1985
%A E. J. Horwitz
%A D. E. Heckerman
%T The Inconsistent use of Measures of Certainty in Artificial
Intelligence Research
%E Kanal
%B Uncertainty in Artificial Intelligence
%I North Holland
%D 1986
%A H. Langmaack
%T A New Transformational Approach to Partial Correctness Proof Calculi
for ALGOL68-Like Programs with Finite Modes and Simple Side Effects
%P 73-102
%D 1985
%A Loveland, D.W.
%A Valtorta, M.
%T Detecting Ambiguity: An Example in Knowledge Evaluation
%B Eigth International Joint Conference on Artificial Intelligence
%P 182-184
%D 1983
%A Jim A. McMannama
%T A Non-cognitive Formal Approach to Knowledge Representation in
Artificial Intelligence
%I US Air Force Institute of Technology (University MicroFilms).
%D 1986
%A Michalski, R.S.
%A Baskin, A.B.
%A Spackman, K.A.
%T A Logic Approach to Conceptual Database Analysis
%B Proceedings of the Sixth Annual Symposium on Computer
Applications in Medical Care
%P 792-796
%D 1982
%A Michalski R.S.
%A Baskin, A.B.
%A Uhrik, C.
%A Channic, T.
%T The ADVISE.1 Meta-Expert System: The General Design and a
Technical Description
%R Report No. UIUCDCS-F-87-962, Department of Computer Science
University of Illinois, Urbana
%D 1987
%A Nguyen, T. A.
%T Verifying Consistency of Production Systems
%B Proc. of the 3rd IEEE Conference on Artificial Intelligence Applications
%C Orlando, Florida
%P 4-8
%D February 1987
%A Nguyen, T.A.
%A Perkins, W.A.
%A Laffey, T.J.
%A Pecora, D.
%T Checking an Expert Systems Knowledge Base for Consistency
and Completeness,
%B Ninth International Joint Conference on Artificial Intelligence
%P 375-378
%D 1985
%A E. Pipard
%T Detection of contradictions in knowledge bases
%B 5th International Workshop on Expert Systems and their Applications
%C Avignon, France
%D May 1985
%P 995-1010 (in French)
%K consistency
%A P. G. Politakis
%A Sholom M. Weiss
%R Technical Report CBM-TR-113
%I Rutgers University, Department of Computer Science
%T Designing Consistent Knowledge Bases:
An Knowledge Acquisition Approach to Expert Systems
%D September 1980
%D March 1982
%K consistency
%A P. G. Politakis
%A Sholom M. Weiss
%T Using Empirical Analysis to Refine Expert System Knowledge Bases
%J Artificial Intelligence
%V 22
%N 1
%P 23-48
%D 1984
%A Quinlan, J.R.
%T Consistency and Plausible Reasoning
%B Eigth International Conference on Artificial Intelligence
%P 137-144
%D 1983
%A Reubenstein, Howard B.
%T OPMAN: An OPS5 Rule Base Editing and Maintenance Package
%I MIT
%B Master's Thesis, Department of Electrical Engineering and Computer Science
%P 115
%D 1985
%A Reinke, Robert E.
%T Knowledge Acquisition and Refinement Tools for the ADVISE
Meta-Expert System
%R Report No. UIUCDCS-F-84-921
%I Department of Computer Science, University of Illinois
%D 1984.
%A J. T. St.Johanser
%A R. M. Harbidge
%T Validating expert systems: problems and solutions in practice
%B KBS 86: Knowledge Based Systems. Proc. of the International Conference
%C London, England
%D July 1986
%P 215-219
%K validation
%A Spackman, Kent Alan
%T QUIN: Integration of Inferential Operators in a Relational Database
%B Masters Thesis
%I Department of Computer Science, University of Illinois, Urbana Illinois
%D 1982.
%A Stachowitz, Rolf A.
%A Combs, Jacqueline B.
%T Validation of Expert Systems
%B Proceedings of the Twentieth Annual Hawaii Conference on System Sciences
%P 686-695
%D 1987
%A R. Steinmetz
%A S. Theissen
%T Integration of Petri nets into a tool for consistency checking of expert
systems with rule-based knowledge representation
%B 6th European Workshop on Applications and Theory of Petri Nets
%C Espoo, Finland
%D June 1985
%P 35-52
%K consistency
%A Suwa, W.
%A Scott, A.C.
%A Shortliffe, E.H.
%T An Approach to Verifying Completeness and Consistency in a Rule-Based
Expert System
%J AI Magazine
%P 16-21
%D Fall 1982.
%A Adrian Walker (Ed.)
%A Michael McCord
%A John F. Sowa
%A Walter G. Wilson
%T Knowledge Systems and Prolog - A Logical Approach to Expert Systems
and Natural Language Processing (Addison-Wesley)
%D 1987
%A Wilkins, David C.
%A Buchanan, Bruce G.
%T On Debugging Rule Sets When Reasoning Under Uncertainty
%B Proceedings of the American Association of Artificial Intelligence
%P 448-454
%D 1986.
The following will appear in the proceedings of the Avignon-87 meeting,
"Expert Systems and their Applications", May 15-18 1987, Avingnon, France.
G. Soula et al: A multi-validation of the PROTIS expert system.
S. Puuronen: A tabular rule-checking method
M.-C. Rousset: On knowledge-base validity: The COVADIS system.
E.F. Miller: Expert systems validation and verification:
Issues and approaches.
------------------------------
End of AIList Digest
********************
∂03-May-87 1958 LAWS@Stripe.SRI.COM AIList Digest V5 #108
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 May 87 19:58:26 PDT
Date: Sun 3 May 1987 15:50-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #108
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 4 May 1987 Volume 5 : Issue 108
Today's Topics:
Linguistics - Grammar and Style Checkers,
Humor - Text Critiquing
----------------------------------------------------------------------
Date: Mon, 20 Apr 87 12:15:28 CST
From: g-chapma@gumby.wisc.edu (Ralph Chapman)
Subject: re: grammar checkers
I was asked to forward this message in response to the article by
Linda G. Means:
Date: Thu, 16 Apr 87 15:18:42 CDT
From: sklein@rsch.wisc.edu (Sheldon Klein)
Message-Id: <8704162018.AA06807@rsch.wisc.edu>
Subject: Re: grammar checkers
I accept the note as one more piece of evidence that
the field of Comp Sci, Comp Ling & AI
are providing the prosthetic devices to allow
otherwise unemployable segments of the World population
to function for pay in occupations for which they would
have been congenitally unqualified in an earlier era.
Those capable of constructing complex sentences which, to some
pundits of an earlier era reflected the ability to think complex
thoughts, will have to abandon their elitist modes of cognition
for the greater benefit of the larger segment of humankind.
------------------------------
Date: Fri, 24 Apr 87 17:11:39-1000
From: scubed!sdcsvax!uhccux.UHCC.HAWAII.EDU!nosc!humu!todd@seismo.CSS.GOV
(The Perplexed Wiz)
Subject: re: writing style checkers
Path: uhccux!todd
From: todd@uhccux.UUCP (The Perplexed Wiz)
Newsgroups: comp.ai.digest
Subject: Re: AIList Digest V5 #95
Message-ID: <443@uhccux.UUCP>
Date: 24 Apr 87 01:25:22 GMT
References: <AIList-REQUEST@SRI-STRIPE.ARPA> <12295086246.19.HAYES@SPAR-20.ARPA>
Reply-To: todd@uhccux.UUCP (The Perplexed Wiz)
Distribution: world
Organization: U. of Hawaii, Manoa (Honolulu)
Lines: 40
In article <12295086246.19.HAYES@SPAR-20.ARPA> HAYES@SPAR-20.ARPA writes:
>Let me briefly add a seconding voice to Linda Means comments on the horrible
>output of the style-criticising programs illustrated a while ago. That
>people should suggest using such things to influence children almost makes
>me agree with Weizenbaum.
...[comment that it couldn't be good if it runs on a PC was here]
>and superficial rules in a context-insensitive fashion. Any kid who was
>'taught' by one of these would quickly learn these rules. A few experiences
>like this, though, and (s)he would learn that most problems are solved by
>applying a few superficial rules without any need for deeper thinking, which is
>a worse and more dangerous lesson.
I think that we have two extreme views here. I agree that the style
checkers available for microcomputers are not very sophisticated. I also
agree that such tools should not be used exclusively to teach children
(or any other age group for that matter). However, to say that these
microcomputer based style checkers have no place in teaching children
to write in not correct. I think that if these style checking tools
are used in conjunction with the efforts of a good teacher of writing,
then these style checkers are of great benefit. It is better that
children learn a few rules of writing to start with than no rules at
all. Of course, reading lots of good examples of writing and a good
teacher are still necessary. [And no, I don't claim to be a good writer :-)]
On another level... I happened to discuss my response above with one
of my dissertation committee members. His reaction? He pulled out
a recent thesis proposal filled with red pencil marks (mostly
grammatical remarks) and said, "So what if the style checkers are
superficial? Most mistakes are superficial. Better that the style
checker should find these things than me."
Todd, Ogasawara
-- PhD. Psychology 1987 (if the phase of the moon is right, I cross
my fingers enough, etc. :-)
--
Todd Ogasawara, U. of Hawaii Computing Center
UUCP: {ihnp4,seismo,ucbvax,dcdwest}!sdcsvax!nosc!uhccux!todd
ARPA: uhccux!todd@nosc.MIL
INTERNET: todd@uhccux.UHCC.HAWAII.EDU
------------------------------
Date: Tue, 21 Apr 87 9:43:04 EDT
From: Bruce Nevin <bnevin@cch.bbn.com>
Subject: text critiquing redux (humor)
The following is a copy of some correspondance which took place between
an editor and a Mr. Lewis Carroll:
Dear Mr. Carroll,
The publisher has referred to me your latest work, a poem
called "Jabberwocky," for editing. "Jabberwocky" seems rife
with misspellings and typos; I assumed that these were
unintentional and the fault of your typist.
Fortunately, we have recently purchased PROFS (Professional
Office Systems), a new IBM package that includes a
sophisticated proofreader and spelling checker. This
program is able to guess quite accurately as to what the
misspelled word may actually be. PROFS also offers synonyms
and alternatives for words, and it can note redundant,
awkward or wordy phrases.
I have run "Jabberwocky" through this program. Granted,
your obvious intent is to produce a work of fantasy, so I've
taken some of your proper nouns to be creations of your
imagination.
Certain words, however, weren't clear. For example, the
first line of your original text read: "Twas brillig, and
the slithy toves." The only words recognized by the PROFS
proofreader were "and the."
When I hit a key marked "aid," I get a list of what PROFS
construes to be possible spellings of a flagged word. With
"slithy," PROFS came up with slithery, slimy, slither,
slimly, silty, slinky, and slight. Your typist must have
inadvertently dropped the "er" from "slithery" and come up
with the nonsense "slithy." Of course, I fixed the word to
say "slithery."
And so it goes. I continued to make repairs as I deemed
fit. But Mr. Carroll, the mistakes were not always clear.
For example, in the first verse your text read: "All mimsy
were the borogoves." The computer thought that you had
meant to say: "All misty were the bongoes," but bongoes is
a far shot from borogoves. What did you mean by borogoves?
In the second verse, you warn to "shun the frumious
Bandersnatch!" "Frumious" is obviously a misspelling of
"furious"; however, I have no idea as to just what a
Bandersnatch might be. Our computer has suggested
"Ballerinas," but I suspect that you had something better in
mind.
Mr. Carroll, I've edited many fantasies, so I must warn you
that I am familiar with all forms of sword, be they elfish,
dwarfish or otherwise. I have already heard of the "vorpal
sword" you mentioned in verse three. It seems to have
gained popularity among role-playing game enthusiasts,(1)
but I'm not sure its reference is appropriate here. The
computer certainly doesn't have "vorpal" in its memory, so
I'm not sure that the public would appreciate your using the
word. I have let the computer substitute "verbal" for
"vorpal," and I believe that you will find the result has a
nice ring to it.
Some of the other gems that your secretary came up with
include an "uffish" thought, "whiffling" when you certainly
meant "waffling," and some sort of wood. She called it a
"tulgey wood." Again the computer came through: Did you
mean "turkey wood?" Admittedly, the computer had quite a
time with "turkey wood"; it insisted that it should have
been "turkey would." But that would have been nonsense. A
good editor shouldn't be afraid to override a computer.
When I first saw the word "chortled" I was sure that you had
made it up!(2) The computer didn't flag it as being
misspelled, but it couldn't offer any synonyms for it
either. On looking it up, I was amused to discover that it
was meant to be a cross between a chuckle and a snort. How
clever of you to find it!
Well, enough criticism. I'm sure your poem is salvageable.
It's a pity, though, that even "cleaned up" this poem would
be far too difficult for children to read. One function of
the PROFS proofreader is to check the comprehension level of
a word. I'm afraid that some of the words you use are level
16, i.e., a person would have to be a graduate student or
better to understand the word. That's too bad, because
there's quite a market for children's verse.
Anyway, I've underlined the unrecognizable words in your
original and I'm returning it to you. I've also enclosed
the result of my collaboration with the computer; I believe
that you will find the corrected version to be pleasing,
understandable and in keeping with your reputation. Let me
know what you think. I hope you understand that there are
few publishers out there who care to take the time to work
with promising authors.
Yours truly,
xxxxx xxxxxx
--------------------
(1) To "Dungeons and Dragons" players, a "vorpal sword" has
the power to sever limbs when the player rolls 18 or higher.
The word is a Carroll creation.
(2) "Chortle," a word coined by Carroll, has worked its way
into standard dictionaries.
JABBERWOCKY
'Twas brillig, and the slithy toves
----- ------- ------ -----
Did gyre and gimble in the wabe:
---- ------ ----
All mimsy were the borogoves,
----- ---------
And the mome raths outgrabe.
---- ----- --------
"Beware the Jabberwock, my son!
----------
The jaws that bite, the claws that catch!
Beware the Jubjub bird, and shun
------
The frumious Bandersnatch!"
-------- ------------
He took his vorpal sword in hand:
------
Long time the manxome foe he sought --
-------
So rested he by the Tumtum tree,
------
And stood awhile in thought
And, as in uffish thought he stood,
------
The Jabberwock, with eyes of flame,
----------
Came wiffling through the tulgey wood,
-------- ------
And burbled as it came!
One, two! One, two! And through and through
The vorpal blade went snicker-snack!
------
He left it dead, and with its head
He went galumphing back.
----------
"And hast thou slain the Jabberwock?
----
Come to my arms, my beamish boy!
-------
O frabjous day! Callooh! Callay!"
-------- ------- ------
He chortled in his joy.
'Twas brillig, and the slithy toves
----- ------- ------ -----
Did gyre and gimble in the wabe:
---- ------ ----
All mimsy were the borogoves,
----- ---------
And the mome raths outgrabe.
---- ----- --------
JABBERWHACKY
'Twas broiling, and the slithery toes
Did gore and gimlet in the wave:
All misty were the bongoes,
And the mole rats outraged.
"Beware the Jabberwock, my son!
The jaws that bite, the claws that catch!
Beware the Jubjub bird, and shun
The furious Ballerinas!"
He took his verbal sword in hand:
Long time the meantime foe he sought --
So rested he by the Tumtum tree,
And stood awhile in thought
And, as in iffiest thought he stood,
The Jabberwock, with eyes of flame,
Came waffling through the turkey wood,
And burbled as it came!
One, two! One, two! And through and through
The verbal blade went snicker-snack!
He left it dead, and with its head
He went galloping back.
"And hast thou slain the Jabberwock?
Come to my arms, my beaming boy!
O fabulous day! Callooh! Callay!"
He chortled in his joy.
'Twas broiling, and the slithery toes
Did gore and gimlet in the wave:
All misty were the bongoes,
And the mole rats outraged.
[For the record, a mailer history (in reverse order):
Resent-From: Jane Doherty <jdoherty@cch.bbn.com>
Resent-Date: Mon, 20 Apr 87 15:58:42 EDT
From: Jack Allen 381-2141 <allen%clt.DEC@decwrl.dec.com>
Date: Friday, 17 Apr 1987 06:43:02-PDT
From: DSSDEV::EPPES "her shoes were full of feet
From: ABACUS::WOOD "If we couldn't laugh we would all go insane 16-Apr-1987
-BN]
------------------------------
End of AIList Digest
********************
∂03-May-87 2202 LAWS@Stripe.SRI.COM AIList Digest V5 #109
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 May 87 22:02:38 PDT
Date: Sun 3 May 1987 15:55-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #109
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 4 May 1987 Volume 5 : Issue 109
Today's Topics:
Bibliography - Leff Bibliography ai.bib54AB
----------------------------------------------------------------------
Date: Tue, 14 Apr 1987 00:07 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: ai.bib54AB
%A Elizabeth Corcoran
%T Strategic Computing: A Status Report
%J IEEE Spectrum
%D APR 1987
%V 24
%N 1
%P 50-54
%K AA18 AI06 ABE Teknowledge KEE AI15 AI09 H03 Mach RP3 Princeton Massive
Memory Machine AI05 AI01
%X 1987 budges for DARPA strategic computing AI related activities
.DS L
DS L
Naval Battle Management $5.3 million
Pilot's Associate $5.3 million
'Smart' Weopons $5.6 million
Adries-Scorpius $5.3 million
Autonomous Land Vehicle $5.3 million
Air-land battle management $3.6 million
Vision $5.5 million
Speech Recognition $5.2 million
Knowledge Based Systems $4.5 million
Natural Language $4.2 million
Planning $1.8 million
Integrated Interfaces $1.3 million
Design and Manufacturing $900 thousand
(The article provides 1989 and 1992 projected amounts as well)
.DE
DE
.sp
sp
Early successes in this program include a data compression method 10,000
times more powerful than anything else.
.sp
sp
There is also a nice matrix indicating which contractors are working
on which phases of the project.
%A Charles Babcock
%T Cullinet Plans SQL-Based Line
%J ComputerWorld
%V 21
%N 14
%D APR 6, 1987
%P 6
%K AA09 AI01 COBOL VAX
%X Cullinet will be offering expert system development environment for
VAXEN and software to allow people to embed expert systems in their
mainframe COBOL environments.
%A James Ledbetter
%T Technology Transfer
%J ComputerWorld
%V 21
%N 14
%D APR 6, 1987
%P 63-68
%K AT18 U. S. West
%X describes efforts at U. S. West in getting users to identify meaningful
applications for artificial intelligence in their own departments.
%A J. F. Watson
%T A Grammar Rule Notation Translator
%J SIGPLAN Notices
%V 22
%N 4
%D APR 1987
%P 16-27
%K Turbo-Prolog T02
%X This article includes the source of a Turbo-Prolog program that
will convert Grammar Rule Notation to Prolog. The Prolog it produces
should run under any standard PROLOG, not necessarily Turbo-Prolog.
%A D. Harel
%T Logic and Databases: A Critique
%J SIGPLAN Notices
%V 22
%N 3
%D MAR 1987
%P 14-20
%K AA09 AI10
%A W. Hankley
%T Feature Analysis of Turbo Prolog
%J SIGPLAN Notices
%V 22
%N 3
%D MAR 1987
%P 111-118
%K C-Prolog H01 AT17 T02
%X This paper extends Weeks review of six microcomputer Prologs to include
Turbo Prolog. Turbo Prolog misses virtual memory and a clause grammar
(represented by the "->" notation.) It does provide access to bios calls,
MS-DOS commands and code written in other languages, the capability of
compilation, a context editor and modularization. There is also a list
of built-in predicates indicating which ones C-PROLOG and TURBO-PROLOG
possess.
%A J. A. Goguen
%A J. Meseguer
%T Remarks on Many-Sorted Equational Logic
%J SIGPLAN NOtices
%V 22
%N 4
%D APR 1987
%P 41-48
%K AI10 AI16
%X Discusses soundness and completeness results for many-sorted
equational logic and models that permit empty carriers. Also
discussion of alleged misstatements in Loeckx, J. and Bernd Mahr, A Note
on the Equational Calculus for Many-Sorted Algebras with Possibly
Empty Carrier Sets, Technical Report A 58/01, Fachbereich Informatik,
Universitat des Saarlandes, 1985 and Ehrig and Mahr 85, Ehrig, Hartmut
and Bernd Mahr, Fundamentals of Algebraic Specification 1: Equations and
Initial Semantics, Springer-Verlag, 1985.
%A T. W. Jerardi
%T Puzzles, PROLOG and Logic
%J SIGPLAN NOtices
%V 22
%N 4
%D APR 1987
%P 63-69
%K T02 AI16 humor
%X A humorous piece about the responses of Gerhard Gentzen, John von Neumann,
Alfred Tarski and David Hilbert to a computational logic conference.
%A David M. Harland
%A Bruno Beloff
%T Objekt: A Persistent Object Store with an Integrated Object Store
With An Integrated Garbage Collector
%J SIGPLAN NOtices
%V 22
%N 4
%D APR 1987
%P 70-79
%A Alexander Wolfe
%T TI Puts Its Lisp Chip Into a System for Military AI
%J Electronics
%D MAR 19, 1987
%P 95-96
%K H02 AA18
%V 60
%N 6
%X The TI Lisp Process chip will become part of the Military ARIES system
a shoe box sized computer for embedded AI systems.
%T Want to Open an AI Office in Dayton, Ohio, Talk to the Air Force
%J Electronics
%D MAR 19, 1987
%P 102
%K AA18
%V 60
%N 6
%X The Wright Patterson Air Force Base is taking bids for a vendor to
provide quick response AI studies and provide training.
%A Ernest R. Tello
%T The GCLISP 286 Developer
%J Byte
%D APRIL 1987
%V 12
%N 4
%P 241-244
%K T01 H01 AT17
%X Review of GOld Hill's Common Lisp System. The interpreter needs
1.5 meg of memory and the compiler needs 3 meg of memory and 700K of
hard disk space. This system supports "stack groups", a Zeta Lisp
feature not part of the Common Lisp standard which allows multiple
environments to exist and communicate like coroutines. The system
includes comparisons of the system with VAX 750, Xerox Dandelion and
Symbolics 3600.
%T What's New
%J Byte
%D APRIL 1987
%V 12
%N 4
%P 42
%K AI05 AT02
%X Voice-Scribe 1000 recognizes 1000 words with 99.3& accuracy. It costs
$1195.00
%T CAN AI Vault into the Banking Industry
%J ComputerWorld
%V 21
%N 10
%D March 9, 1987
%P 72-73
%K AA06 Cogensys Syntelligence Wells Fargo First Wachovia Bank
AI01 AI02
SWIFT electronic fund transfer
%X Cognitive Systems and Citibank Information Resources are marketing
systems to assist in formatting and understanding SWIFT messages
for electronic fund transfer. Cognitive Systems developed Courtier
for Societ de Generale de Bankque in Brussells. This system is
a porfolio management system with natural language interface.
%A Alan J. Ryan
%T Hiring AI Pros Can be Tricky
%J ComputerWorld
%V 21
%N 10
%D March 9, 1987
%K personnel Robert Half
%X Robert Half sees little market for AI specialists. Some vendor
companies are laying off which lowers the demand.
%A Dwight B. Davis
%T Artificial Intelligence Goes to Work
%J High Technology
%D APR 1987
%V 7
%N 4
%P 16-24
%K American Express ART Bob Flast Laurel Miller AI01 AA06 AA05 AA04 AA26
APEX Applied Expert Systems AA18 Westinghouse electric power distribution
relay AI07 Ford Motor AA21 Linda Farrell Home Owners Warranty AI06 AA09
%X American express Corporation has an AI system to help approve
charge authorizations that are outside the typical credit patterns.
One of the original purchasers of Plan Power says that for simple
plans it provides "A-quality" plans and for "very complex" plans,
it works at a "C+-quality"
Northrop is using AI to develop plans for the manufacture of parts
in military aircraft. The system interfaces iwth PC's for the part
description data and a simulation package (SIMKIT) to verify the plans.
They are working to interface the system directly to the CAD/CAM
database. The system also discusses the CORA system to help specify
and customize relay-protection systems for utilities.
Ford Motor is developing a ROBOT diagnosis system on IBM PC's.
The system is already in use and they are making available the
system code to any interested robot supplier. They found that
20% of the necessary rules handle 60 to 80 percent of the problems.
More/2 helps direct mailers optimize their mailings. It examines
the results of previous mailings and limited test mailings.
Also a discussion of Home Owner's Warranties with Artificial Intelligence's
Intellect natural language database interface.
%A Alan J. Ryan
%T RCA to Spruce Voice Package
%J Computer World
%V 21
%N 12
%D MAR 23, 1987
%K AT16 Verbex RCA AI05
%X RCA will integrate VERBEX's continuous speech technology in research
and development projects.
%A Henry Firdman
%T Use English to Sell AI
%J Computer World
%V 21
%N 12
%D MAR 23, 1987
%P 19+
%K AT22
%X Argument that AI company salesman should address the customer's problems.
Also calls for a rise of companies that integrate AI tools with
custom programming to solve a customer's application. England
has two companies AI Ltd and Vanilla Flavor Co. that does this sort of work.
%T Software and Services
%J Computer World
%V 21
%N 12
%D MAR 23, 1987
%P 34
%K Waterloo Watcom Products Mystech Associates T02 T03 AT02
%X Watcom Products from Waterloo has announced a Prolog interpreter
for the IBM mainframe for $1800.00. Mystech Associates sells
expert system tools for Xerox Corp. 1100 ($3500.00), Common
Lisp under IBM PC ($1500 to $2000.00) and C under IBM PC ($2000.00 to $2500.00)
%T Hard Bits
%J Computer World
%V 21
%N 12
%D MAR 23, 1987
%P 64
%K H03 BBN Butterfly MITRE FMC NRL
%X BBN Butterfly sales include Mitre Corporation, FMC, Naval Research
Laboratories and Indiana University
%T Palantir Enhances Processing
%J Computer World
%V 21
%N 12
%D MAR 23, 1987
%P 68
%K AT02 AI06 Palantir
%X Palantir is now selling scanners which includes software to deal
with the reading of poor quality photocopies. They cost $3500.00
%T Software Helps Manage Expert-System Database Storage
%J Computer
%D MAR 1987
%P 92
%V 20
%N 3
%K AT02 AA09 AI01 Software A&E Knowledge-Based Engineering H01
%X DBA Assistant helps manage data base storage. Current versions are
for the IBM PC to work with Cullinet IDMS/R2. Later versions will
support IBM DB2 and Sperry dMS-100.
%T Golden Retrieval Uses AI to Find and Fetch Text
%J Computer
%D MAR 1987
%P 92
%V 20
%N 3
%K AT02 H01 AA14
%X a system to search files for text that can handle queries where spelling
is unclear or the order of words is unknown. S. K. Data, P. O. Box 413,
Burlington, MA 229-8909, $99.00
%T Common Lisp System Interfaces to Microsoft C
%J Computer
%D MAR 1987
%P 90
%V 20
%N 3
%K H01 AT02 T01
%X TransLisp Common Lisp runs on IBM PC and interfaces ith Microsoft C.
Solution Systems, $195.00
%T AI Tools Helps Design Application Interfaces
%J Computer
%D MAR 1987
%P 90
%V 20
%N 3
%K T01 H01 AT02
%X Expertelligence has linked their Common Lisp language to various
application tools on the Macintosh to do application interfaces.
%A James Connolly
%T Builders Will Test Engine
%J ComputerWorld
%V 21
%N 11
%D MAR 16, 1987
%P 51+
%K AT02 H03 H02 Bettex
%X Bettex will be selling an engine supporting both symbolic processing
and parallel processing. It has 1 million pixel/second graphics
and special hardware/software for desktop publishing type applications.
%A James A. Martin
%T IBM Recruits Syntelligence
%J ComputerWorld
%V 21
%N 11
%D MAR 16, 1987
%P 89+
%K AT16 AI01 AA06
%X IBM will be joint marketing Syntelligence's expert systems for insurance
underwriting and commercial lending.
%A Theodore F. Lehr
%A Robert G. Wedig
%T Toward a GaAs Realization of a Production System Machine
%J Computer
%D April 1987
%P 36-46
%V 20
%N 4
%K OPS5 RETE H02 AI01
%X Describes a uniprocessor configuration for the implementation of
such languages as OPS5 and the RETE Algorithm.
%T Symbolics Signs Two Resellers
%J Electronic News
%V 33
%N 1648
%D MAR 30, 1987
%P 38
%K AT16 H02 Symbolics Evans and Sutherland Thinking Machines AI12
%X Symbolics has signed var agreements with the makers of the Connection
Machine and the Pixar graphics unit.
%A Charles Bermant
%T Hand Scanner Reads Data Into Programs
%J Infoworld
%V 9
%N 13
%D MAR 30, 1987
%P 1+
%K AI06 AT02 H01
%X Saba Technologies
is selling a hand-held reader for typewritten, laser-printer, line-printed
and dot-matrix printed text with an error rate of 1 in 1300 (better than
typing).
%T Expert System Designed for Apollo Workstations
%J Infoworld
%V 9
%N 13
%D MAR 30, 1987
%P 1+
%K Apollo Palladian AI01 AA06 AT02 AT16
%X Palladian's Management advisor has been ported from Lisp Machines to
the Apollo Workstation.
%A Jeff Angus
%T Avyx Develops Specialized Scheduling System for NASA
%J Infoworld
%V 9
%N 13
%D MAR 30, 1987
%P 10
%K scheduling project management AI01 AT02 H01
%X An MS-DOS AI based project scheduling system, originally developed
for NASA, is available from Avyx for $995.00
%A Edward Warner
%T Arity Uses Lotus Funding to Ready AI Applicato/n
%J Infoworld
%V 9
%N 13
%D MAR 30, 1987
%P 27
%K AI01 H01 AT16 T02
%X Arity will be introducing a business tool with financing from
Lotus and Bank of America. They also anticipate a new version of its PROLOG
with windows and built in editor. Users of Arity Prolog with percentage
of Arity Prolog sales attributable to each use.
.DS L
DS L
software developer 50%
education and R&D Labs 20%
government and contractors 10%
industrial users 10%
commercial users 10%
.DE
DE
%A Y. V. Reddy
%A Ravi S. Raman
%A Rafal T. Dziedzic
%A Alan W. Bucher
%A Narendar A. Reddy
%T A Unified Approach to AI Programming
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 587-594
%K AA03 T01 AA28
%X describes an integrated AI tool including standard expert system
stuff, knowledge-based simulation, database interface,
object based programming, alternate worlds that is written in C.
Also includes a brief discussion of AI applications to coal mining.
%A Nayel El-Shafei
%T Quantitative Discovery and Reasoning about Failure Mechanisms in
Pavement
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 595-608
%K AA05 AI03
%X The application here is to deal with a field in which new theories
for pavement failure are being developed and it is desired to integrate
these with test cases to help. Th learning work is an extension on BACON
in that it uses dimensional analysis to insure that theories proposed
have physical meaning. It also uses step-wise regression.
%A Michael J. Freiling
%A Steven Rehfuss
%A James H. Alexander
%A Steven L. Messick
%A Sheryl J. Shulman
%T The Ontological Structure of a Troubleshooting System for Electronic
Instruments
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 609-620
%K AI16 AI01 AA04 AA21 AI15 HIPE SPOONS oscilloscope Tektronix
entity relationship model denotational semantics
%X This is a system to allow the entry of the data needed to diagnose
faults in electronic instruments such as oscilloscopes.
This describes a formal approach for defining the physical properties
of the objects, the state space and heuristics using denotational
semantic techniques.
%A Jean Patrick Tsang
%T Genericity in Expert Process Planning Systems
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 621-637
%K machining AA05 assembly AA26 AI01
%X Describes a generic expert system for machining and assembly.
%A D. V. Zelinski
%A R. N. Cronk
%T ES/AG: An Expert System Generating Environment and Its Use in Engineering
Applications
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 639-649
%K OPS5 AA05 inductor magnetic configuration local area network T01 T03
%X Describes an expert system tool that evolved from a configuration/ordering
expert system for 5ESS telephone switches. The system has been used in
local area network expert systems nad the design of magnetic components
such as inductors. It has been benchmarked against OPS4 and performed
the same task in 1/20 of the time. It is also interfaced with the
Franz Lisp and XLISP systems.
%A R. H. Allen
%T Design Guidelines for Expert Systems
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 1
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 651-658
%K AT08 T03 AI01
%X describes a classification for expert systems and a list of types of
expert system tools.
%A John L. Wilson
%A George K. Mikroudis
%A Hsai-Yang Fang
%T GEOTOX: A Knowledge-Based System for Hazardous Site Evaluation
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 661-671
%K AA03 AA10 AA05 O04 AI01
%X This system assists an engineer in evaluating hazardous waste dumps
providing expertise in hydrology, civil engineering, geology, chemistry,
demography and climatology needed for this task.
%A Jorgen Bo Nielsen
%T A Learning System for Identification and Ranking of Severe Storms
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 673-685
%K meteorology oil drilling North Sea AI01 AI04 AA16 AA03
%X This system will look at the meteorological data and identify those
storms that are the most severe and determine the sea-states that those
storms would have caused. The system has been validated and used in
North Sea offshore oil drilling platforms.
%A Sten Lindberg
%A Jorgen Bo Nielsen
%T Modelling of Urban Storm Sewer Systems
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 687-696
%K AA05 AI01 MOUSE AA15
%X An expert system is to be integrated in the MOUSE system for sewer
design to provide consulting expertise and to assist the user in
resolving numerical instability problems. An installation expert
system already exists.
%A Ashok Gupta
%A Arvind K. Jain
%T Application of Artificial Intelligence in Offshore Structures
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 699-706
%K AI01 AA05
%X provides a general framework for expert system for analysis and design
of offshore structures.
%A John C. Kunz
%A Thomas Bonura
%A Marilyn J. Stelzner
%A Raymond E. Levitt
%T Contingent Analysis for Project Management Using Multiple Worlds
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 707-718
%K AI13 AI16 Intellicorp AA03 offshore oil drilling AI15 AI01 AA05
%X Project plans for concrete gravity
offshore oil drilling platforms in the North Sea are treated in
a decision support environment. The Intellicorp "multiple world" feature
is used to help the user understand results of various decisions.
%A R. Pearse
%A M. Rosenbaum
%T The Evaluation of Proposed Road Corridors by the Use of an Expert System
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 699-706
%K AI01 AA05 T02 AI12 AI15
%X This proposed system considers engineering factors, social, economic and
environmental factors in choosing the path for a road.
%A Ian C. Taig
%T Expert Aids to Finite Element System Applications
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 759-770
%K PATRAN mesh generation optimization AA05 AI01 AI03 domain expert
%X This finite element analysis system aid assists in mesh generation,
helps decide how to model joints ando ther features, negotiates iteratively
the problem size, mesh size to insure that the analysis can be done in
the available computer time and space. It has no interface to the
finite element system. It is a 2000 rule expert system and was
produced by a finite element analysis expert (a compiler of the
NAFEMS Guidelines to Finite Element Practice). Other efforts to
be done include interface to PATRAN and use with shape optimization.
%A Michael A. Rosenman
%A John S. Gero
%A Rivka Oxman
%T An Expert System for Design Codes and Design Rules
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 745-758
%K O01 Build T03 T02 SUN AA05 architecture kitchen Australian Model
Uniform Building Code
%X This system assists in the design of buildings and is based
upon design codes. It includes an interface that allows a display
of the drawing of a house layout while the expert system is being
consulted.
%A P. H. Milne
%T An Expert System for Road Curve Design and Setting Out
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 733-743
%K AI01 Apple II-C Basic H01 AA05 surveying theodolite
%X This system allows for the design of the curves necessary in
a road to make turns, allow banking of cars or to deal with changes
in height. It also assists with the survey task in the field in actually
building the road.
------------------------------
End of AIList Digest
********************
∂06-May-87 0004 LAWS@Stripe.SRI.COM AIList Digest V5 #110
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 6 May 87 00:04:25 PDT
Date: Tue 5 May 1987 21:49-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #110
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 6 May 1987 Volume 5 : Issue 110
Today's Topics:
Queries - Common Lisp Books & CAD Document Scanning &
CSG --> Octree Spatial Representation Translation & DataFlow &
Expert Systems for Networking & Extracting Knowledge From Databases,
AI Tools - OPS5 Addresses & Kyoto Common Lisp Addendum,
Application - Grammar Checkers
----------------------------------------------------------------------
Date: 4 May 87 21:23:19 GMT
From: bill@hao.ucar.edu (Bill Roberts)
Subject: Good Common Lisp books
Can anyone make a comparison between Wilensky's "CommonLispCraft" and Tatar's
"A Programmer's Guide to Common Lisp"? What are the strengths and weaknesses
of each book? I know about Steele's book but it is in a different class.
Thanks in advance for any input.
Bill Roberts
NCAR/HAO
Boulder, CO
!hao!bill
------------------------------
Date: 4 May 87 18:37:06 GMT
From: nsc!amdahl!ptsfa!jeg@decwrl.dec.com (John Girard)
Subject: RFI - CAD Systems that can scan existing documents
RFI - CAD
This is a request for information from the *academic* sector.
There are several other people working on the commerical sector
offerings.
Our company has a significant number of hand-drawn diagrams
depicting sites and equipment. We would like to get these
documents into electronic media *and* simultaneously develop an
automated inventory. The documents are fairly consistent and
contain a limited number of symbols, although sometimes the
symbols may be touching. The length of lines connecting the
symbols and the types of lines is important.
The known alternatives are:
Manual data base entry and manual CAD composition
Video scan of documents followed by "touch up" and manual
data base entry
Highly automated scan of documents with automatic touch up,
automatic object identification, and automatic data base
entry - manual monitoring and minor manual adjustments.
Obviously the 3rd alternative is the best. Is anyone working on
this type of problem?
Please contact LALEH FARR
PACIFIC BELL
2600 CAMINO RAMON
ROOM 2S500T
SAN RAMON, CALIF.
U.S.A. 94583
415-823-7277
------------------------------
Date: Mon, 4 May 87 22:56:41 PDT
From: dmittman@Jpl-VLSI.ARPA
Subject: CSG --> Octree Spatial Representation Translation
Does anyone know of a Common Lisp (Symbolics, perhaps) implementation of
a conversion between Constructive Solid Geometry and Octree representations
of spatial configurations? Whatever you have would be appreciated. I hate to
reinvent tools which already exist. - David Mittman
DMITTMAN@JPL-VLSI.ARPA
------------------------------
Date: 4 May 87 23:55:35 GMT
From: jade!lemon!c60a-3ed@ucbvax.Berkeley.EDU (Sugih Jamin)
Subject: DataFlow
I don't know if this is the right news group for this question,
but, can anyone tell me what is the best introductory/reference
book to Data Flow system/language/architecture(?) ?
Sugih Jamin
(c60b-jk@buddy.Berkeley.Edu)
------------------------------
Date: 5 May 87 13:13:51 GMT
From: super.upenn.edu!operations.dccs.upenn.edu!shaffer@RUTGERS.EDU
(Earl Shaffer)
Subject: Expert Systems for networking
Hello:
We are looking for a PC or VAX based expert system that
is capable of handling rules that describe network fault
diagnosis.
Therefore, its rule base capability must be significant,
and its inference capabilities must be rich (backward,
forward, mix). The PC version would be a "portable
expert", whereas the VAX version would be smarter,
bigger, and unmovalbe.
Cost is a factor! Forget ART of KEE. Any help would
be appreciated.
thanx,
------------------------------
Date: 5 May 87 20:51:19 GMT
From: decvax!necntc!ci-dandelion!bunny!gps0@ucbvax.Berkeley.EDU
(Gregory Piatetsky-Shapiro)
Subject: Extracting Knowledge From Databases
******* This is not a line-eater line ******
I am interested in extracting Knowledge from Databases.
For example, by analyzing a medical database, a system can discover
new effects of known drugs (such project was done by Blum & Wiederhold
at Stanford, 1982); by analyzing the planet movements, one may
discover Kepler's third law (this project was done by Kepler).
A more prosaic application is analyzing
a telephone company customer database to find what types of customers
order what types of services. In general, the discovered knowledge
may have the form of rules, functional dependencies,
causal dependencies, or statistical correlations.
A closely related topic is Statistical Expert Systems,
which intelligently use statistical methods and packages to
find statistical correlations in data.
If you know of work in these areas, please email the appropriate
references to me. I would be very grateful and will
summarize the responces to the net.
Gregory Piatetsky-Shapiro at GTE Laboratories.
gps0@gte-labs.relay.cs.net
======== A standard disclaimer =======
------------------------------
Date: 17 Apr 87 00:32:18 GMT
From: decvax!wanginst!masscomp!dlcdev!eric@ucbvax.Berkeley.EDU (eric
van tassell)
Subject: OPS5
To all those of you who asked me to mail OPS5 to them and only gave
arpa addresses of the form. foo@bar.baz, please help a net neophyte
at a uucp only site comprehend how to translate this into a path
from my machine that won't upset the mailer at mit-eddie.
Eric Van Tassell
Data Language Corp.
617-663-5000
clyde!bonnie!masscomp!dlcdev!eric
harvard!mit-eddie!dlcdev!eric
dlcdev!eric@eddie.mit.edu
------------------------------
Date: Tue, 5 May 1987 21:24 EDT
From: "Scott E. Fahlman" <Fahlman@C.CS.CMU.EDU>
Subject: Kyoto Common Lisp addendum
A clarification from Mr. Yuasa:
To whom it may concern,
It seems that the previous note of ours, announcing that we are looking
for a free channel for KCL distribution, may have brought confusions and
misunderstandings to many people. It may be mostly because only the
facts were mentioned, with no explanation of the background necessary to
understand our intention.
Our intention is to make it clear that KCL is an academic free software.
By "free", we mean that any one can get it free of charge, if he agrees
the conditions we put in the License Agreement. It does NOT mean that
anyone has any *free*dom for KCL. In particular, we have no intention
to put KCL into the public domain. We would rather like to keep the
identity of KCL, so that we can keep up its high quality.
Some commercial organizations are now distributing KCL and they charge a
certain amount of fees to their customers. These fees are exclusively
for the distribution costs and the service they offer to their
customers. We require no royalties to them. We are happy if more
people have got the chance to use this software. It is a voluntary work
if we give them technical help on their requests.
Unfortunately, some people believe that we are receiving royalties for
KCL. In order to overcome this wrong belief, we decided to look for a
free channel for KCL distribution. Apparently, some KCL users
(including potential users) do not need any maintenance service at all.
We are glad to make KCL available to such users for free. Note that we
do not intend to restrict the activities of commercial organizations for
KCL distribution. We intend to give a choice to the user and to make it
clear what the user is charged for by commercial organizations. Note
also that some KCL versions require additional programs developed by
commercial organizations and we cannot force them to make their code
open to the public, though we expect them to do so.
We are now seriously looking for a free channel. We already found some
candidates, but it will take some time before we decide the best
appropriate channel for our purpose. In case we cannot find an
appropriate channel, we ourselves will directly distribute KCL.
However, this will require a lot of work and we will have to spend a lot
of time. So, this should be the last solution.
Thanks.
Taiichi Yuasa, Dr.
Research Institute for Mathematical Sciences
Kyoto University
------------------------------
Date: Mon, 4 May 87 12:18 EST
From: "Linda G. Means" <MEANS%gmr.com@RELAY.CS.NET>
Subject: re: grammar checkers
mom: toaster oven, kimono Todd Ogasawara writes in AILIST Digest v.5 #108:
>I think that if these style checking tools are used in conjunction
>with the efforts of a good teacher of writing, then these style
>checkers are of great benefit. It is better that children learn a
>few rules of writing to start with than no rules at all. Of course,
>reading lots of good examples of writing and a good teacher are still
>necessary.
Sure, but the problem is the bogus rules that the child is likely
to infer from the output of the style-checking program, like never
write a sentence longer than x words, or don't use passive voice,
or try not to write sentences with multiple clauses.
>On another level... I happened to discuss my response above with one
>of my dissertation committee members. His reaction? He pulled out
>a recent thesis proposal filled with red pencil marks (mostly
>grammatical remarks) and said, "So what if the style checkers are
>superficial? Most mistakes are superficial. Better that the style
>checker should find these things than me."
Sounds like a rather irresponsible attitude to me, given the state
of the art of automatic style checkers. Your prof needs a graduate
student slave if he dislikes having to correct student grammar
errors. Let's consider separately the issues of grammar correction and
stylistic advice (the two worlds partially overlap, but remain distinct
some areas).
1. Grammar. As your prof points out, lots of grammar errors are
superficial, but your commercial grammar checker will fail to find all
of them, correct perceived mistakes which really aren't, and give plenty
of bad advice. Those programs "know" less about grammar than the students
who use them. Any bonafide grammatical errors which can be found by the
commercially available software could also be found by the writer if he
were to proof his paper carefully. It grieves me to think of students
failing to proof their own papers because the computer can do it for them.
2. Style. The analysis of writing style is not a superficial task; it is,
in fact, a kind of expertise not found in many "literate" individuals.
In my experience, the best way to learn to write well is to scrutinize
your work in the company of a good writer who will think aloud with you
while helping you to rewrite sentences. I've successfully taught various
people to write that way. The second best method is a patient teacher's
red pen. In both cases, your prose is being evaluated by someone who is
trying to understand what you are trying to communicate in your writing.
You must understand that this is not the case with the computer. It
probably has no way of representing the discourse as a whole; all analysis
is performed at the sentence level with a heavy emphasis on syntax and
with no semantic theory of style. The result? Stylistic advice which
is so superficial as to be useless. Many years of research in the area of
computational stylistics have provided evidence that although some (few)
stylistic discriminators can be found through syntactic analysis, the
features which contribute to textual cohesion and to a given writer's
"stylistic fingerprint" cannot. Researchers are still stymied by the
problem of identifying stylistically significant features of a text.
Yet the program advocated by Carl Kadie feigns an understanding of the
effect that the prose will have on its reader; it generalizes from
syntactic structure to stylistic impact. Look at the summary generated
at the end of the text. The program equates active voice and short
sentences with "directness". I won't take the time here to argue
against the use of fuzzy adjectives like 'direct', 'expressive', 'fresh',
and so on to describe prose, since the use of such imprecise language
is a longstanding tradition in the arena of literary criticism. I can't
tell you exactly how to make your writing "direct", but I know that
directness cannot always be computed empirically, which is how your
machine computes it. A paragraph of non sequiturs probably shouldn't
be characterized as direct, even if all sentences are short and contain
only active verbs.
An aside to Ken Laws:
You questioned whether the topic of automatic style checkers is appropriate
to AILIST: is it AI? I believe it is. The study of computational stylistics
is a difficult natural language problem with a long history. Topics range
from authorship studies of anonymous works to trying to identify stylistic
idiosyncrasies to automatic style advisors. In general, many theoretical issues
carry over from other areas of natural language processing, like discourse
analysis and understanding human reasoning processes. Think of a favorite
author. You may sometimes recognize a sample of his writing without
even knowing who wrote it, or you may say of another writer, "Gee, his
style reminds me of X". You may put down a book which you started reading
because the style is too "obtuse". How specifically does a writer use the
language to produce that effect? What characteristics of a text must we
identify to enable a computer to make judgments about style? Of course,
any advances made in tackling these issues may also be of use in the area
of text generation.
- Linda Means
GM Research Laboratories
means%gmr.com@relay.cs.net
------------------------------
Date: Sun, 3 May 1987 23:35 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #108
I agree with Todd, Ogasawara: one should not criticise to extremes. I
found RightWriter useful and suggestive. It was helpful in detecting
obnoxious passive constructions and excessively long sentences. In
final editing of "The Society of Mind" I used spelling checkers to
notify me of unfamiliar words, and I often replaced them by more
familiar ones. I also used it to establish a "gradient". The early
chapters are written at a "grade level" of about 8.6 and the book ends
up with grade levels more like 13.2 - using RightWriter's quaint
scale.
Naturally the program makes lots of errors, but they are instantly
obvious and easily ignored.
I imposed a "style gradient" upon "The Society of Mind" because I
wanted its beginning to be accessible to non-specialists. I
cheerfully assumed that any reader who gets to the end will by then
have become a specialist.
------------------------------
End of AIList Digest
********************
∂07-May-87 2207 LAWS@Stripe.SRI.COM AIList Digest V5 #111
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 7 May 87 22:07:10 PDT
Date: Thu 7 May 1987 09:22-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #111
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 7 May 1987 Volume 5 : Issue 111
Today's Topics:
Queries - Pattern Recognition Application & IJCAI Information &
Multiexpert Knowledge Systems,
Review - Books on Common Lisp and Prolog,
Linguistics - Style Checkers,
Speech Understanding - Difficult Speech Examples
----------------------------------------------------------------------
Date: Wed 6 May 87 11:22:00-PDT
From: Ken Laws <LAWS@STRIPE.SRI.COM>
Subject: Wanted: Pattern Recognition Application
I'm trying to work up a proposal for research in classificatory
neural networks. The computational end is easy, but I need an
application that will provide the data for experimentation. I
need either real-world data or (perhaps even better) a way to
synthesize interesting data. I'm already aware of some work in
image analysis, speech recognition, and character recognition,
but would be interested to hear from people who have current
problems that are not being adequately addressed. Can you suggest
any other pattern recognition problem or "signal" of particular
interest to the Air Force, Navy, Army, NASA, NSF, or other funding
agency?
-- Ken Laws
LAWS@STRIPE.SRI.COM
(415) 859-6467
------------------------------
Date: 5 May 87 20:35:45 GMT
From: hao!gatech!akgua!emory!cmb@ames.arpa (Chang Bang)
Subject: help me
(1) I am getting no information about IJCAI
in Italy. Help me.
(2) I would like to know an economical way to
attend IJCAI in Italy. Help me.
------------------------------
Date: Thu, 7 May 87 09:59:03 edt
From: dg1v#@andrew.cmu.edu (David Greene)
Subject: Multiexpert Knowledge Systems
Does anyone have information on "multiexpert knowledge systems" (MKS).
Specifically a recent blurb in Business Week (May 11, pg.141) mentioned a
system by Major Stephen R. LeClair of the AI group at the Materials Lab. at
Wright-Patterson A.F.B. The system combines expert knowledge from multiple
domains to solve complex problems in manufacturing.
I'm currently starting work on a learning program which attempts to
coordinate disperate knowledge bases to solve a problem so I would greatly
appreciate any information on MKS (or relevant areas).
Thanks.
dg1v@andrew.cmu.edu
------------------------------
Date: Wed 6 May 87 20:03:29-EDT
From: John C. Akbari <AKBARI@cs.columbia.edu>
Subject: books on common lisp & prolog
>Can anyone make a comparison between Wilensky's "CommonLispCraft" and Tatar's
>"A Programmer's Guide to Common Lisp"? What are the strengths and weaknesses
>of each book? I know about Steele's book but it is in a different
>class.
>...
> Bill Roberts
Having spent some time working with several people in learning to
become programmers, I have a few comments regarding books available
(titles are approximate, don't have them in front of me):
in general, experience points to several important needs when teaching
& selecting stuff:
- students learn well by studying *working* examples, both in terms of
how to program as well as details like style, data abstraction, etc.
providing well-documented examples motivates all sorts of queries
regarding syntax, efficiency, portability, etc. as well.
- the trade-off between presenting concepts & gory details is a
personal matter, but i've found that some amount of both needs to done
at the beginning. once the student begins to think in the
mind-expanding frame of lisp (rather than, say, c), more & more
details can be presented, relying on the student himself to find out
about implementation details on his own.
COMMON LISP
not familiar with tartar's book. the following three are the best I
know of for learning. would recommend using winston & horn and
wilensky almost concurrently initially (personal choice as to which
offers a clearer intro to lisp concepts), followed by the second half of
winston & horn for applications. those interested in learning much
more about hacking should spend more time with wilensky. steele tends
to be useful after one has learned a fair amount about lisp hacking in
general. would use with abelson & sussman _structure & interpretation
of computer programs_ (mit press) for great intro to concepts
(streams, data-driven programming, ...).
steele. _common lisp: the language_ digital press, 1984.
besides being the de facto standard in most ways, it is also helpful
when trying to port across machines (much easier than lugging around
documentation for symbolics, ti, lucid, vax lisp...). also good for
those late-night hacking sessions (steele manages to imbue
mind-boggling minutiae [spelling?] with a dash of humor). not
necessarily recommended bedtime reading, however (except for
masochists).
wilensky. _commonlisp craft_ norton.
an excellent, readable intro to common lisp hacking, with just the
right blend of tutorial & documentation. tends to go much more into
the details of common lisp than does winston & horn, but still in a
readable, useful format. last chapter or so presents a pattern matcher.
winston & horn. _lisp_ (2nd edition) addison-wesley.
good, readable intro to lisp in general, with common lisp almost an
incidental choice of dialect. tends to rapidly leave low-level
details in preference for looking at ai applications of lisp. very
helpful in introducing people to concepts that have been robustly
developed elsewhere (e.g., there is a simple frame system, simple
intro to object oriented programming via FLAVORS, mathematical
examples, pattern matcher, expert system inference engine, etc.).
PROLOG
prolog is as different from lisp as lisp is from c, at least in terms
of teaching it. would begin with bratko, followed by sterling &
shapiro after student has done a bit of prolog programming. introduce
clocksin & mellish somewhere in between.
bratko. _introduction to prolog programming for artificial
intelligence_. addison-wesley.
great intro to the language. presents just enought about
backtracking, unification, etc. along with examples to be of real
value. gives many examples & exercises. not too much humor, though.
examples of searching, expert system shells, games, etc.
sterling & shapiro. _the art of prolog_. mit press.
excellent book on advanced topics in prolog: garbage collection,
efficiency, top-down vs. bottom-up construction of data structures,
etc. many such topics have not been covered elsewhere, and are done
very well. would not recommend to inexperienced, motivated people;
first part tends to be a mathematical intro which may not be appealing
to some.
clocksin & mellish. _prolog_ springer-verlag.
standard text. a little hard to read at times, tends to bog down in
gory details before reader has feel for language as whole.
let me know if this helps.
john c akbari
ARPANET & Internet akbari@CS.COLUMBIA.EDU
BITnet akbari%CS.COLUMBIA.EDU@WISCVM.WISC.EDU
uucp & usenet ...!seismo!columbia!cs!akbari
DECnet akbari@cs
PaperNet 380 riverside drive, no. 7d
new york, new york 10025 usa
SoundNet 212.662.2476
------------------------------
Date: 6 May 87 12:46:57 GMT
From: gilbert@aimmi.UUCP (Gilbert Cockton)
Reply-to: gilbert@hci.hw.ac.uk (Gilbert Cockton)
Subject: Style checkers
In article <8704250321.AA15773@uhmanoa.ICS.HAWAII.EDU> todd@humu.UUCP
(The Perplexed Wiz) writes:
>In article <12295086246.19.HAYES@SPAR-20.ARPA> HAYES@SPAR-20.ARPA writes:
>>Let me briefly add a seconding voice to Linda Means comments on the horrible
>>output of the style-criticising programs illustrated a while ago. That
>>people should suggest using such things to influence children almost makes
>>me agree with Weizenbaum.
>I think that we have two extreme views here. I agree that the style
>checkers available for microcomputers are not very sophisticated. I also
>agree that such tools should not be used exclusively to teach children
>(or any other age group for that matter). However, to say that these
>microcomputer based style checkers have no place in teaching children
>to write in not correct.
A few simple grammatical rules (concord, apostrophes, tense structure,
clausal agreement), as these style checkers stand, you are most incorrect -
and I am even more surprised at such comments when they come from a psychology
grad - unless you're doing AI or rat research that is in which case
you're probably a long way from mainstream psychology:-).
The problem with most checkers is that the rules they embody have
often just been made up by technical writing pundits. As long as they
stick to indoctrinating those engineers and other culturally deprived students
WHO NEED HELP WITH THEIR WRITING (not all do), I don't mind - they probably do
improve the writing of some people from dreadful and unintelligible to
ugly and constipated :-).
However, the minute their jibberish is proposed as something for the
whole school population, then the authority of the armchair
philistines has to be scrutinised carefully. There is not an ounce of
decent psychological research on text comprehension behind most of the
pronouncements of technical writing rednecks. As for literary
aesthetics, this doesn't get a look in - anyone care to stick a novel
through one of these joke programs?
So, the first prerequisite for style checkers in schools is proper
experimental validation of the rule base - breaking/obeying rules
must be shown to have a measurable effect on comprehension
performance.
The second prerequisite is the harder one and takes us into the
Weizenbaum camp - the rules checked in the experiments must be
translated faithfully into a program - not easy as we know that
our current formal representations of language and knowledge are
wholly inadequate, and given the nature of computation may never be
adequate. Philosophical objections apart, I will never trust programmers with
no background in what they are programming to get the job right unless
the domain experts have a cast iron way of validating the program (this works
well for many science and engineering problems, as well as for simple
data processing).
So, the current style rules aren't rules, and even if they were their
encapsulation in a computer program cannot be proven.
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.aimmi ARPA: gilbert%aimmi.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..!{backbone}!aimmi.hw.ac.uk!gilbert
------------------------------
Date: 4 May 1987, 16:32:35 EDT
From: Norman Haas <NHAAS@ibm.com>
Subject: Difficult Speech Examples
Two speech recognition trickies from Eng. Lit.:
Our Glass Lake (Hourglass Lake) -- Nabokov
Make-Believe Express (Maple Leaf Express) -- Thurber
------------------------------
Date: 4 May 1987 2252-PDT (Monday)
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Updated list of speech examples
For future purposes, I will be placing a copy of my speech examples
lists on the ames-aurora.arpa host. (Don't check yet.) I've posted
them here and for the comp.ai group on usenet. In the future, I
will separate the ACKs as below for possible liability reasons and to
credit the group as a whole. I will update yearly. The last addition
is particularly interesting. See that type of "writing" has a use after
all.
FYI, aurora is an upgrade of a system which originally did speech synthesis
on an old V*x system, so I only think it appropriate it goes there.
Happy hunting with this little bit of `network memory.'
P.S. I was asked for more Japanese examples, so if anyone in Japan is
working on the subject, I would appreciate examples, I won't be going there
until Fall of 1988 (Cray User Group meeting and more). And this appears
to be a critical area.
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
Acknowledgements:
elman@amos.ling.ucsd.edu (Jeff Elman)
mcguire@aero2.aero.org
minow%thundr.DEC@decwrl.DEC.COM Martin Minow (ex-DECtalk developer)
Marc Majka <ames!seismo!ubc-vision!vision.ubc.cdn!majka>
Joseph_D._Becker.osbunorth@Xerox.COM
Stephen Slade@Yale.Arpa
Keith F. Lynch <KFL%MX.LCS.MIT.EDU@MC.LCS.MIT.EDU>
George Swetnam m06242%mwvm@mitre.ARPA
Erik A. Devereux <GV.DEVEREUX@A20.CC.UTEXAS.EDU>
"In mud eels are, in tar none are".
grey day / grade A
euthanasia / youth in Asia
"Whats that up in the road" ahead / a head?
"Take off your hat and dloves"
and then ask them what you said. 99% of all people will insist that
you said the word "gloves".
I'd be happy if you could do the digits, including "Oh", and Yes/No.
Continuous digits, telephone quality, no training, male and female voice.
The problem is in distinguishing "oh" from "no".
Getting the alphabet (not "alpha", "bravo", but "aye", "bee") would
be nice, too.
I love you
Isle of View
I think you need at least one example in Chinese, and here's my favorite
(because I actually said it by mistake). The numbers after the words
are phonic "tones". What I meant to say was:
Wo(3) hen(3) xiang(3) shui(4)-jiao(4) -- I want to go to sleep
... but what I actually ended up saying was:
Wo(3) hen(3) xiang(4) shui(3)-jiao(3) -- I am like a boiled ravioli
"ice cream"/"I scream"
"beginning"/"big inning"
"soccer"/"sock her"
"its hardware problems are intermittent"/"it's hard where problems ..."
"attacks"/"a tax"
from Mark Twain:
"Good-bye God, I'm going to Missouri."/"Good, by God, I'm going to Missouri."
A notion of water/an ocean of water.
[New York accent only] An arm and a leg/a nominal egg.
Years ago at Bell Labs, I heard the following:
"Joe took mother's shoe bench out; she was waiting at my lawn."
With regard to difficult speech recognition problems, I just saw
variations of the following on the wall of a mens room, so credit goes
to anonymous students at the University of Texas:
``Our understanding of urine formation was clearly wrong.''
``Our understanding of your information was clearly wrong.''
------------------------------
Date: Wed, 6 May 87 09:58:39 pdt
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Speech.examples installed on ames-aurora.arpa
For some reason, our news system is not receiving the AI list.
I have installed the file pub/speech.examples for anonymous login.
Someone else noted the lack of AI and cognitive "biggies" donating
examples. Don Norman contributed an additional example from his book,
so if you are concern with this topic you can try ftp. Someone
can let me know if it works. See you all in a year when I ask for updates.
[January]
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
End of AIList Digest
********************
∂10-May-87 1920 LAWS@Stripe.SRI.COM AIList Digest V5 #112
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 May 87 19:20:34 PDT
Date: Sun 10 May 1987 16:45-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #112
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 11 May 1987 Volume 5 : Issue 112
Today's Topics:
Presentation - Columbia AI/VLSI Project,
Course - Automated Mathematical Reasoning,
Conferences - Automated Reasoning Workshop &
Volunteers still needed for AAAI &
Hawaii Conf. on System Sciences &
ACL Applied Natural Language Conference
----------------------------------------------------------------------
Date: Tue, 28 Apr 87 07:56 EST
From: TAKEFUJI%scarolina.csnet@RELAY.CS.NET
Subject: Presentation - Columbia AI/VLSI Project
[I apologize for the late distribution of this and other announcements.
The list has been a bit more than I could handle this last month due
to illness and personal circumstances. -- KIL]
From: Dr. Yoshiyasu Takefuji
To: whom it may concern
Subjects: INVITATION TO AI & VLSI Project
presentation/demonstration
Date: May 4, 1987
Time: 4 PM
Place: On the third floor at Engineering Building in Columbia,
South Carolina
Hello.
We will have project presentation/demonstration on the following subjects:
15 graduate students are involved
in these projects.
1. Fuzzy inference VLSI parallel-engine
2. Expert system for determination of fuzzy inference engine
architecture
3. Function Description Translator from behavior description
to VLSI layout level (CIF or Magic file)
4. Terminal-based local network project to eliminate RS232c wire-jungle
5. Neuron Network Simulators
6. Error Correction Circuits based on Neuron Networks
7. Petri-to-FSM translator
Let me know whether you can come to see our demo.
csnet: takefuji%scarolina.edu
usenet: ncrcae!usccmi!takefuji
Thank you.
------------------------------
Date: Tue, 21 Apr 87 17:37:43 cst
From: stevens@anl-mcs.ARPA (Rick L. Stevens)
Subject: Course - Automated Mathematical Reasoning
UNIVERSITA' DI CATANIA
Dipartimento di Matematica
Viale A. Doria, 6
95125 CATANIA - ITALY
First Announcement CATANIA SICILY, ITALY
JUNE 8-12, 1987
INTERNATIONAL COURSE ON
NEW TRENDS IN AUTOMATED
MATHEMATICAL REASONING
The meeting will consists of 3 six hours courses form Monday through Friday
given by the following lecturers
- Prof. WU WEN-TSUN - Institute of Systems Science, Academia Sinica, University
of Beijng - CHINA
"Automated Theorem Proving in Geometry and Differential Geometry".
- Prof. JACOB T. SCHWARTZ - Department of Computer Science, Courant Institute
of Mathematical Sciences - New York University - USA.
"Pragmatic Issues in Verification of Programs and Mathematical Theorems".
- Prof. JIAWEI HONG - Beijng Computer Institute and University of Chicago - USA.
"Proving by Example in Geometry".
Director of the course
- Prof. Alfredo Ferro - Department of Mathematics, University of Catania - ITALY
Admission and General Information
---------------------------------
A $ 50 (80,000 Italian lire) registration fee which includes social dinner on
Thursday evening is required.
An excursion to Taormina will be organized on Friday afternoon.
Participants will be accommodated at the beautiful residence "La Perla Ionica".
Full board for each day:
double room L. 57,500 per person
single room L. 72,500 per person.
Half board for each day:
double room L. 48,300 per person
single room L. 63,300 per person.
For any information, hotel reservations, buses from the airport, etc., please
contact TRINACRIA VIAGGI via L. Rizzo 19/A - Catania - Italy - tel. 095/325155 -
Telex 970134.
Several daily flights connect Catania to Rome and Milan. Also, Catania is
connected to Paris, Frankfurt, and London by weekly flights.
Deadline for hotel reservations: May 22, 1987.
Please send applications to dott. G. Gallo, Dipartimento di Matematica -
Viale A. Doria 6, 95125 Catania - Italy.
------------------------------
Date: Tue, 21 Apr 87 17:30:38 cst
From: stevens@anl-mcs.ARPA (Rick L. Stevens)
Subject: Conference - Automated Reasoning Workshop
Automated Reasoning Workshop 1987
Mathematics and Computer Science Division
Argonne National Laboratory
You are invited to a workshop on automated reasoning to
be held at Argonne National Laboratory on June 23 and 24,
1987. This workshop, the sixth of its kind, will take the
form of a set of tutorials. No background is needed in
automated reasoning, simply curiosity and an interest in the
subject.
Our first objective is to acquaint people with the
basic aspects of automated reasoning and with the possible
applications. Thus we shall discuss some of the previously
open questions we have solved and feature topics such as the
design of logic circuits, the validation of existing circuit
designs, and proving properties of computer programs. Our
second objective is to learn of new problems on which the
current methodology might have an impact. In fact, the
preceding workshops did lead to such discoveries, as well as
to collaborative efforts to seek solutions to these prob-
lems.
Enclosed is a tentative schedule that briefly describes
the various talks. On the first day, we shall begin with an
introductory lecture on what automated reasoning is. We
shall illustrate the various concepts first with puzzles.
Next, we shall focus on some applications of automated rea-
soning. We shall include a demonstration of an automated
reasoning program (ITP) that is portable, runs on relatively
inexpensive machines, and is available to other users. On
the second day we shall give an introduction to Prolog, dis-
cuss additional applications, and focus on state/space prob-
lems. On both days, we have scheduled reviews of the
material and open discussions.
We welcome you to this 1987 workshop on automated rea-
soning. Participation will require a small charge, no more
than $60. Included in this fee will be the cost of the book
Automated Reasoning: Introduction and Applications, written
by Wos, Overbeek, Lusk, and Boyle and published by
Prentice-Hall. This book covers the field of automated rea-
soning from its basic elements through various applications.
Its tutorial nature will guide our approach to the workshop.
We urge you to respond to this invitation as soon as
possible for, to retain the tutorial atmosphere of the
workshop, we may be forced to limit the number of partici-
pants. The order in which requests are received will be an
important parameter in issuing invitations to attend the
workshop.
Sincerely,
L. Wos
Senior Mathematician
Schedule for Automated Reasoning Workshop 1987
June 23-24, 1987
Argonne National Laboratory
Argonne, Illinois
Tuesday, June 23
9:00 - 9:15 Preliminary remarks - Larry Wos
9:15 - 10:15 Introduction to automated reasoning
- Larry Wos
10:15 - 10:30 Break
10:30 - 11:30 Solving reasoning puzzles - Brian
Smith
11:30 - 12:30 Lunch
12:30 - 1:15 Choices of strategies and inference
rules - Rusty Lusk
1:15 - 1:30 Demonstration
1:30 - 1:45 Break
1:45 - 2:45 Proving properties of computer pro-
grams - Jim Boyle
2:45 - 3:00 Closing discussion - Larry Wos
Wednesday, June 24
9:00 - 9:15 Discussion - Larry Wos
9:15 - 10:15 Introduction to Prolog - Rusty Lusk
10:15 - 10:30 Break
10:30 - 11:30 State-space problems - Rusty Lusk
11:30 - 12:30 Lunch
12:30 - 1:15 Circuit design and validation - Jim
Boyle
1:15 - 1:45 Open problems in mathematics and
logic - Rusty Lusk
1:45 - 2:00 Break
2:00 - 2:45 Detailed solution of an open prob-
lem in logic - Larry Wos
2:45 - 3:15 Our automated reasoning software -
Rusty Lusk
3:15 - 3:30 Closing remarks - Larry Wos
------------------------------
Date: 24 Apr 87 23:08:36 GMT
From: feifer@locus.ucla.edu
Subject: Conference - Volunteers still needed for AAAI conf.
ANNOUNCEMENT:
Student Volunteers Still Needed for
Artificial Intelligence Conference
AAAI-87
AAAI-87 (American Association on Artificial Intelligence) will
be held July 13-17, 1987 in beautiful Seattle, Washington.
Student volunteers are needed to help with local arrangements
and staffing of the conference. To be eligible for a Volunteer
position, an individual must be an undergraduate or graduate
student in any field at any college or university.
This is an excellent opportunity for students to participate in
the conference. Volunteers receive FREE registration at AAAI-87,
conference proceedings, "STAFF" T-shirt, and are invited to the
volunteer party. More importantly, by participating as a volunteer,
you become more involved and meet students and researchers with
similar interests.
If you are interested in participating in AAAI-87 as a Student
Volunteer, apply by sending the following information:
Name
Electronic Mail Address
USMail Address
Telephone Number(s)
Dates Available
Student Affiliation
Advisor's Name
to:
feifer@locus.ucla.edu
or
Richard Feifer
UCLA
Center for the Study of Evaluation
145 Moore Hall
Los Angeles, California 90024
Thanks, and I hope you join us this year!
Richard Feifer
Student Volunteer Coordinator
AAAI-87 Staff
- Richard
------------------------------
Date: Tue 21 Apr 87 13:36:42-EDT
From: Gail E. Kaiser <KAISER@cs.columbia.edu>
Subject: Conference - Hawaii Conf. on System Sciences
Subject: revised call for papers: 20->26pp
CALL FOR PAPERS
21ST ANNUAL
HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES
(HICSS-21)
Papers are invited for the minitrack on Use of AI Techniques in Software
Design and Implementation in the software track of the 21st annual Hawaii
International Conference on System Sciences (HICSS-21), to be held in Kona,
Hawaii next January 5-8, 1988.
Topics of interest include, but are not limited to, the following artificial
intelligence areas as they apply to software design and implementation,
particularly for large-scale software systems. Techniques may apply to any or
all phases of the software development process: project management,
requirements, functional specification, design specification, modular
decomposition, coding, integration, testing, maintenance, documentation,
delivery, etc. Example applications are given in parentheses.
- Automatic deduction (detecting inconsistencies among programmers'
assumptions, automatic programming)
- Knowledge representation (semantic nets, frames, etc. for
representing programming information)
- Learning (self-tuning of software tools to specific programs,
generalization of program fragments to support reusability)
- Natural language (matching functionality of program parts with the
corresponding program documentation, explaining program components
and their interactions to new project member)
- Planning (detecting interactions among planned changes)
- Rule-based systems (program transformation, performance tuning)
- Search (retrieval of reusable program fragments)
Six copies of the full paper (maximum 26 double-spaced pages) should be sent
to the session chairman at the address given below. Papers must arrive by July
1, 1987. Authors will be notified of acceptance by September 7, 1987.
Camera-ready copies will be due by October 19, 1987.
Minitrack chairman: Prof. Gail E. Kaiser, Columbia University, Department of
Computer Science, New York, NY 10027. Phone: 212-280-3856. Electronic mail:
kaiser@cs.columbia.edu, ...seismo!columbia!cs!kaiser
Software track chairman: Dr. Bruce D. Shriver, IBM T.J. Watson Research
Center, P.O. Box 704, Yorktown Heights, NY 10598. Phone: 914-789-7626.
Electronic mail: shriver@ibm.com
------------------------------
Date: Mon, 27 Apr 87 18:02:30 edt
From: walker@flash.bellcore.com (Don Walker)
Subject: Conference - ACL Applied Natural Language Conference
"CALL FOR PAPERS"
SECOND CONFERENCE ON APPLIED NATURAL LANGUAGE PROCESSING
9-12 February 1988, Austin, Texas, USA
Organized by the Association for Computational Linguistics
CONFERENCE SUMMARY: This meeting will focus on the application of
natural language processing techniques to real world problems. It will
include invited and contributed papers, panel discussions, tutorials,
exhibits, and demonstrations. Original papers are being solicited in
areas such as human-machine interfaces (including databases, expert
systems, report writers, etc.), speech input and output, information
retrieval, text generation, machine translation, office automation,
writing aids, computer-aided instruction, tools for natural-language
processing, and applications to medical, legal, or other professional
areas. Papers may present applications, evaluations, limitations, and
general tools and techniques. Papers that critically evaluate a
formalism or processing strategy are especially welcome. Papers or
panel proposals discussing end-user experience with natural language
systems are also encouraged.
REQUIREMENTS FOR SUBMISSION: Authors should submit ten copies of a 6-8
page summary (single-spaced, exclusive of references, pica or elite
size type). The first page should begin with the title, the name(s) of
the author(s), complete address(es), and a short (5-6 line) abstract.
Papers should be sent to: Bruce Ballard
AT&T Bell Laboratories, 3C-440A
Murray Hill, NJ 07974
(201)582-5440
allegra!bwb@ucbvax.berkeley.edu
The submission should identify distinctive aspects of the work and
clearly indicate the extent to which an implementation has been
completed; vague or unsubstantiated claims will be given little
weight. Submissions should be substantively different from papers
currently under review or to be submitted elsewhere before the
notification date. All papers will be reviewed by members of the
Program Committee , which is composed of Bruce Ballard, chair (AT&T
Bell Laboratories), Madeleine Bates (BBN Laboratories), Tim Finin
(University of Pennsylvania), Ralph Grishman (New York University),
Carole Hafner (Northeastern University), George Heidorn (IBM
Corporation), Paul Martin (SRI International), Graeme Ritchie
(University of Edinburgh), and Harry Tennant (Texas Instruments).
SCHEDULE: Papers must be received by September 1, 1987. Notification
of acceptance will be sent by October 5, 1987. Camera-ready versions
of the full paper must be received by November 30, 1987.
OTHER ACTIVITIES: The meeting will include one day of tutorials by
noted contributors to the field. Facilities for exhibits and system
demonstrations will also be available. Persons wishing to arrange an
exhibit or present a demonstration should contact Kent Wittenburg or
Carl Weir, MCC, 3500 W. Balcones Center Drive, Austin, TX 78759;
(512)338-3626 or 338-3616; wittenburg@mcc.com or weir@mcc.com.
CONFERENCE INFORMATION: Local arrangements are being handled by
Jonathan Slocum and Barbara Smith, MCC, 3500 W. Balcones Center Drive,
Austin, TX 78759; (512)338-3571 and 338-3527; slocum@mcc.arpa and
barbara@mcc.arpa. For additional information on the conference or
about the ACL, contact Donald Walker, Bell Communications Research, 445
South Street, MRE 2A379, Morristown, NJ 07960; (201)829-4312;
walker@flash.bellcore.com or ucbvax!bellcore!walker. In addition to
the persons named above, the Conference Committee includes Norman
Sondheimer, USC/Information Sciences Institute, General Chair; Martha
Palmer, UNISYS, Tutorials; Jeffrey Hill and Brenda Nashawaty,
Artificial Intelligence Corporation, Publicity.
------------------------------
End of AIList Digest
********************
∂10-May-87 2138 LAWS@Stripe.SRI.COM AIList Digest V5 #113
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 May 87 21:38:22 PDT
Date: Sun 10 May 1987 16:49-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #113
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 11 May 1987 Volume 5 : Issue 113
Today's Topics:
Conferences - Production Planning, Control &
ICALP '87 &
Matrix of Biology Workshop &
AI and Law, Final Schedule
----------------------------------------------------------------------
Date: Sun, 3 May 1987 18:48 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Conferences - Production Planning, Control & ICALP '87
AI at Upcoming Conferences
Expert Systems and the Leading Edge in Production Planning and Control
May 10-13, Charleston, South Carolina
Keynote Addresses
"Managing Knowledge for Production Planning"
Thomas Kehler, Chairman, Intellicorp
"Integration of Manufacturing Policy and Corporate Strategy with the
Aid of Decision Support Systems"
Gabriel Bitran, Professor of Management, Sloan School of Management,
Massachusetts Institutes of Technology
May 11
Tutorial I-- Production Planning and Control
William Berry, University of Iowa
Lee Krajewski, Ohio State University
Tutorial II _ Knowledge-based Expert Systems: Theory and Practice
Mark Fox, Director, Intelligent Systems Laboratory, Carnegie Mellon
University
May 12
Keynote Address
Tracy O'Rouke, President, The Allen Bradley Company
JIT - Then AI
James Butcher, Materials Control Manager, 3M Corporation
Design of Flexible Manufacturing Systems
Kathy Stecke, Operations Management, University of Michigan
Factor Representaiton and Design
Ed Fisher, Department of Industrial Engineering, North Carolina State U.
Exploiting Group Technology in Expert Process Designers
Bruce Johnson, Partner in Charge of Ai, Arthur Anderson
Knowledge-based and Collaborative Design Tools
Sanjay Mittal, Xerox University
An Intelligent Decision Support System for Integrated Distribution Planning
Darwin Klingman and Nancy Phillips,
MIS and Information Systems, University of Texas-Austin
Knowledge-based Simulation and Manufacturing
John Kuntz, Senior Knowledge Systems Engineer, Intellicorp
Panel Discussion:
Integrating Planning Frontiers
Ed Davis, University of Virginia, Jim L. Goedhart, GE Calma
Integration of People, Automation and Computers in Job-Shop Electronics
John Lorei, Manager, Computer INtegrated Manufacturing Rockwell
International
Manufacturing Planning Systems for the 1990s
Thomas Vollman, Department of Operations Management, Boston University
Merrill Ebner, Department of Manufacturing Engineering, Boston University
Artificially Intelligent Tools for Manufacturing Process Planners
Karl Kempf, Senior Computer Scientist, FMC
Panel Discussions:
Workshops in Aerospace Applications for AI, Textile Technology,
Scheduling Applications, Flexible Manufacturing Systems, Product Design
Systems, Advanced Automation (AI and OR)
May 13
Keynote: Rapid Prototyping for Expert Systems
Brian Gaines, Department of Computer Science, University of Calgary
Production Control Issues and Challenges
Steve Melnyk, Management, Michigan State University
FMS Producitoon Planning and Control Problems
Kathy STecke, University of Michigan
From the ARMF to the Factory of the Future: AI Tools in Process and
Production Planning and Control
Dennis Swyt, Deputy Director, National Bureau of STandards
Using Knowledge Technology to Gain a Competitive Advantage in
Manufacturing
Neil Cahill, Vice President, Manufacturing Technology, Institute of
Textile Technology
Knowlege-Based Process Management Applications
Michael Fehling, Principal Scientist, Rockwell Science Center
Panel Discussion
Scheduling Research: Past, Present, Future
William L. Maxwell, Cornell University
KNowledge-Based Scheduling Systems
Jack Kanet, Clemson University
Knoweldge-Based Scheduling and Resource Allocation in the CAMPS Architecture
Richard Brown, MITRE Corporatio/n
A Knowledge Based Framework for Reactive Management of Factory Schedules
Steve Smith, Intelligent Systems Lab, Carnegie Mellon University
Panel Discussion
Closing Session
%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑%↑
ICALP 87, July 13-17, 1987, Karlsruhe, West Germany
July 13
Invited Lecture, Recent Developments in the Theory of Learning,
L. Valiant, Harvard University
Probability and Plurality for Aggregations of Learning Machines,
L. Pitt (University of Illinois), C. H. Smith (University of Maryland)
Inverse Image Analyse
P. Dybjer, University of Goteborg
A Unification Algorithm for Confluent Theories
S. Holldobler, Universitat der Bundeswehr, Munchen
On the Knuth Bendix Completion for Concurrent Processes
V. Diekert, Technische Universitat Munchen
On Word Problems in Equational Theories
J. Hsiang, State University of New York, M. Rusinowitch, CRIN, Vandoeuvre-les-
Nancy
Semantics for nondeterministic, Asynchronous Broadcast Networks
R. K. Shyamasundar, K. T. Narayana, T. Pitassi, Pennsylvania State University
Another Look at Abstraction in Process Algebra
J. C. M. Baeten, University of Amsterdam, R. J. van Glabeek, Centre of
Mathematics and Computer Science, Amsterdam
July 14
Computation Tree Logic CTL* and Path Quantifiers in the MOnadic Theory of
the Binary Tree,
T. Hafer, W. Thomas, RWTH Aachen
Modelchecking of CTL Formulae under Liveness Assumptions
B. Josko, RWTH Aachen
A Model Logic for a Subclass of Event Structures
K. Lodaya, Tata Institute of Fundamental Research Bombay
P. S. Thiagarajan, Aarhus University
Term Matching on Parallel Computers
R. Ramesh, R. M. Verma, T. Krishnaprasad, I. V. Ramakrishnan, SUNY, New York
July 17
Invited Lecture: The Geometry of Robot Motion Planning
J. Schwartz, New York University
Nancy Phillips, Associate Profesor, Department of MIS
------------------------------
Date: Thu 23 Apr 87 17:34:04-EDT
From: "Patrick H. Winston" <PHW%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU>
Subject: Conference - Matrix of Biology Workshop
**************** OPPORTUNITY FOR PARTICIPATION ****************
WORKSHOP
ON THE MATRIX OF
BIOLOGICAL INFORMATION
ARTIFICIAL INTELLIGENCE, DATA BANK MANAGEMENT, COMPUTER ANALYSIS OF
MACROMOLECULES --- APPLIED TO CELLULAR BIOLOGY TO DEVELOP AN APPROACH TO
GENERALIZATIONS AND OTHER THEORETICAL INSIGHTS IN BIOLOGICAL SCIENCE.
We have today a unique opportunity to merge research at the forefront of
Artificial Intelligence with efforts to provide a new conceptual
framework for the laws, models, empirical generalizations and physical
foundations of the modern biological sciences.
The Matrix of Biological Knowledge is an attempt to use advanced
computer methods to organize the immense and growing body of
experimental data in the biological sciences, in the expectation that
there are a significant number of as yet undiscovered ordering
relations, new laws and predictive relations embedded in the mass of
existing information. Workshop participants will attempt to define the
interrelations of the matrix of biological knowledge, and to demonstrate
its feasibility by applying the modern tools of computer science to a
small set of case studies. This is an outgrowth of a report from the
Natl. Academy of Sciences, "Models for Biomedical Research: a New
Perspective," produced in response to a request by the Natl. Institutes
of Health (NIH). A brief summary and description appears in "An
Omnifarious Data Bank for Biology?," SCIENCE 228(4706), 21 June 1985.
The workshop is intended to introduce a number of young scientists to
the matrix concept and to explore with these investigators the
possibilities of new theoretical developments and conceptual frameworks.
The workshop will run July 13 - August 14 at St. Johns College in Santa
Fe, in the Sangre de Cristo mountains of northern New Mexico (AAAI
attendees may miss the first week). Participants will be supported with
housing, meals and travel as necessary. Thirty participants (graduate
students, post-doctoral fellows, and working scientists) are expected to
be selected by application from throughout the United States.
Eight groups will be directed by senior scientists:
"Artificial Intelligence," Patrick Winston, A.I. Laboratory, MIT;
"Management of Large Scale Data Bases," Robert Goldstein, U. Brit. Columbia;
"Computers Applied to Macromolecules," Peter Kollman, U. Cal. San Francisco;
"The Organization of Biological Knowledge," Harold Morowitz, Yale University;
"Cell-Cell Interactions," Hans Bode, U. of Calif., Irvine;
"Toxicology," Robert Rubin, Johns Hopkins University;
"Information Flow from DNA to Cells," Richard Dickerson, UCLA,
Harvey Hershman, UCLA, and Temple Smith, Harvard University;
"Peptides and Signalling Molecules," Christian Burks, Los Alamos Natl. Lab.,
and Derek LeRoith, NIH.
A brief description of background and desire to participate, together
with two letters of recommendation, should be sent to
Santa Fe Institute, attn. Ginger Richardson
P.O. Box 9020
Santa Fe, New Mexico, 87504 - 9020
(phone (505) 984-8800)
(Applicants should first review the NAS report or the SCIENCE article,
above, available in most science libraries.)
The workshop has been previously announced in other forums and the
formal application deadline is 1 May 1987. Applicants who will have
difficulty meeting that deadline should telephone Ginger Richardson and
notify her of their intent to submit an application, as few if any
positions will be available after that date. Applicants are strongly
encouraged to apply expeditiously so that an early decision about
participation may be reached.
Some representative connections between Artificial Intelligence and
the Matrix Workshop follow, but the list is suggestive only.
NATURAL LANGUAGE: What constraints on form and content must be met for
a scientific Abstract to be machine-readable? It is generally a single
paragraph in a very restricted form of declarative prose. If tolerable
constraints could be found they would probably be widely adopted.
KNOWLEDGE REPRESENTATION: How much of what knowledge must be captured,
and how, to enable scientific reasoning? Is a single unified
representation scheme possible or must each sub-field have a specialized
representation to support a specialized vocabulary and ontology? ``In
the Knowledge lies the Power.'' How can we organize this tremendous
amount of knowledge to extract the power everyone believes is there?
ANALOGICAL MAPPING: How can we notice when analogous biological
functions are implemented by analogous structures? Can we discover and
validate analogical animal models of human systems? Can we explain an
unknown response in an organism by analogy to a better-understood
system? Given an experimental system, description or outcome, could we
index and retrieve analogous situations and/or literature references?
MACHINE LEARNING: How can we re-structure the large existing databases
to automate induction from data? Can we use more knowledge-intensive
forms of learning in this knowledge-intensive domain? Can existing
learning paradigms be extended to cope with the noisy data that any real
application must face?
RULE-BASED EXPERT SYSTEMS: How much of the expert scientist's knowledge
can be formalized explicitly as rules? Could we produce an expert
system which, given a problem or request for information, could infer
which database contained the answer? Could expert knowledge, say of
toxicology, be used to produce a Toxicology Advisor which knew how to
access databases to find answers to questions not covered by its rules?
Could we create expert systems which continually scanned new additions
to databases to update their rules, or at least flag areas where the new
addition conflicts with or supplants an existing rules?
TRUTH MAINTENANCE: Suppose an Abstract always contained an explicit
statement of the proposition(s) argued for or against by the paper.
Could this be entered into a dependency network, with the paper as
justification? Could we then query the TMS to determine, for some
proposition, whether it is generally believed, disbelieved, or
controversial; and pick out the relevant literature citations? If a new
paper supports or contradicts a result from a neighboring field, can
this be detected reliably?
QUALITATIVE PROCESS THEORY: Can an organism be modeled as a cooperating
system of processes? Can we organize this so as to find similar process
systems shared by different organisms? Can we reliably predict the
effects of perturbing an organism's processes, e.g. in the study of
toxicology or medicine?
SCIENTIFIC REASONING AND DISCOVERY: We have the opportunity to
structure a large, continuously-updated body of real-world scientific
knowledge. What form of Knowledge Base would best facilitate
discovering the unexpected regularities in the data? Could a program
(possibly using a dependency network of experimental results) suggest
crucial experiments and reason about implications of possible outcomes?
SCHEMA COMPLETION: Can an experiment be understood in terms of a
setting which instantiates an ``experiment schema''? Can we use this to
group results that are ``schematically close'', even if they occur in
different biological models or in related but distinct sub-fields? Can
we fill in the default assumptions underlying a description of the
experiment and results?
DISCOURSE/STORY UNDERSTANDING: Could a scientific article be analyzed
as a narrative describing an experimental setting, a group of
observations, and some conclusions? Given a new story (experiment),
could we retrieve closely related or similar stories we've heard before?
Could a highly abridged summary of the story be produced? Could several
stories be automatically merged, and an overall summary produced?
This list is obviously indicative, not exhaustive.
------------------------------
Date: Fri, 1 May 87 15:23:59 ADT
From: hafner%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: Conference - AI and Law, Final Schedule
The First
International Conference on Artificial Intelligence and Law
May 27-29, 1987
Northeastern University, Boston, MA 02115
Sponsored by:
The Center for Law and Computer Science,
Northeastern University
In Cooperation with ACM SIGART
Registration: Ms. Rita Laffey, (617) 437-3346
Information: Prof. Carole Hafner (617) 437-5116
SCHEDULE OF EVENTS
WEDNESDAY, May 27
8:30-12:30 Tutorials
A. "Introduction to Artificial Intelligence (for lawyers)"
Prof. Edwina L. Rissland, University of Massachusetts and
Harvard Law School
B. "Applying Artificial Intelligence to Law: Opportunities
and Challenges"
Profs. Donald H. Berman and Carole D. Hafner, Northeastern
University
2:00-2:30 Welcome; Opening Remarks.
2:30-4:00 Legal Expert Systems I
2:30 "Expert Systems in Law: Out of the Research Laboratory and
into the Marketplace"
Richard E. Susskind
Ernst & Whinney, London, England
3:00 "Expert Systems in Law: The DataLex Project"
Graham Greenleaf, Andrew Mowbray and Alan L. Tyree
University of Sydney, Australia
3:30 "Explanation for an Expert System that Performs Estate
Planning"
Dean A. Schlobohm and Donald A. Waterman
Stanford University, The Rand Corporation
4:00-4:30 Coffee
4:30-6:00 Conceptual Legal Retrieval Systems I
4:30 "Conceptual Legal Document Retrieval Using the RUBRIC System"
Richard M. Tong, Clifford A. Reid, Peter R. Douglas and
Gregory J. Crowe
Advanced Decision Systems
5:00 "Conceptual Organization of Case Law Knowledge Bases"
Carole D. Hafner
Northeastern University
5:30 "Designing Text Retrieval Systems for Conceptual Searching"
Jon Bing
Norwegian Research Center for Computers and Law
6:30-8:30 Welcoming Reception, Northeastern U. Faculty Center
THURSDAY, May 28
9:00-10:30 Models of Legal Reasoning I
9:00 "A Process Specification of Expert Lawyer Reasoning"
D. Peter O'Neil
Harvard Law School
9:30 "A Case-Based System for Trade Secrets Law"
Edwina L. Rissland and Kevin D. Ashley
University of Massachusetts, Amherst
10:00 "But, See, Accord: Generating Blue Book Citations in HYPO"
Kevin D. Ashley and Edwina L. Rissland
University of Massachusetts, Amherst
10:30-11:00 Coffee
11:00-12:30 Legal Expert Systems II
11:00 "A Natural Language Based Legal Expert System for
Consultation and Tutoring -- The LEX Project"
F. Haft, R.P. Jones and Th. Wetter
IBM Heidelberg Scientific Centre, West Germany
11:30 "The Application of Expert Systems Technology to
Case-Based Law"
J.C. Smith and Cal Deedman
University of British Columbia
12:00 "Some Problems in Designing Expert Systems to Aid Legal
Reasoning"
Layman E. Allen and Charles S. Saxon
The University of Michigan, Eastern Michigan University
12:30-2:00 Lunch
2:00-3:00 Panel: "The Impact of Artificial Intelligence on the Legal
System"
Moderator: Cary G. DeBessonet, Law and Artificial Intelligence
Project, Louisiana State Law Institute
3:00-4:00 Conceptual Legal Retrieval Systems II
3:00 "Conceptual Retrieval and Case Law"
Judith P. Dick
University of Toronto
3:30 "A Connectionist Approach to Conceptual Information
Retrieval"
Richard K. Belew
University of California, San Diego
4:00-4:30 Coffee
4:30-6:00 Expert Systems and Tax Law
4:30 "A PROLOG Model of the Income Tax Act of Canada"
David M. Sherman
The Law Society of Upper Canada
5:00 "An Expert System for Screening Employee Pension Plans for
the Internal Revenue Service"
U.S. Internal Revenue Service
Gary Grady and Ramesh S. Patil
5:30 "Handling of Significant Deviations from Boilerplate Text"
U.S. Internal Revenue Service
Gary Morris, Keith Taylor and Maury Harwood
7:00 Reception and Banquet, The Colonnade Hote
Banquet Address: Non-Monotonic Reasoning
Prof. John McCarthy, Stanford University
FRIDAY, May 29
9:00-10:30 Applications of Deontic Logic
9:00 "Legal Reasoning in 3-D"
Marvin Belzer
University of Georgia
9:30 "On the Relationship Between Permission and Obligation"
Andrew J.I. Jones
University of Oslo, Norway
10:00 "System = Program + Users + Law"
Naftaly H. Minsky and David Rozenshtein
Rutgers University
10:30-11:00 Coffee
11:00-12:30 Legal Expert Systems III
11:00 "Support for Policy Makers: Formulating Legislation with
the Aid of Logical Models"
T.J.M. Bench-Capon
Imperial College of Science and Technology, London
11:30 "Logic Programming for Large Scale Applications in Law:
A Formalisation of Supplementary Benefit Legislation"
T.J.M. Bench-Capon, G.O. Robinson, T.W. Routen and
M.J. Sergot
Imperial College of Science and Technology, London
12:00 "Knowledge Representation in DEFAULT: An Attempt to Classify
General Types of Knowledge Used by Legal Experts"
Roger D. Purdy
University of Akron
12:30-2:00 Lunch
2:00-3:00 Panel: Modeling the Legal Reasoning Process: Formal and Computational
Approaches
Moderator: Prof. L. Thorne McCarty, Rutgers University
3:00-4:00 Models of Legal Reasoning II
3:00 "Precedent-Based Legal Reasoning and Knowledge Acquisition
in Contract Law: A Process Model"
Seth R. Goldman, Michael G. Dyer and Margot Flowers
University of California, Los Angeles
3:30 "Reasoning about 'Hard' Cases in Talmudic Law"
Steven S. Weiner
Harvard Law School, MIT
4:00-4:30 Coffee
4:30-6:00 Legal Knowledge Representation
4:30 "OBLOG-2: A Hybrid Knowledge Representation System for
Defeasible Reasoning"
Thomas F. Gordon
GMD, Sankt Augustin, West Germany
5:00 "ESPLEX: A Rule and Conceptual Model for Representing
Statutes"
Carlo Biagioli, Paola Mariani and Daniela Tiscornia
Instituto per la Documentazione Giuridica, Florence, Italy
6:00 "Legal Data Modeling: The Prohibited Transaction Exemption
Analyst"
Keith Bellairs
Computer Law Systems, Inc.
------------------------------
End of AIList Digest
********************
∂10-May-87 2348 LAWS@Stripe.SRI.COM AIList Digest V5 #114
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 May 87 23:48:27 PDT
Date: Sun 10 May 1987 16:53-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #114
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 11 May 1987 Volume 5 : Issue 114
Today's Topics:
Conference - Artificial Life Workshop &
IFIP Workshop on Intelligent CAD &
4th International Conference on Logic Programming
----------------------------------------------------------------------
Date: Fri, 8 May 87 15:24:26 MDT
From: cgl@LANL.GOV (C G Langton)
Subject: Conference - Artificial Life Workshop
About a year ago, I posted a query about work being done on the computer
simulation of life. From the replies to that query and from what I have
been able to dig up in the literature, it has become apparent that there
is an imminent explosion of research in the simulation and synthesis of
life, both in computers and in the laboratory. Therefore, I am organizing
the following workshop:
ARTIFICIAL LIFE
An Interdisciplinary Workshop
on the Synthesis and Simulation
of Living Systems
organized by
Chris Langton
Center for Nonlinear Studies
Los Alamos National Laboratory
Los Alamos, New Mexico 87545
September 21-25 1987
Artificial life is the study of artificial systems that exhibit
behavior characteristic of natural living systems. This includes
computer simulations, biological and chemical experiments, and purely
theoretical endeavors. Processes occurring on molecular, cellular, neural,
social, and evolutionary scales are subject to investigation. The ultimate
goal is to extract the logical form of living systems.
Microelectronic technology and genetic engineering will soon give us
the capability to create new life forms "in-silico" as well as in-vitro.
This capacity will present humanity with some of the most far-reaching
technical, theoretical, and ethical challenges it has ever confronted.
The time seems appropriate for a gathering of those involved in
attempts to simulate or synthesize aspects of living systems. This
workshop will provide a forum to address the fundamental problems
inherent in such an enterprise.
The goals of this first workshop on artificial life are:
To bring the field of artificial life into focus.
To present current work in artificial life, and to provide
an historical perspective.
To open a channel of communication between researchers from
disciplines whose work is relevant to artificial life.
To produce a list of fundamental questions that the field
should address.
To identify ways in which work on artificial life can
contribute to theoretical biology.
To organize the literature in the field by compiling an
annotated bibliography.
-------- (cut here and post above on appropriate bulletin boards) ----------
I have posted a more complete announcement to "news.announce.conferences",
which contains further information about the workshop and includes a
registration form to fill out and return. In the interest of brevity, I
have not included the full posting here. If you are interested in attending
or contributing to a workshop on computer - and other - models of life, its
constituent processes, or the processes that living systems support, please
see the more complete posting in "news.announce.conferences".
One of the primary activities at the workshop will be an "artificial 4H show"
with prizes for the most life-like models or simulations submitted. You need
not attend the workshop to submit an entry to the "4H-show". So, if you have
some simulation of a living system, an origin of life model, an evolving
population of "bugs", a model of social dynamics, a self-replicating Meccano
set, or something else you have been working on - whether as your primary
line of research or as a project that you've been doing on the side - dust
it off, polish it up, and send it (or a brief description) to the address
listed below. I am hoping for a workshop with a large number of hands-on
demonstrations and exhibits, combined with a few selected talks and panel
discussions, so that we can really exchange ideas on a personal level in a
computater-rich environment, allowing us to test new ideas or model parameters
on the spot. I want to avoid the typical format of bumper-to-bumper talks with
little time for discussion in between. I will provide a number of Sun
workstations running 4.2 BSD UNIX, Apple Macintoshes, IBM PC's, and a CAM-6
cellular automaton machine. If your system requires other equipment, let me
know the details and I will try to obtain it.
More information will be available as the workshop evolves.
----------------------------------------------------------------------------
Chris Langton email: cgl@lanl.gov
Center for Nonlinear Studies phone: 505-665-0049 (office)
Los Alamos National Laboratory 505-667-1444 (messages)
Los Alamos, New Mexico
87545
------------------------------
Date: Wed, 6 May 87 22:07:46 pdt
From: farhad%arbab3b2.uucp@usc-cse.usc.edu
Subject: Conference - IFIP Workshop on Intelligent CAD
CALL FOR PAPERS
IFIP W.G.5.2 Workshop on
Intelligent CAD
October 6-8, 1987
Massachusetts Institute of Technology
Cambridge, Massachusetts
U.S.A.
OBJECTIVES
----------
The purpose of this workshop is to provide a forum for discussion of
theories and methodologies of intelligent CAD, aiming at better
realization of practical systems. This workshop is the first in a series
of three, to be held in successive years in the U.S.A., Europe and Japan.
Future CAD systems capable of providing intelligent assistance in design
activities or of autonomous design activity will be of large practical
importance. Major theoretical and practical problems must be solved,
however, before such systems can be realized. Design is a complex human
activity, involving a variety of high-level cognitive tasks. There are
few unifying principles and little consensus as to the basic nature of the
design process, the types of knowledge or reasoning mechanisms involved
or basic approaches to generic systems.
At this first workshop in the series, the organizers wish to bring
together researchers in the fields of artificial intelligence and
computer-aided design with the goal of identifying and developing basic
theoretical foundations for future intelligent CAD systems. This workshop
will be a unique opportunity for the exchange of views and ideas.
The second workshop will focus on the specialization of intelligent CAD
systems, and in the third workshop, practical applications of intelligent
CAD systems based on new theories are expected to appear.
The organizers would like to encourage your participation in the first
workshop of this challenging and important series.
WORKSHOP TOPICS
---------------
- Design theory and methodology
- Cognitive models of the design process
- Artificial intelligence in the design process
- Design knowledge and representations
- Paradigms for intelligent CAD
CALL FOR PAPERS
---------------
Potential participants are invited to submit three copies of a 1000 word
abstract or a full paper before June 30, 1987. The abstracts or full
papers should be position papers indicating the viewpoints of the
prospective participant in the workshop. Contributors whose abstracts are
accepted are requested to send revised abstracts or full papers by
September 10, 1987. Notification of acceptance for participation will be
issued by July 31, 1987.
CONFERENCE FORMAT
-----------------
The number of participants will be limited to about 40. 2 or 3
presentations will be made by invited speakers. A number of subgroups
will be formed during the workshop to discuss specialized topics. Each
subgroup will consist of discussion by the participants, though some
papers may be presented as appropriate. The preliminary schedule is as
follows:
- October 6 -
Morning Presentation by 2 or 3 invited speakers
Afternoon Discussion about the format of the workshop and the formation
of subgroups
- October 7 -
All day Discussion and presentations in subgroups
- October 8 -
Morning Discussion and presentation in subgroups
Afternoon Summary and remarks by chairmen of subgroups, discussion of
future plans
LANGUAGE
--------
The official language of the workshop will be English.
CONFERENCE FEE
--------------
The registration fee for the workshop will be $200. The payment method
will be noticed with the notification of acceptance.
BOOK
----
The proceedings of the workshop will be published by North Holland. The
Organizing Committee will ask some of the participants to write papers for
this book.
TIMETABLE
---------
June 30 Deadline for abstracts or full papers
July 31 Notification of acceptance
Sept. 10 Deadline for revised abstracts or full papers
ORGANIZING COMMITTEE
--------------------
- Chairmen -
Yoshikawa, H. University of Tokyo, Japan
Gossard, D. Massachusetts Institute of Technology, U.S.A.
- Secretary -
Kimura, F. University of Tokyo, Japan
- Members -
Arbab, F. University of Southern California, U.S.A.
Bo, K. Productivity Support AS, Norwary
Chairman of W.G. 5.2 IFIP
Forbus, K.D. University of Illinois, U.S.A.
Fox, M. Carnegie Group, U.S.A.
Onosato, M. University of Tokyo, Japan
Popplestone, R. J. University of Massachusetts, U.S.A.
Suzuki, H. University of Tokyo, Japan
ADDRESS FOR CORRESPONDENCE
--------------------------
Professor Hiroyuki Yoshikawa,
Dept. of Precision Machinery Engineering,
Faculty of Engineering, University of Tokyo
7-3-1 Hongo, Bunkyo-ku Tokyo 113, Japan
Phone: (03) 812-2111, ext. 6446
Fax: (03) 812-8849
Telex: 272 2111 FEUT J
==========================================================================
IFIP W.G.5.2 Workshop on Intelligent CAD
October 6-8, 1987 Massachusetts U.S.A.
Please complete and return this separate form with your abstract or paper
before June 30, 1987.
Family Name:____________________________ First Name:_____________________
Company/Institute_________________________________________________________
Title/Position:___________________________________________________________
Mail Address:_____________________________________________________________
__________________________________________________________________________
Country:__________________________________
Business Phone:_____________________ ext. ( ) Telex:_________________
Title of your Paper (Abstract):___________________________________________
__________________________________________________________________________
------------------------------
Date: Tue, 05 May 87 10:38:39 +1000
From: munnari!mulga.oz!kgm@seismo.CSS.GOV
Subject: Conference - 4th International Conference on Logic
Programming
could you please post this to comp.ai.digest ...thanks
----------------------------------------------------------
4th International Conference on Logic Programming
University of Melbourne, Australia
25-29 May 1987
The 4th International Conference on Logic Programming is to
be held at the University of Melbourne. Melbourne is a city
in the south east of Australia. It is located beside a large
bay and has a population of around 3 million. During May
the weather is expected to be clear and sunny but bring an
umbrella(!).
Accommodation is available at the adjacent University Col-
leges, a nearby hotel and a hotel in the city itself.
Delegates staying at the University Colleges are requested
to check in at the registration desk at Trinity College
which will be staffed on the Sunday and Monday.
There is a Sky Bus coach service from Tullamarine (Mel-
bourne) Airport to central Melbourne about 25km away. It
departs on the hour and half hour and the cost is about $6
per person. When boarding the coach delegates should tell
the driver the name of the hotel they are staying at.
Delegates staying at the University Colleges should ask to
be dropped off at Trinity College.
Anybody still requiring a registration form or more informa-
tion concerning the conference should contact either
Ms Buzz McCarthy
Director
Bloomsbury Conference Services
319 Lennox Street
Richmond, 3121, Victoria, Australia
Telephone: (03) 428 1983
Telex: AA 36224
or
UUCP: iclp@munnari.uucp
ARPA: iclp%munnari.oz@seismo.css.gov
CSNET: iclp%munnari.oz@australia
JANET: iclp%munnari.oz@uk.ac.ukc
The preliminary conference programme follows.
Monday 25 May (Tutorials Only)
09:00 - 13:00: Tutorial A
Topic: Introduction to Logic Programming
Speakers: L. Naish, K. Ramamohanarao (University of Melbourne)
09:00 - 13:00: Tutorial B
Topic: Natural Language Processing
Speaker: V. Dahl (Simon Fraser University)
14:00 - 18:00: Tutorial C
Topic: Logic Programming for Expert Systems
Speaker: M. Sergot (Imperial College)
14:00 - 18:00: Tutorial D
Topic: Parallel Logic Programming Languages
Speaker: K. Ueda (ICOT)
14:00 - 18:00: Tutorial E
Topic: Advanced PROLOG Programming
Speaker: L. Sterling (Case Western Reserve University)
Tuesday 26 May
09:00 - 10:00: Keynote Address: J.A. Robinson (Syracuse
University), Chairperson: J-L. Lassez (IBM T.J. Watson
Research Center)
10:40 - 12:20: Session on Warren Abstract Machine, Chairper-
son: E. Lusk (Argonne National Lab)
* Advantages of Implementing PROLOG by Microprogramming a
Host General Purpose Computer, J. Gee, S.W. Melvin and Y.N.
Patt (Univ. of California, Berkeley)
* Efficient Implementation of a Defensible Semantics for
Dynamic PROLOG Code, T. Lindholm and R.A. O'Keefe (Quintus
Computer Systems)
* Freeze, Indexing and Other Implementation Issues in the
WAM, M. Carlsson (SICS)
* A Performance Comparison between PLM and an M68020 PROLOG
Processor, H. Mulder and E. Tick (Stanford University)
13:30 - 15:35: Session on Databases, Chairperson: R.W. Topor
(University of Melbourne)
* A Database-Complete Proof Procedure based on SLD-
Resolution, L. Vieille (ECRC)
* Implementation of Recursive Queries for a Data Language
based on Pure Horn Logic, D. Sacca (CRAI) and C. Zaniolo
(MCC)
* Stratification and Knowledge Based Management, C. Lassez,
K. McAloon (IBM T.J. Watson Research Center) and G.S. Port
(University of Melbourne)
* Set Grouping and Layering in Horn Clause Programs, O.
Shmueli and S. Naqvi (MCC)
* Concurrent Database Updates in PROLOG, L. Naish, J.A.
Thom and K. Ramamohanarao (University of Melbourne)
16:05 - 17:20: Session on Constraints, Chairperson: R. Nasr
(MCC)
* Methodology and Implementation of a CLP System, J. Jaffar
(IBM T.J. Watson Research Center) and S. Michaylov (Monash
University)
* Answer Sets and Negation-as-Failure, K. Kunen (University
of Wisconsin)
* Forward Checking in Logic Programming, P. van Hentenryck
and M. Dincbas (ECRC)
17:20 - 18:05: Invited Talk: K.L. Clark and S. Gregory
(Imperial College), PARLOG and PROLOG United, Chairperson:
H. Tamaki (Ibaraki University)
Wednesday 27 May
09:00 - 09:45: Invited Talk: F. Pereira (SRI International),
Grammars and Logics of Partial Information, Chairperson:
R.A. O'Keefe (Quintus Computer Systems)
10:15 - 12:20: Session on Parallelism - Part I, Chairperson:
S. Morishita (IBM Tokyo Research Lab)
* A Distributed Implementation of Flat GHC on the Multi-
PSI, N. Ichiyoshi, T. Miyazaki and K. Taki (ICOT)
* Multiple Reference Management in Flat GHC, T. Chikayama
and Y. Kimura (ICOT)
* PARLOG and ALICE: a Marriage of Convenience, M. Lam and
S. Gregory (Imperial College)
* An OR-parallel Execution Algorithm for PROLOG and its FCP
Implementation, E. Shapiro (Weizmann Institute)
* KL1 Execution Model for PIM Cluster with Shared Memory,
M. Sato, H. Shimizu, A. Matsumoto, K. Rokusawa and A. Goto
(ICOT)
13:30 - 15:35: Session on Implementation Issues, Chairper-
son: M. Carlsson (SICS)
* Making Exhaustive Search Programs Deterministic, Part II,
K. Ueda (ICOT)
* Stream-based Compilation of Ground I/O PROLOG into
Committed-choice Languages, H. Tamaki (Ibaraki University)
* Meta-level Programming: a Compiled Approach, H. Bacha
(Syracuse University)
* Hash Tables in Logic Programming, J. Barklund and H.
Millroth (Uppsala University)
* Evaluating Logic Programs via Set-valued Functions, C.
Cecchi, D. Sartini and L. Aiello (Universita di Roma)
Thursday 28 May
09:00 - 09:45: Invited Talk: M. Sato (Tohoku University),
Quty: A Concurrent Language based on Logic and Functions,
Chairperson: K. Kunen (University of Wisconsin)
10:15 - 12:20: Session on Language Issues, Chairperson: C.
Palamidessi (Universita di Pisa)
* Near-Horn PROLOG, D.W. Loveland (Duke University)
* A Theoretical Combination of SLD-resolution and Nar-
rowing, A. Yamamoto (Kyushu University)
* Inductive and Deductive Control of Logic Programs, A.R.
Helm (University of Melbourne)
* An Efficient Logic Programming Language and its Applica-
tion to Music, K. Ebcioglu (IBM T.J. Watson Research Center)
* Symbolical Construction of Truth Valued Domain for Logic
Programs, S. Morishita, M. Numao and S. Hirose (IBM Tokyo
Research Lab)
13:30 - 15:35: Session on Parallelism - Part II, Chairper-
son: N. Ichiyoshi (ICOT)
* Relating Goal-scheduling, Precedence and Memory
Management in AND-parallel execution of Logic Programs, M.V.
Hermenegildo (MCC)
* Experiments with OR-parallel Logic Programs, T. Disz, E.
Lusk and R. Overbeek (Argonne National Lab)
* A Performance-oriented Design for OR-parallel Logic Pro-
gramming, P. Tinker and G. Lindstrom (University of Utah)
* Parallel Evaluation of Logic Programs: the REDUCE-OR Pro-
cess Model, L.V. Kale (University of Illinois, Urbana-
Champaign)
* Implementing Backward Execution in Non-deterministic
AND-parallel Systems, J.S. Conery (University of Oregon)
16:05 - 17:20: Session on Applications, Chairperson: P. Cox
(Tech. Univ. of Nova Scotia)
* PYTHON: An Expert Squeezer, L. Sterling and Y. Nygate
(Case Western Reserve University)
* CLP(R) and Some Electrical Engineering Problems, N.C.
Heintze, S. Michaylov and P.J. Stuckey (Monash University)
* Logical Secrets, M.S. Miller, D. Bobrow, E.D. Tribble and
J. Levy (XEROX PARC)
17:20 - 18:05: Invited Talk: H. Gallaire (ECRC), Boosting
Logic Programming, Chairperson: F. Kluzniak (Warsaw Univer-
sity)
Friday 29 May
09:00 - 09:45: Invited Talk: K. Ramamohanarao and J.A.
Shepherd (University of Melbourne), Answering Queries in
Deductive Database Systems, Chairperson: C. Zaniolo (MCC)
10:15 - 12:20: Session on Program Analysis, Chairperson:
M.J. Maher (IBM T.J. Watson Research Center)
* Finite Fixed-point Theorems, R.A. O'Keefe (Quintus Compu-
ter Systems)
* Construction of Logic Programs based on Generalised
Fold/Unfold Rules, T. Kanamori and K. Horiuchi (Mitsubishi
Research Lab)
* A System of Precise Modes for Logic Programs, Z. Somogyi
(University of Melbourne)
* Type Synthesis for Ground PROLOG, F. Kluzniak (Warsaw
University)
* Derivation of Polymorphic Types for PROLOG Programs, J.
Zobel (University of Melbourne)
13:30 - 15:35: Session on Concurrent Languages, Chairperson:
S. Gregory (Imperial College)
* Channels: a Generalization of Streams, E.D. Tribble, M.S.
Miller, K. Kahn, D.G. Bobrow, C. Abbott (XEROX PARC) and E.
Shapiro (Weizmann Institute)
* Logic Semantics for a Class of Committed-choice Programs,
M.J. Maher (IBM T.J. Watson Research Center)
* An Approach to the Declarative Semantics of Synchroniza-
tion in Logic Languages, G. Levi and C. Palamidessi (Univer-
sita di Pisa)
* An Object-oriented Programming Language based on the
Parallel Logic Programming Language KL1, M. Ohki, A. Takeu-
chi and K. Furukawa (ICOT)
* Logic Operating Systems: Design Issues, I.T. Foster
(Imperial College)
16:05 - 16:55: SICS Presentation, S. Sundstrom
16:55 - 18:05: Panel Discussion: What are the Novel Applica-
tions of Logic Programming?, Chairperson: F. Mizoguchi
(Science University of Tokyo)
------------------------------
End of AIList Digest
********************
∂11-May-87 0144 LAWS@Stripe.SRI.COM AIList Digest V5 #115
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 11 May 87 01:44:14 PDT
Date: Sun 10 May 1987 16:57-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #115
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 11 May 1987 Volume 5 : Issue 115
Today's Topics:
Seminars - Reporting the Non-Monotonic News (BTL) &
Should McCarthy and Feigenbaum Talk to Each Other (SU) &
Qualitative Mechanical Reasoning (UPenn) &
Semi-Automatic Construction of Control Software (UPenn) &
Explaining and Refining Decision-Theoretic Choices (UPenn) &
General E-Unification (UPenn)
----------------------------------------------------------------------
Date: Thu 23 Apr 1987 13:50:34
From: dlm.allegra%btl.csnet@RELAY.CS.NET
Subject: Seminar - Reporting the Non-Monotonic News (BTL)
May 7th 10:30 AM
AT&T Bell Laboratories - Murray Hill 1E-449
REPORTING THE NON-MONOTONIC NEWS:
Keeping the Beat Local
Benjamin Grosof
Stanford University
"Non-monotonic" reasoning systems are ones in which some conclusions
have a default or retractable status. A prime motivation for such
systems is to build agents that revise their beliefs in response to
news from their environment. Efficient updating is problematic,
however, because adding new information in general may require the
revision of many, or even all, previous retractable conclusions. An
understanding is needed of the "partial monotonicities" of updating,
i.e. of the irrelevance of updates to parts of the previous
retractable conclusions.
To define non-monotonic theories, we introduce a formalism based on
McCarthy's circumscription that directly expresses, as axioms, both
default beliefs and preferences among default beliefs. It has a
strong semantics based on first- and second-order logic. We
characterize non-monotonic theories as hierarchically decomposable
in a manner more analogous to programming languages than to ordinary
monotonic logics. We then give a set of results about partial
monotonicities of updating. We discover some surprising differences
between updates consisting of default axioms and those consisting of
non-retractable axioms. These results bear on a wide variety of
applications of non-monotonic reasoning.
Sponsor: R.J.Brachman
------------------------------
Date: 22 Apr 87 1556 PDT
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Should McCarthy and Feigenbaum Talk to Each Other
(SU)
SHOULD JOHN MCCARTHY AND ED FEIGENBAUM
TALK TO EACH OTHER?
Thursday, April 23, 4:15pm
Bldg. 160, Room 161K
Matt Ginsberg
In this talk, I discuss one possible way to bridge the apparently
widening gap between the "neats" and the "scruffies" in AI. According
to Kuhn, a necessary step in resolving the differences between the
two camps is that one attack problems of interest to the other.
I attempt to do this by suggesting that the scruffy programs
are doing essentialy two things: a recognizable approximation
to first-order inference (such as MYCIN's backward chaining), and
some sort of bookkeeping with the results returned (e.g., manipulation
of certainty factors).
Formalizing this bookkeeping is attractive for a variety of reasons:
it will allow precise statements to be made about what the scruffies'
programs are doing, and may lead to more effective implementations of
their ideas. There are also advantages for the neats, since understanding
some of the proposed extensions to first-order inference in this fashion
appears to lead to computationally tractable algorithms for some simple
non-mononotonic logics.
If time permits, I will present a formalization which appears to
have the properties described in the previous paragraph.
------------------------------
Date: Fri, 24 Apr 87 22:29:33 AST
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Qualitative Mechanical Reasoning (UPenn)
Qualitative reasoning of mechanical devices and repair automation
Pearl Pu
COmputer and Information Science
University of Pennsylvania
216 Moore School
1pm April 28, 1987
A knowledge representation scheme, QUORUM (QUalitative reasoning of
Repair and Understanding of Mechanisms), has been constructed to apply
qualitative techniques to the mechanical domain, which is an area that
has been neglected in qualitative reasoning field. In addition, QUORUM
aims at providing foundations for the construction of a repair expert
system.
The problem in constructing a representation is the difficulty of
recognizing a feasible ontology with which we can express the behavior
of mechanical devices and, more importantly, faulty behaviors of a
device and its cause. Unlike most other approaches, our ontology
employs the notion of force and energy transfer, and motion
propagation. We discuss how the overall behavior of a device can be
derived from the knowledge about the structure and topology of the
device, and how faulty behaviors can be predicted based on information
about the perturbation of some of the original conditions of the
device. Necessary predicates and functions are constructed to express
the physical properties of a wide variety of basic and complex
mechanisms, and the interconnection relationships among the parts of a
mechanism. Several examples analyzed with QUORUM include a pair of
gears, a spring-driven cam mechanism, and a pendulum clock. An
algorithm for the propagation of force, motion, and causality is
proposed and examined.
------------------------------
Date: Mon, 27 Apr 87 16:31:00 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Semi-Automatic Construction of Control Software
(UPenn)
CIS COLLOQUIUM
UNIVERSITY OF PENNSYLVANIA
The Semi-Automatic Construction of Large Software Control System
David Bourne, Research Scientist, Robotics Institute, Carnegie Mellon
Large manufacturing software systems have taken many man-years of
effort to build in the past. For example, it is not uncommon for even a
small robotic cell to take several man years of effort to construct. Most
of this effort is spent over-coming the communication incompatibilities
(protocols and programming languages) that exist between machines from
multiple vendors. This talk presents a new AI programming language (CML -
the Cell Management Language) that greatly simplifies these major
difficulties. In addition, control systems for manufacturing will be
logically decomposed into several layers, and for each layer a semi-automatic
software tool will be described for constructing that layer in a new
application.
Thursday, April 30, 1987
3:00 - 4:30
Room 216
The Faculty Lounge
2:30 - 3:00
------------------------------
Date: Tue, 28 Apr 87 23:59:45 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Explaining and Refining Decision-Theoretic Choices
(UPenn)
EXPLAINING AND REFINING DECISION-THEORETIC CHOICES
Doctoral Thesis Proposal
Dave Klein
Computer and Information Science
University of Pennsylvania
As the need to make complex choices among competing alternative actions
is ubiquitous, the reasoning machinery of many intelligent systems will
include an explicit model for making choices. Decision analysis is
particularly useful for modelling such choices, and its potential for use
in intelligent systems motivates the construction of facilities for
automatically explaining decision-theoretic choices and for helping
users to incrementally refine the knowledge underlying them.
The proposed thesis addresses the problem of providing such
facilities. Specifically, we propose the construction of a
domain-independent facility called UTIL for explaining and refining a
restricted but widely applicable decision-theoretic model called the
additive multiattribute value model. We anticipate that this research
will provide contributions to both AI and decision analysis. In this
talk, the relevant issues are addressed in the context of examples
from the domain of intelligent process control.
Thursday, 30 April 1987
10:00 AM
5th floor conference room
Committee:
Dr. T.W. Finin (advisor)
Dr. N.I. Badler (chairman)
Dr. A.K. Joshi
Dr. E.K. Clemons (Wharton/Penn CIS)
Dr. E.H. Shortliffe (Stanford)
Dr. M.O. Weber (Institute fuer Wirtschaftswissenschaften, RWTH Aachen,
Germany)
------------------------------
Date: Wed, 29 Apr 87 00:04:32 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - General E-Unification (UPenn)
PhD Dissertation Proposal
General E-Unification:
Complete Transformations for Equational
Theorem Proving and Logic Programming
Wayne Snyder
Computer and Information Science
University of Pennsylvania
There has been much work in the past two decades on the problem of
incorporating methods for equational reasoning into computational
logic. Unfortunately, the ``substitution of equals for equals'' which
forms the basis of equational reasoning is fundamentally different
from the analytic methods used for non-equational reasoning, which are based
on an interpretation of the connectives in the language. This dicotomy
has convinced many researchers that we should stratify theorem provers
into a (non-equational) refutation mechanism and an E-unification
mechanism which performs equational reasoning during unification steps,
so that two terms E-unify if they are unifiable modulo the congruence
on terms induced by the set of equations E. Many special purpose E-unification
procedures have been designed for particular equational theories, and
several also for the class of theories which can be compiled into
rewrite rules via the Knuth-Bendix procedure. So far the problem
of E-unification for arbitrary equational theories has received little
attention, and in general there seems to be a need for some integrated
approach which will show the structure of the class of all
E-unification problems.
Our current research attempts to address the problem of general
E-unification and higher-order unification by extending the method
of transformations on term systems, developed in the context of
standard unification by Martelli and Montanari. We hope that this
approach will provide not only a basis for practical procedures, but
also a means for analysing unification problems in an abstract and
mathematically elegant fashion. Our results so far include a completeness
proof for our procedure and a new analysis of the occur check problem
in E-unification. We propose to extend these methods to refutation
methods incorporating equality, to a fundamentally new form of
E-unification which has come up in the study of equational matings,
and to the problem of higher-order E-unification. It is our hope that
this research will not only yield interesting theoretical results,
but will also help us to find practical algorithms for theorem proving
and logic programming in the presence of equality.
Friday, May 1, 10:00am
556 Moore (Conference Room)
Supervisor: Dr. Jean Gallier
Committee: Dr. Dale Miller (Chairman)
Dr. Peter Buneman
Dr. Frank Pfenning (CMU)
Dr. Paliath Narendran (GE)
Dr. Andre Scedrov
------------------------------
End of AIList Digest
********************
∂11-May-87 0329 LAWS@Stripe.SRI.COM AIList Digest V5 #116
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 11 May 87 03:29:40 PDT
Date: Sun 10 May 1987 17:01-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #116
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 11 May 1987 Volume 5 : Issue 116
Today's Topics:
Seminars - Automatic Equation Derivation (SU) &
Managing Uncertainties: Prospective Reasoning (CMU) &
A Shell for Intelligent Help Systems (UPenn) &
A Computational Model of Creative Writing (UPenn) &
Speaking to a Computer (CMU) &
BB* Layered Environment for AI Systems (HP)
----------------------------------------------------------------------
Date: 27 Apr 87 1318 PDT
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Automatic Equation Derivation (SU)
AUTOMATIC DERIVATION OF THE
EQUATION OF MOTION OF A PENDULUM
Thursday, April 30, 4:15pm
Bldg. 160, Room 161K
Michael Beeson
(beeson@csli.stanford.edu)
San Jose State University
Some knowledge of elementary physics has been formalized in first-order
logic. The domain of discourse includes physical objects and their
relations, mathematical formulas, and the semantic relation between
formulas and objects. The knowledge in question has been written in
Prolog and is sufficient to support an automatic derivation of the
differential equation of motion of a pendulum. The inference engine
makes use of the Knuth-Bendix method and also of a symbolic computation
system for algebra and calculus. Perhaps this is the first program to
use both knowledge representation in logic and symbolic computation.
------------------------------
Date: 30 Apr 87 14:50:08 EDT
From: Patricia.Mackiewicz@isl1.ri.cmu.edu
Subject: Seminar - Managing Uncertainties: Prospective Reasoning (CMU)
AI SEMINAR
TOPIC: Managing Uncertainties: The MU System For
Prospective Reasoning
SPEAKER: Paul Cohen, University of Massachusetts, Amherst
WHEN: Tuesday, May 5, 1987, 3:30 p.m.
WHERE: Wean Hall 5409
ABSTRACT:
I will describe a style of problem solving, prospective reasoning, and
a development environment, MU, for building prospective reasoning
systems. Prospective reasoning is a form of planning in which
knowledge of the state of the world and the effects of actions is
incomplete. I will illustrate one implementation of prospective
reasoning in MU with examples from medical diagnosis.
------------------------------
Date: Mon, 4 May 87 11:50:36 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - A Shell for Intelligent Help Systems (UPenn)
COLLOQUIUM
Computer and Information Science
University of Pennsylvania
A Shell for Intelligent Help Systems
Joost Breuker, Radboud Winkels, Jacobijn Sandberg
University of Amsterdam
Department of Social Science Informatics
The research reported here is part of a project
aimed at the construction of an environment for
building intelligent help systems. A help system
supports the user in handling and mastering an
information processing system. Core of this
environment is a shell that contains all domain
independent procedures and knowledge. A
comprehensive help system not only answers
questions of users, but also 'looks over their
shoulders' and interrupts when appropriate. This
means that a help system is equiped with a
PERFORMANCE INTERPRETER, consisting of a PLAN
RECOGNISER, a DIAGNOSER, and a QUESTION
INTERPRETER. Part of this shell and focus of this
paper is a generic COACH. In a help system a COACH
has two functions: to assist the user with a
current problem and to teach the user about the
IPS. The proposed COACH consists of three layers:
1) A DIDACTIC GOAL GENERATOR which genrates an
overlay of domain concepts that may be taught, 2)
STRATEGY PLANNER which constructs coaching
strategies, and 3) TACTICS which are the terminal
elements of strategies. They are the speech acts
finally "uttered" by the COACH. In this paper
these three layers are discussed in greater detail
and are related to empirical research.
Tuesday, May 12, 1987
Room 216
3:00 to 4:30
Refreshements Available
The Faculty Lounge
2:30 to 3:00
------------------------------
Date: Tue, 5 May 87 10:49:58 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - A Computational Model of Creative Writing (UPenn)
CIS Colloquium
Computer and Information Science
University of Pennsylvania
A COMPUTATIONAL MODEL OF CREATIVE WRITING
Masoud Yazdani
Dept. of Computer Science
University of Exeter, UK
The overal aim of the project is to examine a computational model
model of creativity based on the process of meta-level inspection and
control of loosely controlled simulations. The test bed for this
study is the act of creative writing. Various proposals for
computational story writing are considered and one of them, TALE-SPIN,
is critically evaluated. A more comprehensive model for storywriting
is then presented to account for the shortcomings pointed out. The
model presented consists of five distinct processes of plot-making,
world-making, simulation, narration and text generation. These
processes are further expanded within a computational framework. A
computer program, ROALD, is described which attempts to produce
stories within this general framework. ROALD, although basically the
simulation part of the model, acts as a test bed for the more general
idea of controlled simulation. we also look at other areas (picture
making and machine learning) where related work is being carried out.
Our argument can be stated at three levels of generality:
1. That the core of the act of creative writing is simulation of life
2. That this simulation needs to be part of a model which provides
situations within which the simulations occur as well as providing
sources of constraints so that the results are consistant and
interesting.
3. That not only creative writing but other creative acts can be
be viewed as the process of a loosely controlled simulation with
metal-level validation and revision of the results.
Wednesday, May 13, 1987
Room 216
3:00 to 4:30
Refreshments Available
2:30 to 3:00
The Faculty Lounge
------------------------------
Date: 5 May 1987 1002-EDT
From: Elaine Atkinson <EDA@C.CS.CMU.EDU>
Subject: Seminar - Speaking to a Computer (CMU)
SPEAKER: Alexander Hauptmann
TITLE: "Speaking to a Computer"
DATE: Tuesday, May 5
TIME: 12:00 - 1:20 p.m.
PLACE: Adamson Wing, Baker Hall
ABSTRACT: This talk describes an empirical study of man-computer speech
interaction. I will describe the experiment, its goals and outline the
experimental design and the many results. The experiment shows that
speech to a computer is not as ill-formed as one would expect. People
speaking to a computer are more disciplined than when speaking to
each other. There are large differences in the usage of spoken language
compared to typed language, and several phenomena which are unique to
spoken or typed input respectively. Usefulness for work in speech
understanding systems for the future is considered.
------------------------------
Date: Thu 7 May 87 19:08:52-PDT
From: Ted Kamins
Reply-to: KAMINS@Sierra.Stanford.EDU
Subject: Seminar - BB* Layered Environment for AI Systems (HP)
HEWLETT-PACKARD LABORATORIES
COMPUTER COLLOQUIUM
Speaker: Barbara Hayes-Roth
Senior Research Associate
Stanford Knowledge Systems Lab
Subject: BB*: A modular and layered environment for AI systems
Time: Thursday, May 14, 1987, 4 pm
Place: Hewlett-Packard
5M Auditorium
1501 Page Mill Road
Palo Alto
Non-HP Employees: Welcome! Please come to the lobby shortly before 4 pm
so that you can be escorted to the auditorium.
Refreshments will be served following the talk.
Host: Barry Bronson (857-3033)
Stanford contact: Ted Kamins (kamins@sierra)
Abstract:
An intelligent system reasons about--controls, explains,
learns about--its actions, thereby improving its efforts to achieve
goals and function in its environment. In order to perform
effectively, a system must have knowledge of the actions it can
perform, the events and states that can occur, and the relationships
among instances of those actions, events, and states. The BB*
environment represents this knowledge in an abstraction hierarchy and
defines uniform standards of knowledge content and representation for
modules within each of three hierarchical levels: architecture,
framework, and application.
The speaker will illustrate BB* with some of its current modules: (a)
the BB1 blackboard control architecture; (b) the ACCORD framework for
arrangement-assembly tasks; and (c) several domain-specific
applications of BB1-ACCORD. BB* advantages for system representation
and performance, system design and implementation, reusable knowledge
modules, and open systems integration will be discussed.
------------------------------
End of AIList Digest
********************
∂12-May-87 0242 LAWS@Stripe.SRI.COM AIList Digest V5 #117
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 May 87 02:42:11 PDT
Date: Mon 11 May 1987 23:51-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #117
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 12 May 1987 Volume 5 : Issue 117
Today's Topics:
Administrivia - BITNET Distribution,
AI Tools - Source Code Archives
----------------------------------------------------------------------
From: SCHNEIDER Daniel <shneider%cui.uucp@RELAY.CS.NET>
Subject: Re: Administrivia - BITNET Distribution
Newsgroups: mod.ai
Organization: University of Geneva, Switzerland
HI,
Lot's of people in Switzerland (and elsewhere too I guess) have access
to both BITNET and usenet, sometimes on two different machines, e.g. there
is very often a VMS/BITNET and a UNIX/usenet VAX around.
... so maybe you could ask all these people to use rn (i.e. the newsgroup
system) on unix and tell them that this way they save a lot of space
for *themselves*. A lot of people (even on unix) just don't know about mod.ai !
-Daniel
Daniel K.Schneider
ISSCO, University of Geneva, 54 route des Acacias, 1227 Carouge (Switzerland)
Tel. (..41) (22) 20 93 33 ext. 2114
to VMS/BITNET: to UNIX/EAN (preferable):
BITNET: SCHNEIDER@CGEUGE51 shneider%cui.unige.chunet@CERNVAX
ARPA: SCHNEIDER%CGEUGE51.BITNET@WISCVM shneider@cui.unige.CHUNET
or: shneider%cui.unige.chunet@ubc.csnet
uucp: mcvax!cernvax!cui!shneider
[I've held this message a lot longer than I should have, partly
because I don't really understand what goes on on the other
side of the gateways. I'm not sure, for instance, whether
mod.ai is still mod.ai since the recent name reorganization.
Anyway, there is a moderated newsgroup and an unmoderated one
(comp.ai, formerly net.ai); together they provide all that is
in the Arpanet AIList digests plus occasionally a little bit
more that I choose not to pass along. You can certainly cut
mailer costs if you drop direct digest delivery in favor of the
Usenet newsgroup distribution. For those of you with access to
BITNET, redistribution via the FINHUTC LISTSERV utility should
also be prefered to direct distribution. (FINHUTC seems to be
the only such LISTSERV at the moment; I'm told that other
LISTSERVs will pass AIList signups on to that host.) -- KIL]
------------------------------
Date: Wed, 1 Apr 87 10:21:04 EST
From: ucbcad!ames!rutgers!harvard!panda!suntzu!rmc@ucbvax.Berkeley.EDU
Subject: Re: Policy - Source Code Archives
[The following tells all you would ever want to know about
the mod.sources code redistribution. I give up on trying
to make a summary of how one would access the AI Expert code
(if it has even been submitted). Anyone who figures that out
might send us a little summary. Meanwhile Lawrence Leff tells
me that the North Texas AI Association has nearly finished
setting up a redistribution system for code and for report
lists. Thanks, everyone! -- KIL]
Well, here be the articles wherein i found the information on SIMTEL-20 and
mod.sources. I think the SIMTEL article is from the moderator of their
archives, and the mod.sources one definitely is. I kept all the mail
headers in the hopes that they will make it easier to contact them
(always difficult on an amorphous net.)
R Mark Chilenskas
decvax!genrad!panda!rmc
>From panda!genrad!mit-eddie!mirror!sources-request
Article: 737 of mod.sources
Path: teddy!panda!genrad!mit-eddie!mirror!sources-request
>From: sources-request@mirror.TMC.COM
Newsgroups: mod.sources
Subject: v09INF1: Introduction to mod.sources
Message-ID: <2127@mirror.TMC.COM>
Date: 6 Mar 87 21:13:12 GMT
Sender: rs@mirror.TMC.COM
Lines: 191
Approved: rs@mirror.TMC.COM
Submitted by: Rich Salz <rs@mirror.TMC.COM>
Mod.sources: Volume 9, Info 1
Archive-name: index9.1
This is the first of two introductory messages about mod.sources. This
one describes how to submit source to mod.sources, where the archive
sites are, and how to contact them. The companion articles lists all
previously-published mod.sources articles.
I am always looking for suggestions on how to improve the usefulness
of mod.sources, and can be contacted as listed below.
-Rich Salz
--------------------------------------------------------
SUBMITTING SOURCE FOR PUBLICATION
Items intended for posting should be sent to mirror!sources; requests
for missing copies or other queries should be sent to mirror!sources-request.
In Australia, Robert Elz is a "sub-moderator"; people there can work
with him (kre@munnari.OZ) to get postings out more easily.
If you want verification of arrival, so say in a cover note, or at the
beginning of your submission, if it is small. I try to verify that a
program works, and if I can't get it to work, I may hold up posting it
for a couple of days. Please note that, except in rare cases, source
without documentation and a Makefile will not be published. The backlog
from receival to posting is now about two weeks; this will probably
shrink down to one week in the upcoming weeks.
When you send mail, MAKE SURE to include a return address relative to
some well-known site(s). When all else fails, my conventional address
and phone number are:
Rich $alz
Mirror Systems
2067 Massachusetts Avenue
Cambridge, MA 02140
617-661-0777
---------------------------------------------------------------------------
THE STRUCTURE OF MOD.SOURCES ARTICLES
Each posting in mod.sources is called an "issue"; there are 100 issues
to a volume. The division is arbitrary, and has varied greatly in the
past. There are two types of articles in mod.sources; sources and
"information postings." They can be distinguished by the subject
line:
Subject: v07INF8: Index for Volume 7 and other info
This first word in the title identifies this as the eight info posting
in volume seven. Similarly, the subject line shown below:
Subject: v07i081: Public-domain Unix kernel
identifies this as the 81st source article in Volume 7. Large sources
are broken up into smaller pieces, and have subject lines that look like
this:
Subject: v07i082: System VI Source Distribution, Part03/08
The first few lines of an article are auxiliary headers that look like this:
Submitted by: root@freeware.ATT.COM
Mod.sources: Volume 7, Issue 82
Archive-name: new-login
The "Submitted by" is the author of the program. If you have comments about
the sources published in mod.sources, this is the person to contact.
When possible, this address is in domain form, otherwise it is a UUCP bang
path relative to site "mirror" (my machine).
The second line repeats the volume/issue information for the aide of NOTES
sites and automatic archiving programs.
The Archive-name is the "official" name of this source in the archive. Large
postings will have names that look like this:
Archive-name: patch2/Part01
Please try to use this name when requesting that sources be mailed to you.
Also, note that the "part number" given in the title, and the archive name
given in the auxiliary header need not be identical.
-------------------------------------------------------------
ACCESSING THE MOD.SOURCES ARCHIVE
The complete mod.sources archives are fairly large:
Volume Size (Kbytes)
1 4004
2 1204
3 3434
4 4220
5 390
6 4220
7 3976
8 4416
There are several active archive sites around the net. I am particularly
interested in helping set up a BITNET archive. A French archive site
is being set up, and it may be extended to provide full European coverage;
I will post more information as soon as things are settled.
When you request something before Volume 6, please make sure to be as
descriptive as possible as articles before then do not have official
names.
Several sites below will send tapes through the mail. For those sites,
send a 1/2" mag tape WITH RETURN POSTAGE and RETURN MAILER. Tapes
without postage or mailer will not be returned. No other methods (COD,
etc.) are available; please don't ask.
Finally, please note that I am Rich $alz, rs@mirror; Rick Adams is
rick@seismo, and Rich Kulawiec is rsk@j.cc.purdue.edu; we appreciate
the extra effort to get our names right. :-)
1. Phil Burdi has an archive on-line; contact usenet@cuae2.ATT.COM for more
info. He has also set up an off-hours UUCP login providing anonymous
UUCP access to the archives. The L.sys (Systems file) entry looks like:
(for HoneyDanBer UUCP users)
cuaepd Wk1830-0530,Sa,Su ACU 1200 3129643773 in:--in: pduucp
(for other UUCP users)
cuaepd Any1830-0530 ACU 1200 3129643773 in:--in: pduucp
Retrieve the file cuaepd!~/netnews/mod.sources/howto.snarf and follow the
directions therein.
2. Pyramid Technology has an archive arranged topically, and in compressed
tar files. They are happy to take new UUCP connections. They are also
somewhat willing to make tapes for people to come by and pick up,
provided you call WELL in advance and bring lunch money. This is being
managed by Claudia Dimmers and/or Carl Gutekunst. Contact
pyramid!usenet for more info.
3. Robert Elz (kre@munnari.OZ) keeps mod.sources in different ways
depending on his available disk space; contact him for more info.
4. Thos Sumner at UCSF will respond to requests for material, but cannot
promise an ongoing commitment. Anyone requesting material via mail
should supply a path from ucbvax. Anyone requesting tape should
contact me first. Contact him at thos@cca.ucsf.edu, or
ucbvax!ucsfcgl!cca.UCSF!thos
5. Tom Patterson at Washington University can make 800/1600/6250 BPI
tar tapes. If you give him a "real good reason," he can also make
1600 BPI VMS BACKUP or ANSI tapes. Send your tape, mailer, and postage
to Tom at:
Engineering Computer Lab, Bryan 509
Lindell & Skinker Blvd
Washington University
St. Louis, MO 63130
For best results, first send mail to wucs!archive (you stand a better
chance of getting processed quickly that way).
6. Jim Thompson (otto!jim) can make 1600 and 6250 tar and cpio tapes,
as well as VMS backup in a real pinch. He will also provide a
temporary UUCP login for interested parties at 1200 or 2400 baud.
His postal address is:
Jim Thompson
c/o Sun Teleguide
2551 Green Valley Pkwy
Henderson, Nv. 89015
(702) 454-4636
7. Of course, I have a complete set of archives. I can mail individual
postings, make files available for UUCP, and will send tapes (1600
BPI tar; 6250 or cpio in a crunch). Last time I checked, it cost
about $3 to send a 2400' tape across the country in a padded envelope
via first-class mail.
8. Rick Adams (rick@seismo.CSS.GOV) provides archive access to those on the
Internet. Access is available directly via anonymous FTP (Outside of
9am-7pm EST M-F.) The files are in a directory mod.sources, then a
sub-directory Volume[1-7]. They are named as closely as possible to the
names in the Index. Files that have not been assigned a "short name"
reside in the directory sources/mod temporarily. Send tape, mailer,
and postage to Rick at:
Center for Seismic Studies
1300 North 17th Street, Suite 1450
Arlington, VA 22209-3871
9. Internet sites may also retrieve archives from j.cc.purdue.edu via
anonymous ftp. The archive is in the directory "mod.sources",
subdivided into "volume1", etc. Due to disk space considerations,
many of the sources are compressed; these may be recognized by the
".Z" suffix. If you don't have compress & friends, they are in
~ftp/pub/compress.shar for the taking. This is being managed by
Rich Kulawiec (Wombat), pucc-j!rsk, rsk@j.cc.purdue.edu. If your
host tables don't grok "j.cc.purdue.edu", try "purdue-asc.arpa".
They would appreciate it if you would avoid large file transfers
in the middle of the day. [Rick also points out that the FTP'able
archies also contain mod.amiga, a bunch of kermit sources, news
2.11, rn 4.3, nntp, and whatever else happens to be in ~ftp/pub at
the moment.]
10. The CSNET CIC has been doing a fair amount of work to bring their
automated retrieval up-to-speed. They now have a complete archive,
and are making things available as quickly as possible (they have
special legal restrictions on what they can distribute, so everything
may not be available). Look in the latest issue of the CSNET Forum,
or contact postmaster@sh.cs.net.
________
>From panda!genrad!decvax!ucbvax!ucbcad!ames!styx!lll-lcc!seismo!brl-adm
!brl-smoke!w8sdz
Article: 2430 of comp.sys.ibm.pc
Path: teddy!panda!genrad!decvax!ucbvax!ucbcad!ames!styx!lll-lcc!seismo!brl-adm
!brl-smoke!w8sdz
>From: w8sdz@brl-smoke.ARPA (Keith B. Petersen )
Newsgroups: comp.sys.ibm.pc
Subject: Re: "pr" for dos
Message-ID: <5665@brl-smoke.ARPA>
Date: 7 Mar 87 04:28:30 GMT
References: <286@micropro.UUCP> <1108@uwmacc.UUCP> <2120@tekgvs.TEK.COM>
<1129@uwmacc.UUCP>
Reply-To: w8sdz@brl.arpa (Keith B. Petersen (WSMR|towson) <w8sdz>)
Distribution: na
Organization: Ballistic Research Lab (BRL), APG, MD.
Lines: 106
Status: RO
To obtain up to five files in a single request message by netmail from
the public domain archives kept on SIMTEL20.ARPA, send a message to:
ARCHIVE-REQUEST@SIMTEL20.ARPA
or via uucp:
...!ucbvax!simtel20.arpa!archive-request
...!uw-beaver!simtel20.arpa!archive-request
...!decwrl!simtel20.arpa!archive-request
...!lll-crg!simtel20.arpa!archive-request
...!ut-sally!simtel20.arpa!archive-request
...!harvard!simtel20.arpa!archive-request
[do NOT use host "seismo" - they are blocking messages from the server]
The message body must contain lines beginning with the keyword SEND,
one SEND line for each file requested. Case is not significant.
The general syntax of a SEND line is:
SEND format filename
In general, a filename consists of the following components:
device:<directory>file.type.generation
"device:" is usually PD:, and the combination of PD:<directory> is
expected unless an alias has been advertised of the form "alias:",
which takes the place of both device and directory fields. The
generation field should be left off in order to default to the highest
generation number so you can be sure of getting the latest version of
the file requested. "file.type" follows the usual filenaming
conventions.
In all formats listed below, if the file to be sent is larger than
55K, the file is sent in numbered parts. The parts must be
reassembled in order and edited to remove any headers, preface, and
trailers before the process can be reversed to reconstruct the
original file.
Allowable formats are:
SEND HELP
This file you are reading now.
SEND INFO
A detailed description of the SIMTEL20 Archives, which
includes this file, pointers to certain key files, and
descriptions of various file transfer programs and related
utilities.
SEND BOOTSTRAP
A brief quick reference listing of filenames of the key
utilities used to reconstruct files sent by the compression
and encoding techniques listed below.
SEND DIR filespec
This format returns a CRC list of the requested files, and is
the only format which allows wildcard filenames (but not
wildcard directory names). The list is sent as an ASCII text
file. The wildcard characters are "*" and "%". The asterisk
means any number of characters, while the percent sign means
exactly one character. Either or both may appear in any
combination in either or both the file or type fields, while
only the asterisk may appear in the generation field.
SEND RAW filename
If the file is ASCII, it is sent as-is, regardless of size.
This format is the least efficient over network and mail
gateway resources. Use this format only if you absolutely
must.
With the four formats listed below, if the file is ASCII and under 25k
characters, it is sent as-is, as if RAW format was requested. Binary
files are always processed according to the requested format.
However, a request for ARC or SQ processing of files with type ".ARC",
".LBR", or ".%Q%" is ignored and the original file is either uuencoded
or hexified (if possible), according to the requested format. If the
file was not sent RAW, a short preface is inserted at the front of the
message describing the process actually taken and a CRC entry
describing the original file.
SEND ARE filename or SEND filename
The original file is made into a uuencoded ARC file.
SEND ARH filename
The original file is made into a hexified ARC file if the ARC
file is under 64K bytes long. Otherwise, an apology is
returned instead of the requested file.
SEND SQE filename
The original file is made into a uuencoded SQueezed file.
SEND SQH filename
The original file is made into a hexified SQueezed file if the
Squeezed file is under 64K bytes long. Otherwise, an apology
is returned instead of the requested file.
To get started in finding your way around the SIMTEL20 archives, send
a message to the server with the request: SEND INFO
--
--Keith Petersen
Arpa: W8SDZ@SIMTEL20.ARPA
Uucp: {bellcore,decwrl,harvard,lll-crg,ucbvax,uw-beaver}!simtel20.arpa!w8sdz
GEnie Mail: W8SDZ
------------------------------
End of AIList Digest
********************
∂12-May-87 0506 LAWS@Stripe.SRI.COM AIList Digest V5 #118
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 May 87 05:06:18 PDT
Date: Tue 12 May 1987 00:00-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #118
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 12 May 1987 Volume 5 : Issue 118
Today's Topics:
Queries - Design Info for Expert Systems &
Publicly available Expert Systems? & KA Workshop Proceedings &
Post-Graduate Research in Visual Recognition using AI,
Conference - IJCAI Information,
Philosophy - The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 7 May 87 04:53:54 GMT
From: oliveb!intelca!mipos3!omepd!psu-cs!psueea!lendaris@ames.arpa
(George G. Lendaris)
Subject: Wanted: Design Info re: Operational Expert Systems
For the last year I have been studying papers
which give a high level treatment of design con-
siderations for expert systems in various con-
texts. Currently, I am studying a book by Sowa
titled "Conceptual Structures".
I am now interested in more detailed descriptions
of operational expert systems to gain familiarity
with "lower level" issues that need attention in
actually realizing the representation and manipu-
lation of "knowledge".
I would like a reasonably detailed description (in
English) of the "nitty gritties" of such an imple-
mentation.
Leads to people who might have such information
will be greatly appreciated.
Please send to lendaris@psueea.UUCP
Thanks in advance.
George G. Lendaris
Professor of Systems Science
and Electrical Engineering
------------------------------
Date: 8 May 87 07:48:18 GMT
From: arman@locus.ucla.edu
Subject: Publicly available Expert Systems?
Dear colleagues,
I was wondering if there are any publicly availble Expert Systems
out there. It doesn't really matter what machine it is running on,
or what language it is written in, I just want to look at some real
(and maybe) working code. I would also appreciate any pointers to places
(universities) where I could get expert systems from. Please Email
responses and I shall summarize the results if there is any interest.
Thank You, (in advance)
Arman Bostani,
arman@cs.ucla.edu
[...]
------------------------------
Date: Fri, 8 May 87 09:46:24 edt
From: dg1v#@andrew.cmu.edu (David Greene)
Subject: KA workshop proceedings
Can anyone tell me where I can get the proceedings from :
Knowledge Acquisition for Knowledge-Based Systems Workshop, Banff, Alberta,
Canada, November 2-7, 1986.
Also is there any information about future workshops?
Thanks in advance.
- David Greene
dg1v@andrew.cmu.edu
------------------------------
Date: Tue, 12 May 87 15:55:24 +1000
From: J.T. Teh <munnari!mulga.oz!jteh@seismo.CSS.GOV>
Subject: Information wanted on Post Graduate research in Visual
Recognition using AI
Information wanted on Post Graduate research in Visual Recognition using AI
I am an Honours student at the University of Melbourne, Australia and am
interested in persuing a PostGraduate degree in the field of Visual
Recognition systems using Prolog. My Honours project is to develop a
Visual Recognition system to run on the Apple Macintosh Plus using Prolog.
I am looking for information about universities in the United States, UK
or within Australia that are involved and with experience in this area
of research. If anyone has any information or names of people of whom I
should contact, could they mail me directly? Thanks in advance.
Or, if you know of anyone who might know, could you please redirect this
article to them? Thank you.
J.T. Teh
===========================
UUCP: {seismo,mcvax,ukc,ubc-vision}!munnari!jteh
or {seismo,mcvax,ukc,ubc-vision}!mulga!jteh
ARPA: jteh%munnari.oz@seismo.css.gov
or jteh%mulga.oz@seismo.css.gov
CSNET: jteh%munnari.oz@australia
or jteh%mulga.oz@australia
Postal Address:
J.T. Teh
c/o Department of Computer Science
University of Melbourne
Parkville,
Melbourne,
Australia 3052.
--------
J.T Teh
"He is no fool who gives up what he cannot keep to gain what he cannot lose."
- James Elliot
------------------------------
Date: Sun, 10 May 87 16:27:31 BST
From: "G. Joly" (Birkbeck) <gjoly@Cs.Ucl.AC.UK>
Subject: Re: IJCAI information (Vol 5 # 111).
Can I echo Chang Bang in a request for info on IJCAI-87? I would like
to know if there is any financial support available from IJCAII (the
sponsors). I note that US citizens can get support for air travel from
abroad (this was announced in the digest).
I have not seen any mention of sources of support in the conference
brochure. (I have applied to local (U.K.) sources for partial support.)
Gordon Joly,
Computer Science,
Birkbeck College,
Malet Street,
LONDON WC1E 7HX.
+44 1 631 6468
ARPA: gjoly@cs.ucl.ac.uk
BITNET: UBACW59%uk.ac.bbk.cu@AC.UK
UUCP: ...!seismo!mvcax!ukc!bbk-cs!gordon
------------------------------
Date: Mon 11 May 87 10:09:11-PDT
From: Georgia Navarro <NAVARRO@Stripe.SRI.COM>
Subject: Early Registration for IJCAI
[Forwarded by Laws@STRIPE.SRI.COM.]
The deadline for early registration for IJCAI in Milan
is JUNE 15. The registration fee has to be in lira. IT TAKES AT LEAST 3
WEEKS TO GET A CHECK FROM THE BofA. Also, there is a special on hotel
accomodations, but that check is supposed to be there no later than May 30.
[...]
------------------------------
Date: Sat, 9 May 87 11:45:17 EDT
From: harnad@Princeton.EDU
Subject: The Symbol Grounding Problem
[Also forwarded to the Neuron Digest. -- KIL]
To define a SUBsymbolic "level" rather than merely a NONsymbolic
process or phenomenon one needs a formal justification for the implied
up/down-ness of the relationship. In the paradigm case -- the
hardware/software distinction and the hierarchy of compiled
programming languages -- the requisite formal basis for the hierarchy is
quite explicit. It is the relation of compilation and implementation.
Higher-level languages are formally compiled into lower level ones
and the lowest is implemented as instructions that are executed by a
machine. Is there anything in the relation of connectionist processes
to symbolic ones that justifies calling the former "sub"-symbolic in
anything other than a a hopeful metaphorical sense at this time?
The fact that IF neural processes are really connectionistic (an
empirical hypothesis) THEN connectionist models are implementable in
the brain defines a super/sub relationship between connectionist
models and neural processes (conditional, of course, on the validity
-- far from established or even suggested by existing evidence -- of
the empirical hypothesis), but this would still have no bearing on
whether connectionism can be considered to stand in a sub/super relationship
to a symbolic "level." There is of course also the fact that any discrete
physical process is formally equivalent in its input/output relations
to some turing machine state, i.e., some symbolic state. But that would
make every such physical process "subsymbolic," so surely turing
equivalence cannot be the requisite justification for the putative
subsymbolic status of connectionism in particular.
[Has Turing-equivalence of connectionist systems been established?
My understanding is that asynchronous analog systems need not be
"discrete physical processes" or finite algorithms. -- KIL]
A fourth sense of down-up (besides hardware/software, neural
implementability and turing-equivalence) is psychophysical
down-upness. According to my own bottom-up model, presented in the book I
just edited (Categorical Perception, Cambridge University Press 1987),
symbols can be "grounded" in nonsymbolic representations in the
following specific way:
Sensory input generates (1) iconic representations -- continuous,
isomorphic analogs of the sensory surfaces. Iconic representations
subserve relative discrimination performance (telling pairs of things
apart and judging how similar they are).
Next, constraints on categorization (e.g., either natural
discontinuities in the input, innate discontinuities in the internal
representation, or, most important, discontinuities *learned* on the
basis of input sampling, sorting and labeling with feedback) generate
(2) categorical representations -- constructive A/D filters which preserve
the invariant sensory features that are sufficient to subserve reliable
categorization performance. [It is in the process of *finding* the
invariant features in a given context of confusable alternatives that I
believe connectionist processes may come in.] Categorical
representations subserve identification performance (sorting things
and naming them).
Finally, the *labels* of these labeled categories -- now *grounded*
bottom/up in nonsymbolic representations (iconic and categorical)
derived from sensory experience -- can then be combined and recombined
in (3) symbolic representations of the kind used (exclusively, and
without grounding) in contemporary symbolic AI approaches. Symbolic
representations subserve natural language and all knowledge and
learning by *description* as opposed to direct experiential
acquaintance.
In response to my challenge to justify the "sub" in "subsymbolic" when
one wishes to characterize connectionism as subsymbolic rather than
just nonsymbolic, rik%roland@sdcsvax.ucsd.edu (Rik Belew) replies:
> I do intend something more than non-symbolic when I use the term
> sub-symbolic. I do not rely upon "hopeful neural analogies" or any
> other form of hardware/software distinction. I use "subsymbolic"
> to refer to a level of representation below the symbolic
> representations typically used in AI... I also intend to connote
> a supporting relationship between the levels, with subsymbolic
> representations being used to construct symbolic ones (as in subatomic).
The problem is that the "below" and the "supporting" are not cashed
in, and hence just seem to be synonyms for "sub," which remains to
be justified. An explicit bottom-up hypothesis is needed to
characterize just how the symbolic representations are constructed out
of the "subsymbolic" ones. (The "subatomic" analogy won't do,
otherwise atoms risk becoming subsymbolic too...) Dr. Belew expresses
some sympathy for my own grounding hypothesis, but it is not clear
that he is relying on it for the justification of his own "sub."
Moreover, this would make connectionism's subsymbolic status
conditional on the validity of a particular grounding hypothesis
(i.e., that three representational levels exist as I described them,
in the specific relation I described, and that connectionistic
processes are the means of extracting the invariant features underlying
the categorical [subsymbolic] representation). I would of course be
delighted if my hypothesis turned out to be right, but at this point
it still seems a rather risky "ground" for justifying the "sub" status of
connectionism.
> my interest in symbols began with the question of how a system might
> learn truly new symbols. I see nothing in the traditional AI
> definitions of symbol that helps me with that problem.
The traditional AI definition of symbol is simply arbitrary formal
tokens in a formal symbol system, governed by formal syntactic rules
for symbol manipulation. This general notion is not unique to AI but
comes from the formal theory of computation. There is certainly a
sense of "new" that this captures, namely, novel recombinations of
prior symbols, according to the syntactic rules for combination and
recombination. And that's certainly too vague and general for, say,
human senses of symbol and new-symbol. In my model this combinatorial
property does make the production of new symbols possible, in a sense.
But combinatorics is limited by several factors. One factor is the grounding
problem, already discussed (symbols alone just generate an ungrounded,
formal syntactic circle that there is no way of breaking out of, just as
in trying to learn Chinese from a Chinese-Chinese dictionary alone). Other
limiting factors on combinatorics are combinatory explosion, the frame problem,
the credit assignment problem and all the other variants that I have
conjectured to be just different aspects of the problem of the
*underdetermination* of theory by data. Pure symbol combinatorics
certainly cannot contend with these. The final "newness" problem is of
course that of creativity -- the stuff that, by definition, is not
derivable by some prior rule from your existing symbolic repertoire. A
rule for handling that would be self-contradictory; the real source of
such newness is probably partly statistical, and again connectionism may
be one of the candidate components.
> It seems very conceivable to me that the critical property we will
> choose to ascribe to computational objects in our systems symbols
> is that we (i.e., people) can understand their semantic content.
You are right, and what I had inadvertently left out of my prior
(standard) syntactic definition of symbols and symbol manipulation was
of course that the symbols and manipulations must be semantically
interpretable. Unfortunately, so far that further fact has only led to
Searlian mysteries about "intrinsic" vs. "derived intentionality" and
scepticism about the the possibility of capturing mental processes
with computational ones. My grounding proposal is meant to answer
these as well.
> the fact that symbols must be grounded in the *experience* of the
> cognitive system suggests why symbols in artificial systems (like
> computers) will be fundamentally different from those arising in
> natural systems (like people)... if your grounding hypothesis is
> correct (as I believe it is) and the symbols thus generated are based
> in a fundamental way on the machine's experience, I see no reason to
> believe that the resulting symbols will be comprehensible to people.
> [e.g., interpretations of hidden units... as our systems get more
> complex]
This is why I've laid such emphasis on the "Total Turing Test."
Because toy models and modules, based on restricted data and performance
capacities, may simply not be representative of and comparable to
organisms' complexly interrelated robotic and symbolic
functional capacities. The experiential base -- and, more
important, the performance capacity -- must be comparable in a viable
model of cognition. On the other hand, the "experience" I'm talking
about is merely the direct (nonsymbolic) sensory input history, *not*
"conscious experience." I'm a methodological epiphenomenalist on
that. And I don't understand the part about the comprehensibility of
machine symbols to people. This may be the ambiguity of the symbolic
status of putative "subsymbolic" representations again.
> The experience lying behind a word like "apple" is so different
> for any human from that of any machine that I find it very unlikely
> that the "apple" symbol used by these two system will be comparable.
I agree. But this is why I proposed that a candidate device must pass
the Total Turing Test in order to be capture mental function.
Arbitrary pieces of performance could be accomplished in radically different
ways and would hence be noncomparable with our own.
> Based on the grounding hypothesis, if computers are ever to understand
> NL as fully as humans, they must have an equally vast corpus of
> experience from which to draw. We propose that the huge volumes of NL
> text managed by IR systems provide exactly the corpus of "experience"
> needed for such understanding. Each word in every document in an IR
> system constitutes a separate experiential "data point" about what
> that word means. (We also recognize, however, that the obvious
> differences between the text-base "experience" and the human
> experience also implies fundamental limits on NL understanding
> derived from this source.)... In this application the computer's
> experience of the world is second-hand, via documents written by
> people about the world and subsequently through users'queries of
> the system
We cannot be talking about the same grounding hypothesis, because mine
is based on *direct sensory experience* ("learning by acquaintance")
as oppposed to the symbol combinations ("learning by description"),
with which it is explicitly contrasted, and which my hypothesis
claims must be *grounded* in the former. The difference between
text-based and sensory experience is crucial indeed, but for both
humans and machines. Sensory input is nonsymbolic and first-hand;
textual information is symbolic and second-hand. First things first.
> I'm a bit worried that there is a basic contradiction in grounded
> symbols. You are suggesting (and I've been agreeing) that the only
> useful notion of symbols requires that they have "inherent
> intentionality": i.e., that there is a relatively direct connection
> between them and the world they denote. Yet almost every definition
> of symbols requires that the correspondence between the symbol and
> its referent be *arbitrary*. It seems, therefore, that your "symbols"
> correspond more closely to *icons* (as defined by Peirce), which
> do have such direct correspondences, than to symbols. Would you agree?
I'm afraid I must disagree. As I indicated earlier, icons do indeed
play a role in my proposal, but they are not the symbols. They merely
provide part of the (nonsymbolic) *groundwork* for the symbols. The
symbol tokens are indeed arbitrary. Their relation to the world is
grounded in and mediated by the (nonsymbolic) iconic and categorical
representations.
> In terms of computerized knowledge representations, I think we have
> need of both icons and symbols...
And reliable categorical invariance filters. And a principled
bottom-up grounding relation among them.
> I see connectionist learning systems building representational objects
> that seem most like icons. I see traditional AI knowledge
> representation languages typically using symbols and indices. One of
> the questions that most interests me at the moment is the appropriate
> "ontogenetic ordering" for these three classes of representation.
> I think the answer would have clear consequences for this discussion
> of the relationship between connectionist and symbolic representations
> in AI.
I see analog transformations of the sensory surfaces as the best
candidates for icons, and connectionist learning systems as
as possible candidates for the process that finds and extracts the invariant
features underlying categorical representations. I agree about traditional
AI and symbols, and my grounding hypothesis is intended as an answer about
the appropriate "ontogenetic ordering."
> Finally, this view also helps to characterize what I find missing
> in most *symbolic* approaches to machine learning: the world
> "experienced" by these systems is unrealistically barren, composed
> of relatively small numbers of relatively simple percepts (describing
> blocks-world arches, or poker hands, for example). The appealling
> aspect of connectionist learning systems (and other subsymbolic
> learning approaches...) is that they thrive in exactly those
> situations where the system's base of "experience" is richer by
> several orders of magnitude. This accounts for the basically
> *statistical* nature of these algorithms (to which you've referred),
> since they are attempting to build representations that account for
> statistically significant regularities in their massive base of
> experience.
Toy models and microworlds are indeed barren, unrealistic and probably
unrepresentative. We should work toward models that can pass the Total
Turing Test. Invariance-detection under conditions of high
interconfusability is indeed the problem of a device or organism that
learns its categories from experience. If connectionism turns out to
be able to do this on a life-size scale, it will certainly be a
powerful candidate component in the processes underlying our
representational architecture, especially the categorical level. What
that architecture is, and whether this is indeed the precise
justification for connectionism's "sub" status, remains to be seen.
Stevan Harnad
{seismo, psuvax1, bellcore, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.princeton.edu
(609)-921-7771
------------------------------
End of AIList Digest
********************
∂12-May-87 0808 LAWS@Stripe.SRI.COM AIList Digest V5 #119
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 May 87 08:07:14 PDT
Date: Tue 12 May 1987 00:07-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #119
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 12 May 1987 Volume 5 : Issue 119
Today's Topics:
Application - Grammar Checkers,
AI Tools - Academic Release of NU-Prolog System
----------------------------------------------------------------------
Date: 8 May 87 08:32:10 GMT
From: humu!uhccux!todd%nosc.UUCP@sdcsvax.ucsd.edu (The Perplexed Wiz)
Reply-to: todd@uhccux.UUCP (The Perplexed Wiz)
Subject: Re: grammar checkers
I would rather see mainstream AI-related topics given space in AIList
rather than take up more space with yet another "grammar checker"
related messsage. And while I accept the criticism of my comments in
the spirit of academic give and take in the exchange of ideas, I will
make, I hope, the final comment in this discussion and then consider
it closed for the moment.
I wish the two following commentators
"Linda G. Means" <MEANS%gmr.com@RELAY.CS.NET>
gilbert@aimmi.UUCP (Gilbert Cockton)
had *read* what I said before they reacted. I wrote:
>I think that if these style checking tools are used in conjunction
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
***********
>with the efforts of a good teacher of writing, then these style
↑↑↑↑ ↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
>checkers are of great benefit. It is better that children learn a
>few rules of writing to start with than no rules at all. Of course,
>reading lots of good examples of writing and a good teacher are still
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑ *** ↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
***
>necessary
↑↑↑↑↑↑↑↑↑
I don't think that anyone would seriously suggest that these borderline
"AI" programs be used *exclusively* to teach children (or people of any
other age group) to write.
My thanks to Ken Laws for allowing this interesting little discussion
to take place here instead of forcing us to move it to AI-ED (where it
probably belongs, I admit). Now, let's get back to mainstream AI :-)
Todd Ogasawara, U. of Hawaii Computing Center
UUCP: {ihnp4,seismo,ucbvax,dcdwest}!sdcsvax!nosc!uhccux!todd
ARPA: uhccux!todd@nosc.MIL
INTERNET: todd@uhccux.UHCC.HAWAII.EDU
[NL-KR@CS.ROCHESTER.EDU has also been reprinting these messages. -- KIL]
------------------------------
Date: Fri 8 May 87 10:08:45-PDT
From: PAT <HAYES@SPAR-20.ARPA>
Subject: Grammar Checkers
On 'Style checkers'. Of course one shouldnt criticise to extremes, and
no doubt a competent adult would find these things useful sometimes.
That wasnt what I was complaining about: it was using them to
INFLUENCE children. The word was chosen carefully. Marvin isnt going
to think that the thing should be taken as an authority on how to
write, or that in order to write well he should simply arrange that
the style checker doesnt find any problems. But if they are used to
grade or influence the way children write in a school setting, that is
exactly what almost all kids will rapidly decide. ( Unless an
extraordinarily good teacher is in charge, and maybe even then. Just
think of the pressures on a teacher to come to rely on the programs
judgement, and on a pupil to take the machine as authoritative. The
machine finds no fault with Joes essay and complains about Bettys, but
the teacher gives Betty a higher grade..... )
Pat Hayes
------------------------------
Date: 9 May 87 18:17:44 GMT
From: gilbert@aimmi.UUCP (Gilbert Cockton)
Reply-to: gilbert@aimmi.UUCP (Gilbert Cockton)
Subject: Grammar Checkers
In article <MINSKY.12299573623.BABYL@MIT-OZ> MINSKY@OZ.AI.MIT.EDU writes:
>I agree with Todd, Ogasawara: one should not criticise to extremes.
What does this mean? I thought accuracy was the only goal in
criticism, not avoiding the ends of some quaint invented continuum.
Can we have a style checker which rates our extremity with marks out
of 10 (0 for credulous and 10 for rampant scepticism perhaps :-))
> I also used it to establish a "gradient". The early
>chapters are written at a "grade level" of about 8.6 and the book ends
>up with grade levels more like 13.2 - using RightWriter's quaint
>scale.
How about MIT turning some of its resources towards VALIDATING this
quaint gradient? Do you seriously think there is any real computable ordering,
partial or otherwise, which can be applied to your chapters and
actually square up with any of our everyday evaluations of text
complexity? If so, where's the beef? How would US data square up with
European data. English teachers in the UK, for example, do not apply
unimaginative inflexible rules to students' writing, so it could be
that many educated English students will be turned off by an 8.6
introduction. Luckily we have not yet been carried away with the
belief that all complex ideas can have banal presentations without
bowdlerisation creeping in. Doubtless your style checker would ask me
to drop 'bowdlerise'? What should I have used instead, given that I
want an EXACT synonym with all its connotations? When I taught,
I would have advised my students to find a dictionary (many of them carried
them anyway - and I taught children from a wide range of cultural and
economic backgrounds). God knows what the French would say to a
mechanical style checker (a Franglais remover would go down well
though).
Finally, how on earth do these style checkers know which words will be
commonly understood? Surely they don't use word frequency in newspapers
or something like that? Does the overuse of a word in the media imply
universal understanding of/consensus on its meaning - eg. 'moral',
'freedom', 'extreme', 'quaint', 'seriously', 'inflexible' etc?
Does the limited use of a word in the media imply universal ignorance
- eg. 'ok', 'alright', 'balls', 'claptrap', 'space cadet', 'avid',
'stroppy', 'automaton'?
I would not regard any of the criticisms of style checkers I have read
as 'extreme' at all. The difference seems to be one of gross credulity
versus informed criticism. People who know nothing about good style
will believe all the things which the style checker hackers have MADE
UP - I defy any style checker implementor to point to a sound
experimental/statistical basis for the style rules they have palmed
off onto their gullible customers. Perhaps they did at least read some
books by self-proclaimed authorities, but this would only shift the charge
from invention to uncritical acceptance. I'd still be unimpressed.
This may sound extreme - that however is irrelevant. The point is,
am I accurate?. Note that my substantial assertions are few:
i) Style don't compute. Verify by Chinese characters test
between a style checker and the editors of the New Yorker
(US) or the Listener (UK). Other quality magazine editors
will do. Can you spot the editors' critiques?
ii) The current 'reading age' metrics have no validity.
They are bogus psychometric tools. Operationally I am
saying that their will be no strong correlation (say r >
0.9, p < 0.001) between the reading age of text and a
reader's performance on a comprehension test. Allow the
author to add a glossary and the correlation will weaken.
People can learn new words you know.
iii) Current measures of popular understanding of words are
equally bogus and there is NO decent research to back it
up. There has been some good work on correlating
vocabulary with educational achievement, but this tells
us nothing about the typical adult's vocabulary.
Every assertion above is falsifiable, so let's all forget about emotive
subjective concepts like extremity (= I disagree a lot and wish you hadn't
said that) and get back to an objective, informed debate. The motion
is:
"All computer based style checkers can stunt the literary
growth of their users"
A second order effect is that, although 1,000 chimpanzees could
between them type out the works of Shakespeare given enough time, they
would fail miserably if their output had to be passed by a computer
style checker.
To be, or not to be, that is the question.
>> Sentence starts with infinitive
Sentence has no subject.
Whether it is ....
>> "Whether" may not be understood by people who just read
comics. (? spelling mistake = weather ?).
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.aimmi ARPA: gilbert%aimmi.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..!{backbone}!aimmi.hw.ac.uk!gilbert
------------------------------
Date: Thu, 7 May 87 22:56 EDT
From: Brad Miller <miller@ACORN.CS.ROCHESTER.EDU>
Reply-to: miller@cs.rochester.edu
Subject: re: grammar checkers
Date: Mon, 4 May 87 12:18 EST
From: "Linda G. Means" <MEANS%gmr.com@RELAY.CS.NET>
An aside to Ken Laws:
You questioned whether the topic of automatic style checkers is
appropriate to AILIST: is it AI? I believe it is. The study of
computational stylistics is a difficult natural language problem
with a long history. [...]
- Linda Means
GM Research Laboratories
means%gmr.com@relay.cs.net
Personally, I suspect the question is should the discussion be carried in
AIList or moved to NL-KR. NL-KR is, indeed, already picking it up; further
such things are directly in NL-KR's scope, and the idea of the list was to be
somewhat subtractive from AIList, keeping traffic on Ken's list a little
lower.
Brad Miller
nl-kr-request@cs.rochester.edu
miller@cs.rochester.edu
miller@acorn.cs.rochester.edu
------------------------------
Date: Fri, 08 May 87 12:19:01 +1000
From: munnari!mulga.oz!jas@seismo.CSS.GOV
Subject: Announcement of availability of new Prolog system
If the following announcement is suitable for posting in either of
these newsgroups, would you be able to forward it to the list ASAP.
Thanks, jas
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
John Shepherd
Department of Computer Science,
University of Melbourne, CSNET: jas%mulga.oz@australia
Parkville, 3052, ARPA: jas%mulga.oz@seismo.css.gov
AUSTRALIA UUCP: ...!munnari!mulga!jas
Announcement:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Subject: Academic Release of NU-Prolog System
Version 1.1 of the NU-Prolog system is now available for release to
academic institutions (schools, colleges, universities).
NU-Prolog is a second generation Prolog system which incorporates a
number of important advances in Logic Programming implementation.
NU-Prolog was implemented as part of the Machine Intelligence Project+
in the Department of Computer Science at the University of Melbourne.
It is the successor to Lee Naish's successful MU-Prolog system and
attempts to move Prolog closer to the ideals of Logic Programming by
allowing the user to program in a style closer to first order logic.
In addition, it provides substantial performance gains over interpreted
systems such as MU-Prolog.
NU-Prolog has the following features:
* compiles Prolog programs into machine code for an enhanced version
of the Warren abstract machine (implementing the delay/coroutine
style of programming of MU-Prolog)
* incorporates a database system based on superimposed codeword
indexing which can store general Prolog terms in external databases
for fast retrieval by NU-Prolog programs; the database system
makes use of the superjoin algorithm to perform efficient join
operations
* uses "when" declarations (the successor to MU-Prolog's "wait") to
control the execution of NU-Prolog programs according to the
availability of data
* implements a large set of built-in predicates, including many Quintus
Prolog predicates; most DEC-10/Edinburgh/MU-Prolog library predicates
are available through compatibility libraries
The NU-Prolog system contains the following major components:
* "nc", the NU-Prolog compiler
* "np", a simple interpreter-style interface which implements the
standard Edinburgh Prolog style debugging facilities and has a
sophisticated query language for accessing external database
predicates
* "nac", a program for adding control information to NU-Prolog programs
written in a purely logical style
* "nit", a program for reporting common errors in NU-Prolog programs
(cf. Unix/C's "lint")
NU-Prolog runs under Unix System V and Berkeley BSD Unix 4.?. It has
been implemented on the following machines: Elxsi 6400, Vax 11/780,
Perkin Elmer 3240, Sun workstations, Pyramid 98x, Integrated Solutions
Workstations. The system comes complete with a manual and all source
code. The preferred distribution medium is 1/2" tape, Unix tar-format
at 1600bpi. There is a A$400.00 fee to cover distribution costs.
In order to obtain a copy of the system, you must first complete a
licence agreement with the University of Melbourne. Licences can be
obtained by contacting:
NU-Prolog Distribution
Department of Computer Science
University of Melbourne
Parkville, Victoria, 3052
AUSTRALIA
or
CSNET: mip%munnari.oz@australia
ARPA: mip%munnari.oz@seismo.css.gov
UUCP: ...!munnari!mip (maybe, mip@munnari.uucp)
ACSnet: mip@munnari.oz
The system will be demonstrated at the Fourth International Conference
on Logic Progrmaming in Melbourne later in May.
+ The Machine Intelligence Project has been
assisted in the development of NU-Prolog by:
the Commonwealth Department of Science,
the Australian Research Grants Scheme,
the University of Melbourne and
Pyramid Technology, Aust.
------------------------------
End of AIList Digest
********************
∂13-May-87 0025 LAWS@Stripe.SRI.COM AIList Digest V5 #120
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 May 87 00:25:40 PDT
Date: Tue 12 May 1987 21:41-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #120
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 13 May 1987 Volume 5 : Issue 120
Today's Topics:
Reports - NMSU Computer and Cognitive Science Abstracts (1 of 2)
----------------------------------------------------------------------
Date: Sun, 10 May 87 16:07:45 MDT
From: yorick%nmsu.csnet@RELAY.CS.NET
Subject: Computer and Cognitive Science Abstracts (1 of 2)
ABSTRACTS OF
MEMORANDA IN COMPUTER AND COGNITIVE SCIENCE
Computing Research Laboratory
New Mexico State University
Box 30001
Las, Cruces, NM 88003.
Kamat, S.J. (1985), Value Function Approach to Multiple Sensor
Integration, MCCS-85-16.
A value function approach is being tried for integrating multiple sensors
in a robot environment with known objects. The state of the environment is
characterized by some key parameters which affect the performance of the
sensors. Initially, only a handful of discrete environmental states will be
used. The value of a sensor or a group of sensors is defined as a function
of the number of possible object contenders under consideration and the
number of contenders that can be rejected after using the sensor information.
Each possible environmental state will have its effect on the function, and
the function could be redefined to indicate changes in the sampling frequency
and/or resolution for the sensors. A theorem prover will be applied to the
sensor information available to reject any contenders. The rules used by the
theorem prover may be different for each sensors, and the integration is
provided by the common decision domain. The values for the different sensor
groups will be stored in a database. The order of use of the sensor groups
will be according to the values, and can be stored as the best search path.
The information in the database can be adaptively updated to provide a
training methodology for this approach.
Cohen, M. (1985), Design of a New Medium for Volume Holographic
Information Processing, MCCS-85-17.
An optical analog of the neural networks involved in sensory
processing consists of a dispersive medium with gain in a narrow
band of wavenumbers, cubic saturation, and a memory nonlinearity
that may imprint multiplexed volume holographic gratings. Coupled
mode equations are derived for the time evolution of a wave
scattered off these gratings; eigenmodes of the coupling
matrix $$kappa$$ saturate preferentially, implementing stable
reconstruction of a stored memory from partial input and
associative reconstruction of a set of stored memories. Multiple
scattering in the volume reconstructs cycles of associations that
compete for saturation. Input of a new pattern switches all
the energy into the cycle containing a representative of that
pattern; the system thus acts as an abstract categorizer with
multiple basins of stability. The advantages that an imprintable
medium with gain biased near the critical point has over either
the holographic or the adaptive matrix associative paradigms
are (1) images may be input as non-coherent distributions which
nucleate long range critical modes within the medium, and (2) the
interaction matrix $$kappa$$ of critical modes is full, thus implementing
the sort of `full connectivity' needed for associative reconstruction
in a physical medium that is only locally connected, such as a
nonlinear crystal.
Uhr, L. (1985), Massively Parallel Multi-Computer
Hardware = Software Structures for Learning, MCCS-85-19.
Suggestions are made concerning the building and use of appropriately
structured hardware/software multi-computers for exploring ways that
intelligent systems can evolve, learn and grow. Several issues are addressed
such as: what computers are, the great variety of topologies that can be used
to join large numbers of computers together into massively parallel
multi-computer networks, and the great sizes that the micro-electronic VLSI
(``very large scale integration'') technologies of today and tomorrow make
feasible. Finally, several multi-computer structures that appear
especially appropriate as the substrate for systems that evolve, learn and
grow are described, and a sketch of a system of this sort is begun.
Partridge, D. (1985), Input-Expectation Discrepancy Reduction:
A Ubiquitous Mechanism, MCCS-85-24.
The various manifestations of input-expectation discrepancy that occurs in a
broad spectrum of research on intelligent behavior is examined. The point
is made that each of the different research activities highlights different
aspects of an input-expectation reduction mechanism and neglects others.
A comprehensive view of this mechanism has been constructed and applied in
the design of a cognitive industrial robot. The mechanism is explained as
both a key for machine learning strategies, and a guide for the selection of
appropriate memory structures to support intelligent behavior.
Ortony, A., Clore, G. & Foss, M. A. (1985), Conditions of Mind,
MCCS-85-27.
A set of approximately 500 words taken from the literature on emotion was
examined. The overall goal was to develop a comprehensive taxonomy of the
affective lexicon, with special attention being devoted to the isolation of
terms that refer to emotions. Within the taxonomy we propose, the best
examples of emotion terms appear to be those that (a) refer to [i]internal,
mental[xi] conditions as opposed to physical or external ones, (b) are clear
cases of [i]states[xi], and (c) have [i]affect[xi] as opposed to behavior or
cognition as their predominant referential focus. Relaxing one or another of
these constraints yields poorer examples or nonexamples of emotions; however,
this gradedness is not taken as evidence that emotions necessarily defy
classical definition.
Wilks, Y. (1985), Machine Translation and Artificial Intelligence:
Issues and their Histories, MCCS-85-29.
The paper reviews the historical relations, and future prospects for
relationships, between artificial intelligence and machine translation. The
argument of the paper is that machine translation is much more tightly bound
into the history of artificial intelligence than many realize (the MT origin
of Prolog is only the most striking example of that), and that it remains,
not a peripheral, but a crucial task on the AI agenda.
Coombs, M.J. (1986), Artificial Intelligence Foundations
for a Cognitive Technology: Towards The Co-operative Control of Machines,
MCCS-85-45.
The value of knowledge-based expert systems for
aiding the control of physical and
mechanical processes is not firmly established. However, with experience,
serious weaknesses have become evident which, for solution, require a new
approach to system architecture.
The approach proposed in this paper is based on the direct manipulation of
models in the control domain. This contrasts with the formal syntactic
reasoning methods more conventionally employed. Following from work on the
simulation of qualitative human reasoning, this method has potential for
implementing truly co-operative human/computer interaction.
Coombs, M.J., Hartley, R. & Stell J.F. (1986), Debugging
User Conceptions of Interpretation Processes, MCCS-85-46.
The use of high level declarative languages has been advocated since they allow
problems to be expressed in terms of their domain facts, leaving details of
execution to the language interpreter. While this is a significant advantage,
it is frequently difficult to learn the procedural constraints imposed by
the interpreter. Thus, declarative failures may arise from misunderstanding
the implicit procedural content of a program. This paper argues for a
\fIconstructive\fR approach to identifying poor understanding of procedural
interpretation, and presents a prototype diagnostic system for Prolog.
Error modelling is based on the notion of a modular interpreter, misconceptions
being seen as modifications of correct procedures. A trace language,
based on conceptual analysis of a novice view of Prolog, is used by
both the user to describe his conception of execution, and the system to
display the actual execution process. A comparison between traces enables the
the correct interpreter to be modified in a manner which progressively
corresponds to the user's mental interpreter.
Dorfman, S.B. & Wilks, Y. (1986), SHAGRIN: A Natural
Language Graphics Package Interface, MCCS-85-48.
It is a standard problem in applied AI to construct a front-end to some
formal data base with the user's input as near English as possible. SHAGRIN
is a natural language interface to a computer graphics package. In
constructing SHAGRIN, we have chosen some non-standard goals: (1) SHAGRIN
is just one of a range of front-ends that we are fitting to the same formal
back-end. (2) We have chosen not a data base in the standard sense, but a
graphics package language, a command language for controlling the production
of graphs on a screen. Parser output is used to generate graphics world
commands which then produce graphics PACKAGE commands. A four-component
context mechanism incorporates pragmatics into the graphics system as well
as actively aids in the maintenance of the state of the graph world.
Manthey, M.J. (1986), Hierarchy in Sequential and
Concurrent Systems or What's in a Reply, MCCS-85-51.
The notion of hierarchy as a tool for controlling conceptual
complexity is justifiably well entrenched in computing in general,
but our collective experience is almost entirely in the realm of
sequential programs. In this paper we focus on exactly what the
hierarchy-defining relation should be to be useful in the realm of
concurrent programming. We find traditional functional dependency
hierarchies to be wanting in this context, and propose an alternative
based on shared resources. Finally we discuss some historical and
philosophical parallels which seem to have gone largely unnoticed in
the computing literature.
Huang, X-M (1986), A Bidirectional Chinese Grammar
in A Machine Translation System, MCCS-85-52.
The paper describes a Chinese grammar which can be run bidirectionally, ie.,
both as a parser and as a generator of Chinese sentences. When used as a
parser, the input to the grammar is single Chinese sentences, and the output
would be tree structures for the sentences; when used as a generator, tree
structures are the input, and Chinese sentences, the output. The main body
of the grammar, the way bidirectionality is achieved, and the performance of
the system with some example sentences are given in the paper.
Partridge, D. & Wilks, Y. (1986), Does AI have a methodology different
from Software Engineering?, MCCS-85-53.
The paper argues that the conventional methodology of software
engineering is inappropriate to AI, but that the failure of many
in AI to see this is producing a Kuhnian paradigm ``crisis''. The
key point is that classic software engineering methodology (which
we call SPIV: Specify-Prove-Implement-Verify) requires that the
problem be circumscribable or surveyable in a way that it is not
for areas of AI like natural language processing. In addition, it
also requires that a program be open to formal proof of
correctness. We contrast this methodology with a weaker form SAT
( complete Specification And Testability - where the last term is
used in a strong sense: every execution of the program gives
decidably correct/incorrect results) which captures both the
essence of SPIV and the key assumptions in practical software
engineering. We argue that failure to recognize the
inapplicability of the SAT methodology to areas of AI has
prevented development of a disciplined methodology (unique to AI,
which we call RUDE: Run-Understand-Debug-Edit) that will
accommodate the peculiarities of AI and also yield robust,
reliable, comprehensible, and hence maintainable AI software.
Slator, B.M., Conley, W. & Anderson, M.P (1986), Towards an Adaptive
Front-end, MCCS-85-54.
An adaptive natual language interface to a graphics package has
been implemented. A mechanism for modelling user behavior
operating over a script-like decision matrix capturing
co-occurrence of commands is used to direct the interface, which
uses a semantic parser, when ambiguous utterances are
encountered. This is an adaptive mechanism that forms a model of
a user's tendencies by observing the user in action. This
mechanism provides a method for operating under conditions of
uncertainty, and it adds power to the interface - but, being a
probabilistic control scheme, it also adds a corresponding
element of nondeterminism.
A hidden operator experiment was conducted to collect utterance files
for a user-derived interface development process. These empirical
data were used to design the interface; and a second set, collected
later, was used as test data.
Lopez, P., Johnston, V. & Partridge, D. (1986), Automatic Calibration
of the Geometric Workspace of an Intelligent Robot, MCCS-85-55.
An intelligent robot consisting of an arm, a single camera, and a computer,
functioning in an industrial environment, is described. A variety of
software algorithms that compute and maintain, at task-execution time,
the mappings between robot arm, work environment (the robot's world),
and camera coordinate systems, are presented.
These mappings are derived through a sequence of arm movements
and subsequent image ``snapshots'', from which arm motion is
detected. With the aid of world self-knowledge (i.e., knowledge of the
length of the robot arm and the height of the arm to the base
pivot), the robot then uses its ``eye'' to calculate a
pixel-to-millimeter ratio in two known planes. By ``looking''
at its arm at two different heights, it geometrically computes the
distance of the camera from the arm, hence deriving the mapping from
the camera to the work environment. Similarly, the calculation of
the intersection of two arm positions (where wrist location
and hypothetical base location form a line) gives a base pivot
position. With the aid of a perspective projection, now possible
since the camera position is known, the position of the base and
its planar angle of rotation in the work environment (hence the world
to arm mapping) is determined. Once the mappings are known,
the robot may begin its task,
updating the approximate camera and base pivot positions with
appropriate data obtained from task-object manipulations. These
world model parameters are likely to remain static
throughout the execution of a task, and as time passes, the
old information receives more weight than new information when
updating is performed. In this manner, the robot first
calibrates the geometry of its workspace with sufficient accuracy
to allow operation using perspective projection, with performance
``fine-tuned'' to the nuances of a particular work environment
through adaptive control algorithms.
Fass, D. (1986), Collative Semantics: An Approach to Coherence,
MCCS-85-56.
Collative Semantics (CS) is a domain-independent semantics for
natural language processing that focusses on the problem of
coherence. Coherence is the synergism of knowledge (synergism is the
interaction of two or more discrete agencies to achieve an effect of
which none is individually capable) and plays a substantial role in
cognition. The representation of coherence is distinguished from
the representation of knowledge and some theoretical connections are
established between them. A type of coherence representation has
been developed in CS called the semantic vector. Semantic vectors
represent the synergistic interaction of knowledge from diverse
sources (including the context) that comprise semantic relations.
Six types of semantic relation are discriminated and represented:
literal, metaphorical, anomalous, novel, inconsistent and redundant.
The knowledge description scheme in CS is the senseframe, which
represents lexical ambiguity. The semantic primitives in senseframes
are word-senses which are a subset of the word-senses in natural
language. Because these primitives are from natural language, the
semantic markerese problem is avoided and large numbers of primitives
are provided for the differentiated description of concepts required
by semantic vectors. A natural language program called meta5 uses
CS; detailed examples of its operation are given.
McDonald, D.R. & Bourne, L.E. Jr. (1986), Conditional Rule Testing in
the Wason Card Selection Task, MCCS-85-57.
We used the Wason card selection task, with variations, to study
conditional reasoning. Disagreement exists in the literature, as to
whether performance on this task improves when the problem is
expressed concretely and when instructions are properly phrased. In
order to resolve some inconsistencies in previous studies, we examined
the following variables, (1) task intructions, (2) problem format,
and (3) the thematic compatibility of solution choices with formal
logic and with pre-existing schemas. In Experiment 1, performance
was best in an 8-card, rather than a 4-card or a hierarchical
decision-tree format. It was found in Experiment 2 that instructions
directing subjects to make selections based on ``violation'' of the
rule, rather than assessing its truth or falsity, resulted in more
correct responses. Response patterns were predictable in part from
formal logical considerations, but primarily from mental models, or
schemas, based on (assumed) common prior experience and knowledge.
Several explanations for the findings were considered.
Partridge, D, McDonald, J., Johnston, V. & Paap, K. (1986)
AI Programs and Cognitive Models: Models of Perceptual Processes,
MCCS-85-60.
We examine and compare two independently developed computer models of
human perceptual processes: the recognition of objects in a scene and
of words. The first model was developed to support intelligent
reasoning in a cognitive industrial robot - an AI system. The second
model was developed to account for a collection of empirical data and
known problems with earlier models - a cognitive science model. We
use these two models, together with the results of empirical studies
of human behaviour, to generate a generalised model of human visual
processing, and to further our claim that AI modelers should be more
cognizant of empirical data. A study of the associated human
phenomena provides an essential basis for understanding complex
models as well as valuable constraints in complex and otherwise
largely unconstrained domains.
------------------------------
End of AIList Digest
********************
∂13-May-87 0255 LAWS@Stripe.SRI.COM AIList Digest V5 #121
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 May 87 02:55:20 PDT
Date: Tue 12 May 1987 21:45-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #121
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 13 May 1987 Volume 5 : Issue 121
Today's Topics:
Reports - NMSU Computer and Cognitive Science Abstracts (2 of 2)
----------------------------------------------------------------------
Date: Sun, 10 May 87 16:07:45 MDT
From: yorick%nmsu.csnet@RELAY.CS.NET
Subject: Computer and Cognitive Science Abstracts (2 of 2)
Computing Research Laboratory
New Mexico State University
Box 30001
Las, Cruces, NM 88003.
Krueger, W. (1986)
Transverse Criticality and its Application to Image Processing,
MCCS-85-61.
The basis for investigation into visual recognition of objects is
their representation. One appealing approach begins by replacing the
objects themselves by their bounding surfaces. These then are represented by
surfaces which have been smoothed according to various prescriptions.
The resulting smoothed surfaces are subjected to geometric analysis
in an attempt to find critical events which correspond to
``landmarks'' that serve to define the original object.
Many vision researchers have used this outline, often incorporating
it into a larger one that uses the critical events as constraints in
surface generation programs. To deal with complex objects these
investigators have proposed a number of candidates for the notion of
critical event, most of which take the form of zero-crossings of some
differentially defined quantity associated to surfaces (e.g. Gaussian
curvature, etc.). Many of these require some a posteriori geometric
conditioning (e.g. planarity) in order to be visually significant.
In this report, we introduce the notion of a transverse critical line
of a smooth function defined on a smooth surface. Transverse
criticality attempts to capture the trough/crest behavior manifested
by quantities which are globally defined on surfaces (e.g. curvature
troughs and crests, irradiance troughs and crests). This notion can
be used to study both topographic and photometric surface behavior
and includes, as special cases, definitions proposed by other
authors, among which notions are the regular edges of Phillips and
Machuca [PM] and the interesting flutings of Marr [BPYA].
Applications are made to two classes of surfaces which are important
in computer vision height surfaces and generalized cones.
Graham, N. & Harary, F. (1986)
Packing and Mispacking Subcubes into Hypercubes,
MCCS-85-65.
A node-disjoint packing of a graph G into a larger graph H
is a largest collection of disjoint copies of G contained
in H; an edge disjoint packing is defined similarly, but no two
copies of G have a common edge. Two packing numbers of G into H
are defined accordingly. It is easy to determine both of these numbers
when G is a subcube of a hypercube H.
A mispacking of G into H is a maximal collection of disjoint
copies of G whose removal from H leaves no subgraph G, such that
the cardinality of this collection is minimum. Two mispacking numbers
of G into H are defined analogously. Their exact determination
is quite difficult but we obtain upper bounds.
Dietrich, E. & Fields, C. (1986),
Creative Problem Solving Using Wanton Inference:
It takes at least two to tango,
MCCS-85-70.
This paper introduces \fBwanton inference\fR, a problem solving strategy for
creative problem solving. The central idea underlying wanton inference is
that creative solutions to problems are often generated by ignoring
boundaries between domains of knowledge and making new connections between
previously unassociated elements of one's knowledge base. The major
consequence of using the wanton inference strategy is that the size of search
spaces is greatly increased. Hence, the wanton inference strategy is
fundamentally at odds with the received view in AI that the essence of
intelligent problem solving is limiting the search for solutions. Our view
is that the problem of limiting search spaces is an artificial problem in AI,
resulting from ignoring both the nature of creative problem solving and the
social aspect of problem solving. We argue that this latter aspect of
problem solving provides the key to dealing with the large search spaces
generated by wanton inference.
Ballim, A. (1986),
The Subjective Ascription of Belief to Agents,
MCCS-85-74.
A computational model for determining an agent's beliefs from the viewpoint
of an agent known as the system is described. The model is based on the
earlier work of Wilks and Bien(1983) which argues for a method of dynamically
constructing nested points of view from the beliefs that the system holds.
This paper extends their work by examining problems involved in ascribing
beliefs called meta-beliefs to agents, and by developing a representation
to handle these problems. The representation is used in ViewGen, a
computer program which generates viewpoints.
Partridge, D. (1986), The Scope and Limitations of
First Generation Expert Systems, MCCS-85-43.
It is clear that expert system's technology is one of AI's
greatest successes so far. Currently we see an ever increasing
application of expert systems, with no obvious limits to their
applicability. Yet there are also a number of
well-recognized problems associated with this new technology.
I shall argue that these problems are not the puzzles of normal
science that will yield to advances within the current
technology; on the contrary, they are symptoms of severe inherent
limitations of this first generation technology. By reference
to these problems I shall outline some important aspects of the
scope and limitations of current expert system's technology.
The recognition of these limitations is a prerequisite of
overcoming them as well as of developing an awareness of the
scope of applicability of this new technology.
Gerber, M., Dearholt, D.W., Schvaneveldt, R.W., Sachania,
V. & Esposito, C. (1987), Documentation for PATHFINDER: A Program
to Generate PFNETs, MCCS-87-47.
This documentation provides both user and programmer documentation for
PATHFINDER, a program which generates PFNETs from symmetric distance
matrices representing various aspects of human knowledge. User
documentation includes instructions for input and output file formats,
instructions for compiling and running the program, adjustments to
incomplete or incompatable data sets, a general description of the
algorithm, and a glossary of terms. Programmer documentation includes a
detailed description of the algorithm with an explanation of each
function and procedure, and hand execution examples of some of the more
difficult to read code. Examples of input and output files are included.
Ballim, A. (1986)
Generating Points of View,
MCCS-85-68.
Modelling the beliefs of agents is normally done in a static manner.
This paper describes a more flexible dynamic approach to generating
nestings which represent what the system believes other agents
believe. Such nestings have been described in Wilks and Bien (1983)
as has their usefulness. The methods presented here are based upon
those described in Wilks and Bien (ibid) but have been augmented to
handle various problems. A system based on this paper is currently
being written in Prolog.
The Topological Cubical Dimension of a Graph
Frank Harary
MCCS-86-80
A cubical graph G is a subgraph of some hypercube $Q sub n$. The
cubical dimension cd(G) is the smallest such n. We verify that the
complete graph $K sub p$ is homeomorphic to a cubical graph H \(sb $Q
sub p-1$. Hence every graph G has a subdivision which is a cubical
graph. This enables us to define the topological cubical dimension
tcd(G) as the minimum such n.
When G is a full binary tree, the value of tcd is already known.
Computer scientists, motivated by the use of the architecture of a
hypercube for massively parallel supercomputers, defined the dilation
of an edge e of G within a subdivision H of G as the lenth of the image
of e in H, and the dilation of G as the maximum dilation of an edge
of G. The two new invariants, tcd(G) and the minimum dilation of G
among all cubical subdivisions H of G, are studied.
CP: A Programming Environment for
Conceptual Interpreters
M.J. Coombs and R.T. Hartley
MCCS-87-82
A conceptual approach to problem-solving is explored which we
claim is much less brittle than logic-based methods. It also
promises to support effective user/system interaction when
applied to expert system design. Our approach is ``abductive''
gaining its power from the generation of good hypotheses rather
than deductive inference, and seeks to emulate the robust
cooperative problem-solving of multiple experts. Major
characteristics include:
(1) use of conceptual rather than
syntactic representation of knowledge;
(2) an empirical approach to reasoning by model generation and
evaluation called Model Generative Reasoning;
(3) dynamic composition of reasoning strategies from actors embedded
in the conceptual structures; and
(4) characterization of the reasoning cycle in terms of cooperating
agents.
Semantics and the Computational
Paradigm in Cognitive Psychology
Eric Dietrich
MCCS-87-83
There is a prevalent notion among cognitive scientists and philosophers of
mind that computers are merely formal symbol manipulators, performing the
actions they do solely on the basis of the syntactic properties of the
symbols they manipulate. This view of computers has allowed some
philosophers to divorce semantics from computational explanations. Semantic
content, then, becomes something one adds to computational explanations to
get psychological explanations. Other philosophers, such as Stephen Stich
have taken a stronger view, advocating doing away with semantics entirely.
This paper argues that a correct account of computation requires us to
attribute content to computational processes in order to explain which
functions are being computed. This entails that computational psychology
must countenance mental representations. Since anti-semantic positions are
incompatible with computational psychology thus construed, they ought to be
rejected. Lastly, I argue that in an important sense, computers are not
formal symbol manipulators.
Problem Solving in Multiple Task Environments
Eric Dietrich and Chris Fields
MCCS-87-84
We summarize a formal theory of multi-domain problem solving
that provides a precise representation of the inferential dynamics
of problem solving in multiple task environments. We describe
a realization of the theory as an abstract virtual machine that
can be implemented on standard architectures. We show that
the behavior of such a machine can be described in terms of
formally-specified analogs of mental models, and present a necessary
condition for the use of analogical connections between such
models in problem solving.
An Automated Particulate Counting System for Cleanliness
Verification of Aerospace Test Hardware
\fIJeff Harris and Edward S. Plumer\fR
MCCS-87-86
An automated, computerized particle counting system
has been developed to verify the cleanliness of aerospace test
hardware. This work was performed by the Computing Research
Laboratory at New Mexico State University (CRL) under a contract
with Lockheed Engineering and Management Services Company at the
NASA Johnson Space Center, White Sands Test Facility. Aerospace
components are thoroughly cleaned and residual particulate matter
remaining on the components is rinsed onto 47 mm diameter test filters. The
particulates on these filters are an indication of the
contamination remaining on the components. These filters are
examined under a microscope, and particles are sized and counted.
Previously, the examination was performed manually; this
operation has now been automated. Rather than purchasing a
dedicated particle analysis system, a flexible system utilizing
an IBM PC-AT was developed. The computer, combined with a
digitizing board for image acquisition, controls a
video-camera-equipped microscope and an X-Y stage to allow
automated filter positioning and scanning. The system provides
for complete analysis of each filter paper, generation of
statistical data on particle size and quantity, and archival
storage of this information for further evaluation. The system is
able to identify particles down to 5 micrometers in diameter and
discriminate between particles and fibers. A typical filter scan
takes approximately 5 minutes to complete. Immediate operator
feedback as to pass-fail for a particular cleanliness standard is
also a feature. The system was designed to be operated by
personnel working inside a class 100 clean room. Should it be
required, a mechanism for more sophisticated recognition of
particles based on shape and color may be implemented.
Solving Problems by Expanding Search Graphs:
Mathematical Foundations for a Theory of Open-world Reasoning
Eric Dietrich and Chris Fields
MCCS-87-88
We summarize a mathematical theory describing a virtual machine
capable of expanding search graphs. This machine can, at least
sometimes, solve problems where it is not possible to precisely
and in detail specify the space it must search. The mechanism for
expansion is called wanton inference. The theory specifies which
wanton inferences have the greatest chance of producing solutions
to given problems. The machine, using wanton inference,
satisfies an intuitive definition of open-world reasoning.
Software Engineering Constraints Imposed by
Unstructured Task Environments
Eric Dietrich and Chris Fields
MCCS-87-91
We describe a software engineering methodology for building
multi-domain (open-world) problem solvers which inhabit
unstructured task environments. This methodology is based on a
mathematical theory of such problem solving. When applied, the
methodology results in a specification of program behavior that
is independent of any architectural concerns. Thus the
methodology produces a specification prior to implementation
(unlike current AI software engineering methodology). The data
for the specification are derived from experiments run on human
experts.
Multiple Agents and the Heuristic Ascription of Belief.
Yorick Wilks and Afzal Ballim
MCCS-86-75
A method for heuristically generating nested beliefs (what some agent
believes that another agent believes ... about a topic) is described.
Such nested beliefs (points of view) are esential to many processes
such as discourse processing and reasoning about other agents' reasoning
processes. Particular interest is paid to the class of beliefs known as
\fIatypical beliefs\fR and to intensional descriptions. The heuristic
methods described are emboddied in a program called \fIViewGen\fR which
generates nested viewpoints from a set of beliefs held by the system.
An Algorithm for Open-world Reasoning
using Model Generation
M.J. Coombs, E. Dietrich & R.T. Hartley
MCCS-87-87
The closed-world assumption places an unacceptable constraint on a
problem-solver by imposing an \fIa priori\fR notion of relevance on
propositions in the knowledge-base. This accounts for much of the
brittleness of expert systems, and their inability to model natural
human reasoning in detail.
This paper presents an algorithm for an open-world problem-solver.
Termed Model Generative Reasoning, we replace deductive inference
with a procedure based on the generation of alternative, intensional
domain descriptions (models) to cover problem input, which are then evaluated
against domain facts as alternative explanations. We also give an illustration
of the workings of the algorithm using concepts from process control.
Pronouns in mind: quasi-indexicals and the ``language of thought''
Yorick Wilks, Afzal Ballim, & Eric Dietrich
MCCS-87-92
The paper examines the role of the natural-formal language
distinction in connection with the "language of thought"
(LOT) issue. In particular, it distinguishes a
realist-uniform/attributist-uniform approach to LOT and seeks to link
that distinction to the issue of whether artificial
intelligence is fundamentally a science or engineering. In a
second section, we examine a particular aspect of natural
language in relation to LOT: pronouns/indexicals. The focus
there is Rapaport's claims about indexicals in belief
representations. We dispute these claims and argue that he
confuses claims about English sentences and truth
conditions, on the one hand, with claims about beliefs, on
the other. In a final section we defend the representational
capacity of the belief manipulation system of Wilks, Bien
and Ballim against Rapaport's published criticisms.
------------------------------
End of AIList Digest
********************
∂13-May-87 0455 LAWS@Stripe.SRI.COM AIList Digest V5 #122
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 May 87 04:55:03 PDT
Date: Tue 12 May 1987 21:51-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #122
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 13 May 1987 Volume 5 : Issue 122
Today's Topics:
Queries - Connection Graphs & Xerox/Apollo Compatibility,
Administrivia - USENET Side of AIList,
Education - Grammar Checkers & Teaching Programming,
Literature - Data Flow References
----------------------------------------------------------------------
Date: Tue, 12 May 87 10:15:18 -0100
From: enea!kuling!nilsh@seismo.CSS.GOV (Nils Hagner)
Subject: CONNECTION GRAPHS
CONNECTION GRAPHS
=================
Me and my friend is just about starting a little project on the
Connection Graphs of Kowalski. Now, the problem is that we're
having a hard time finding appropriate literature. Our special
interest is parallel execution of logic programs with the use
of Connection Graphs. As far as we know there are a larger research
project going on in the University of Maryland. We would like to
get in touch with people involved with these Connection Graphs
and, if possible, get hold of papers concerning particularly
parallel processing with Connection Graphs.
E-mail: nilsh@kuling.UUCP
S-mail: Nils Hagner, Studentvagen 14:51, 752 34 Uppsala, SWEDEN
------------------------------
Date: 8 May 87 20:22:00 EDT
From: Daniel (D.R.) Zlatin <DANIEL%BNR.BITNET@wiscvm.wisc.edu>
Subject: Xerox and Apollo compatibility
Hello!
We have a network of Xerox Lisp Machines (1109's and 1186's) with
file server and printer. Lately, the question of compatibility with
other vendor's networks has arisen.
Does anyone have any first-hand experience trying to make Xerox machines
talk to a file server on an Apollo network? The generalization to
other Unix-based workstations would also be of interest.
Thanks!!
Daniel Zlatin,
Bell-Northern Research,
Ottawa, Ontario
DANIEL@BNR.BITNET
[This might get a better response on the INFO-1100@SUMEX.STANFORD.EDU
or WorkS list. -- KIL]
------------------------------
Date: Tue, 12 May 87 10:49:04-1000
From: scubed!sdcsvax!uhccux.UHCC.HAWAII.EDU!nosc!humu!todd@seismo.CSS.
GOV (The Perplexed Wiz)
Subject: Clarification - USENET side of AIList
Ken, there are two USENET newsgroups discussing AI.
'comp.ai' used to be called 'net.ai' and is unmoderated. 'comp.ai.digest'
is a moderated group that is made up of the individual articles which
you bundle up into AIList. Hope this information is useful...todd
Todd Ogasawara, U. of Hawaii Computing Center
UUCP: {ihnp4,seismo,ucbvax,dcdwest}!sdcsvax!nosc!uhccux!todd
ARPA: uhccux!todd@nosc.MIL
INTERNET: todd@uhccux.UHCC.HAWAII.EDU
------------------------------
Date: 12-May-1987 2145
From: shimono%tkov58.DEC@decwrl.DEC.COM (Takao 'Ta?i' Shimono)
Subject: Re: V5 #117
1. mod.ai was renamed to comp.ai.digest.
2. I don't think we can get "AI Expert" code from SIMTEL-20.
Because it was posted to comp.ai, not to mod.sources.
than?,
-Ta?i (Takao shimono%tkov58.DEC@decwrl.DEC.COM)
/DEC-Japan/SWS/AITC/studio.h Project Hatena Tokyo
------------------------------
Date: Tue, 12 May 87 09:21:02 CDT
From: preece%mycroft@gswd-vms.ARPA (Scott E. Preece)
Subject: Re: Grammar Checkers
Out of curiosity, would any of the automated checkers people have
been talking about have caught the "their" for "there"
error in the following:
> ii) The current 'reading age' metrics have no validity.
> They are bogus psychometric tools. Operationally I am
> saying that their will be no strong correlation (say r >
> 0.9, p < 0.001) between the reading age of text and a
> reader's performance on a comprehension test. Allow the
> author to add a glossary and the correlation will weaken.
> People can learn new words you know.
--
scott preece
gould/csd - urbana
uucp: ihnp4!uiucdcs!ccvaxa!preece
arpa: preece@gswd-vms
------------------------------
Date: 11 May 87 14:12:12 GMT
From: seismo!sun!cwruecmp!nitrex!rbl@rutgers.edu ( Dr. Robin Lake )
Subject: Re: books on common lisp & prolog
In article <12300321403.18.AKBARI@CS.COLUMBIA.EDU>
AKBARI@CS.COLUMBIA.EDU (John C. Akbari) writes:
>>Can anyone make a comparison between Wilensky's "CommonLispCraft" and Tatar's
>>"A Programmer's Guide to Common Lisp"? [...]
>> Bill Roberts
>
>in general, experience points to several important needs when teaching
>& selecting stuff:
>
>- students learn well by studying *working* examples, both in terms of
>how to program as well as details like style, data abstraction, etc.
>providing well-documented examples motivates all sorts of queries
>regarding syntax, efficiency, portability, etc. as well.
>
Yes!! And it is amazing how we humans learn natural languages by first
learning to read --- and THEN learning to write. Precious few computer
programming texts ever use this approach. I taught C and reviewed texts
for publishers for a decade before I found a lucid explaination of how
to READ C.... and that was in a newsletter.
Rob Lake
------------------------------
Date: 11 May 87 16:54:52 GMT
From: jade!lemon.berkeley.edu!c60a-3ed@ucbvax.Berkeley.EDU (Sugih Jamin)
Subject: Data Flow Summary
Hello,
I posted a question about references to Data Flow. A person asked me to send
him the answers I get, but all the mails bounced back, and I thought this might
be useful to other people on the net, so here they are:
===============================================================================
I found "Data Flow Computing" by John A. Sharp publ. by Ellis Horwood useful
--
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
voice: (918) 660-4047 Mark Logicon, Inc.
uucp: ...rutgers!okstate!apctrc!zmel0a P.O.B 3385
ditto: zmel0a@.apctrc.UUCP Tulsa, OK 74102
===============================================================================
You want this:
%A Philip C. Treleaven
%A David R. Brownbridge
%A Richard P. Hopkins
%T Data-Driven and Demand-Driven Computer Architecture
%J Computing Surveys
%V 14
%N 1
%D March 1982
%P 93-143
%K Required,
CR Categories and Subject Descriptors: C.0 [Computer System Organization]:
General - hardware/software interfaces; system architectures;
C.1.2 [Processor Architecture]:
Multiple Data Stream Architectures (Multiprocessors);
C.1.3 [Processor Architecture]: Other Architecture Styles
- data flow architectures; high level language architectures;
D.3.2 [Programming Languages]: Language Classifications - data-flow
languages; macro and assembly languages; very high-level languages
General Terms: Design
Additional Key Words and Phrases: Demand = driven architecture,
data = driven architecture
%X * The aim of this paper is to identify the concepts and relationships
that exist both within and between the two areas of research of
data-driven and demand-driven architectures.
>From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
===============================================================================
P.C. Treleaven, D.R. Brownridge, R.P. Hopkins: "Data-driven and
demand-driven computer architecture", Computing Surveys, vol. 14, no.1,
pp. 93-143 (1982)
Martin Rathke
Institut f}r Informatik
Universit{t Stuttgart
Herdweg 51
D-7000 Stuttgart
West Germany
===============================================================================
That's all. Thank's to all. (I still can't figure out how to use refer.)
Sugih Jamin
(c60b-jk@buddy.Berkeley.EDU)
------------------------------
End of AIList Digest
********************
∂14-May-87 0031 LAWS@Stripe.SRI.COM AIList Digest V5 #123
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 14 May 87 00:31:33 PDT
Date: Wed 13 May 1987 21:59-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #123
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 14 May 1987 Volume 5 : Issue 123
Today's Topics:
Seminars - Should Feigenbaum and Ginsberg Talk to Each Other? (SU) &
ONTIC: Knowledge Representation for Mathematics (MCC) &
PARLOG and Prolog: A Marriage of Convenience (MCC) &
Unframing the Frame Problem (UTexas) &
Concurrent Logic Programming Languages (MCC) &
Coda: An extended debugger for PROLOG (MCC) &
Some Graph Theoretic Models in AI (MCC) &
Causal Reasoning as Nonmonotonic Temporal Reasoning (SU),
Conference - Computer Vision Workshop
----------------------------------------------------------------------
Date: 11 May 87 1633 PDT
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Should Feigenbaum and Ginsberg Talk to Each Other? (SU)
SHOULD ED FEIGENBAUM AND I TALK TO EACH OTHER?
Matt Ginsberg, Stanford
(SJG@SAIL.STANFORD.EDU)
Thursday, May 14, 4:15pm
Bldg. 160, Room 161K
In a previous talk, I argued on philosophical grounds that the
time has come for the "neats" and "scruffies" in AI to begin
to resolve their differences by working on problems of interest
to each other. I suggested that, if one were to view the scruffy
programs as performing two distinct tasks, one being conventional
inference, and the other being some sort of "bookkeeping" with
the results, insights could be obtained that would be of interest
to both the formal and informal camps.
In this talk, I discuss the application of this idea to problems
of interest to the informal camp. Specifically, I will discuss
the construction of a "flexible" expert sytem shell that can be easily
tailored to solve problems using a variety of different methods, simply
by changing an explicit set of bookkeeping functions. I will show
the system using first-order logic to simulate a digital circuit, as
suggested by Genesereth in his DART work, using an ATMS to diagnose the
same digital circuit, as suggested recently by deKleer, solving a
simple problem in default reasoning, and then solving the same problem
more efficiently by using bookkeeping functions that include both
default and justification information.
------------------------------
Date: Fri 3 Apr 87 08:39:00-CST
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - ONTIC: Knowledge Representation for Mathematics
(MCC)
Please join the AI Group for the following talk:
David McAllester
MIT AI Lab
April 7 - 10:30am
MCC Auditorium
"Ontic: A Knowledge Representation
Language for Mathematics"
Ontic is an interactive system for developing and verifying
mathematics. The system appears to be able to verify "proofs" that
are only one to three times longer than corresponding previously
published English arguments. Furthermore, the structure of the
machine readable proofs closely matches the structure of the English
arguments. Ontic's ability to read concise proofs is based on a
mechanism for automatically finding and applying information from a
lemma library containing hundreds of mathematical facts. Starting
with only the axioms of Zermello Fraenkel set theory, the Ontic system
has been used to build a data base of definitions and lemmas
culminating in a proof of the Stone representation theorem for Boolean
lattices. This proof involves an ultrafilter construction and is
similar in complexity to the Tychonoff theorem that an arbitrary
product of compact spaces is compact. This talk will discuss the
structure of Ontic's machine readable proofs, the automatic theorem
proving mechanisms used, and the empirically observed differences
between Ontic's proofs and English arguments.
April 7 - 10:30am
MCC Auditorium
------------------------------
Date: Mon 6 Apr 87 15:30:39-CDT
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - PARLOG and Prolog: A Marriage of Convenience (MCC)
Please join the AI Program for the following speaker:
Steve Gregory
Imperial College
April 8 - 10:00am
MCC Auditorium
"PARLOG and Prolog: A Marriage of Convenience"
Joint Research with Keith Clark)
PARLOG and Prolog are suited to distinct application areas because of
a fundamental difference. PARLOG (and other committed choice
languages) feature stream and-parallelism, while Prolog (and its
parallel variants) allow don't-know non-determinism. These two
properties are not easily combined efficiently.
In this talk, we present a new combination of PARLOG and Prolog which
features "don't-know non-deterministic stream and-parallelism". This
makes PARLOG suitable for AI applications. We show how this can be
achieved with only minor extensions to existing PARLOG and Prolog
implementations.
April 8 - 10:00am
MCC Auditorium
------------------------------
Date: Tue 14 Apr 87 13:17:08-CDT
From: AI.CHRISSIE@R20.UTEXAS.EDU
Subject: Seminar - Unframing the Frame Problem (UTexas)
UNFRAMING THE FRAME PROBLEM
Dennis de Champeaux
Hewlett Packard Labs
Palo Alto, California
Date: Thursday, April 16, 1987
Time: 3:00 pm - 4:00 pm
Where: Taylor Hall 3.128
COFFEE 2:30 pm, TAYLOR 3.128
The predicate calculus in uncommitted to any ontology. Consequently it has a
nearly boundless domain of application. The price of this generality is that
some pervasive properties of the domain are represented at great implementation
cost. The Frame Problem is an example par excellence. To cope with this
problem, we propose to employ a fragment of intensional logic. Consequently
frame axioms or their equivalent have only to be injected for those entities
that are affected by an event, i.e., those for which a new extension must be
introduced. The situation calculus allows the description of a state of
affairs to coexist with the history. This property is preserved in our
proposal. The formalism has been implemented in the context of program
verification.
------------------------------
Date: Thu 16 Apr 87 11:20:45-CDT
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - Concurrent Logic Programming Languages (MCC)
As announced earlier, please join the AI Program for the following
talk:
Concurrent Logic Programming Languages
Vijay A. Saraswat
CSD CMU
April 17 - 9:30am
MCC Auditorium
In this talk we present the language CP(!,|,&), which, together with
languages such as Concurrent Prolog and GHC explores the space of
concurrent logic programming (CLP) languages. Theoretically, CLP
languages offer a simple model of concurrent computation; practically,
they offer a powerful pointer-based, concurrent programming vehicle
that supports new paradigms of computation.
We illustrate the conceptual simplicity of CLP languages by presenting
a simple formal semantics for (Flat) CP(!,|,&), showing how to extend
the semantic techniques to GHC and Concurrent Prolog, and proving some
relationships between these languages. We show that there is a natural
definition of the relationship `IS-A-SUBSET-OF' between CLP languages,
and that:
GHC is-a-subset-of CP(!,|) is-a-subset-of (Safe) Concurrent Prolog
We also present the notion of CONSISTENT COMPLETENESS of LP languages
and argue that it serves to identify those languages which may
legitimately be called (Horn) LOGIC programming languages. We show:
CP(!,|,&), and hence GHC, is consistently complete.
Concurrent Prolog and (sequential) Prolog (with cut) are not.
On the practical side, of the various styles of programming supported
by CP, perhaps the most novel is that of CONCURRENT, CONTROLLABLE
constraint systems. We argue that purely declarative search
formalisms, whether they are based on dependency-directed backtracking
(as in Steele's thesis or the work of Bruynooghe et al) or bottom-up
breadth-first definite clause theorem provers (deKleer's ATMS) or
built-in general purpose heuristics (Laurier's ALICE) are unlikely to
be efficient enough to serve as the basis of a GENERAL PURPOSE
programming formalism which supports the notion of constraint-based
computation. CP allows the user to express domain-specific heuristics
and CONTROL the forward search process based on eager propagation of
constraints and early detection of determinacy and contradiction.
This control follows naturally from the alternate metaphor of viewing
constraints as processes that communicate by exchanging messages. The
language, in addition, provides naturally for the dynamic generation
and hierarchical specification of constraints, for concurrent
exploration of alternate solutions, for pruning and merging sub-spaces
and for expressing preferences over which portions of the search space
to explore next.
Friday - April 17
9:30am
MCC Auditorium
------------------------------
Date: Fri 24 Apr 87 11:34:28-CDT
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - Coda: An extended debugger for PROLOG (MCC)
Please join the AI Program for the following speaker:
David Plummer
University of Texas
April 29 - 10:00am
MCC Auditorium
Coda: An extended debugger for PROLOG
=====================================
In this talk I will describe @b<Coda>, an extension of the @i<de
facto> standard debugger which presents more information about the
execution of the program to the user as the program is debugged.
@b<Coda> extends the standard debugger in a number of ways. First,
@b<Coda> allows the user to interact with the pattern matching
computation step. Thus the reason for the failure of a particular
goal may be more precisely determined by the programmer. Second,
@b<Coda> displays the program trace in terms of the clauses of the
program rather than the goals that are executed. Thus, the program
trace is directly related to the program that was written, and is at a
level more appropriate to the programmer than that of the standard
debugger. Finally, @b<Coda> allows finer control over the information
that is displayed by the debugger, by an extended command set and a
more powerful language for describing " spy points".
April 29 - 10:00am
MCC Auditorium
------------------------------
Date: Tue 5 May 87 09:02:33-CDT
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - Some Graph Theoretic Models in AI (MCC)
Please join the AI Program for the following speaker:
Frank Harary
Consultant
May 7 at 10:00am
MCC Auditorium
"Some Graph Theoretic Models in AI"
Trees and other graphs abound in AI theory, e.g., in:
a) Searching trees and labeling them
b) Three proofs from the apochryphal "Best Book of Mathematical
Proofs":
1) The ramsly number of a triangle is 6
2) Every self-complementary graph has diameter 2 or 3
3) Every weakly connected nontrivial acryclic digraph has a
receiver
c) On converting a theorem into a game
d) On games and game trees
Thursday, May 7
10:00am
MCC Auditorium
------------------------------
Date: Wed, 13 May 87 17:11:10 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Causal Reasoning as Nonmonotonic Temporal
Reasoning (SU)
CAUSAL REASONING AS NONMONOTONIC TEMPORAL REASONING
Yoav Shoham (SHOHAM@SCORE.STANFORD.EDU)
Stanford University
11:00 AM, MONDAY, May 18
SRI International, Building E, Room EJ228
This talk will address the following topics:
* A definition of the problems of Qualification and Extended Prediction,
and their relation to the Frame Problem.
* An outline of a semantical approach to nonmonotonic logics.
* A definition of a specific nonmonotonic epistemic logic, the logic
of Chronological Ignorance, and a demonstration of its utility in
solving the two problems mentioned above.
I will argue that the above analysis explains the meaning of causation,
and its central role in commonsense reasoning.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Mon 11 May 87 13:08:24-PDT
From: Keith Price <PRICE@GANELON.ARPA>
Subject: Conference - Computer Vision Workshop
WORKSHOP ON COMPUTER VISION
IEEE COMPUTER SOCIETY
FONTAINEBLEAU HILTON, MIAMI BEACH, FLORIDA
NOVEMBER 30-DECEMBER 2, 1987
General Chair: Program Chairs:
Keith Price Narendra Ahuja
Institute for Robotics and Thomas Huang
Intelligent Systems, MC 0273 Coordinated Science Laboratory
Electrical Engineering - Systems University of Illinois
University of Southern California 1101 W. Springfield Ave
Los Angeles, CA 90089 Urbana, IL 61801
price@ganelon.usc.edu ahuja@uicsl.csl.uiuc.edu
Tel: (213) 743-5526 Tel: (217) 333-1837
Papers are solicited on the following and related topics:
Image structure (edges, regions, High level vision
texture, ...) Vision guided manipulation,
Segmentation and 2-D description navigation
3-D from 2-D (motion, stereo, Vision systems
texture, ...) Industrial vision
Shape and 3-D description Human visual perception
Range imaging
Model based vision
REVIEW OF PAPERS
In order to maintain quality of papers and consistency in the
reviewing standards, all papers will be reviewed by two members of the
program committee (membership yet to be announced). The program
committee will then make the final selections. Papers will be accepted
either for regular peresentations (6 proceedings pages) or poster
presentations (3 proceedings pages). It is important that regular papers
report on new and interesting research ideas; research proposals and
minor changes to old ideas are discouraged. Poster presentations could
be less complete or present novel results of established techniques.
SUBMISSION OF PAPERS
Each paper should be complete and have a cover sheet with the
title, authors' names, primary address, index terms including at least
one of the above topics, and the type of paper (regular or poster). The
cover page will not be sent to the reviewers. The body of the paper must
contain the title of the paper and an abstract of about 250 words,
followed by the text of the paper. The authors' names and organization
should not be on the body of the paper. The length of the paper should
not exceed: 25 double spaced typed pages for regular papers (including
about 6000 words of text and illustrations), or 12 double spaced typed
pages for poster papers (including about 3000 words of text and
illustrations).
Four copies of papers should be sent to:
Narendra Ahuja
Coordinated Science Laboratory
University of Illinois
1101 W. Springfield Avenue
Urbana, Illinois 61801
The deadline for submission of papers is July 14, 1987. Authors
will be notified of acceptance by late August 1987. Final camera ready
copies of the papers will be due at IEEE early in October 1987.
------------------------------
End of AIList Digest
********************
∂18-May-87 0028 LAWS@Stripe.SRI.Com AIList Digest V5 #124
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 18 May 87 00:28:16 PDT
Date: Sun 17 May 1987 22:24-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #124
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 18 May 1987 Volume 5 : Issue 124
Today's Topics:
Queries - Behavioral Simulation Sources & IntelligenceWare &
AI in Third-World Countries & OPS5 Programs Source Library &
Biomedical Vision or Expert Systems,
Application - Grammar Checkers,
Humor - Artificial Life,
Seminars - Planlunch Time Change (SRI) &
Exploration and Adaptation in Design (CMU) &
Probabilistic Analysis of Algorithms (SU) &
AND-Parallelism of Logic Programming (KAIST) &
Inheritance Hierarchies: Semantics and Unification (UTexas)
----------------------------------------------------------------------
Date: 13 May 87 16:27:41 GMT
From: mcvax!nikhefh!u13@seismo.css.gov (Rene van 't Veen)
Subject: sources wanted
I am posting this for a friend of mine without access to the net,
but I will accept any replies.
My friend is writing a thesis about Artificial Intelligence,
especially about programs that simulate pathological behaviour.
( Like PARRY from Colby ).
My friend would be interested in public-domain programs that do
this sort of thing, to play a little with them.
Source can be in : C ( preferred ), Pascal, Modula-2, Lisp ( Xlisp ),
Icon, Basic, Prolog, Fortran.
Thanks in advance ...
Please e-mail to u13@nikhefh.UUCP
...!seismo!mcvax!nikhefh!u13
R. van 't Veen .. mcvax!nikhefh!u13. All opinions are my own.
------------------------------
Date: 14 May 87 18:37:34 GMT
From: super.upenn.edu!operations.dccs.upenn.edu!shaffer@RUTGERS.EDU
(Earl Shaffer)
Subject: IntelligenceWare
Does anyone have any practical experience with InteliigenceWare's
Intelligence/Compiler product?
==============================================================================
Earl Shaffer - University of Pennsylvania - Data Communications Department
"Time was invented so that everything wouldn't happen at once." Steven Wright
==============================================================================
------------------------------
Date: Sat, 16 May 87 15:36:30 -0700
From: "Jose A. Ambros-Ingerson" (Dept of ICS, U of California,
Irvine) <jose@BONNIE.UCI.EDU>
Subject: AI in Third-World Countries
Could you please post this in the AIList? Can you suggest other
boards where it would appropriate to post?
[sent to AIList and AI-ED]
AI IN THIRD WORLD COUNTRIES
We are interested in constructing a global picture of the impact AI is
having in the Third World and of the implications this impact can have
upon these countries in the future.
We would therefore like to assess the current state of AI in the
Third World, especially:
- Current AI research in Third World Countries (3WC).
- Current AI research in the US/Europe related to Third World problems
or applications.
Research outlines and papers would be most appreciated.
- Current Applied AI in 3WC.
Which applications (Expert Systems, ICAI, Planning, Robotics, etc.)
are being considered for what purpose?
Are there any systems currently in use?
Any AI companies targeting products at 3WCs?
- Social impacts of AI in 3WC.
Reorganization of the work-place, unemployment, economic repercussions,
cultural transformations, etc.
We'd also like to assess how the Third World sees the future of
AI, and more specifically, whether there are any:
- Government programs for the support/funding of AI research and
development.
Like the Fifth Generation Project, MCC, Strategic Computing, Alvey or
Espirit.
- AI graduate programmes and undergrate courses in 3WC universities.
Please mail information to either
jose@bonnie.uci.edu in the USA, or
wobcke@esgr.essex.ac.uk in the United Kingdom
or send copies of papers or other information to me at
Jose A. Ambros-Ingerson
Dept. of Information and Computer Science
University of California
Irvine, CA, 92717, USA.
The information obtained will be collated and summarized and made available
to researchers on request. If enough interest is manifest a network forum
for the interchange of ideas amongst researchers working in similar areas
could be considered.
Thanks for your assistance,
Jose A. Ambros-Ingerson.
------------------------------
Date: Fri, 15 May 87 15:45:40 EDT
From: Alexander Pasik <al@cheshire.columbia.edu>
Subject: OPS5 Programs source library
We at columbia have compiled a library of OPS5 programs. We are
making them available to the general public for benchmarking,
analysis, or any other production system related research.
We are eager to expand this library so any submissions are welcome.
If you have an OPS5 program to add to our library, send its net
address and any instructions to me (al@cheshire.columbia.edu) and I
will pull the systems over.
If you wish to use the library it is available via anonymous ftp on
columbia.edu in the directory prosys. This directory contains one
subdirectory per system.
Alexander Pasik
Department of Computer Science
Columbia University
New York, NY 10027
------------------------------
Date: Fri, 15 May 87
From: knewton@watdcsu
Subject: vision query (and reply)
hello :
I am looking for any refences having anything to do with the
following : computer-assisted identification of cells/tissue; biomedical
expert systems; general computer vision and pattern recognition
algorithms. I seem to remember someone, maybe from York University in
Toronto, posting something on vision , but I can't seem to remember or
be able to find it. If you can help me, just email me.
glen newton
knewton@watdcsu
[There are two vision lists: Vision-List@ADS.ARPA (machine vision)
and CVNET%YORKVM1@WISCVM.WISC.EDU (primarily biological vision).
There is also an enormous literature, growing by over a thousand
papers per year. See, for instance, the IEEE conferences on
Computer Vision and Pattern Recognition. There have also been
conferences on medical vision (cell classification, CAT-scanning,
tumor detection, etc.). The annual IEEE conferences on pattern
recognition are even larger than those on vision, but very little
is directly applicable to biological vision problems. You should
check out back issues of Computer Vision, Graphics, and Image
Processing (formerly Computer Graphics and Image Processing) or
IEEE Transactions on Pattern Analysis and Machine Vision. -- KIL]
------------------------------
Date: 13 May 87 20:41:53 GMT
From: john@viper.lynx.mn.org (John Stanley)
Reply-to: john@viper.UUCP (John Stanley)
Subject: Re: Grammar Checkers
In article <8705121527.AA01698@gswd-vms.ARPA>
preece%mycroft@GSWD-VMS.ARPA (Scott E. Preece) writes:
>Out of curiosity, would any of the automated checkers people have
>been talking about have caught the "their" for "there" error in....
I don't know about the ones people have been talking about, but I
do know there is a program under development that can handle "there"
vs "their" or, for that matter, the "two" vs "too" vs "to". It's a
new program, not yet released, but should be out by the end of the
year. The company working on it is a small Minnesota based company
working on AI related software products for mini/micro/word-processor
applications.
---
John Stanley (john@viper.UUCP)
Software Consultant - DynaSoft Systems
UUCP: ...{amdahl,ihnp4,rutgers}!{meccts,dayton}!viper!john
------------------------------
Date: 14 May 1987, 00:01:30 EDT
From: Norman Haas <NHAAS@ibm.com>
Subject: Humor - Artificial Life
(In case this point hasn't already been made, re the "Artificial Life" confer-
ence announcement a few issues back:)
Why stop with life? Let's go all the way:
1. Artificial Culture and Civilization, including
Artificial Natural Languages
2. Artificial Science, including
Artificial Research in the field of Artificial Intelligence
------------------------------
Date: Thu, 14 May 87 15:41:28 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: PLANLUNCH TIME CHANGE
The time for next week's Planlunch has been changed to 2PM.
---
Sorry about any inconvenience....
CAUSAL REASONING AS NONMONOTONIC TEMPORAL REASONING
Yoav Shoham (SHOHAM@SCORE.STANFORD.EDU)
Stanford University
2:00 PM, MONDAY, May 18
SRI International, Building E, Room EJ228
------------------------------
Date: 14 May 87 09:50:47 EDT
From: Patricia.Mackiewicz@isl1.ri.cmu.edu
Subject: Seminar - Exploration and Adaptation in Design (CMU)
SPECIAL SEMINAR
TOPIC: CYCLOPS: A Computational Model of Exploration & Adaptation
In Design
SPEAKER: Dundee Navinchandra, MIT
WHEN: Thursday, May 14, 1987 at 10:00 am
WHERE: Doherty Hall 3313, CMU
ABSTRACT:
A design system has two basic and essential components: a @b(search)
component and a @b(knowledge) based reasoning component. Designs are
generated by searching the state space of designs, and knowledge is
used to keep the search manageable.
@b(Search Component:) The first part of our research has been in
understanding how designers deal with multiple interacting criteria.
Criteria in design problems can be in the form of constraints, goals or
objectives. It is the job of the designer to produce an artifact that
simultaneously satisfies all the criteria. In the process of achieving
this, the designer has to relax constraints and tradeoff among
objectives. Our system uses pareto-optimality to identify and present
the user with critical tradeoffs in the design problem. The program
also helps the designer @b(explore) the design space by systematically
relaxing constraints and looking for interesting alternatives.
@b(Knowledge-based Component:) The second part of our research is
aimed at developing a technique for recognizing and adapting interesting
designs. This is done through a precedents-based reasoning system.
Precedents are frames that hold knowledge about past design experiences
from within and without the current domain. These experiences are used
to recognize interesting designs. A design is labeled as interesting
if its characteristics cause the reminding of a precedent that was
previously labeled as interesting. Precedents are also used to
@b(adapt) designs that have problems. A technique, called @i(demand
posting) has been developed for solving design problems by reasoning
analogically from the database of precedents.
The above ideas have been implemented in the domain of Landscape
Architecture. The program is called CYCLOPS.
------------------------------
Date: 15 May 1987 1027-PDT (Friday)
From: Tanya Walker <tanya@mojave.stanford.edu>
Subject: Seminar - Probabilistic Analysis of Algorithms (SU)
Computer Science Colloquium
PLACE: Terman Auditorium
TIME: 4:15-5:15
DATE: May 19, 1987
TITLE: An Introduction to the Probabilistic Analysis of Combinatorial
Algorithms
SPEAKER: Richard Karp, Computer Science Dept, UC Berkeley
In fields such as operations research, artificial intelligence and
computer-aided design, algorithms are often used that perform well in
practice even though there is no theoretical guarantee of their good
performance. The simplex algorithm for linear programming is perhaps
the most notable example of this phenomenon. It is a major challenge
to algorithm designers to provide a theoretical foundation for such
quick-and-dirty heuristic algorithms. One approach is through
probabilistic analysis, in which one defines a probability distribution
over the set of instances of a problem, and the endevors to prove
that some fast, simple algorithm performs well with high probability.
The speaker will discuss this approach, using examples related to set
partitioning, bin packing and linear programming. He will then make an
assessment of the strengths and weaknesses of probabilistic analysis as
a method of validating quick-and-dirty algorithms.
------------------------------
Date: Sat, 9 May 87 15:48:58+0900
From: Dongwook Shin <dwshin%csd.kaist.ac.kr@RELAY.CS.NET>
Subject: Seminar - AND-Parallelism of Logic Programming (KAIST)
KAIST CS SEMINAR
AND-Parallelism of Logic Programming
K. M. Choe
choe@cosmos.kaist.ac.kr
11 May, 4:00 -
Professor Choe will present a seminar on AND_Parallelism of logic
programming. He is an assistant professor at KAIST. The abstract of
this seminar is described below.
ABSTRACT
In this seminar, some of the speaker's recent contributions to
the AND-Parallelism of logic programming are to be presented.
First, a brief explanation on the AND/OR-Parallelism is to be
given. And then (1) the incompleteness of Conery's backtracking
model and it's solution, (2) the increased efficiency in combining
the "fork" and "join" scheme, (3) the definitions and the efficient
handling multiple failures, and (4) the multiple backtrackings in general
case are to be described in sequence.
------------------------------
Date: Fri 15 May 87 10:50:11-CDT
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - Inheritance Hierarchies: Semantics and Unification
(UTexas)
Please join the AI Program for the following talk:
Gert Smolka
Universitat Kaiserslauten
May 20 - 2:00pm
AI Conference Room 2.502
"Inheritance Hierarchies: Semantics and Unification"
Inheritance hierarchies are employed in knowledge representation and
object-oriented programming as a means of representing taxonomically
organized data. In our approach, inheritance hierarchies are built up
from so-called feature types, which are ordered by subtyping and whose
elements are records. Every feature type comes with a set of features
corresponding to the fields of its record elements.
Given an inheritance hierarchy, so-called feature terms are used to
denote sets of values. Unification of two feature terms computes a
feature term denoting the intersection of their denotations. Feature
unification is employed in logic programming and computational
linguistics.
In this talk, we express feature types and inheritance hierarchies as
algebraic types in order-sorted equational logic. This reduction
provides a meaningful initial algebra semantics and a well understood
notion of equality. In particular, our framework supports the
combination of algebraic types and inheritance hierarchies.
Feature unification turns out to be unification with respect to
equational axioms and to subsume order-sorted and untyped unification.
We specify a unitary feature unification algorithm by a set of
simplification rules and prove its soundness and completeness with
respect to the model-theoretic semantics.
May 20 - 2:00pm
AI Conference Room 2.502
------------------------------
End of AIList Digest
********************
∂21-May-87 0035 LAWS@Stripe.SRI.Com AIList Digest V5 #125
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 21 May 87 00:35:16 PDT
Date: Wed 20 May 1987 22:06-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #125
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 21 May 1987 Volume 5 : Issue 125
Today's Topics:
Bindings - Mailing List for Lucid Users,
Queries - Consistency and Completeness Checking &
Knowledge-Based Document Retrieval,
AI Tools - Commonlisp for IBM/AT & Chart Parser References,
Philosophy - The Symbol Grounding Problem,
Humor - Spelling Correction for Jabberwocky
----------------------------------------------------------------------
Date: Mon, 18 May 1987 11:10 EDT
From: "Scott E. Fahlman" <Fahlman@C.CS.CMU.EDU>
Subject: Mailing List for Lucid Users
We have set up an ARPAnet mailing list, "lucites@c.cs.cmu.edu", for the
exchange of information related to Lucid Common Lisp. This mailing list
is meant to function as a sort of informal users' group; it is not under
the control of Lucid, though some Lucid people will receive it.
"Lucites" is an appropriate channel for queries, programming hints, and
the sharing of software (large programs can be announced but should not
be distributed over this mailing list). "Lucites" is not an appropriate
channel for bug reports, commercial announcements, or sales pitches.
Because our machine's capacity to forward mail is limited, we must
reserve the right to refuse any request to add more than two recipients
to the list from any given site; if you have three or more people who
want to receive this mail, you are expected to set up you own local
redistribution list or to direct the mail to a bulletin board that your
people can access. (If anyone wants to set up a version of this list
without such restrictions, please contact us and we will gladly turn the
task over to you.)
To get your name on the list, send mail to
"lucites-request@c.cs.cmu.edu". Requests sent to us personally will be
ignored. Requests sent to the mailing list as a whole will result in
scorn and abuse being heaped upon you. If any address on the list
starts bouncing mail sent to it, it will be excised from the list at
once.
Scott E. Fahlman
David B. McDonald
Computer Science Department
Carnegie-Mellon University
------------------------------
Date: Tue, 19 May 87 10:09:30 SST
From: Eng-Lian Lim <ISCLIMEL%NUSVM.BITNET@wiscvm.wisc.edu>
Subject: References on consistency and completeness checking
WANTED!!!
I urgently need references on consistency and completeness checking
on rule-based expert systems with 1st order predicates, including
possible reasoning and approximate reasoning.
Many thanks in advance...
Regards - Eng-Lian Lim
MAIL TO: ISCLIMEL@NUSVM <--- BitNet
------------------------------
Date: Tue, 19 May 87 13:44:40+0900
From: mcvax!csd.kaist.ac.kr!ywkim@seismo.CSS.GOV (Kim Young Whan)
Subject: References on Knowledge-based Document Retrieval
I'm writing a Ph.D Thesis about Knowledge Based System for Document
Retrieval, especially about rule based system using uncertainty handling
mechanism (Bayesian, D-S Theory, Fuzzy Set Theory).
I'm looking for any reference having anything to do with it.
I'm also interesting in public-domain programs that are related to this field.
Sources written in LISP(Common LISP, GCLISP,Frantz-LISP, Zeta LISP) would be
preferred.
The information obtained will be collected and summarized and made
available to researcher on request.
Thanks for your assistance.
Young-Whan Kim
Dept. of CS KAIST
P.O.Box 150, Cheongryang
Seoul, 131
Republic of Korea.
ywkim%csd.kaist.ac.kr@relay.cs.net(from cs-net)
ywkim%csd.kaist.ac.kr@wiscvm.wisc.edu(from bitnet)
------------------------------
Date: 19 May 87 17:03:00 GMT
From: mcvax!unido!iaoobelix!wagner@seismo.css.gov
Subject: Re: Commonlisp for IBM/AT ? - (nf)
[ National lineeater week... ]
How about GCLISP? It is a nice system including editor, compiler and provides
a sensible CommonLISP environment even on the relatively small IBM PCs.
Juergen Wagner, (USENET) ...seismo!unido!iaoobel!wagner
("Gandalf") Fraunhofer Institute IAO, Stuttgart
------------------------------
Date: 20 May 87 01:47:46 GMT
From: decvax!dartvax!uvm-gen!emerson@ucbvax.Berkeley.EDU (Tom
"Oliver W. Jones" Emerson)
Subject: Chart Parser and Related References
Many people have requested sources for further research into chart parsers.
I have also included several sources related to parsing formalisms:
Hirakawa, H. "Chart Parsing in Concurrent PROLOG". TR-008, ICOT,
Tokyo, Japan: May 1983
Kay, M. "Experimenting with a Powerful Parser", Proc. 2nd Int. COLING,
August 1967
Winograd, T. Language as a Cognitive Process, Volume 1: Syntax.
Addison-Wesley, 1983
Relating to Parsing Formalisms:
Emerson, T. "Parsing Formalisms", AI EXPERT, May 1987
Matsumoto, Y., Tanaka, H., Hirakawa, H., Miyoshi, H., Yasukawa, H.,
Mukai, K. and Yokoi, T. "BUP: A Bottom Up Parser
Embedded in PROLOG" ICOT, 1983
------------------------------
Date: 20 May 87 03:21:31 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: The symbol grounding problem
John X. Laporta <rutgers!mit-eddie!apollo!laporta> Apollo Computer,
Chelmsford, MA wrote:
> You say that symbols are grounded in nonsymbolic sensory input.
> You propose a model of segmentation... by which discontinuities
> in the input map to segment boundaries... I wonder what you do with
> the problem of segmentation of the visual spectrum.
> ...spectral segmentations differ widely across cultures.
> The problem is that these breaks and their number vary widely...
> what system intervenes to choose the set a particular culture favors
> and asserts as obvious? What is the filter in the A/D converter?
More recent evidence seems to suggest that color segmentation does not
vary nearly as widely as had been believed (see M. Bornstein's work). There
may be some variability in the tuning of color boundaries, and some
sub-boundaries may be added sometimes, but the focal colors are governed by our
innate color receptor apparatus and they seem to be universal. The
partial flexibility of the boundaries -- short and long term -- must
be governed by learning, and the learning must consist of readjustment
of boundary locations as a function of color naming experience and
feedback, or perhaps even the formation of new sub-boundaries where
there are none. The innate color-detector mechanism would be the A/D
filter in the default case, and learning may set some of the boundary
fine-tuning parameters.
The really interesting case, though, and one that has not been tested
directly yet, is the one where boundary formation occurs de novo purely
as a result of learning. This does not happen with evolutionarily "prepared"
categories such as colors (although it may have happened in phylogeny),
but it may happen with arbitrary learned ones (e.g., perhaps musical
semitones). Here the A/D filter would be acquired from categorization
training alone: labeling with feedback. In simple one-dimensional continua,
what would be acquired would simply be some sort of a threshold
detector, but with more complex multidimensional stimuli the
feature-filter would have to be constructed by a more active inductive
process. This may be where connectionist algorithms come in.
Another important factor in the selectivity of the A/D feature-filter
is the "context" of alternatives: the sample of confusable members and
nonmembers of the categories in question on the basis of which the
features must be extracted; these also focus the uncertainty that the
filter must resolve if it is to generate reliable categorization
performance.
All this is described in the book under discussion (Categorical
Perception: The Groundwork of Cognition, Cambridge University Press
1987, S. Harnad, Ed.).
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: Mon 18 May 87 12:27:57-PDT
From: Lee Altenberg <CCOCKERHAM.ALTENBERG@BIONET-20.ARPA>
Subject: Humor - Spelling Correction
After reading about PROFS, I discovered that my PC-WRITE software has
a spell-checker with a "Guess" feature that is like PROFS. Below are
three actual revisions of Jabberwocky produced by PC-WRITE, "Jabbing:,
"Jabs", and "Suppress", employing the first, second, and third guesses,
respectively, of PC-WRITE. Some of the poetic leaps I think you'll find
extraordinary. AI is a whole new frontier. The religious and political
overtones are those of PC-WRITE, not my own.
Jabbing
'Tweak brim, and the slits tow
Did gyrfalcon and gimmicks in the wac:
All min were the boron,
And the moment ratification outgrow.
"Beware the Jabbing, my son!
The jaws that bite, the claws that catch!
Beware the Judaism bird, and shun
The frustrate Bandies!"
He took is vortex sword in hand:
Long time the many foe he sought -
So rested he by the Tumult tree,
And stood awhile in thought.
And, as in ufos thought he stood,
The Jabbing, with eyes of flame,
Came whiffs through the tulip wood,
And burch as it came!
One, two! One, two! And through and through
The vortex blade went snickered-snack!
He left it dead, and with its head
He went galvanic back.
"And hast thou slain the Jabbing?
Come to my arms, my beams boy!
O fracas day! Callous! Called!
He chortled in his joy.
'Tweak brim, and the slits tow
Did gyrfalcon and gimmicks in the wac:
All min were the boron,
And the moment ratification outgrow.
Jabs
'Tweaks brimful, and the slitter toward
Did gyrfalcons and gimpy in the wacky:
All minaret were the borough,
And the momentarily ratified outgrows.
"Beware the Jabs, my son!
The jaws that bite, the claws that catch!
Beware the Judas bird, and shun
The frustrated Banding!"
He took his vortices sword in hand:
Long time the mao foe he sought -
So rested he by the Tumultuous tree,
And stood awhile in thought.
And, as in uganda thought he stood,
The Jabs, with eyes of flame,
Came whig through the tulips wood,
And burden as it came!
One, two! One, two! And through and through
The vortices blade went snider-snack!
He left it dead, and with its head
He went galvanism back.
"And hast thou slain the Jabs?
Come to my arms, my bean boy!
O fraction day! Calloused! Calligraphy!
He chortled in his joy.
'Tweaks brimful, and the slitter toward
Did gyrfalcons and gimpy in the wacky:
All minaret were the borough,
And the momentarily ratified outgrows.
Suppress
'Ts farewells, and the sled advice
Did gro and compel in the vow:
All mimeos were the breakups,
And the mm radios outcrop.
"Beware the Suppress, my son!
The jaws that bite, the claws that catch!
Beware the Shipshape bird, and shun
The freeing Bandersnatch!"
He took his barfly sword in hand:
Long time the manikin foe he sought -
So rested he by the Automation tree,
And stood awhile in thought.
And, as in abbeys thought he stood,
The Suppress with eyes of flame,
Came affluence through the atlas wood,
And fairfield as it came!
One, two! One, two! And through and through
The barfly blade went snigger-snack!
He left it dead, and with its head
He went clamping back.
"And hast thou slain the Suppress?
Come to my arms, my baying boy!
O barbecues day! Call! Call!
He chortled in his joy.
'Ts farewells, and the sled advice
Did gro and compel in the vow:
All mimeos were the breakups,
And the mm radios outcrop.
------------------------------
End of AIList Digest
********************
∂22-May-87 1438 LAWS@Stripe.SRI.Com AIList Digest V5 #126
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 22 May 87 14:38:10 PDT
Date: Fri 22 May 1987 11:08-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #126
To: AIList@STRIPE.SRI.COM
AIList Digest Friday, 22 May 1987 Volume 5 : Issue 126
Today's Topics:
Seminar - Object Communication in Allegro (SU),
Review - AI and Simulation Workshop,
Conferences - National Conference on AI &
Knowledge Acquisition Workshop &
Symbolics LISP Users Meeting &
Office Information Systems &
AI Tutorials at Foothill College
----------------------------------------------------------------------
Date: 20 May 1987 1254-PDT (Wednesday)
From: Taleen Marashian <taleen@pescadero.stanford.edu>
Subject: Seminar - Object Communication in Allegro (SU)
WHO: Mark Linton of Stanford University (CSL-EE)
WHEN: Thursday, May 28, 1987; 4:15 p.m.
WHERE: Magaret Jacks Hall, Room 352
TITLE: "Object Communication in Allegro"
ABSTRACT:
Large scale object-oriented systems must be able to span machines while
providing efficient and transparent access to small objects. To build
a distributed programming environment, we are using the concept of an
object space that provides remote access to a group of objects. Object
spaces are managed by independent servers that unify the traditional
concepts of commands and files, thereby simplifying the problems of
data management and concurrency control. Objects communicate with
remote objects synchronously or asynchronously, multiplexing messages
through an underlying connection between spaces.
We are implementing a prototype system, named Allegro, in which
software objects are distributed across multiple object spaces. In
this talk, we describe the Allegro object model, the protocol for
accessing remote objects, the runtime support necessary for building
the servers, and the current implementation.
------------------------------
Date: Thu, 21 May 87 10:26:23 PDT
From: Mike Hamilton, AI Magazine <AIMAG@SUMEX-AIM.STANFORD.EDU>
Subject: Review - AI and Simulation Workshop
Report on the 1986 Artificial Intelligence and Simulation Workshop
Richard B. Modjeski
US Army Concepts Analysis Agency,
Advanced Research Projects Office
8120 Woodmont Ave, Bethesda, MD 20814
The first Artificial Intelligence (AI) and simulation workshop was
held during the National Conference on Artificial Intelligence (AAAI)
on August 11, 1986 at the University of Pennsylvania (Wharton Hall).
It was attended by over 40 participants from academic, government, and
industrial institutions. It included paper presentations, informal
discussions, and a panel summary of AI and simulation applications in
the areas of: 1) State of the art and future directions in AI and
simulation (Authur Gerstenfeld, Worcester Polytechnic Institute); 2)
AI problem solving using simulation (Y.V. Ramana Reddy, University of
West Virginia); 3) Knowledge representation issues related to
simulation (Marilyn Stelzner, Intellicorp); 4) Engineering issues
related to AI and simulation (Dick Modjeski, US Army Concepts Analysis
Agency). Individual presentations given in each of the above areas of
the workshop are published in a technical report distributed by the
Defense Technical Information Center (DTIC Number AD-A174 053). A
copy of the report can be obtained by calling DTIC at
(202)274-6847/6874.
The fields of computer simulation and artificial intelligence offer
each other something of value. The methods and techniques of each
discipline offer a fresh approach to revitalizing each other. The
intersection of AI and simulation may offer a unique application of
computer science that may be of use to both fields. Many of the
concepts in this area of AI applied from simulation are developed from
engineering and computer science application experiments. Some
formalisms have appeared but much work needs to be done to establish
relations between constructs and processes. Applications developed
using combinations of AI and simulation techniques by universities,
industry, and government have demonstrated that this aspect of AI is
already maturing as a useful area of development.
LTC Russell E. Frew, Program Manager of the Air-Land Battle Management
Project, Defense Advanced Research Projects Agency (DARPA), suggested
that their was growing interest in applying AI and simulation within
the Department of Defense. A request was made that proposals for
research in this area be sent to DARPA.
The Second Workshop on AI and Simulation will be held on July 14, 1987
in conjuction with the AAAI-87 Conference in Room 316-B of South
Campus Center, University of Washington, Seattle. This workshop is
open to Conference attendees and will provide another opportunity for
researchers and applications designers to exchange ideas and debate
issues in this growing area of interest.
------------------------------
Date: Wed, 20 May 87 09:49:47 PDT
From: AAAI <AAAI-OFFICE@SUMEX-AIM.STANFORD.EDU>
Subject: Conference - National Conference on AI, July 13-17, 1987
AAAI-87
JULY 13-17, 1987
(a month earlier this year!)
SEATTLE, WASHINGTON
Just a reminder that the pre-registration deadline date for the
National Conference on AI is June 12. If you would like more
information about the program, send a msg to AAAI-Office
@sumex-aim.stanford.edu or call 415-328-3123 (PST 7 am-5:30
pm).
------------------------------
Date: 18 May 87 20:02:12 GMT
From: bcsaic!john@june.cs.washington.edu (John Boose)
Subject: Conference - Knowledge Acquisition Workshop at Reading,
England
CALL FOR PAPERS
FIRST EUROPEAN WORKSHOP ON
KNOWLEDGE ACQUISITION FOR KNOWLEDGE-BASED SYSTEMS
Reading University, England
1st-3rd September 1987
A workshop on Knowledge Acquisition for Knowledge-Based Systems will be
held at Reading University, England, from 1st-3rd September 1987.
Topics include:
- Transfer of expertise - systems which interview experts and
structure knowledge
- Knowledge engineering - manual techniques, training knowledge
engineers
- Induction of knowledge from examples
- Extraction of knowledge from text
- Knowledge acquisition methodologies
The attendence at the workshop will be limited to 30 people. Four copies
of an extended abstract (up to 8 pages, double spaced) or a full-length
paper should be sent to Tom Addis or Brian Gaines before July 1, 1987.
Reading University is near Heathrow Airport and a short train journey from
central London. The workshop is residential and accomodation may be
booked at the University through Tom Addis.
Co-Chairmen:
Tom Addis (Tom.Addis@reading.ac.uk)
Department of Computer Science
University of Reading
Whitenights, PO Box 220, Reading RG6 2AX, UK
John Boose (john@boeing.com)
Boeing Advanced Technology Center
Boeing Computer Services M/S 7L-64
PO Box 24346, Seattle, WA, 98124, USA
Brian Gaines (gaines@calgary.cdn)
Department of Computer Science
University of Calgary, Calgary, Alberta, Canada T2N 1N4
--
John Boose, Boeing Artificial Intelligence Center
arpa: john@boeing.com uucp: uw-beaver!uw-june!bcsaic!john
------------------------------
Date: Tue, 19 May 1987 17:11 CDT
From: CS.PURVIS@R20.UTEXAS.EDU
Subject: Conference - Symbolics LISP Users Meeting
SLUG 87
Symbolics LISP Users Group Meeting
July 6-10, 1987
The Third Annual Symbolics LISP Users Group Meeting will be held in
Seattle, Washington at the University of Washington from July 6-10,
1987. This is the week before the AAAI Conference, so participants can
coordinate their travel plans if they plan to attend that conference.
Inexpensive accommodations on the university campus are available and
can be reserved on the registration form that is being mailed out.
TUTORIALS:
The first two days of the Meeting will be devoted to full-day and
half-day tutorials. Below is a list of tutorial topics:
Tutorial instructor
==================================================================
AI Program Design (Monday -- F) Elaine Rich
Overview of Site Administration (Monday -- F) Symbolics Ed. Services
Color Graphics I (Mon. - a.m.) Dave Dyer
Color Graphics II (Mon. - p.m.) Dave Dyer
Color Graphics III (Mon. - p.m.) Symbolics Graphics
Introduction to ART (Tuesday -- F) Inference Corporation
Building Knowl. Sys. Interfaces (Tues. - a.m.) IntelliCorp
Programming Productivity I (Tues. - a.m.) Symbolics Ed. Services
Programming Productivity II (Tues. - p.m.) Symbolics Ed. Services
Elaine Rich, from MCC, is author of the textbook, "Artificial
Intelligence". Dave Dyer is the principle software developer of
Symbolics color graphics system software. The tutorials taught by
Inference and IntelliCorp will feature their expert system development
tools, ART, and KEE, respectively.
CONFERENCE SESSIONS:
The remaining three days of the Meeting will feature presentations by
users and members of the Symbolics technical staff. Planned topics
* New Product Announcements
* Networking
* Expert System Tools and Environments
* The SLUG software library
* The Common Lisp standard and proposed extensions to it
* "Programming Pearls" on the Lisp Machine
* Software Engineering Methodology in Genera 7
REGISTRATION:
Registration for the conference is $90. Each full-day tutorial is $90,
and each half-day tutorial is $45. Registration forms are being mailed
out concurrent with this announcement. Requests for additional forms
and questions concerning the conference and tutorials should be directed
to:
Martin Purvis
SLUG-87 Chairman
Computer Science Department
2.124 Tayor Hall
University of Texas
Austin, TX 78712 USA
(512) 471-9555
cs.purvis@r20.utexas.edu
Questions concerning registration and housing should be directed to:
Conference Management/SLUG
University of Washing, GH-25
Seattle, Washington 98195 USA
(206) 543-2300
------------------------------
Date: Thu, 21 May 87 09:59:59 edt
From: rba@flash.bellcore.com (Robert B. Allen)
Subject: Conference - Office Information Systems
CONFERENCE ON OFFICE INFORMATION SYSTEMS
Palo Alto, CA - March 23-25, 1988
Sponsored by: ACM-SIGOIS IEEE Computer Society TC-OA
In Cooperation with IFIP W.G. 8.4
COIS is a conference concerned with intelligent processing of information in
organizations - topics of interest include:
Effects of Technology on Human Organizations Information Systems
Object-Oriented and Intelligent Databases Planning Systems
Computer-Supported Cooperative Work Information Retrieval
Multimedia/Hypertext Systems Organizational Design
Distributed Artificial Intelligence User Models
Voice/Video/Graphics Interconnect
PROGRAM COMMITTEE: G. Bracchi (Milan), S. Christodoulakis (Waterloo),
Bruce Croft (UMass), Peter DeJong (MIT), Les Gasser (USC), Eli Gerson
(San Francisco), Irene Greif (Lotus), Benn Konsynski (Harvard), Yoshifumi
Masunaga (Tokyo), Norm Meyrowitz (Brown), Alain Michard (INRIA), Juzar
Motiwalla (Singapore), John Mylopoulos (Toronto), Bill Newman (London),
Margi Olson (NYU), Fausto Rabitti (Pisa), Ron Rice (USC), Jeff Rulifson
(Syntelligence), Chris Schmandt (MIT), Lucy Suchman (Xerox PARC), Dennis
Tsichritzis, Geneva), C.J. van Rijsbergen (Glasgow), Andrew Whinston
(Purdue), Thomas Wu (NPS), Stan Zdonik (Brown)
CONFERENCE COMMITTEE: Najah Naffah (General Chair, Bull), Bob Allen
(Program Chair, Bellcore), Dave Choy (IBM, SJ), Skip Ellis (MCC), Carl
Hewitt (MIT), Fred Lochovsky (Toronto), Bob Root - (Treasurer, Bellcore),
Sig Treu (Pittsburgh), Alex Verrijn-Stuart (Leiden)
KEYNOTE SPEAKER: TERRY WINOGRAD
INFORMATION FOR AUTHORS: Submissions by September 21, 1987.
Papers will be judged for technical merit by appropriate subgroups of
the program committee. Submissions (max. 3500 words) may be made
either on paper (5 copies) or on some standard electronic medium to:
Conference on Office Information Systems
Dr. Robert B. Allen
2A-367
Bell Communications Research
Morristown, NJ 07960
------------------------------
Date: Thu 21 May 87 18:20:17-PDT
From: Marcelo Hoffmann <HOFFMANN@KL.SRI.Com>
Subject: Conference - AI Tutorials at Foothill College
IEEE in association with the Foothill College CIS Department is
offering tutorials on AI technologies and applications
Date: Saturday, June 13, 1987, 8:30 A.M. to 5:00 P.M.
Location: Foothill College, Los Altos, California
Subjects:
AI Application Track
PC based expert systems- Paul Harmon, lecturer & consultant
AI in Finance-Dr. Richard Duda, Senior Scientist, Syntelligence
AI Project Management - Tom Schwarz, AI Editor EE Times
AI Technology Track
Neural networks- Robert Hecht-Neilsen, Hecht Neilsen
Neurocomputer Corporation
Claude Cruz-Young, IBM Research Center(PA)
John Vovodsky, President of Neurotech
Intelligent Interfaces- Shelley Horwitz, SRI International
AI Hardware- Robert Keller, Quintus
Anoop Gupta, Stanford University
Shing Kong, UC Berkeley
George Adams, Research Institute for
Advanced Computer Science
Program Schedule:
8:00 Registration
8:30-10:30 Intelligent Interfaces, AI in finance
10:30-10:45 Break
10:45-12:45 AI Hardware; AI Project Managment
12:45:1:45 Lunch
2:00-4:00 Neural Networks; PC Based Expert Systems
----------------------------------------------------------------
REGISTRATION FORM
Fees
_____ $85 for IEEE Members Name__________________Title____________
who reg. before 6/1 Company Name __________________________
_____ $90 for IEEE Members Address________________________________
who reg. on site ________________________________
_____ $95 non members on IEEE Membership #______________________
site (space avail.) Daytime phone# ( )___________________
_____ $90 non members
before 6/1
_____ $65 full-time students
Make checks out to SVC/CS and mail to: IEEE Council Office
701 Welsh Rd., #2205
Palo Alto, CA 94304
For additional information call IEEE Council at(415) 327-662
------------------------------
End of AIList Digest
********************
∂22-May-87 1715 LAWS@Stripe.SRI.Com AIList Digest V5 #127
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 22 May 87 17:14:42 PDT
Date: Fri 22 May 1987 11:12-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #127
To: AIList@STRIPE.SRI.COM
AIList Digest Friday, 22 May 1987 Volume 5 : Issue 127
Today's Topics:
Bindings - sci.philosophy.tech List,
Queries - FRL and Analogy & CLIPS: Parallel Version &
Perceptual Primitives & KNOWOL by IMCO--Intelligent Machine Company,
Application - Grammar Checkers,
Humor - Word Proof takes the Jabberwocky Test,
AI Tools - Scheme References
----------------------------------------------------------------------
Date: 21 May 87 11:37:58 GMT
From: mcvax!botter!klipper!biep@seismo.css.gov (J. A. "Biep" Durieux)
Subject: Zeno, quantum, semantics, Hofstadter, philosophy, inuitionism
Please learn (as I just did) that there is an (as yet unmoderated) forum
to discuss philosophy of logic, math, and science.
It is sci.philosophy.tech .
Please at least cross-post all philosophical articles to that group, and let
follow-ups go there. Many people don't want to wade through many newsgroups
to see if there are any philosophical articles.
Are infinitesimals physically possible?
Can (programming/natural) languages describe their own semantics
(and what are the prerequisites)?
Does the Aspect experiment imply faster-than-light information transfer?
What does "meaning" mean (and: does this question mean anything if
one doesn't know what "to mean" means)?
What do the results of Heisenberg and Goedel imply for the possibility
of knowledge?
Is there a fundamental difference between the subjects of discourse for
mathematics and natural languages?
All these discussions don't belong where they pop up now. They belong
in sci.philosophy.tech.
Thanks for reading this.
--
Biep. (biep@cs.vu.nl via mcvax)
My F-key has autorepeat
------------------------------
Date: Thu, 21 May 87 14:32:00 CDT
From: GE0242%SIUCVMB.BITNET@wiscvm.wisc.edu
Subject: FRL and Analogy
I am looking for a copy of public domain code for a frame-based
representation language such as FRL, KRL, etc., written in Franz
Lisp. If anyone has a copy that they wouldn't mind distributing,
I would appreciate hearing from you.
Also, I would like to hear from people doing research in analogical
problem solving. Pointers to CURRENT research will be very much
appreciated.
Thanks in advance...
Tom Eskridge
Dept of Computer Science
Southern Illinois University at Carbondale
Carbondale, Il. 62901
BITNET: ge0242 at SIUCVMB
------------------------------
Date: 19 May 87 20:49:00 GMT
From: lopez@p.cs.uiuc.edu
Subject: CLIPS: Parallel Version
CLIPS: C Language's Integrated Production System. (NASA/Cosmic)
If anyone out there is using CLIPS and knows of any features they would
like to see in a new parallel version of the language, please feel free to
send your comments to me. The new version should be done for the world to
use by early December.
F. Lopez
------------------------------
Date: Thu, 21 May 87 11:43 EDT
From: LEN MOSKOWITZ <MOSKOWITZ%TSD%atc.bendix.com@RELAY.CS.NET>
Subject: Request for assistance
I'm working on a memory model that learns concepts from scratch. Given
events consisting of sensory input (e.g. for the vision modality, some
description of scenes), it will (hopefully) learn appropriate groupings of
features that define concepts. I am looking for sets of primitives that can
describe sensory perceptions. The primitives need not be "correct" nor
"exhaustive" when evaluated for psychological/perceptual validity, but they
should be "adequate" to describe the range of features they apply to. I have
one set of visual primitives (Irving Biederman's from SUNY Buffalo's Psych
department) that may handle volumetric descriptions of objects describable by
count nouns. To fill out the vision primitives, I think I need textural,
motion, size, orientation, and color/brightness/contrast primitives too. I'm
also looking for perceptual primitives for the other sensory modalities (aural,
tactile, olfactory, kinesthetic...). Any pointers would be greatly
appreciated.
Len Moskowitz
moskowitz@bendix.com (CSnet)
moskowitz%bendix.com@relay.cs.net (ARPAnet)
moskowit@topaz.rutgers.edu (alternate ARPAnet)
rutgers!topaz!moskowit (uucp)
------------------------------
Date: Wed, 13 May 87 08:08:46 PDT
From: lambert%cod@nosc.mil
Subject: How can I find KNOWOL by IMCO--Intelligent Machine Company?
I'm looking for Intelligent Machine Company's PC expert system tools KNOWOL
&/or KNOWOL+, which were recently advertised (Nov 86 AI Expert) and reviewed
(Mar 87 Computer Language). So far, all leads (ad, publisher, phone directory
service) have terminated at a telephone number which is "no longer in service"
(813-844-3262). Does either the company or the product still exist?
D. Lambert
REPLY TO: lambert@nosc.mil
------------------------------
Date: 21 May 87 11:35:11 GMT
From: gilbert@aimmi.UUCP (Gilbert Cockton)
Reply-to: gilbert@aimmi.UUCP (Gilbert Cockton)
Subject: Re: Grammar Checkers
In article <974@viper.UUCP> viper!john (John Stanley) writes:
>
> I don't know about the ones people have been talking about, but I
>do know there is a program under development that can handle "there"
>vs "their" or, for that matter, the "two" vs "too" vs "to".
Anyone got one for "which" versus "that"?
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.aimmi ARPA: gilbert%aimmi.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..!{backbone}!aimmi.hw.ac.uk!gilbert
------------------------------
Date: Thu 21 May 87 17:36:08-PDT
From: Ed Brink <brink@Sushi.Stanford.EDU>
Subject: Word Proof takes the Jabberwocky Test
Inspired by the research presented to me this morning, I decided to put Word
Proof (version 1) to the Jabberwocky test. I used a slightly different
decision rule: I picked the first suggestion that scanned, or if none did, the
one that came closest. Word Proof appears to know more words than PCWrite,
which does not surprise me a bit. WP is primarily a spelling checker; PCWrite
does it as sideline.
Anyhow, here goes:
Jabberers
'Twangs brailling, and the slithery totes
Did gore and gamble in the wake:
All misty were the broodiest,
And the mole wraths outraged.
"Beware the Jabberer, my son!
The jaws that bite, the claws that catch!
Beware the Jumbo bird, and shun
The furious Balderdash!"
He took his vernal sword in hand:
Long time the mangoes foe he sought -
So rested he by the Tumult tree,
And stood awhile in thought.
And, as in unfit thought he stood,
The Jabberer, with eyes of flame,
Came whiffing through the turkey wood,
And burbled as it came!
One, two! One, two! And through and through
The vernal blade went snicker-snack!
He left it dead, and with its head
He went galloping back.
"And hats thou slain the Jabberer?
Come to my arms, my bearish boy!
O fractious day! Callow! Calmly!"
He chortled in his joy.
'Twangs brailling, and the slithery totes
Did gore and gamble in the wake:
All misty were the broodiest,
And the mole wraths outraged.
..Ed
------------------------------
Date: 21 May 87 18:42:41 GMT
From: trh@arizona.edu
Subject: Response to Scheme Ref Question
The response to my request for information on two Scheme references
has been so overwhelming that I have decided to summarize the infor-
mation I have received. Thanks to everyone who replied, with special
thanks to the people at Indiana, who were most encouraging.
About THE BOOKS:
Will Clinger <willc%tekchips.tek.com@RELAY.CS.NET> of Tektronix,
(Beaverton, OR) provides:
> Friedman, Haynes, Kohlbecker, & Wand
> Fundamental Abstractions of Programming Languages
> This book, in draft form, is used in the undergraduate programming
> languages course, C 311, at Indiana University.
> I expect the book will be published later this year or early next year.
> Until then, you might be able to get a copy from the Indiana University
> bookstore.
One of the authors, Dan Friedman, is more cautious stating only that:
> ...is class notes that will be a book published
> with MIT-Press & McGraw-Hill sometime in the future.
Ken Dickey <kend%tekla.tek.com@RELAY.CS.NET>, also of Tektronix,
and Dan Friedman gave the same reference:
> "Programming with Continuations",
> Program Transformations and Programming Environments
> ed: P. Pepper, Springer Verlag, 1984, Pg 263-274.
Several people supplied ADDRESSES FOR THE AUTHORS.
For Dr. Friedman:
> dfried@iuvax.cs.indiana.edu
> <cmcl2!seismo!iuvax!iucs!dfried>
For Chris Haynes
> <cth@indiana.csnet>
Both may (apparently) be reached by Smail at:
Computer Science Department
Lindley Hall
Indiana University
Bloomington, IN 47405
Finally, Daniel Schneider <cmcl2!seismo!mcvax!cui!shneider> at the
University of Geneva, Switzerland passed on some ADDITIONAL (new?)
REFERENCES which he had received from Dr Haynes:
C. T. Haynes and D. P. Friedman, ``Abstracting timed preemption with
engines," to appear in {\it Computer Languages.}
An earlier version of this paper appeared in the 1984 Lisp
Conf. Proc.
C. T. Haynes, D. P. Friedman and M. Wand, ``Obtaining coroutines with
continuations," {\it Computer Languages,\/} Vol. II, No.~3/4 (1986),
143--153.
D. P. Friedman and C. T. Haynes, ``Embedding continuations in
procedural objects,"
to appear in {\it ACM Trans. Progr. Lang. Sys.\/}
An earlier version appeared in the 1985 POPL.
C. T. Haynes, ``Logic continuations," {\it Proceedings of the Third
Int'l. Conf. on Logic Programming\/} (July, 1985), London, England,
{\it Lecture Notes in Computer Science,\/} Vol.~225, Springer-Verlag,
Berlin (1985), 671--685. Revised version to appear in {\it The
Journal of Logic Programming.\/}
This paper gives an embedding of Prolog into Scheme.
R. K. Kybvig, D. P. Friedman, and C. T. Haynes, ``Expansion-passing
style: beyond conventional macros," {\it Proceedings 1986 ACM
Symposium on LISP and Functional Programming\/} (Aug., 1986),
143--150.
Proposes a better macro facility for Scheme and other Lisp
like languages.
D. P. Friedman, C. T. Haynes and E. E. Kohlbecker, ``Programming with
continuations," {\it Program Transformation and Programming
Environments,\/} (P. Pepper, Ed.), Springer-Verlag, Berlin (1984),
263--274.
Once again, thanks to everyone who responded!
-Tom (trh@arizona)
------------------------------
End of AIList Digest
********************
∂28-May-87 0233 LAWS@Stripe.SRI.Com AIList Digest V5 #128
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 28 May 87 02:33:10 PDT
Date: Wed 27 May 1987 23:01-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #128
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 28 May 1987 Volume 5 : Issue 128
Today's Topics:
Theory - Subsymbolic Pointers & IR Semantics & Symbol Grounding
----------------------------------------------------------------------
Date: Thu, 21 May 87 13:01:33 n
From: DAVIS%EMBL.BITNET@wiscvm.wisc.edu
Subject: framing problems
I'd like to briefly say that perhaps an even more astounding problem
than that proposed by Stevan Harnad is that connected with the means by
which literate, intelligent and interested persons can totally obscure
the central core of an idea by the use of unnecessarily obtuse jargon.
If we're going to discuss the more philosphical end of AI (*yes please!*),
then we don't *have* to throw everyone else off the track by bogging
down the chat in a maze of terms intended to have *such* a precise meaning
as to prevent anyone but the author from truly grasping the intended meaning.
Hofstadter's mention of the journal "Art - Language" in metamagical themas
should be than just humourous - it should have warned us all about the
dangers of ridiculously narrow terminology.
thankyou, and goodnight (yaaaawn!)
paul davis
netmail: davis@embl.bitnet
"and when calculating the promise, remember this - the real of the matter -
`to shatter tradition makes us *feel* free, but tradition, is a static
defence against a chaotic community, and what do we gain by destroying it'?"
------------------------------
Date: Thu, 21 May 87 12:56:10 PDT
From: rik%roland@sdcsvax.ucsd.edu (Rik Belew)
Subject: Subsymbolic pointers & IR Semantics
I now see why you consider my use of ``subsymbolic'' sloppy. It is
because you have a well thought out, concrete proposal for three distinct
representational levels that captures extremely well the distinctions I
was trying to make. In the main, I think I accept and even like your
``psycho-physically grounded'' symbol theory. I do have a few
questions, however.
\section{Icon/Pointer/Symbol != Icon/Category/Symbol}
First, what evidence causes you to postulate iconic and categorical
representations as being distinct? Your distinction appears to rest
on differences between the types of performance at task these two
representations each ``subserve.'' Apart from a relatively few
cognitive phenomena (short-term sensory storage, perhaps mental
imagery) I am aware of little evidence of ``... continuous, isomorphic
analogues of the sensory surfaces'' that is the basis of your iconic
representations. In any case, I see great difficulty in distinguishing
between such representations and ``... constructive A/D filters which
preserve the invariant sensory features'' based simply on performance
at any particular task. More generally, could you motivate your
``subserve'' basis for classifying cognitive representations.
I use ``icon'' to mean much the same as your ``categorical
representations'' (which I'm sure will cause us no end of problems as
we discuss these issues!). These representations --- whatever they
are called --- are characterized by their direct, albeit statistical,
relationship with sensory features. This distinguishes icons from
``symbols'' which are representations without structural
correspondence with the environment.
Your, more restricted, notion of ``symbol'' seems to differ in two
major respects: its emphasis on the systematicity of symbols; and its
use of LABELS (of categories) as the atomic elements. I accept
the systematicity requirement, but I believe your labeling notion
confounds several important factors.
First, I believe you are using labels to mean POINTERS:
computationally efficient references to more elaborate and complete
representations. Such pointers correspond closely to Peirce's notion
of INDICES, and are valuable not only for pointing from symbols
to icons (the role you intend for labels) but also from one place in
the symbolic representation to another. Consider Peirce's view on the
primacy of pronouns.
However, I have come to use the term ``pointer'' instead of ``index''
because I also mean to refer to the vast economy of representation
afforded by such representational devices, as recognized by computer
science. Pointers have obviously been an integral part of traditional
data structures in computer science since the beginning. Quillian's
use of TOKEN --> TYPE pointers is still a
classic example of their benefit to AI knowledge structures. More
recently, many connectionists have taken this pointer quality to be
what they mean by ``symbol.'' For example, Touretzky and Derthick say:
\begin{quotation}
Intelligence seems to require the ability to build complex structures
and to refer to them with simpler objects that may be passed among
processes easily. In this paper we use ``symbol'' to denote such
objects... Symbols in Lisp are mobile [one of five properties
Touretzky ascribes to symbols] because their addresses are easily
copied and passed around. In connectionist models where symbols are
identified with activity in particular units, symbols are not mobile.
[Touretzky \& Derthick, ``Symbol structures in connectionist
networks'' IEEE COMPCON 1987]
\end{quotation}
A more sophisticated form of pointer has been discussed by Hinton as
what he calls a ``reduced description.'' The idea here is to allow the
pointer to contain some reduced version of the description to which it
is pointing. (For example, consider the use of tag bits in some
computer architectures that indicate whether the pointer address
refers to an integer, a real, a string, etc.) If the reduced
description is appropriately constructed, the pointer itself may
contain sufficient information and so the computational overhead of
following it to the full description can be avoided. In general,
however, it might seem impossible to construct such appropriate
reduced descriptions. But if a PROCESS view of cognition is
adopted, rather than relying on a STATIC structure to encode all
information , such generalized pointers become more conceivable:
reduced descriptions correspond to PARTIALLY ACTIVE
representations which, when more FULLY ACTIVE, lead to more
completely specified descriptions.
The other feature of your labeling notion that intrigues me is
the naming activity it implies. This is where I see the issues
of language as becoming critical. I would go so far as to
propose that truly symbolic representations and language are
co-dependent. I believe we agree on this point. It is
important to point out that by claiming true symbol
manipulation arose only as a response to language, I do not
mean to belittle the cognitive abilities of pre-lingual
hominids. Current connectionist research is showing just how
powerful iconic (and perhaps categorical) representations can
be. By the same token I use the term language broadly, to
include the behavior of other animals for example.
In summary, it seems to me that the aspect of symbols connectionism
needs most is something resembling pointers. More elaborate notions of
symbol introduce difficult semantic issues of language that can be
separated and addressed indepently (see below). Without pointers,
connectionist systems will be restricted to ``iconic'' representations
whose close correspondence with the literal world severly limits them from
``subserving'' most higher (non-lingual) cognitive functioning.
\section{Total Turing Test}
While I agree with the aims of your Total Turing Test (TTT),
viz. capturing the rich interrelated complexity characteristic
of human cognition, I have never found this direct comparison
to human performance helpful. A criterion of cognitive
adequacy that relies so heavily on comparison with humans
raises many tangential issues. I can imagine many questions
(e.g., regarding sex, drugs, rock and roll) that would easily
discriminate between human and machine. Yet I do not see such
questions illuminating issues in cognition.
On the other hand, I also want to avoid the ``... Searlian mysteries
about `intrinsic' vs. `derived' intentionality....'' Believe it or
not, it is exactly these considerations that has led me to the
information retrieval task domain. I did not motivate this well in my
last message and would like to give it another try.
\section{Semantics in information retrieval}
First, let's do our best to imagine providing an artificial cognitive
system (a robot) with the sort of grounding experience you and I both
believe necessary to full cognition. Let's give it video eyes,
microphone ears, feedback from its affectors, etc. And let's even
give it something approaching the same amount of time in this
environment that the developing child requires. I want to make two
comments on this Gedanken experiment. First, the corpus of experience
acquired by such a robot is orders of magnitude more complex than any
system today. Second, there is no doubt that even such a complete
system as this would have a radically different experience of the
world than our own. In short, I simply mean to highlight the huge
distance between the psycho-physical experience of any artificial
system and any human.
The communication barrier between the symbols of man and the
symbols of machine to which I referred in my last message is a
consequence of this distance. When we say ``apple'' I would
expect the symbol in our heads to have almost no correspondence
to the symbol ``apple'' in any computers. Since I see such a
correspondence as a necessary precondition to the development
of language, I am not hopeful that language between man and
machine can develop in the same fashion as language develops
within a species.
So the question for me becomes: how might we give a machine the
same rich corpus of experience (hence satisfying the total part
of your TTT) without relying on such direct experiential
contact with the world? The answer for me (at the moment) is
to begin at the level of WORDS. I view the enormous textual
databases of information retrieval (IR) systems as merely so
many words. I want to take this huge set of ``labels,''
attached by humans to their world, as my primitive experiential
database.
The task facing my system, then, is to look at and learn from this
world. This experience actually has two components. The textbase
itself provides the first source of information, viz., how authors use
and juxtapose words. The second, ongoing source of experience are the
interactions with IR users, in which people use these same words and
then react positively or negatively to my systems interpretation of
those words. The system then adapts its (connectionist) representation
of the words and documents so as to reflect what the consensus of its
users indicate by these words. In short, I am using the original
authors and the browsing users as the systems ``eyes'' into the human
world. I am curious to see what structural relationship arise among
these words, via low level connectionist learning procedures, to
facilitate access to the IR database.
------------------------------
Date: Fri, 22 May 87 11:12:29 EDT
From: harnad@Princeton.EDU
Subject: Symbol Grounding - Pt. 1
This is part 1 of a response to a longish exchange on the symbol grounding
problem. Rik Belew <rik%roland@SDCSVAX.UCSD.EDU> asks:
> ... [1] what evidence causes you to postulate iconic and categorical
> representations as being distinct?... Apart from a relatively few
> cognitive phenomena (short-term sensory storage, perhaps mental
> imagery), I am aware of little evidence of "continuous, isomorphic
> analogues of the sensory surfaces" [your "iconic" representations].
> [2] I see great difficulty in distinguishing between such
> representations and "constructive A/D filters [`categorical'
> representations] which preserve the invariant sensory features" based
> simply on performance at any particular task. More generally, could
> you [3] motivate your ``subserve'' basis for classifying cognitive
> representations.
[1] First of all, short-term sensory storage does not seem to constitute
*little* evidence but considerable evidence. The tasks we can perform
after a stimulus is no longer present (such as comparing and matching)
force us to infer that there exist iconic traces. The alternative
hypthesis that the information is already a symbolic description at
this stage is simply not parsimonious and does not account for all the
data (e.g., Shepard's mental rotation effects). These short-term
effects do suggest that iconic representations may only be temporary
or transient, and that is entirely compatible with my model. Something
permanent is also going on, however, as the sensory exposure studies
suggest: Even if iconic traces are always stimulus-bound and
transient, they seem to have a long-term substrate too, because their
acuity and reliability increases with experience.
I would agree that the subjective phenomenology of mental imagery is very
weak evidence for long-term icons, but successful performance on some
perceptual tasks drawing on long-term memory is at least as economically
explained by the hypothesis that the icons are still accessible as by the
alternative that only symbolic descriptions are being used. In my
model, however, most long-term effects are mediated by the categorical
representations rather than the iconic ones. Iconic representations
are hypothesized largely to account for short-term perceptual
performance (same/difference judgment, relative comparisons,
similarity judgments, mental rotation, etc.). They are also, of
course, more compatible with subjective phenomenology (memory images
seem to be more like holistic sensory images than like selective
feature filters or symbol strings).
[2] The difference between isomorphic iconic representations (IRs)
and selective invariance filters (categorical representations, CRs)
is quite specific, although I must reiterate that CRs are really a
special form of "micro-icon." They are still sensory, but they are
selective, discarding most of the sensory variation and preserving
only the features that are invariant *within a specific context of
confusable alternatives*. (The key to my approach is that identifying
or categorizing something is never an *absolute* task but a relative,
context-dependent one: "What's that?" "Compared to What?") The only
"features" preserved in a CR are the ones that will serve as a reliable
basis for sorting the instances one has sampled into their respective
categories (as learned from feedback indicating correct or incorrect
categorizing). The "context" (of confusable alternatives), however, is
not a short-term phenomenon. Invariant features are provisional, and
always potentially revisable, but they are parts of a stable,
long-term category-representational system, one that is always being
extended and updated on the basis of new categorization tasks and
samples. It constitutes an ever-tightening approximation.
So the difference between IRs and CRs ("constructive A/D filters") is
that IRs are context-independent, depending only on the
comparison of raw sensory configurations and on any transformations that
rely on isomorphism with the unfiltered sensory configuration, whereas
IRs are context-dependent and depend on what confusable alternatives
have been sampled and must then be reliably identified in
isolation. The features on which this successful categorization is based
cannot be the holistic configural ones, which blend continuously into
one another; they are features specifically selected and abstracted to
subserve reliable categorization (within the context of alternatives
sampled to date). They may even be "constructive" features, in the sense
that they are picked out by performing an active operation -- sensory,
comparative or even logical -- on the sensory input. Apart from this invariant
basis for categorization (let's call these selectively abstracted features
"micro-iconic") all the rest of the iconic information is discarded from the
category filter.
[3] Having said all this, it is easy to motivate my "subserve" as you
request: IRs are the representations that subserve ( = are required in
order to generate successful performance on) tasks that call for
holistic sensory comparisons and isomorphic transformations of
the unfiltered sensory trace (e.g., discrimination, matching,
similarity judgment) and CRs are the representations required to
generate successsful performance on tasks that call for reliable
identification of confusable alternatives presented in isolation. As a
bonus, the latter provide the grounding for a third representational
system, symbolic representations (SRs), whose elementary symbols are
the labels of the bounded categories picked out by the CRs and
"fleshed out" by the IRs. These elementary symbols can then be
rulefully combined and recombined into symbolic descriptions which, in
virtue of their reducibility to grounded nonsymbolic representations,
can now refer to, describe, predict and explain objects and events in
the world.
Stevan Harnad
{seismo, psuvax1, bellcore, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.princeton.edu
(609)-921-7771
------------------------------
End of AIList Digest
********************
∂28-May-87 0520 LAWS@Stripe.SRI.Com AIList Digest V5 #129
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 28 May 87 05:01:19 PDT
Date: Wed 27 May 1987 23:44-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #129
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 28 May 1987 Volume 5 : Issue 129
Today's Topics:
Theory - Symbol Grounding
----------------------------------------------------------------------
Date: 22 May 87 18:08:53 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem (Part 2 of 2)
Rik Belew <rik%roland@SDCSVAX.UCSD.EDU> writes:
> I use ``icon'' to mean much the same as your ``categorical
> representations''... their direct, albeit statistical,
> relationship with sensory features... distinguishes icons from
> ``symbols'', which are representations without structural
> correspondence with the environment.
The criterion for being iconic is physical isomorphism
( = "structural correspondence"). This means that the relationship
between an object and its icon must be a physically invertible
(analog) transformation. In my model, iconic representations
are isomorphic with the unfiltered sensory projection of the
input they represent, whereas categorical representations
are only isomorphic with selected features of the input.
In that sense they are "micro-iconic." The important point is
that they are selective and based on abstracting some features and
discarding all the rest. The basis of selection is: "What features do
I need in order to categorize this input correctly, relative to other
confusable alternatives I have encountered and may encounter in the
future?" To call the input an "X" on the basis of such a selective,
context-governed feature filter, however, is hardly to say that one
has an "icon" of an "X" in the same sense that iconic representations
are icons of input sensory projections. The "structural
correspondence" is only with the selected features, not with the "object"
being named.
On the other hand, the complete absence of any structural
correspondence whatever is indeed what distinguishes both iconic and
categorical representations from symbolic ones. The heart of my symbol
grounding proposal is that in allowing you to speak of (identify,
label, categorize) "X's" at all, categorical representations have
provided you with a set of elementary labels, based on nonsymbolic
representations, that can now ground an otherwise purely syntactic
symbol system in the objects and events to which it refers. Note,
though, that the grounding is a strong constraint, one that renders
the symbolic system no longer the autonomous syntactic module of
conventional AI. The system is hybrid through-and-through. The
relations between the three kinds of representation are not modular but
bottom-up, with the nonsymbolic representations supporting the
symbolic representations' relation to objects. Most of the rules for
symbol binding, etc. are now constrained in ways that depart from the
freedom of ungrounded formal systems.
> Your, more restricted, notion of ``symbol'' seems to differ in two
> major respects: its emphasis on the systematicity of symbols; and its
> use of LABELS (of categories) as the atomic elements. I accept
> the systematicity requirement, but I believe your labeling notion
> confounds several important factors...
> First, I believe you are using labels to mean POINTERS:
> computationally efficient references to more elaborate and complete
> representations... valuable not only for pointing from symbols
> to icons (the role you intend for labels) but also from one place in
> the symbolic representation to another...
> many connectionists have taken this pointer quality to be
> what they mean by "symbol."
I believe my grounding proposal is a lot more specific than merely a
pointing proposal. Pointing is, after all, a symbol-to-symbol
function. It may get you to an address, but it won't get you from a
word to the nonsymbolic object to which it refers. The labeling
performance that categorical representations subserve, on the other
hand, is an operation on objects in the world. That is why I proposed
grounding elementary symbols in it: Let the arbitrary labels of
reliably sorted object categories be the elementary symbols of the
symbolic system. Such a hybrid system would continue to have most of
the benefits of higher-order systematicity (compositionality), but with
nonsymbolic constraints "weighing down" its elementary terms. Consider
ordinary syntactic constraints to be "top-down" constraints on a
symbol-system. A grounded hybrid system would have "bottom-up"
constraints on its symbol combinations too.
As to the symbolic status of connectionism -- that still seems to be moot.
> The other feature of your labeling notion that intrigues me is
> the naming activity it implies. This is where I see the issues
> of language as becoming critical. ...truly symbolic representations and
> language are co-dependent. I believe we agree on this point...
> true symbol manipulation arose only as a response to language
> Current connectionist research is showing just how
> powerful iconic (and perhaps categorical) representations can
> be... I use the term language broadly, to
> include the behavior of other animals for example.
Labeling and categorizing is much more primitive than language, and
that's all I require to ground a symbol system. All this calls for is
reliable discrimination and identification of objects. Animals
certainly do it. Machines should be able to do it (although until they
approach the performance capacity of the "Total Turing Test" they may be
doing it modularly in a nonrepresentative way). Language seems to be
more than labeling and categorizing. It also requires *describing*,
and that requires symbol-combining functions that in my model depend
critically on prior labeling and categorizing.
Again, the symbolic/nonsymbolic status of connectionism still seems to
be under analysis. In my model the provisional role of connectionistic
processes is in inducing and encoding the invariant features in the
categorical representation.
> the aspect of symbols [that] connectionism
> needs most is something resembling pointers. More elaborate notions of
> symbol introduce difficult semantic issues of language that can be
> separated and addressed independently... Without pointers,
> connectionist systems will be restricted to ``iconic'' representations
> whose close correspondence with the literal world severely limits them
> from ``subserving'' most higher (non-lingual) cognitive functioning.
I don't think pointer function can be divorced from semantic issues in
a symbol system. Symbols don't just combine and recombine according to
syntactic rules, they are also semantically interpretable. Pointing is a
symbol-to-symbol relation. Semantics is a symbol-to-object
relationship. But without a semantically interpretable system you
don't have a symbol system at all, so what would be pointing to what?
For what it's worth, I don't personally believe that there is any
point in connectionism's trying to emulate bits and pieces of the
virtues of symbol systems, such as pointing. Symbolic AI's
problem was that it had symbol strings that were interpretable as
"standing for" objects and events, but that relation seemed to be in
the head of the (human) interpreter, i.e., it was derivative, ungrounded.
Except where this could be resolved by brute-force hard-wiring into a
dedicated system married to its peripheral devices, this grounding
problem remained unsolved for pure symbolic AI. Why should
connectionism aspire to inherit it? Sure, having objects around that
you can interpret as standing for things in the world and yet still
manipulate formally is a strength. But at some point the
interpretation must be cashed in (at least in mind-modeling) and then
the strength becomes a weakness. Perhaps a role in the hybrid mediation
between the symbolic and the nonsymbolic is more appropriate for
connectionism than direct competition or emulation.
> While I agree with the aims of your Total Turing Test (TTT),
> viz. capturing the rich interrelated complexity characteristic
> of human cognition, I have never found this direct comparison
> to human performance helpful. A criterion of cognitive
> adequacy that relies so heavily on comparison with humans
> raises many tangential issues. I can imagine many questions
> (e.g., regarding sex, drugs, rock and roll) that would easily
> discriminate between human and machine. Yet I do not see such
> questions illuminating issues in cognition.
My TTT criterion has been much debated on the Net. The short reply is
that the goal of the TTT is not to capture complexity but to capture
performance capacity, and the only way to maximize your confidence
that you're capturing it the right way (i.e., the way the mind does it)
is to capture all of it. This does not mean sex, drugs and rock and
roll (there are people who do none of these). It means (1) formally,
that a candidate model must generate all of our generic performance
capacities (of discriminating, identifying, manipulating and describing
objects and events, and producing and responding appropriately to names
and descriptions), and (2) (informally) the way it does so must be
intuitively indistinguishable from the way a real person does, as
judged by a real person. The goal is asymptotic, but it's
the only one so far proposed that cuts the underdetermination of
cognitive theory down to the size of the ordinary underdetermination of
scientific theory by empirical observations: It's the next best thing
to being there (in the mind of the robot).
> First, let's do our best to imagine providing an artificial cognitive
> system (a robot) with the sort of grounding experience you and I both
> believe necessary to full cognition. Let's give it video eyes,
> microphone ears, feedback from its affectors, etc. And let's even
> give it something approaching the same amount of time in this
> environment that the developing child requires...
> the corpus of experience acquired by such a robot is orders of magnitude
> more complex than any system today... [yet] even such a complete
> system as this would have a radically different experience of the
> world than our own. The communication barrier between the symbols
> of man and the symbols of machine to which I referred in my last
> message is a consequence of this [difference].
My own conjecture is that simple peripheral modules like these will *not* be
enough to ground an artificial cognitive system, at least not
enough to make any significant progress toward the TTT. The kind of
grounding I'm proposing calls for nonsymbolic internal representations
of the kind I described (iconic representations [IRs] and categorical
representations [CRs]), related to one another and to input and output in
the way I described. The critical thing is not the grounding
*experience*, but what the system can *do* with it in order to
discriminate and identify as we do. I have hypothesized that it must have
IRs and CRs in order to do so. The problem is not complexity (at least
not directly), but performance capacity, and what it takes to generate
it. And the only relevant difference between contemporary machine
models and people is not their *experience* per se, but their
performance capacities. No model comes close. They're all
special-purpose toys. And the ultimate test of man/machine
"communication" is of course the TTT!
> So the question for me becomes: how might we give a machine the
> same rich corpus of experience (hence satisfying the total part
> of your TTT) without relying on such direct experiential
> contact with the world? The answer for me (at the moment) is
> to begin at the level of WORDS... the enormous textual
> databases of information retrieval (IR) systems...
> I want to take this huge set of ``labels,'' attached by humans to
> their world, as my primitive experiential database...
> The task facing my system, then, is to look at and learn from this
> world:... the textbase itself [and] interactions with IR users...
> the system then adapts its (connectionist) representation...
Your hypothesis is that an information retrieval system whose only
source of input is text (symbols) plus feedback from human users (more
symbols) will capture a significant component of cognition. Your
hypothesis may be right. My own conjecture, however, is the exact
opposite. I don't believe that input consisting of nothing but symbols
constitutes "experience." I think it constitutes (ungrounded) symbols,
inheriting, as usual, the interpretations of the users with which the
system interacts. I don't think that doing connectionism instead of
symbol-crunching with this kind of input makes it any more likely to
overcome the groundedness problem, but again, I may be wrong. But
performance capacity (not experience) -- i.e., the TTT -- will have
to be the ultimate arbiter of these hypotheses.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 27 May 87 15:55:33 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem (Part 2 of 2)
In article <770@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
>The criterion for being iconic is physical isomorphism
>( = "structural correspondence"). This means that the relationship
>between an object and its icon must be a physically invertible
>(analog) transformation.
As I've seen you broach this criterion a few times now, I just thought I'd
remind you of a point that I thought was clearly made in our earlier
discussion of the A/D distinction: loss of information, i.e.
non-invertibility, is neither a necessary nor sufficient condition for
analog to digital transformation.
Anders Weinstein
------------------------------
End of AIList Digest
********************
∂28-May-87 0746 LAWS@Stripe.SRI.Com AIList Digest V5 #130
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 28 May 87 07:46:10 PDT
Date: Wed 27 May 1987 23:53-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #130
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 28 May 1987 Volume 5 : Issue 130
Today's Topics:
Queries - Philosophy and Complexity Theory &
Prolog Interpreter in C Available (Wanted/Offered) &
Graduate Schools with a Good AI Program,
Bindings - Les Kitchen & Interactive Fiction Discussion,
Applications - Knowledge-Based Document Retrieval &
Knowledge from Databases Summary,
Humor - Artificial Reasoning,
Review - Spang Robinson Report 3/5, May 1987
----------------------------------------------------------------------
Date: 25 May 87 14:14:46 GMT
From: munnari!basser.cs.su.oz!ray@seismo.CSS.GOV
Subject: Philosophy, Artificial Intelligence and Complexity Theory
Lately I've been chating informally to a philosopher/friend about
common interests in our work. He was unfamiliar with the concept of the
TIME TO COMPUTE consequences of facts. Furthermore, the ramifactions of
intractability (ie. if P != NP is, as we all suspect, true) seemed to
be new to my friend. The absolute consequences are hard to get across
to a non-computer scientist; They always say "but computers are getting
faster all the time...".
I'm digging around for references in AI on these ideas. This isn't my area.
Can anyone suggest some?
I've dug up a couple of relevant papers:
"Some Philosophical Problems from the Standpoint of Artificial Intelligence",
McCarthy and Hayes, 1969. I think this is the most obvious starting point,
with its description of the frame problem. However, the authors seem to
discuss the issue from the standpoint of what a formalism must contain so
that the system is CAPABLE of computing what it needs rather than the TIME
to compute these things (please correct me if I'm wrong). This is hardly
suprising, as it predates the seminal P=NP? work.
"The Tractability of Subsumption in Frame-Based Description Languages",
Brachman and Levesque, AAAI-84. This paper is relevant, but too
implementation specific for what I want. I want something more general
and preferably philosophically oriented.
*NOTE*: I'm certainly NOT implying that AI is impossible! But the notion
of intractability is one that must be addressed. I'm sure it has been
addressed. I'm just chasing a few references, more for the benefit of my
colleague than myself.
Raymond Lister
Basser Department of Computer Science
University of Sydney
NSW 2006
AUSTRALIA
ACSnet: ray@basser
ARPANET: ray%basser.oz@seismo.arpa
------------------------------
Date: 22 May 87 19:49:57 GMT
From: sundc!hadron!inco!mack@seismo.css.gov (Dave Mack)
Subject: Prolog Interpreter in C Available (Wanted/Offered)
I am looking for a public domain Prolog interpreter. I am also
offering to post one to the USENET, depending on the response
I get to this posting.
The reason for the strange form of this request is that I no
longer have time to hack at my version of Prolog. My implementation
is an incomplete Clocksin-Mellish syntax interpreter. Many of
the built-in functions are not yet implemented and it has several
major bugs ("cut" doesn't work quite right, for example.) It
does correctly parse CM prolog and performs resolution (mostly)
correctly. It is written in C for BSD4.2, but should be easily
portable System V, since about the only OS dependent feature is
"index".
If I get a reasonable number of positive responses to this posting,
I will finish documenting the beast and ship a couple of shar
files to comp.sources.unix.
If you want a copy, let me know. If you manage to fix any of
the bugs, mail me the diffs. I'll test them and post them to
the net.
Happy Hacking!
Dave Mack
McDonnell Douglas-Inco, Inc. (home of the laser-guided hamburger)
8201 Greensboro Drive DISCLAIMER: Until they pay me for
McLean, VA 22101 them, my opinions are my own. Call
(703)883-3911 for prices.
...!seismo!sundc!hadron!inco!mack
------------------------------
Date: 26 May 87 15:58:22 GMT
From: hp-sdd!nick@sdcsvax.ucsd.edu (Nick Flor)
Subject: Need info on grad schools with a good AI program
Could someone e-mail me a list of graduate schools with a good
AI program. (Like the top 25 or top 10)
If not, a pointer to where I could find this information in a concise form
would also be helpful.
Sorry to ask this question. I know it gets asked alot, I just never
payed attention before.
Thanks in advance.
Nick
--
+ Disclaimer: The above opinions are my own, not necessarily my employers'.
/ Nick V. Flor / ..hplabs!hp-sdd!nick / Hewlett Packard, San Diego Division
* "What's going down in this world, you got no idea. Believe me."-The Comedian
- "Less Thunder with the Mouth, More Lightning with the Fists." - The Ripper
------------------------------
Date: Mon, 25 May 87 16:28 EDT
From: "Les Kitchen." <KITCHEN%cs.umass.edu@RELAY.CS.NET>
Subject: Binding (actually setq)
From 1st of July 1987:
Les Kitchen
Department of Computer Science
University of Western Australia
Nedlands, W.A. 6009
AUSTRALIA
munnari!wacsvax.oz!les@seismo.css.gov
les%wacsvax.oz@australia.csnet
------------------------------
Date: 27 May 87 15:43:22 GMT
From: oliveb!pyramid!tcgould!engst@ames.arpa (Adam C. Engst)
Subject: Interactive fiction
Hi,
I am currently starting a discussion group on misc.misc that deals with
interactive fiction. Interactive fiction has as its basic concept that of
non-linear text, though there are many other additions that can (and should)
be added for the enhancment of the text. If you are unsure as to what
interactive fiction is, read misc.misc. Somewhere in there (among many
other good articles mostly calling for AI-based systems) is my brief
description of interactive fiction. I would like the opinion of AI workers
in order to determine the level at which AI can be used to help advance
interactive fiction, either now or in the future. I accept all email, but I
can't guarantee any responses since I have terrible luck with paths. So,
please check it out, and if you are interested, join the discussion. I hope
to have it large enough soon to get our own newsgroup to stop bothering
everyone else in misc.misc.
Adam Engst
pv9y@cornella.bitnet
engst@batcomputer.tn.cornell.edu
------------------------------
Date: Thu, 21-MAY-1987 09:19 EST
From: FOXEA%VTVAX3.BITNET@wiscvm.wisc.edu
Subject: Reply - Knowledge-Based Document Retrieval
[Forwarded from the IRList Digest by Laws@STRIPE.SRI.COM.]
Date: Tue, 19 May 87 13:44:40+0900
From: Kim Young Whan <mcvax!csd.kaist.ac.kr!ywkim@seismo.css.gov>
Subject: References on Knowledge-based Document Retrieval
I'm writing a Ph.D Thesis about Knowledge Based System for Document
Retrieval, especially about rule based system using uncertainty handling
mechanism (Bayesian, D-S Theory, Fuzzy Set Theory). [...]
Young-Whan Kim
Dept. of CS KAIST
P.O.Box 150, Cheongryang
Seoul, 131
Republic of Korea.
ywkim%csd.kaist.ac.kr@relay.cs.net(from cs-net)
ywkim%csd.kaist.ac.kr@wiscvm.wisc.edu(from bitnet)
[Note: there has been quite a lot of work on this. There will be a
special issue of Information Processing and Management out this summer
on this topic. Several papers at the ACM SIGIR Conf. on R&D in
Information Retrieval in New Orleans in a few weeks will be about this -
I will announce how to get proceedings from ACM when they become available.
There was a 2 part article in JASIS by Biswas et al. recently.
Notable other systems include I3R by Croft and Thomson, RUBRIC by Tong
et al., CODER by Fox et al, CANSEARCH by Pollitt, ... Also, there are
abstracts in issues of ACM SIGIR Forum. If you are not an ACM SIGIR
member, I encourage joining -- it still only costs $6 to ACM members,
but dues will jump to $12 soon. - Ed]
------------------------------
Date: 22 May 87 20:50:19 GMT
From: necntc!ci-dandelion!bunny!gps0@ames.arpa (Gregory
Piatetsky-Shapiro)
Subject: Knowledge from Databases? A follow-up
This is a promised follow-up on the subject of extracting knowledge
from databases. I have received about a dozen replies and my thanks
to all the respondents. I have also tried to reply individually, but
not always succeeded (all blame is on the mailer).
I have found two recent references in this area.
The Spring, 1987 issue of IEEE Expert contains a good article by Michael Walker
on "How Feasible is Automated Discovery?". This article also contains
references to other relevant systems, including Meta-Dendral, AM, Bacon, RX,
Prospector and others. There is also an article by Gio Wiederhold et al, on
"KSYS: An Architecture for Integrating Databases and Knowledge Bases".
It was submitted to IEEE transactions on Software Engineering and it can be
obtained by writing to Prof. Wiederhold at Stanford.
I have found that there is some work on extracting expert system rules
from databases at GM (contact samy@gmr.com). There is also a company
in Hawaii working on automatic analysis of medical databases and there
is a small start-up in Boston area working on extracting data models
from databases. However, none of the above have published anything.
There are some commercial expert system tools that interface to databases:
Intellicorp has KEE Connection to interface KEE to SQL databases
Inference is working on a similar tool for ART
Arity Prolog has an interface to SQL
Guru from mdbs combines an ES and DBMS (and other stuff).
Insight 2+ interfaces to dbase II, III
VP Expert also has an interface to dbase II, III
Mad Intelligent Systems from San Jose, CA has produced
Relational Lisp - Lisp extended by relational operations
Herman Rubin from Purdue expressed doubts that
it is possible to come up with new theories in a mechanical way.
He says
>I do not trust anyone to come up with anything new by that device. Data
>analysis is necessary, but it should only be done by geniuses, or at least
>very bright people, who are constantly aware of the dangers of incorrect
>analysis, or even accidently incorrect analysis.
True - "extracting knowledge from data" will not come up with
radically new theories. However this approach can and does come up with
new relationships, the general form of which is known - look at Bacon,
Meta-Dendral, RX, Prospector.
>If Kepler had one more decimal place to work with, his laws would not fit;
>The data analysis problem is to get theories
>which are certainly incorrect, and which fit "more or less."
An excellent observation. But who says that a computer cannot search
for relations that hold more or less? In fact, accounting for
approximate relationships is a must prerequisite in analyzing any real
data, and it was done before.
Comments are welcome.
------------------------------
Date: 21 May 87 11:35:26 GMT
From: gilbert@aimmi.UUCP (Gilbert Cockton)
Reply-to: gilbert@aimmi.UUCP (Gilbert Cockton)
Subject: Re: Humor - Artificial Life
In article <8705180545.AA27470@ucbvax.Berkeley.EDU> NHAAS@IBM.COM
(Norman Haas) writes:
>(In case this point hasn't already been made, re the "Artificial Life" confer-
>ence announcement a few issues back:)
>
> Why stop with life? Let's go all the way:
>
> 1. Artificial Culture and Civilization, including
> Artificial Natural Languages
> 2. Artificial Science, including
> Artificial Research in the field of Artificial Intelligence
Nah - that's not all the way. We also need
3. Artificial reasoning.
This is when people who nothing about epistemology (philosophical and
anthropological/sociologial aspects) or psychology lock themselves away on
an AI project and make things up about how people reason. I may be
oldfashioned, but I do miss empirical substance and conceptual coherence
:-) :-):-) :-) :-):-) :-) :-):-) :-) :-):-) :-) :-):-) :-) :-):-) :-) :-):-)
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.aimmi ARPA: gilbert%aimmi.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..!{backbone}!aimmi.hw.ac.uk!gilbert
------------------------------
Date: Mon, 25 May 1987 13:38 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Review - Spang Robinson Report 3/5, May 1987
Spang Robinson Report, May 1987, Volume 3 No. 5 (Summary)
The lead article is on difficulties that LISP machine vendors have
had.
Currently, here is the breakdown of how many of each machine is
installed for AI applications:
DEC 5000
SUN 1800
Apollo 600
Tektronix 100
Lisp Machines
Symbolics 4000
Xerox 2500
TI 1500
LMI 500
Integrated Inference Machines has just entered the market.
DEC reports that 30 percent of DEC's AI sales are MicroVAXEN with
ten per cent being the high end 800 machines. DEC has put all
AI efforts under Bill Johnson and two buildings will be dedicated
to AI activities with 300 people involved.
They also have a table of all LISP Machine Vendors as well as general
purpose machine vendors entering the AI market indicating pricing,
number of units sold for AI and AI software available for each machine.
They estimate that the revenue for sales of conventional machines to
do AI is about the same as that for LISP machine with both groups
totalling about $200 million each.
There is also a nice table summarizing the activities and machines
for both LISP Machine companies and conventional machine vendors entering
the AI market.
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-
The next article discusses Gold Hill's Gold Works, an expert sytem. The system
requires 5 MB extended memory, 512K of RAM and 7MB of disk space. The
system interfaces with Lotus, dBASE, C, and Assembler as well as Mice and
EGA drivers. The system
supports frames, multiple inheritance, object oriented programming,
forward and backward chaining, the RETE algorithm, an agenda mechanism,
a screen editor for developing the presentation part of the
expert system and a dependency Network which can be used in multiple words
type applicatons. It costs $5,000 between now and July 31 with
the price at $7500 thereafter.
$-$-$-$-$-$-$-$-$-$-$-$ SHORTS -$-$-$-$-$-$-$-$-$-$-$-$-$-$-$-$-$-$-
The AI Show at Long Beach drew 3438 attendees.
Teknowledge reports third quarter revenues of $4,469,000 and a net loss
of $721,000.
The former head of Sperry's AI center has founded PEAKSolutions in
Minneapolis which provides AI services.
Eloquent Systems is now marketing its in-house developed AI toolkit
optimized for real-time multi-user applications. This company also
developed systems for the hotel industry.
Teknowledge will be marketing Framatomes's AI tool, K1.
CP international will be selling a natural language interface for their
text retrieval system, STRATUS.
Two banks have licensed Syntelligence's Lending Advisor, an expert system to
assist loan officers.
Larry Geisel who used to be president of Carnegie Group is now president
of Intelligent Technology Group.
_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-
They also have a list of papers on LISP machines and reviews of
The T Programming Language: A Dialect of LISP by Stephen Slade
PROLOG: A Relational Language and Its Applications by John Malpas
Prolog Programming: Applications for Database Systems, Expert
Systems, and Natural Language Systems by Claudia Marcus
------------------------------
End of AIList Digest
********************
∂30-May-87 0000 LAWS@Stripe.SRI.Com AIList Digest V5 #131
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 May 87 00:00:28 PDT
Date: Fri 29 May 1987 21:08-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #131
To: AIList@STRIPE.SRI.COM
AIList Digest Saturday, 30 May 1987 Volume 5 : Issue 131
Today's Topics:
Bibliography - Leff order.addresses6 & ai.bib53TR
----------------------------------------------------------------------
Date: Mon, 25 May 1987 13:38 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: order.addresses6
Laboratory for Computer Science research
Rutgers University
New Brunswick, NJ 08903
Center for Supercomputing Research and Development
University of Illinois
305 Talbot Lab
104 S. Wright Street
Urbana, IL 61801-2932
Department of Computer Science
915 Patterson Office Tower
University of Kentucky
Lexington, Kentucky 40506-0027
L. A. Stratmann
Department of Computer Science
Rice University
P. O. Box 1892
Houston, Texas 77251
Robot Systems Division
University of Michigan
Ann Arbor, Michigan 48109
Department of Computer Science
University of Illinois at Urbana-Champaign
1304 West Springfield AVenue
Urbana, Illinois 61801
Department of Computer Sciences
Technical REport Center
Taylor Hall 2.124
The University of Texas at Austin
Austin, Texas 78712-1188
Diane Speekman
USC/Information Sciences Institute
4676 Admiralty Way, Ste. 1001
Marina del Rey, CA 90292-6695
------------------------------
Date: Mon, 25 May 1987 13:38 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: ai.bib53TR
%A N. V. Murray
%A E. Rosenthal
%T Theory Links
%I State University of New York at Albany, Department of Computer Science
%R 86-3
%K AI11
%X We develop the notiton of theory link, which is a generalization of ordinary
link to a set of literals that are simultaneously unsatisfiable relative
to a given set of clauses. We show that theory links may be 'activated' in
much the same manner as ordinary links when inferencing with respect to the
given set of clauses. Several link deletion results are shown to hold for
theory links, and several examples, including Schubert's Steamroller,
are presented using first-order theory links.
%A N. V. Murray
%A E. Rosenthal
%T Path Dissolution for Propositional Logic
%I State University of New York at Albany, Department of Computer Science
%R 86-6
%K AI10 Prawitz matrix reduction semantic graphs path resolution
Noetherean
%A M. Balaban
%A N. V. Murray
%T Logic Programming with LOGLISP
%I State University of New York at Albany, Department of Computer Science
%R 86-9
%K AT08 AI11 T01
%A M. Balaban
%T The Generalized-Concept Approach to Knowledge Representation: A Frame
Like Interface to Logic
%I State University of New York at Albany, Department of Computer Science
%R 86-12
%K Generalized-Concept Model AI10 AI16 AA25
%X see Tech Report 86-13 for extended version of the same paper
%A M. Balaban
%A N. V. Murray
%T A First Order Calculus for Temporal Knowledge
%I State University of New York at Albany, Department of Computer Science
%R 86-26
%K AI10 AI16
%A M. Balaban
%T The Generalized-Concept (G-C) Formalism- An Object Oriented, Logic
Framework for Knowledge Representation in AI
%I State University of New York at Albany, Department of Computer Science
%R 86-27
%K AI10 AI16
%A A. Ginsberg
%A S. M. Weiss
%A P. Politakis
%T Automatic Knowledge Base Refinement for Classification Systems
%I Rutgers University
%R CBM-TR-148
%K SEEK SEEK2 AI03 AI01
%X system to refine knowledge bases automatically
%A C. V. Apte
%A S. M. Weiss
%T An Expert Systems Methodology for Control and Interpretation of
Applications Software
%I Rutgers University
%R CBM-TR-149
%K AA03 AI01 AA15
%X System for the Control and Interpretation of interactive software systems
%A A. Van der Mude
%T Some Formal Properties of Version Spaces
%I Rutgers University
%R DCS-TR-201
%K AI04 AI16 Inductive Inference
%X Version Spaces are a method for learning a general model which describes some
input data, by keeping track of a number of equally likely alternative
models (versions) consistent with the data, while deleting unacceptable
models and adding new versions as the need arises
%A T. Imielinski
%T Complexity of Query Processing in the Deductive Databases with Incomplete
Information
%I Rutgers University
%R DCS-TR-206
%K AA09 AI10
%X The Query Processing problem on relation databases with intensions
built from Linear Horn clauses, prefixes of the type all, some, all and
conjunctive queries. Two properties are described which determine
the decidability of query processes. A query is given which has exponential
lower bound.
%A T. Imielinski
%T Domain Abstraction and Limited Reasoning
%I Rutgers University
%R DCS-TR-207
%K O04 AI10 AI11
%X Approximate reasoning methods for first order logic
%A R. M. Keller
%T The Role of Explicit Contextual Knowledge in Learning Concepts to Improve
Performance
%I Rutgers University
%R ML-TR-7
%K AI03 AI01
%$ 15.00
%X Difficulties in using concept learning methods to improve an existing
systems performance.
%A W. Ludwell Harrison
%T Compiling Lisp for Evaluation on a Tightly Coupled Multiprocessor
%R CSRD Report No. 565
%I Center for Supercomputing Research and Development, University of Illinois
%D MAR 1986
%K T01 H03
%X 281 pages
%A Santosh Abraham
%A J. Patel
%T Parallel Garbage Collection on a Virtual Memory System
%I Center for Supercomputing Research and Development, University of Illinois
%R 620
%D AUG 1987
%K T01 H03
%X to appear in 1987 International Conference on Parallel Processing
%A W. Marek
%A M. Truszyczynski
%T Incompleteness of Information in Rule-Based Systems: The
Role of Minimal Sets
%R 87-87
%I Department of Computer Science, University of Kentucky
%K AI01 AI16
%A W. Marek
%T A Natural Semantics for Modal Logic Over Databases
%R 88-87
%I Department of Computer Science, University of Kentucky
%K AA09 AI10
%A Tom Altman
%A Suresh Easwar
%T Rotation-Invariant Enclodings for Linear-Time Shape Matching Algorithms
%R 89-87
%I Department of Computer Science, University of Kentucky
%K AI06 O06
%A W. Marek
%A M. Truszyczynski
%T Forcing Autoepistemic Statements
%R 90-87
%I Department of Computer Science, University of Kentucky
%K AI16
%A Robert Cartwright
%T Types as Intervals
%R TR84-5
%I Department of Computer Science, Rice University
%D NOV 1984
%$ 2.50
%K AI16 AI15
%X To accommodate polymorphic data types and operations, several computer
scientists - most notably MacQueen, Plotkin, and Sethi -- have proposed
formalizing types as ideas. Although this approach is intuitively
appealing, the resulting type system is both complex and restrictive
because the type constructor that creates function types in [sic] not
monotonic, and hence not computable. As a result, types cannot be
treated as data values, precluding the formalization of type constructors
and polymorphic program modules (where types are values) as higher order
computable functions. Moreover, recursive definitions of new types do not
necessarily have solutions.
.sp
sp
This paper proposes a new formulation of types -- called intervals-- that
subsumes the theory of types as ideals, yet avoids the pathologies caused
by non-monotonic type constructors. In particular, the set of interval
types contains the set of ideal types as a proper subset and all the
primitive type operations on intervals are extensions of the corresponding
operations on ideas. Nevertheless, all of the primitive interval type
constructors including the function type constructor and type quantifiers
are computable operations. Consequently, types are higher order data
values that can be freely manipulated within programs.
%A Robert Hood
%T Efficient Applicative Operations on Recursive Data Structures
%R TR 85-515
%I Department of Computer Science, Rice University
%D FEB 1985
%K T01
%$ 1.20
%X Gives O(1) time and space functions in Pure Lisp for a given set of
operations to manipulate recursive data structures such as LISP's S
expressions including array-like selection.
%A Hans Boehm
%A Alan Demers
%A James Donahue
%T A Programmers' Introduction t0o Russel
%R TR 85-16
%I Department of Computer Science, Rice University
%D MAR 1985
%$ 1.95
%X Russell is a programming language based on the view that a data type
is simply a collection of operations which can itself be manipulated.
This permits compile-type checking with the flexibilities of languages
supporting dynamic typing.
%A William G. Golson
%T A Complete Proof System for an Acceptance Refusal Model of CSP
%R TR 85-19
%D APR 1985
%I Department of Computer Science, Rice University
%K AA09 Concurrent Sequential Processes Hoare
%$ 2.25
%A Paul Besl
%A Ramesh Jain
%T An Overview of Three-Dimensional Object Recognition
%R RSD-TR-19-84
%I Robot Systems Division, University of Michigan
%K AI06
%$ 4.50
%A Paul Besl
%A Ramesh Jain
%T Surface Characterization for Three-Dimensional Object Recognition in
Depth Maps
%R RSD-TR-20-84
%I Robot Systems Division, University of Michigan
%K AI06
%$ 5.00
%A I. K. Sethi
%A Ramesh Jain
%T Finding Trajectories of Point in Monocular Image Sequence
%R RSD-TR-3-85
%I Robot Systems Division, University of Michigan
%K AI06
%$ 2.50
%X finding the same physical point in more than one dimension, formulated
as an optimization problem for the case of several nonrigid objects
in a scene.
%A Richard A. Volz
%A Tony C. Woo
%A Jan D. Wolter
%T Optimal Algorithms for Symmetry Detection in Two and Three Dimensions
%I Robot System Division, University of Michigan
%R RSD-TR-5-85
%K O06
%$ 2.50
%X Algorithms for finding rotational and involutional symmetries in point
sets, polygons nad polyhedrons. Time is O(n) for polygons and O(nlogn) for
two and three-dimensional point sets. Polyhedra with planar connected surface
graphs can be done in O(n) time.
%A Mubarak Shah
%A Arun Sood
%A Ramesh Jain
%T Pulse and Staircase Models for Detecting Edges at Multiple Resolution
%I Robot Systems Division, University of Michigan
%R RSD-TR-7-85
%K AI06
%$ 2.50
%A P. S. Bhugra
%A T. N. Mudge
%T Comparisons Between Ada and Lisp
%I Robot Systems Division, University of Michigan
%R RSD-TR-9-85
%K AI06
%$ 2.00
%A T. F. Knoll
%A R. C. Jain
%T Recognizing Partially Visible Objects Using Feature Indexed Hypotheses
%I Robot Systems Division, University of Michigan
%R RSD-Tr-10-85
%K AI06
%$ 2.50
%A S. M. Hyanes
%A Ramesh Jain
%T Event Detection and Correspondence
%I Robot Systems Division, University of Michigan
%R RSD-Tr-12-85
%K AI06
%$ 2.00
%X Detection of changes in uniformly accelerated motion of objects from
pictures of their movement
%A Paul Besl
%A Kurt Skifstad
%A Ramesh Jain
%T Objective Dimensionality Reduction Using Out-of-Class Covariance
%I Robot Systems Division, University of Michigan
%R RSD-TR-17-85
%K O06 AI06 O04
%$ 3.00
%X Non-hierarchical statistical decision algorithms spend a significant
portion of their time entertaining incorrect hypotheses in multiple class,
pattern recognition problems. Maximum-likelihood multivariatie-Gaussian (MLMVG)
hypotheses testing is a common example of such a statistical pattern
rognition technique. It is shown that the use of out of class covariance
matrices can significantly reduce the run-time computations required to
make MLMVG decisions. The Analysis directly leads to an objective
dimensionality reduction (ODR) technique that indicate the preferred,
intrinsic dimensionality omultiple class decision spaces given the training
data. Run-time computatio/ns are reduced even further using these reduced
dimension class decision spaces with dimensionality reduction technique to
stress the essential concepts of out-of-class covariance. The theory has been
applied to a nine(9) class, twenty-seven (27) feature, automatic visual solder
joint inspection problem with excellent results; run-time computations
are reduced by more than a factor of three while maintaining excellent design
performance.
%A Shih-Ping Liou
%A Ramesh C. Jain
%T Detecting Road Edges Using Hypothesized Vanishing Points
%R RSD-TR-18-85
%I Robot Systems Division, University of Michigan
%K AI06 AA19
%$ 2.50
%A Suk In Yoo
%T A Methodology For Solving Problems in Artificial Intelligence
%R RSD-TR-20-85
%I Robot Systems Division, University of Michigan
%K AI03 A* heuristic function traveling salesman robot planning consistent
labelling theorem proving
%$ 11.50
%A Ramesh Jain
%A Sandra L. Bartlett
%A Nancy O'Brien
%T Motion Stereo Using Ego-Motion Complex Logarithmic Mapping
%I Robot Systems Division, University of Michigan
%R RSD-TR-3-86
%K AI06
%$ 2.50
%X Obtaining and using stereo information from a moving camera
%A Charles J. Conrad
%A N. Harris McClamroch
%T The Drilling Problem: A Stochastic Modeling and Control Example in
Manufacturing
%I Robot Systems Division, University of Michigan
%R RSD-TR-4-86
%K AA26
%$ 2.50
%A Paul Besl
%A Ramesh Jain
%T Segmentation Through Symbolic Surface Descriptions
%I Robot Systems Division, University of Michigan
%R RSD-TR-5-86
%K AI06
%$ 3.00
%A Pual Joseph Besl
%T Surfaces in Early Range Image Understanding
%I Robot Systems Division, University of Michigan
%R RSD-TR-10-86
%K AI06
%$ 18.00
%A Rajeev Agrawal
%A Ramesh Jain
%T An Overview of Tactile Sensing
%I Robot Systems Division, University of Michigan
%R RSD-TR-11-86
%K AI06 AI07
%$ 2.50
%A Jerry Lee Turney
%T Recognition of Partially Occluded Parts
%I Robot Systems Division, University of Michigan
%R RSD-TR-16-86
%K AI06 AI07 AA26
%$ 7.00
%T Behavior of Edges in Scale Space
%I Robot Systems Division, University of Michigan
%R RSD-2-87
%K AI06
%A Daniel Pual Miranker
%T TREAT: A New and Efficient Match Algorithm for AI Production Systems
%I University of Texas at Austin, Department of Computer Sciences
%R TR-87-03
%K AI01 H03 O06
%X The algorithm which was designed specifically for the DADO parallel
machine in fact is more efficient on sequential machines as well.
%A Allan Collins
%A Ryszard Michalski
%T The Logic of Plausible Reasoning: A Core Theory
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R NO. 951
%D FEB 1986
%A John A. Bentrup
%A Gary J. Mehler
%A Joel D. Riedesel
%T INDUCE 4: A Program for Incrementally Learning Structural Descriptions
from Examples
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 958
%D FEB 1987
%K AI04
%A Peter Haddawy
%T A Variable Precision Logic Inference System Employing the Dempster-Shafer
Uncertainty Calculus
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 959
%D DEC 1986
%K O04 Construction Project Cost Estimation
%A R. S. Michalski
%A A. B. Baskin
%A C. Uhrik
%A T. Channik
%T The ADVISE.1 Meta-Expert System: The General Design and a Technical
Description
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 962
%D JAN 1987
%K AI01
%A Kaihu Chen
%T The Inductive Acquisition of Temporal Knowledge
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 964
%D DEC 1986
%K AI04 O03
%A Ryszard S. Michalski
%T Two-Tiered Concept Meaning, Inferential Matching and Conceptual
Cohesiveness
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 968
%D JUN 1986
%K AI04
%A Kenneth D. Forbus
%T The Qualitative Process Engine
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 1288
%D DEC 1986
%K AT15 qualitative physics
%A Kenneth D. Forbus
%T The Logic of Occurrence
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 1300
%D DEC 1986
%K Zeno's paradox pruning
%A Mitchell D. Lubas
%T A Knowledge-Based Design aid for the Construction of Software Systems
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 1304
%D NOV 1986
%K AA08
%A Larry Rendell
%A Powell Benedict
%A Howard Cho
%T Concept Acquisition from Examples: Measurement of System Performance and
Suggestions for Improved Design
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 1315
%D JAN 1987
%K AI04
%A Dedre Gentner
%T Evidence for A Structure-Mapping Theory of Analogy and Metaphor
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 1316
%D DEC 1986
%K AI02
%A Larry Rendell
%T Conceptual Knowledge Acquisition in Search
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 1317
%D JAN 1987
%K AI03 AI04
%A Larry Rendell
%A Raj Seshu
%A david Tcheng
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%T Robust Concept Learning Using Dynamically-Variable Bias
%R 1318
%D MAR 1987
%K AI04
%A Larry Rendell
%T Layered Concept Learning and Its Advantages
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 1320
%D MAR 1987
%K AI04
%A L. V. Kale
%T "Completeness" and "Full Parallelism" of Parallel Logic Programming
Schemes
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 1321
%D FEB 1987
%K H03 AI10
%A Larry Rendell
%T Representations and Models for Concept Learning
%I Department of Computer Science, University of Illinois at Urbana-
Champaign
%R 1324
%D MAR 1987
%K AI04
%T ANTITHESIS: A STUDY IN CLAUSE COMBINING AND DISCOURSE STRUCTURE
%A William C. Mann
%A Sandra A. Thompson
%R ISI/RS-87-171
%D April 1987
%I USC/Information Sciences Institute
%X approx. 30 pages
.sp
sp
AI research in text generation needs a strong linguistically justified
descriptive theory as a basis for creating methods by which programs can write
multiparagraph texts. This paper sketches Rhetorical Structure Theory, which
has been designed to support text generation, and then applies RST to
describing a particular class of discourse constructs.
.sp
sp
There is no consensus as to the status of clause combining relations relative
to larger texts. This paper demonstrates a clause combining relation that is
also found as part of larger text structures, and shows how this fact can be
used to explain cases in which contrastive clause combining appears between
clauses that are not in fact in contrast. The appropriate generalization is
that the relations of clause combining and the relations of general text
structure are the same. Use of this generalization should make AI text
planning and text generation significantly easier.
%T NOTES ON THE ORGANIZATION OF THE ENVIRONMENT OF A TEXT GENERATION GRAMMAR
%A Christian Matthiessen
%R ISI/RS-87-177
%D April 1987
%I USC/Information Sciences Institute
%K AI02
%X approx. 52 pages
.sp 1
sp 1
One of the tasks in designing a text generation system is to organize the
environment of the grammatical component of the generation system in such a
way that it supports the grammatical resources in generation. This report
discusses the methods used for the Penman generation system to infer aspects
of the organization of the knowledge base and other components of the
environments of the Nigel grammar of the Penman system. It is shown how the
design task can be broken down into a number of very explicit demands on the
environment. In the main part of the report, the results of application of
such an approach is sketched, with particular emphasis on the general
organization of the knowledge base and the discourse model parts of the
environment.
%T Systemic Grammar and Functional Unification Grammar
and
Representational Issues In Systemic Functional Grammar
%A Christian Matthiessen
%A Robert Kasper
%R ISI/RS-87-179
%D April 1987
%I USC/Information Sciences Institute
%X approx. 55 pages
.sp
sp
SYSTEMIC GRAMMAR AND FUNCTIONAL UNIFICATION GRAMMAR: Systemic Functional
Grammar (SFG) and Functional Unification Grammar (FUG) are superficially very
different approaches to grammatical knowledge, but they share an underlying
comparability that runs very deep. FUG shares with systemic descriptions an
emphasis on the functions of linguistic objects, and an explicit
representation of feature choices. This paper explores how a systemic
grammar can be represented in FUG notation, as a step toward creating a
grammatical analysis program for English. Because FUG has been developed as a
computational tool, expressing a systemic grammar in FUG notation allows new
computational techniques to be applied to it. Among other benefits, this
program will make it possible to study how much the grammatical functions of
sentences are recoverable from them. It will also provide a method to test the
amount of ambiguity implicit in a systemic description, a topic which has so
far been inaccessible. This use of FUG as an alternate representation for SFG
may have some additional benefits for both frameworks. It provides some
solutions to problems in systemic notation which are described by Matthiessen
(in this volume). Several extensions to the FUG framework are also suggested
by this study.
.sp
sp
REPRESENTATIONAL ISSUES IN SYSTEMIC FUNCTIONAL GRAMMAR: Nigel is a large
diverse computational grammar for text generation. Its
framework is an implementation of Systemic Functional Theory of grammar and it
constitutes a context in which the representation of systemic theory can be
explored and studied.
.sp
sp
This paper surveys the representational devices used in the Nigel grammar and
the representational issues that they raise in relation to systemic theory.
These issues are diagnosed in the light of the metafunctional differentiation
of systemic theory.
------------------------------
End of AIList Digest
********************
∂30-May-87 0256 LAWS@Stripe.SRI.Com AIList Digest V5 #132
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 May 87 02:56:33 PDT
Date: Fri 29 May 1987 21:13-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #132
To: AIList@STRIPE.SRI.COM
AIList Digest Saturday, 30 May 1987 Volume 5 : Issue 132
Today's Topics:
Bibliography - Leff ai.bib51C
----------------------------------------------------------------------
Date: Wed, 27 May 1987 12:15 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: defs for ai.bib51C
D MAG105 Computer Vision, Graphics and Image Processing\
%V 36\
%N 2-3\
%D NOV-DEC 1986
D MAG106 Pattern Recognition\
%V 19\
%N 6\
%D 1986
D BOOK62 Annual Review of Computer Science\
%I Annual Reviews Inc\
%C Palo Alto, CA\
%D 1986
D BOOK63 Proceedings of the Sixth International Conference on Robot Vision and S
ensory Controls\
%I IFS Publications Limited\
%C Kempston
D BOOK64 Automata, Languages and Programming (Rennes 1986)\
%V 226\
%S Lecture Notes in Computer Science\
%I Springer-Verlag\
%C Berlin-Heidelberg-New York\
%D 1986
D MAG107 Cybernetics\
%V 22\
%N 3\
%D MAY-JUN 1986
D MAG108 Computer Vision, Graphics and Image Processing\
%V 37\
%N 2\
%D FEB 1987
D MAG109 Computer Vision, Graphics and Image Processing\
%V 37\
%N 3\
%D MAR 1987
D MAG110 Journal of Parallel and Distributed Computing\
%V 4\
%N 1\
%D FEB 1987
D BOOK65 Proceedings of the IEEE Computer Society - 1986 International\
Conference on Computer Languages (Miami Florida, October 27-30 1986)\
%I IEEE Computer Society\
%D 1986\
%C Washington D. C.
D MAG112 Pattern Recognition Letters\
%V 12\
%N 1\
%D JAN 1987
D MAG114 Computer Vision, Graphics and Image Processing\
%V 38\
%N 1\
%D APR 1987
------------------------------
Date: Wed, 27 May 1987 12:15 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: ai.bib51C
%A D. M. C. Francesetti
%T Expert Systems and DSS for Strategic Planning
%B Managing Advanced Manufacturing Technology
%E A. Voss
%I IFS Publications Limited
%D 1986
%P 319-326
%K AA26
%A T. Chart
%T Human Versus Machine - A Comparison of a Computer Expert System with
Human Experts in the Diagnosis of Vaginal Discharge
%J International Journal of Bio-Medical Computing
%V 20
%N 1-2
%D JAN 1987
%P 71-78
%K AA01 AI01
%A A. Bouckaert
%T Medical Diagnosis - Are Expert Systems Needed
%J International Journal of Bio-Medical Computing
%V 20
%N 1-2
%D JAN 1987
%P 123-134
%K AA01 AI01
%A H. W. Glaser
%A P. Thompson
%T Lazy Garbage Collection
%J Software Practice and Experience
%P 1-4
%V 17
%N 1
%D JAN 1987
%K T01
%A R. Ballard
%T Prospects for Expert Systems in Quality Management
%J CME The Chartered Mechanical Engineer
%V 34
%N 1
%P 16-18
%K AI01 AA05
%A S. Tan
%A D. Juvin
%B BOOK63
%P 49-60
%K AA26 AI06
%A W. J. Bogers
%T Circular Array Sensor, Control Algorithm and Hardware for Fast Tracking of
Planar Contours
%B BOOK63
%P 69-80
%K AA26 AI06 AI07
%A G. W. Davis
%T Classifying and Coping with Lighting Variation
%B BOOK63
%P 89-90
%K AA26 AI06
%A G. Nicolas
%A J. P. Hermann
%T Inspection of Moulds by 3-Dimensional Vision
%B BOOK63
%P 99-106
%K AA26 AI06
%A A. R. Desaintvincent
%T 3-Dimensional Perceptory Systems for Autonomous Mobile Robots
%B BOOK63
%P 127-138
%K AA19 AI07 AI06
%A M. Guichard
%A A. Renault
%T Industrial Use of Ultrasonic Ranging Sensors in Robotics
%B BOOK63
%P 157-164
%K AI06 AI07
%A S. R. Ruocoo
%T The Design of a 3D Vision Sensor for Robot Multisensory Feedback
%B BOOK63
%P 187-196
%K AI06 AI07
%A A. Michel
%T The Quantification of Qualitative Aspects - A Problem of Perception and
Communication
%B BOOK63
%P 209-216
%K AI08 AI16 AI06
%A Y. Li
%A L. Wu
%A D. H. Chen
%T A Study on Direct Vision Sensor for Welding Visual Sensing
%B BOOK63
%P 245-248
%K AI06 AA26
%A B. S. Barclay
%T Sensing Techniques Applied to Electronics Assembly
%B BOOK63
%P 249-266
%K AA26 AI06 AI07
%A J. C. Perez
%T Holography and Image Analysis to Test IBM Modules Airproofness
%B BOOK63
%P 267
%K AA26 AA04 AI06
%A Michael J. Hudak
%A Daniel H. Marcellus
%T Demon-Based Associative Memories
%J Cybernetics and Systems
%V 17
%N 4
%D 1986
%P 249-276
%A Amedeo Capelli
%A Gianni Caracoglia
%A Lorenzo Moretti
%T Chunking Mechanism for a Knowledge Representation System
%J Cybernetics and Systems
%V 17
%N 4
%D 1986
%P 277-288
%K AI16
%A Germano Rosconi
%T Applications of GSLT (General System Logical Theory) to Control in
Transformation Systems
%J Cybernetics and Systems
%V 17
%N 4
%D 1986
%P 289
%K AI16 AI10
%A L. Wood
%T Out of the Ivory Tower - The Major AI Software Developers Are Leaving the
Lab and Attending to the Real World Demands of Corporate MIS
%J Computer Decisions
%V 19
%N 2
%D JAN 26, 1987
%K AI16 AA06
%A B. H. Rudall
%T Contemporary Cybernetics (Automation; Behavioural Systems; Business
Cybernetics; Innovations in Cybernetics; Legged Locomotion Study; Machine
Intelligence; Machine Vision; Medical Cybernetics; Software Developments)
%J Kybernetes
%V 16
%N 1
%D 1987
%P 1-10
%K AI16 AT08
%A Guy Jumarie
%T New Decision Rules in Statistical Pattern Recognition
%J Kybernetes
%V 16
%N 1
%D 1987
%K AI06 O04
%A E. Andreewsky
%A V. Rosenthal
%A D. Bourcier
%T Preliminary Phase of Language Comprehension: Outline of a Systems Model
%J Kybernetes
%V 16
%N 1
%D 1987
%P 27-32
%K AI02
%A Khaled M. Bugrara
%A Cynthia A. Brown
%T On the Average Case Analysis of Some Satisfiability Model Problems
%J Inform. Sci
%V 40
%D 1986
%N 1
%P 21-37
%K AI03
%A Mao Kang Wu
%T The Problem of No Relationship Between PI-Clash and the Order of
Electrons in Mechanical Theorem Proving
%J Shanghai Keji Daxue Xuebao
%V 1986
%N 1
%P 99-106
%K AI11
%X Chinese with English summary
%A V. V. Zadorozhnyi
%T A Method for Synthesis of a Correct Pattern Recognition Algorithm
for a Given Control Sample
%J Zh. Vychisl. Mat. i. Mat. Fiz
%V 26
%N 10
%P 1559-1566
%K O06 AI06
%X in Russian
%A Sudarshan K. Dhall
%A S. Lakshmivarahan
%T Effect of Data Organization in A System of Interleaved Memories on
the Performance of Parallel Search
%J Inform. Sci
%V 39
%D 1986
%N 3
%P 219-246
%K H03 AI03
%A Hoang Klem
%A Pham Ngoc Khoi
%T Some Aspects of Image Coding Based on Run Length Codes and Chain Codes
%J Elektron. Informationsverarb. Kybernet.
%V 22
%D 1986
%N 7-8
%P 411-421
%K O06 AI06
%A G. Gottlob
%T Subsumption and Implication
%J Information Processing Letters
%V 24
%N 2
%D JAN 30, 1987
%P 109-112
%K AI11
%A B. Ackland
%T Flute - An Expert Floorplanner for Full Custom VLSI Design
%J IEEE Design and Test
%V 4
%N 1
%D FEB 1987
%P 32-41
%K AA04 AI01
%A A. Kusiak
%T Artificial Intelligence and Operations Research in Flexible Manufacturing
Systems
%J Infor
%V 25
%N 1
%D FEB 1987
%P 2-12
%K AA26
%A Jia-Huai You
%A P. A. Subrahmanyam
%T E-Unification Algorithms for a Class of Confluent Term Rewriting Systems
%B BOOK64
%P 454-463
%K AI11
%A Wen Jun Wu
%T A Mechanization Method of Geometry. I Elementary Geometry
%J Chinese Quart. J. Math
%V 1
%D 1986
%N 1
%P 1-14
%K AA13 AI11
%A S. G. Vorob'ev
%T Applications of Conditional Systems of Permutations of Terms in
Program Verification
%J Programmirovanie
%V 1986
%N 4
%P 3-14
%D 1986
%K AI11 AA08
%X in Russian
%A G. von Trzebiatowski
%A B. Bank
%T On the Convergence of the Fuzzy Clustering Algorithm "Fuzzy Isodata"
%J Z. Agew. Math. Mech
%V 66
%D 1986
%N 6
%P 201-208
%K O04 O06
%A Egidijus Ostasevicius
%T Recognition of Random Processes Described by a Mixture of Normal
Distributions
%J Statist. Problemy Upravieniya No. 71
%D 1985
%P 9-18
%K O06 AA12
%A Heikki Mannila
%A Esko Ukkonen
%T The Set Union Problem with Backtracking
%B BOOK64
%P 236-246
%K AI03
%A Neil V. Murray
%T On Deleting Links in Semantic Graphs
%B BOOK64
%P 404-415
%K AI16
%A Sarit Kraus
%A Daniel J. Lehmann
%T Knowledge, Belief and Time
%B BOOK64
%P 186-195
%K AI16
%A Giorgio Levi
%T Logic Programming: The foundations, the Approach and the Role of
Concurrency
%B Current Trends in Concurrency (Noordwijkerhout, 1985)
%I Lecture Notes in Computer Science
%V 224
%I Springer-Berlin-New York
%P 396-441
%D 1986
%K AI11 H03 AA08
%A Mikulas Hermann
%A Igor Privara
%T On Nontermination of of Knuth-Bendix Algorithm
%B BOOK64
%P 146-156
%K AI14 AI11
%A L. Fribourg
%T A Strong Restriction of the Inductive Completion Procedure
%B BOOK64
%P 105-115
%K AI14 AI11
%A Antonio Di Nola
%A Witold Pedrycz
%A Salvatore Sessa
%T Coping with Uncertainty for Knowledge Acquisition and Inference
%J Kybernetes
%V 15
%D 1986
%N 4
%P 243-249
%K AI16 O04
%A Hirofumi Yokouchi
%T Retraction Map Categories and Their Applications to the Construction
of Lambda Calculus Models
%J Inform. and Control
%V 71
%D 1986
%N 1-2
%P 33-86
%K T01
%A Colin Stirling
%T A Compositional Reformulation of Owicki-Grie's Partial Correctness
Logic for a Concurrent While Language
%B BOOK64
%P 407-415
%K AA08
%A A. Pnueli
%T Applications of Temporal Logic to the Specification and Verification
of Reactive Systems: A Survey of Current Trends
%B BOOK64
%P 510-584
%K AA08 AI16 AI11
%A Ernst-Rudiger Olderog
%T Process Theory: Semantics, Specification and Verification
%B Current Trends in Concurrency (Noordwijkerhout, 1985)
%I Lecture Notes in Computer Science
%V 224
%I Springer-Berlin-New York
%P 442-509
%D 1986
%K AA08
%A Ketan Mulmuley
%T Fully Abstract Submodels of Typed Lambda Calculi. Twenty-Fifth
Annual Symposium on Foundations of Computer Science (Singer Island, Fla.)
%J J. Comput. System Sci.
%V 33
%D 1986
%N 1
%P 3-46
%K AA08 T01
%A Jozef Hooman
%A Wiullem P. De Roever
%T The Quest Goes on: A Survey of Proofsystems for Partial Correctness of
CSP
%B Current Trends in Concurrency (Noordwijkerhout, 1985)
%I Lecture Notes in Computer Science
%V 224
%I Springer-Berlin-New York
%P 343-395
%D 1986
%A M. Coppo
%A M. Dezani-Ciancaglini
%A M. Zacchi
%T Type Theories, Normal Forms, and $D sub inf$ Lambda models
%J Information and Computation
%V 72
%N 2
%D FEB 1987
%P 85-116
%K AA08
%A C. D. Hurt
%T Conceptual Citation Differences in Science, Technology and Social
Sciences Literature
%J Information Processing and Management
%V 23
%N 1
%D 1987
%P 1-6
%K AA14
%A Jorge Moser
%A Richard Christoph
%T Management Expert Systems (M. E. S.): A Framework for Development
and Implementation
%J Information Processing and Management
%V 23
%N 1
%D 1987
%K AA06 AI01
%A Marcia J. Bates
%T Interaction in Information Systems: A Review of Research from Document
Retrieval to Knowledge Based Systems by N. J. Belkin and A. Vickery
%J Information Processing and Management
%V 23
%N 1
%D 1987
%K AT07 AA14
%A D. H. Freedman
%T AI Meets Corporate Mainframe
%J Infosystems
%V 34
%N 2
%D FEB 1987
%P 32-37
%K AA06
%A S. A. Kurtz
%A M. J. O'Donnell
%A J. S. Royer
%T How to Prove Representation-Independent Independence Results
%J Information Processing Letters
%V 24
%N 1
%D JAN 15, 1987
%P 5-10
%K AI16
%A R. S. Bird
%A J. Hughes
%T An Alpha Beta Algorithm: An Exercise in Program Transformation
%J Information Processing Letters
%V 24
%N 1
%D JAN 15, 1987
%P 53-58
%K AA08 AI03
%A Yaser S. Abu-Mostafa
%A Demetri Psaltis
%T Optical Neural Computers
%J Scientific American
%V 256
%N 3
%D MAR 1987
%K AI06 AI12
%A Yu. N. Zhuravlev
%A I. V. Sergienko
%A V. I. Artemenko
%A A. M. Chernyakova
%T The Use of Classification Theory for Automated Selection of Algorithms
in Program Packages
%J MAG107
%P 270-278
%K AA08
%A N. I. Galagan
%A Z. L. Rabinovich
%T Intelligent Problem Solvers
%J MAG107
%P 279-289
%K AI16
%A I - A. A. Voronkov
%A A. I. Degtyarev
%T Automatic Theorem Proving
%J MAG107
%P 290-297
%K AI11
%A A. I. Degtyarev
%A A. A. Voronkov
%T Equality Control Methods in Machine Theorem Proving
%J MAG107
%P 298-307
%K AI11
%A R. G. Bukharaev
%A D. Sh. Suleimanov
%T Development of Computer-Assisted Instruction Systems with Intelligent
Capabilities
%J MAG107
%P 308-317
%K AA07
%A V. I. Vasil'ev
%A F. P. Ovsyannikova
%T Learning Pattern Recognition with Prespecified Confidence
%J MAG107
%P 318-326
%K AA06
%A A. S. Dolgopolov
%T Automatic Spelling Correction
%J MAG107
%P 332-339
%K AA15
%A V. M. Bondarovskaya
%A L. A. Bogush
%A I. Yu Kirichenko
%T Development of Action-Planning Systems on the Basis of Psychological
Studies of the Process of Solving Situation Transformation Problems
%J MAG107
%P 391-398
%K AI08 AI09 AA11
%A G. M. Zarakovskii
%A S. L. Rysakova
%A P. S. Turzin
%T Psychophysiological Optimization of the Set of Signs for Man-Machine
Communication
%J MAG107
%P 399
%K AI08 AA11 AA15
%A J. H. M.ter Brake
%T The AI Development Environment POPLLOG
%B Proceedings of Expert Systems: Available Hard- and Software
%C Mol. Belgium
%D 18-19 JUL 1986
%K T01 T02 T03
%X describes POPLOG which is an integrated combination of POP-11, PROLOG
and Common LISP and Expert System development tools.
%A J. H. Arbeter
%T A Multi-Dimensional Video Imaging Processing Architecture
%B Proc. SPI Int. Soc. Opt. Eng. (USA)
%V 564
%P 81-86
%D 1985
%K AI06
%X This system is designed for the interpretation of TV systems in
real-time.
%A R. F. Bessler
%T A Video Real-Time Pyramid Processor
%B Proc. SPI Int. Soc. Opt. Eng. (USA)
%V 564
%P 81-86
%D 1985
%K AI06 H03
%X This system simulates the human visual system and interpretes NTSC video at
30 frames per second.
%A G. Y. Tang
%T Expert System Makes Image Processing Easier
%B Proc. SPIE Int. Soc. Opt. Engineering
%V 635
%P 119-123
%K AI06 AI01
%X This system assists a user of image processing software.
%A K. H. Feng
%A K. Sugihara
%A N. Sugie
%T A Method for Extracting Three-Dimensional Information Using Cone-Shaped
Beams of Light
%J Syst. & Comput. Jpn. (USA)
%V 17
%N 8
%P 70-9
%K AI06
%X Texture information is generated from a scene by using several point
sources of light at different location.
%A D. E. Guyer
%A G. E. Miles
%A M. M. Schreiber
%A O. R. Mitchell
%A V. C. Vanderbilt
%T Machine Vision and Image Processing for Plant Identification
%J Transactions of the ASAE
%V 29
%N 6
%D NOV-DEC 1986
%P 1500-1507
%K AI06 AA23
%A A. Fanni
%A A. Mura
%T Artificial Intelligence and Expert Systems - Developments in the
Electrotechnical and Electronic Fields
%J L'Elettrotecnica
%V 73
%N 12
%D DEC 1986
%K AA04 AI01
%X in Italian
%A J. L. A. Van de Snepscheut
%T "Algorithms for on-the-fly garbage collection" revisited
%J Information Processing Letters
%V 24
%N 4
%D MAR 2, 1987
%K T01
%A M. W. Kurzynski
%T Diagnosis of Acute Abdominal Pain Using a Three-Stage Classifier
%J Computers in Biology and Medicine
%V 17
%N 1
%D 1987
%K AI01 AA01
%P 19-28
%A Patrick Cavanagh
%T Reconstructing the Third Dimension: Interactions Between Color, Texture,
Motion, Binocular Disparity and Shape
%J MAG108
%K AI06
%P 171-195
%A Steven W. Zucker
%A Lee Iverson
%T From Orientation Selection to Optical Flow
%J MAG108
%K AI06
%P 196-220
%A Julian Hochberg
%T Machines Should Not See as People Do, but Must Know How People See
%J MAG108
%K AI06 AI08
%P 221-237
%A Kent A. Stevens
%A Allen Brookes
%T Detecting Structure by Symbolic Constructions on Tokens
%J MAG108
%K AI06
%P 238-260
%A Deborah Walters
%T Selection of Image Primitives for General-Purpose Visual Processing
%J MAG108
%K AI06
%P 261-298
%A Jacob Beck
%A Anne Sutter
%A Richard Ivry
%T Spatial Frequency Channels and Perceptual Grouping in Texture
Segregation
%J MAG108
%P 299-330
%K AI06
%A Bean-Arie Jezekiel
%A A. Zvi Meiri
%T 3D Objects Recognition by Optimal Matching Search of Multinary Relations
Graphs
%J MAG109
%P 331-344
%K AI06
%A Michael Kass
%A Andrew Witkin
%T Analyzing Oriented Patterns
%J MAG109
%P 362-385
%K AI06
%A Lawrence O'Gorman
%A Arthur C. Sanderson
%T A Comparison of Methods and Computation for Multi-Resolution Low-and-Band-
Pass Transforms for Image Processing
%J MAG109
%P 386-401
%K AI06
%A L. Brevdo
%A S. Sideman
%A R. Beyar
%T A Simple Approach to the Problem of 3-d Reconstruction
%J MAG109
%P 420-427
%K AI06
%A F. Golferini
%A P. Facchin
%T Computer Diagnosis of Primary Headaches in Children
%J MAG109
%P 55-63
%K AI01 AA01
%A Gerhard X. Ritter
%A Paul D. Gader
%T Image Algebra Techniques for Parallel Image Processing
%J MAG110
%P 7-44
%K AI06 H03
%A Eric B. Hinkle
%A Jorge L. C. Sanz
%A Anil K. Jain
%A Dragutin Petkovit
%T $P sup 3 E$: New Life for Projection-Based Image Processing
%J MAG110
%P 45-78
%K AI06 H03
%A T. N. Mudge
%A T. S. Abdel-Rahman
%T Vision Algorithms for Hypercube Machines
%J MAG110
%P 79-94
%K AI06 H03
%A Quentin F. Stout
%T Supporting Divide-and-Conquer Algorithms for Image Processing
%J MAG110
%P 95
%K AI06 H03 O06
%A Charles J. Malmborg
%A Marvin H. Agee
%A Gene R. Simons
%A J. V. Choudry
%T Articial Intelligence Series, Part 4: A Prototype Expert System for
Industrial Truck Type Selection
%J Industrial Engineering
%V 19
%N 3
%D MAR 1987
%K AA05 AI01
%A S. K. Debray
%T Towards Banishing the Cut from Prolog
%B BOOK65
%P 2-12
%K T02
%A S. S. Epstein
%T A Logic Programming Language with Descriptions
%B BOOK65
%P 13-23
%K AI10
%A H. H. Chen
%A I. P. Lin
%A C. P. Wu
%T LOGFOL- A Prolog-Based Frame-Oriented Language
%B BOOK65
%P 24-33
%K T02
%A B. Jayaraman
%A F. S. K. Silbermann
%A G. Gupta
%T Equational Programming - A Unifying Approach to Functional and Logic
Programming
%B BOOK65
%P 47-61
%K AI10 AI11
%A T. Murata
%A D. Zhang
%T A High-Level Petri Net Model for Parallel Interpretation of Logic Programs
%B BOOK65
%P 123-135
%K H03 AI10
%A F. Y. Zhu
%A S. D. Bedrosian
%T Monochrome Images: An Approach to Choosing Fuzzy Distributions
%J Journal of the Franklin Institute
%V 322
%N 5-6
%D NOV-DEC 1986
%P 103-112
%K AI06 O04
%A Markus Lusti
%T Knowledge Based Systems in Education - An Example From Financial Analysis
%J Angewandte Informatik
%N 1
%D JAN 1987
%P 12-19
%K AA07 AA06
%A N. Nansalmaa
%T Application of the Rule of Inference in Informal Mathematical Proofs
%J Cybernetics
%V 22
%N 4
%D JUL-AUG 1986
%P 518-521
%K AA13
%A P. W. Woods
%A C. J. Taylor
%A D. H. Cooper
%A R. N. Dixon
%T The Use of Geometric and Grey-Level Models for Industrial Inspection
%J MAG112
%P 11-18
%K AA05 AI06
%A F. Klein
%A O. Kubler
%T Euclidean Distance Transformations and Model-Guided Image Interpretation
%J MAG112
%P 19-30
%K AI06
%A D. Cruse
%A A. Wright
%T The Use of Segmentation and Shape Recognition Techniques in Synthetic
Aperture Radar Images
%J MAG112
%P 41-48
%K AI06 AA18
%A H. Shvaytser
%A S. Peleg
%T Inversion of Picture Operators
%J MAG112
%P 49-62
%K AI06
%A P. Grossmann
%T Depth From Focus
%J MAG112
%P 63-70
%K AI06
%A T. J. Fountain
%A M. Postranecky
%A G. K. Shaw
%T The CLIP4S System
%J MAG112
%P 71-80
%K AI06
%A H. H. S. Ip
%A D. J. Potter
%T Comparison of 2-D Gel Electrophoresis Images
%J MAG112
%P 81-86
%K AA10 AI06
%A D. B. Sharman
%A T. S. Durrani
%T Goal Driven Parameter Evaluation for the Detection of Objects in SAR Data
%J MAG112
%P 87
%K AI06 AA18
%A V. Lacroix
%T Pixel Labeling in a Second Order Markov Mesh
%J Signal Processing
%V 12
%N 1
%D JAN 1987
%P 59-82
%K AI06
%A K. J. Kokjer
%T The Information Capacity of the Human Fingertip
%J IEEE Transactions on Systems, Man, and Cybernetics
%V 17
%N 1
%D JAN-FEB 1987
%P 100-101
%K AA10 AI08 AI06
%A P. J. Werbos
%T Building and Understanding Adaptive Systems: A Statistical/Numerical Approach
to Factory Automation and Brain Research
%J IEEE Transactions on Systems, Man, and Cybernetics
%V 17
%N 1
%D JAN-FEB 1987
%P 7-20
%K AI08 AA05
%A G. Henrion
%A R. Henrion
%A H. J. Lunk
%A V. Reidel
%T Combination of Non-Supervised and Supervised Pattern Recognition Methods for
Classification of Tungsten Materials
%J Chemische Technik
%V 38
%N 12
%D DEC 1986
%P 525-527
%K AA05 AI06
%X Article in German, Abstract in English and German
%A D. I. Blockley
%A J. F. Baldwin
%T Uncertain Inference in Knowledge Based Systems
%J Journal of Engineering Mechanics ASCE
%V 113
%N 4
%D APR 1987
%P 467-481
%K AA05 O04
%A Zilla Sinuany-Stern
%A Meir J. Rosenblatt
%T Budgeting in Hierarchical Systems Under Uncertainty
%J IIE Transactions
%V 19
%N 1
%P 2-12
%D MAR 1987
%K AI13 O04
%A L. A. Marks
%T Digital Enhancement of the Peripheral Admittance Plethysmogram
%J IEEE Transactions on Biomedical Engineering
%V 34
%N 3
%D MAR 1987
%P 192-198
%K AI06 AA01
%A R. S. Prasad
%A T. M. Srinivasan
%T An Image Processing Method for Cardiac Motion Analysis
%J IEEE Transactions on Biomedical Engineering
%V 34
%N 3
%D MAR 1987
%P 244-246
%K AA01 AI06
%A M. A. Bickel
%T Automatic Correction to Misspelled Names - A Fourth Generation Language
Approach
%J Communications of the ACM
%V 30
%N 3
%D MAR 1987
%P 224-228
%K AA15
%A Lowell Jacobson
%A Harry Wechsler
%T Derivation of Optical Flowing a Spatiotemporal-Frequency Approach
%J MAG114
%P 29-64
%K AI06
%A Robert A. Hummel
%A B. Kimia
%A Stephen W. Zucker
%T Deblurring Gaussian Blur
%J MAG114
%P 66-80
%K AI06
%A George Harauz
%A Richard Gordon
%A Marin Van Heel
%T Oblique Sampling of Projections for Direct-Three-Dimensional Reconstruction
%J MAG114
%P 81-89
%K AI06
%A H. Westphal
%A H. H. Nagel
%T Exploiting Reflectance Properties to Analyze Images of Moving Objects
Needs Local Constraints
%J MAG114
%P 90
%K AI06
%A R. Moskowitz
%T MIS Hedges on the AI Gamble
%J Computer Decisions
%V 19
%N 5
%D MAR 9, 1987
%P 58
%K AA06
------------------------------
End of AIList Digest
********************
∂30-May-87 0515 LAWS@Stripe.SRI.Com AIList Digest V5 #133
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 May 87 05:15:37 PDT
Date: Fri 29 May 1987 21:32-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #133
To: AIList@STRIPE.SRI.COM
AIList Digest Saturday, 30 May 1987 Volume 5 : Issue 133
Today's Topics:
Queries - Pattern Recognition Keynote Speaker Wanted &
Expert Systems for CAD & Approximate Structure Matching,
Philosophy - Complexity Theory and Philosophy,
Ethics - Text Critiquing and Eliza,
Humor - Artificial Stupidity,
Theory - The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 21 May 87 16:00:42 GMT
From: sun!sunburn!gtx!al@seismo.CSS.GOV (Al Filipski 839-0732)
Reply-to: al@gtx.UUCP (Al Filipski 839-0732)
Subject: keynote speaker wanted
I am looking for a keynote speaker for a Symposium on Pattern Recognition
and Machine Intelligence to be held in Wichita, Kansas in the Spring of
1988. The Symposium will be part of the annual meeting of the Southwest
and Rocky Mountain Division of the American Association of the Advancement
of Science and will be attended mostly by scientists from the Midwest.
The speaker should be someone with a national reputation
and a historical perspective on the field (PR/AI) and its relation to problems
of interest to scientists. I would appreciate any advice and suggestions as
to qualified speakers who might not be too expensive.
Richard Duda (co-author of the text "Pattern Classification and Scene
Analysis") has been recommended, but I can't find him. I tried SRI,
but he is not there. Does anyone know where he is now?
[Syntelligence; 1000 Hamlin Court; Sunnyvale, CA 94088.
Phone (408) 745-6666. -- KIL]
--------------------------------------------------------------
| Alan Filipski, GTX Corporation, |
| 2501 W. Dunlap, |
| Phoenix, Arizona 85021, USA |
| |
| (602)870-1696 |
| |
| {ihnp4,cbosgd,decvax,hplabs,seismo}!sun!sunburn!gtx!al |
------------------------------
Date: Fri, 29 May 87 09:15 EST
From: SPANGLER%gmr.com@RELAY.CS.NET
Subject: Wanted: Information on current work in Expert Systems for CAD
I am beginning a survey of the current status of work in applying Expert
Systems technology to Computer Aided Design. This survey is being done
for the Knowledge Engineering group at General Motors.
I would greatly appreciate any descriptions of or references to research
in this area, as well as information on what CAD expert systems and
expert system shells are available for purchase.
-- Scott Spangler, spangler@gmr.com
-- Advanced Engineering Staff, GM
------------------------------
Date: Thu, 28 May 87 09:28 EDT
From: Roland Zito-Wolf <RJZ@JASPER.PALLADIAN.COM>
Reply-to: Roland Zito-Wolf <RJZ%JASPER@LIVE-OAK.LCS.MIT.EDU>
Subject: references re (approximate) structure matching
I am looking for references regarding the matching of complex structures
(matching on semantic networks or portions of networks) such as arise in doing
retrieval operations on knowledge-bases so represented.
Since the general mathcing problem is most likely intractable, I'm
looking for approximate or incomplete techniques, such as partial match,
resource-bounded match, matches using preference rules, etc.
References which explore algorithms in detail, and implemented systems,
would be especially useful. For example, does anyone know of a
detailed description of the KRL matcher?
Information on the more general problem of query/data-retrieval from
semantic networks would also be useful.
If there's sufficient interest, I'll post the results to the digest.
Thanks in advance.
Roland J. Zito-wolf
Palladian Software
4 Cambridge Center
Cambridge, Mass 02142
617-661-7171
RJZ%JASPER@LIVE-OAK.LCS.MIT.EDU
------------------------------
Date: 28 May 87 10:13:15 GMT
From: tedrick@ernie.Berkeley.EDU (Tom Tedrick)
Reply-to: tedrick@ernie.Berkeley.EDU (Tom Tedrick)
Subject: Complexity and Philosophy
>Lately I've been chating informally to a philosopher/friend about
>common interests in our work. He was unfamiliar with the concept of the
>TIME TO COMPUTE consequences of facts. Furthermore, the ramifactions of
>intractability (ie. if P != NP is, as we all suspect, true) seemed to
>be new to my friend. The absolute consequences are hard to get across
>to a non-computer scientist; They always say "but computers are getting
>faster all the time...".
>
>I'm digging around for references in AI on these ideas. This isn't my area.
>Can anyone suggest some?
I believe the philosophical consequences of complexity theory are
enormous and that the field is wide open for someone with the
ambition to pursue it.
------------------------------
Date: 29 May 87 15:48:17 GMT
From: tanner@osu-eddie.UUCP (Mike Tanner)
Reply-to: tanner@osu-eddie.UUCP (Mike Tanner)
Subject: Re: Philosophy, Artificial Intelligence and Complexity Theory
We have a paper to appear in this year's IJCAI called "On the
computational complexity of hypothesis assembly", by Allemang, Tanner,
Bylander, and Josephson.
Hypothesis assembly is a part of many problem solving tasks. Eg, in
medical diagnosis the problem is to find a collection of diseases
which are consistent, plausible, and collectively explain the
symptoms.
Our paper analyzes a particular algorithm we've developed for solving
this problem. The algorithm turns out to be polynomial under certain
assumptions. But the problem of hypothesis assembly is shown to be
NP-Complete, by reduction to 3-SAT, when those assumptions are
violated. In particular, if there are hypotheses which are
incompatible with each other it becomes NP-complete. (Another well
known algorithm for the same problem, Reggia's generalized set
covering model, is shown to be NP-complete also, by reduction to
vertex cover.)
The interesting part of the paper is the discussion of what this
means. The bottom line is, people solve problems like this all the
time without apparent exponential increase in effort. We take this to
mean human problem solvers are taking advantage of features of the
domain to properly organize their knowledge and problem solving
strategy so that these complexity issues don't arise.
In the particular case discussed in the paper the problem is the
identification of antibodies in blood prior to giving transfusions.
There exist pairs of antibodies that people simply cannot have both
of, for genetic reasons. So we're in the NP-complete case. But, it
is possible to reason up front about the antibodies and typically rule
out one of each pair of incompatible antibodies (the hypotheses).
Then do the assembly of a complete explanation. This results in
assembly being polynomial.
If you send me your land mail address I can send you a copy of the
paper. Or you can wait for the movie. (Dean Allemang will present it
in Milan.)
-- mike
ARPA: tanner@ohio-state
UUCP: ...!cbosgd!osu-eddie!tanner
------------------------------
Date: Thu, 28 May 87 19:29:27 pdt
From: Ethan Scarl <ethan@BOEING.COM>
Subject: Text Critiquing and Eliza
The "grammar checker" discussions were stirring some old memories which I
finally pinpointed: a 1973 debate (centered on Joe Weizenbaum and Ken
Colby) over whether Eliza should be used for actual therapy.
The heart of the grammar checker issue is whether a computational package of
limited or doubtful competence should be given an authoritative role for some
vulnerable part of our population (young students, or confused adults). What
was most shocking in the Eliza situation (and may be true here as well) was
the quick and profound acceptance of a mechanical confidante by naive users.
Competent and experienced writers have no trouble discarding (or
extrapolating from) Rightwriter's sillier outputs; the problem is with
inexperienced or disadvanted users. Many of us were (are) enraged at this
automated abuse as absurd, irresponsible, and even inhuman," only to be
stopped short by a sobering argument: "if competent human help is scarce,
then isn't this better than nothing?"
The Rightwriter discussion summarizes/coheres rather well: Such systems are
suggestive aids for competent writers and may be useful in tutoring the
incompetent. Such systems will be unsuitable as replacement tutors for some
time to come, but may be worthwhile (in time and effort expended for results
achieved) as aids to be be used by a competent tutor or under the tutor's
supervision.
We are in deep trouble if there are no competent humans available to help
others who need it. But the secondary question: "Is sitting in front of a
CRT better than sitting in a closet?" can at least be tested empirically.
In the Rightwriter case, I would expect that most students will quickly
understand the the program's analytic limitations after they are pointed out
by a teacher. However, the human teacher's perspective is essential.
------------------------------
Date: Thu, 28 May 87 09:35:48 pdt
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Re: Humor - Artificial Life: actually artificial stupidity
In article <23@aimmi.UUCP> Gilbert Cockton writes:
>
>Nah - that's not all the way. We also need
>
> 3. Artificial reasoning.
>
>This is when people who nothing about epistemology (philosophical and
>anthropological/sociologial aspects) or psychology lock themselves away on
>an AI project and make things up about how people reason. I may be
>oldfashioned, but I do miss empirical substance and conceptual coherence
>:-) :-):-) :-) :-):-) :-) :-):-) :-) :-):-) :-) :-):-) :-) :-):-) :-) :-):-)
Permit me to add what I mentioned to John Pierce when he was a Chief
Engineer over me:
4. Artificial stupidity
And I got the comment about there being enough natural stupidity in the
world.
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
Date: 28 May 87 05:46:28 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
Anders Weinstein of BBN wrote:
> a point that I thought was clearly made in our earlier
> discussion of the A/D distinction: loss of information, i.e.
> non-invertibility, is neither a necessary nor sufficient condition for
> analog to digital transformation.
The only point that seems to have been clearly made in the sizable discussion
of the A/D distinction on the Net last year (to my mind, at least) was that no
A/D distinction could be agreed upon that would meet the needs and
interests of all of the serious proponents and that perhaps there was
an element of incoherence in all but the most technical and restricted
of signal-analytic candidates.
In the discussion to which you refer above (a 3-level bottom-up model
for grounding symbolic representations in nonsymbolic -- iconic and
categorical -- representions) the issue was not the A/D
transformation but A/A transformations: isomorphic copies of the
sensory surfaces. These are the iconic representations. So whereas
physical invertibility may not have been more successful than any of
the other candidates in mapping out a universally acceptable criterion
for the A/D distinction, it is not clear that it can be faulted as a
criterion for physical isomorphism.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 29 May 87 00:46:47 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem
Replying to my claim that
>> ...loss of information, i.e.
>> non-invertibility, is neither a necessary nor sufficient condition for
>> analog to digital transformation.
in article <786@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
>The only point that seems to have been clearly made in the sizable discussion
>of the A/D distinction on the Net last year (to my mind, at least) was that no
>A/D distinction could be agreed upon ...
>
>In the discussion to which you refer above ... the issue was not the A/D
>transformation but A/A transformations: isomorphic copies of the
>sensory surfaces. These are the iconic representations. So whereas
>physical invertibility may not have been more successful than any of
>the other candidates in mapping out a universally acceptable criterion
>for the A/D distinction, it is not clear that it can be faulted as a
>criterion for physical isomorphism.
Well the point is just the same for the A/A or "physically isomorphic"
transformations you describe. Although the earlier discussion admittedly did
not yield a positive result, I continue to believe that it was at least
established that invertibility is a non-starter: invertibility has
essentially *nothing* to do with the difference between analog and digital
representation according to anybody's intuitive use of the terms.
The reason I think this is so clear is that for any one of the possible
transformation types -- A/D, A/A, D/A, or D/D -- one can find paradigmatic
examples in which invertibility either does or does not obtain. A blurry
image is uncontroversially an analog or "iconic" representation, yet it is
non-invertible; a digital recording of sound in the audible range is surely
an A/D transformation, yet it is completely invertible, etc. All the
invertibility or non-invertibility of a transformation indicates is whether
or not the transformation preserves or loses information in the technical
sense. But loss of information is of course possible (and not necessary) in
any of the 4 cases.
I admit I don't know what the qualifier means in your criterion of "physical
invertibility"; perhaps this alters the case.
Anders Weinstein
------------------------------
Date: 29 May 87 15:27:31 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
aweinste@Diamond.BBN.COM (Anders Weinstein) of BBN Laboratories, Inc.,
Cambridge, MA writes:
> invertibility has essentially *nothing* to do with the difference
> between analog and digital representation according to anybody's
> intuitive use of the terms... A blurry image is uncontroversially
> an analog or "iconic" representation, yet it is non-invertible;
> a digital recording of sound in the audible range is surely an A/D
> transformation, yet it is completely invertible. [I]nvertibility...
> [only] indicates whether... the transformation preserves or loses
> information in the technical sense. But loss of information is...
> possible in any of the 4 cases... A/D, A/A, D/A, D/D...
> I admit I don't know what the qualifier means in your criterion
> of "physical invertibility"; perhaps this alters the case.
I admit that the physical-invertibility criterion is controversial and
in the end may prove to be unsatisfactory in delimiting a counterpart
of the technical A/D distinction that will be useful in formulating
models of internal representation in cognitive science. The underlying
idea is this:
There are two stages of A/D even in the technical sense. Signal
quantization (making a continuous signal discrete) and symbolization
(assigning names and addresses to the discrete "chunks"). Unless the
original signal is already discrete, the quantization phase involves a
loss of information. Some regions of input variation will not be retrievable
from the quantized image. The transformation is many-to-fewer instead
of one-to-one. A many-to-few mapping cannot be inverted so as to
recover the entire original signal.
Now I conjecture that it is this physical invertibility -- the possibility
of recovering all the original information -- that may be critical in
cognitive representations. I agree that there may be information loss in
A/A transformations (e.g., smoothing, blurring or loss of some
dimensions of variation), but then the image is simply *not analog in
the properties that have been lost*! It is only an analog of what it
preserves, not what it fails to preserve.
A strong motivation for giving invertibility a central role in
cognitive representations has to do with the second stage of A/D
conversion: symbolization. The "symbol grounding problem" that has
been under discussion here concerns the fact that symbol systems
depend for their "meanings" on only one of two possibilities: One is
an interpretation supplied by human users -- "`Squiggle' means `animal' and
`Squoggle' means `has four legs'" -- and the other is a physical, causal
connection with the objects to which the symbols refer. The first
source of "meaning" is not suitable for cognitive modeling, for
obvious reasons (the meaning must be intrinsic and self-contained, not
dependent on human mental mediation). The second has a surprising
consequence, one that is either valid and instructive about cognitive
representations (as I tentatively believe it is), or else a symptom of
the wrong-headedness of this approach to the grounding problem, and
the inadequacy of the invertibility criterion.
The surprising consequence is that a "dedicated system" -- one that is
hard-wired to its transducers and effectors (and hence their
interactions with objects in the world) may be significantly different
from the very *same* system as an isolated symbol-manipulating module,
cut off from its peripherals -- different in certain respects that could be
critical to cognitive modeling (and cognitive modeling only). The dedicated
system can be regarded as "analog" in the input signal properties that are
physically recoverable, even if there have been (dedicated) "digital" stages
of processing in between. This would only be true of dedicated systems, and
would cease to be true as soon as you severed their physical connection to
their peripherals.
This physical invertibility criterion would be of no interest whatever
to ordinary technical signal processing work in engineering. (It may
even be a strategic error to keep using the engineering "A/D"
terminology for what might only bear a metaphorical relation to it.)
The potential relevance of the physical invertibility criterion
would only be to cognitive modeling, especially in the constrain that
a grounded symbol system must be *nonmodular* -- i.e., it must be hybrid
symbolic/nonsymbolic.
The reason I have hypothesized that symbolic representations in cognition
must be grounded nonmodularly in nonsymbolic representations (iconic and
categorical ones) is based in part on the conjecture that the physical
invertibility of input information in a dedicated system may play a crucial
role in successful cognitive modeling (as described in the book under
discussion: "Categorical Perception: The Groundwork of Cognition,"
Cambridge University Press 1987). Of course, selective *noninvertibility*
-- as in categorizing by ignoring some differences and not others --
plays an equally crucial complementary role.
The reason the invertibility must be physical rather than merely
formal or conceptual is to make sure the system is grounded rather
than hanging by a skyhook from people's mental interpretations.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
End of AIList Digest
********************
∂01-Jun-87 1336 LAWS@Stripe.SRI.Com AIList Digest V5 #134
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 1 Jun 87 13:36:24 PDT
Date: Mon 1 Jun 1987 09:27-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #134
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 1 Jun 1987 Volume 5 : Issue 134
Today's Topics:
Seminars - Knowledge-Based Software Development Tools (SRI) &
The Inverse Method (MCC) &
So What if Macsyma is an Expert System? (TI),
Conference - AI and SEA &
CFP: CSCSI-88 (Canadian AI Conference) &
HICSS-21, Rapid Prototyping &
Theoretical Aspects of Reasoning about Knowledge
----------------------------------------------------------------------
Date: Wed, 27 May 87 16:49:56 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Knowledge-Based Software Development Tools (SRI)
KNOWLEDGE-BASED SOFTWARE DEVELOPMENT TOOLS
Douglas R. Smith (SMITH@KESTREL.ARPA)
Kestrel Institute
11:00 AM, MONDAY, June 1
SRI International, Building E, Room EJ228
We describe some of the experimental knowledge-based software
development tools under development at Kestrel Institute. In
particular, we discuss systems for automatically performing algorithm
design, deduction, optimization (finite differencing), data structure
selection, and performance estimation. We show how these systems
could cooperate in supporting the transformation of a formal
specification of a schedule optimization problem into efficient code.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Thu 21 May 87 15:44:50-CDT
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - The Inverse Method (MCC)
Vladimir Lifschitz
Stanford University
May 27 - 10:00pm
ACA Conference Room 2.806
"What is the Inverse Method?"
A large part of work on proof procedures for predicate logic done in
the Soviet Union in the sixties and seventies was based on the
"inverse method", proposed by Sergey Maslov. This important work has
not been duly appreciated outside the small circle of Maslov's
associates. I will review the basic ideas of the method in the form
which stresses its connection with resolution.
May 27 - 10:00
ACA Conference Room
------------------------------
Date: Thu, 28 May 1987 12:37 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Seminar - So What if Macsyma is an Expert System? (TI)
Texas Instruments Computer Science Center Lecture Series
SO WHAT IF MACSYMA IS AN EXPERT SYSTEM?
Prof. David Y. Y. Yun
Southern Methodist University
10:00 am, Friday, 5 June 1987
North Building Cafeteria Room C-4
ABSTRACT
The real question is how MACSYMA, or any other symbolic math system,
can be used to help scientists and engineers. Existing symbolic math
systems are too narrowly focused and too difficult to integrate with
other computing capabilities. Such limitations keep these systems at
the level of casual tools for scientists and engineers. Technologies
in symbolic computing and system support have progressed sufficiently
far for us to envision an integrated working environment that can not
only provide expert performance on special problems through a large
repository of knowledge bases, but also cater to individual needs by
providing guidance and consultation on these available capabilities.
We will first survey the current state of symbolic math systems by
presenting sample capabilities. Then assess available techniques that
will enable us to achieve such a goal.
------------------------------
Date: 22 May 1987 15:50:38 EDT
From: Herve.Lambert@PS2.CS.CMU.EDU
Subject: Conference - AI and SEA
ARTIFICIAL INTELLIGENCE AND SEA
18 - 19 Juin 1987, Marseille (France)
________________
Organised by: Institut International de Robotique et d'Intelligence
Artificielle de Marseille, 2 rue Henri Barbusse, 13241 Marseille cedex 1
Registration Information: Viviane Bernadac, IIRIAM,
tel (33) 91 91 36 72
telex 440 860
telefax (33) 91 91 70 24
Address: IIRIAM
2 rue Henri Barbusse
13241 Marseille cedex 1
France
PROGRAM OF THE CONFERENCE
Thursday 18th June 1987:
8h30 - 9h00 Members reception
9h00 - 9h30 Welcome speech
Jean-Francois Le Maitre, IIRIAM
Session 1, chairman: Vieillard Baron, IRCN
9h30 - 10h00 Jean-Claude Rault, EC2, France
State of the Art of expert systems applications
10h00 - 10h30 M.F. Mac Gowan, Cooperative Institute for Marine and
Atmospheric Studies, Miami,
USA Catcurv1, a fishery management expert system module
10h30 - 11h00 Break
Session 2, chairman: Jean-Claude Rault, EC2
11h00 - 11h30 M. Alquier, ENSEEIHT, France
Artificial Intelligence and Navigation in sail boat races.
11h30 - 12h00 J. Schoellkopf, S2O Developpement, France
PNAO, an expert system for offshore positionning and navigation
12h00 - 12h30 J. Fox, University of Hawaii, USA
Laser aided machine vision in the ocean
12h30 - 14h00 Lunch
Session 3, chairman: Georges Thebaud, Comite Central des Armateurs de France
14h00 - 14h30 J.P. Poitou, CNRS, France
The expert and the system, consequence for cognitive analysis:
example in naval ship building
14h30 - 15h00 M. Daniel, J.M. Kobus, C. Sayettat, ENSAM, France
Artificial Intelligence Techniques in CAD for fishing boats
15h00 - 15h30 B. Baret, M. Cayrol, J. Laforgue, IRCN, France
Use of Artificial Intelligence in CAD: CAD evolution for the Steel
Hull Design in Shipbuilding Industry
15h30 - 16h00 Break
Session 4, chairman: Pierre Orsero, IMT
16h00 - 16h30 J.M. Andre, Laboratoire de Marcoussis, France
CADOO, an expert system in spatial accomodations.
16h30 - 17h00 B. Neveu, INRIA, France
SMECI, an expert system for breakwater conception
18h00 - 19h30 Cocktail at the City Hall of Marseilles
Friday 19th June 1987
Session 5, chairman: Hubert Du Mesnil, Port Autonome de Marseille, France
9h30 - 10h00 R Baleydier, Port Autonome de Marseille, France
Expert System of maintenance diagnostic fro handling container
machine
10h00 - 10h30 D. Peguin, CEFI, France
Expert System for long term harbour traffic prediction
10h30 - 11h00 Break
Session 6, chairman: J.P. Fail, IFP
11h00 - 11h30 B. Hamidi, R. Tremollieres, IAE France
Information and decision expert system in harbour management
11h30 - 12h00 M. Bennett, Cambridge Consultants LTD, UK
Machine Intelligence and the underwater vehicle (ROV'S)
12h00 - 12h30 D. Lane, Heriot Watt University, Scotland
The rational Cell: a modular KBS Architecture for the integration
of diverse information processing operations. Applications in sector
scan imagery.
12h30 - 14h00 Lunch
Session 7, chairman: Michel Brechet, B+ Developpement, France
14h00 - 14h30 J.F. Strutt, Cranfield Institute of Technology, UK
EXPRES, a rule-based pipeline design expert system
14h30 - 15h00 R. Nossum, Computas Expert Systems, Norway
CPS/IF, an intelligent front-end to a Computer mapping package
15h00 - 15h30 M. Blaquiere, Centre de Recherches, CFP Total, France
Simulation of processes for risk predictions
15h30 - 16h00 Break
Session 8, chairman: C. Roger
16h00 - 16h30 J.P. Quilleveyre, Elf Aquitaine, France
SERSO, an expert system for offshore platform reanalysis
16h30 - 17h00 S. Zeuthen, Norvegian Institute of technology, Norway
STABRIG and PROLIX: knowledge-based systems for marine operations
(semi-subs stability problems and mooring systems).
------------------------------
Date: Wed, 27 May 87 12:06:19 pdt
From: Bob Woodham <woodham%ubc.csnet@RELAY.CS.NET>
Subject: Conference - CFP: CSCSI-88 (Canadian AI Conference)
Please post the following to AIList-Digest:
C A L L F O R P A P E R S
Canadian Artificial Intelligence Conference
C S C S I - 8 8
Edmonton Convention Centre
Edmonton, Alberta
June 6 - 10, 1988
CSCSI-88 is the seventh biennial conference on Artificial Intelligence
sponsored by the Canadian Society for Computational Studies of
Intelligence/la Societe canadienne pour l'etude de l'intelligence par
ordinateur (CSCSI/SCEIO). The 1988 conference will be held in Edmonton in
conjunction with Graphics Interface '88 and Vision Interface '88.
Contributions are requested describing original research results, either
theoretical or applied, in all areas of Artificial Intelligence research.
The following areas are especially of interest:
Knowledge Representation Robotics
Perception (Vision, Touch, Speech) Knowledge Acquisition and Maintenance
Natural Language Understanding Cognitive Modelling
Expert Systems and Applications Social Aspects of AI
Reasoning (Formal, Qualitative) Architectures and Languages
Learning Applications
All submissions will be refereed by a Program Committee. Authors are
requested to prepare full papers of no more than 5000 words in length and to
specify in which area they wish their papers to be reviewed. All papers
must contain a concise statement of the original contribution made to
Artificial Intelligence research, with proper reference to the relevant
literature. At the time of submission, authors must indicate if the paper
has appeared, or has been submitted, elsewhere. Failure to do so will lead
to automatic rejection. Figures and illustrations should be professionally
drawn. Photographs, if included, should be of publication quality. All
accepted papers will be published in the conference proceedings. As a
condition of acceptance, the author, or one of the co-authors, will be
required to present the paper at the conference.
The international journal, Artificial Intelligence, has offered a best paper
prize for the conference. Selection of a best paper will be done by the
Program Committee.
Three (3) copies of the paper due: October 31, 1987.
Notification of acceptance or rejection: February 1, 1988.
Camera ready copy due: March 28, 1988.
Send papers and other correspondence to:
Nick Cercone Bob Woodham
School of Computing Science Department of Computer Science
Simon Fraser University University of British Columbia
Burnaby, B.C. V5A 1S6 Vancouver, B.C. V6T 1W5
CANADA CANADA
(604) 291-4277 (604) 228-4368
nick@lccr.sfu.CDN woodham@vision.ubc.CDN
sfulccr!nick@ubc-vision.UUCP woodham@ubc-vision.UUCP
woodham@ubc.CSNET
------------------------------
Date: Fri, 29 May 1987 20:33 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Conference - HICSS-21, Rapid Prototyping
CALL FOR PAPERS AND REFEREES
"Rapid Prototyping of Large-Scale Software" Mini-Track
HAWAII INTERNATIONAL CONFERENCE on SYSTEM SCIENCES (HICSS-21)
SOFTWARE TRACK
January 5-8, 1988
Murat M. Tanik
Southern Methodist University
Computer Science Department
Dallas, TX 75275-0122
(214) 692-2854
CSNET: tanik@smu.uucp
Mini-Track Concept:
This mini-track involves the investigation of the ways of rapid
development of large-scale software prototypes. Software developers
are constantly faced with both a changing problem definition and a
changing solution environment. This results in costly modification or
replacement of software. Present systems do not address this problem
adequately. A partial solution lies in the rapid development of
software. The resulting rapid feedback could be used to effectively
detect and resolve errors and inconsistencies in the problem
definition.
Prototyping provides early execution of software capabilities, to let
end-users see the operational results of a system specification so
that they can identify de ficiencies before the system is hardened
into production code. To be effective, a prototype must be rapidly
constructed and modified, so that the effort required to do the
specification development and evaluation does not constraint system
capabilities.
Examples of suitable topics include:
. The role of knowledge engineering in prototyping enviroments.
. Rapid prototyping of real-time systems.
. Rapid prototyping paradigms.
. Graphics oriented user interfaces for prototyping systems.
. Domain specific prototyping systems.
. Stimulation/simulation environments for prototypes of real-time systems.
. Support tools for prototyping environments.
. Intelligent documentation/help systems for prototypes.
. Reusability in prototyping environments.
. Prototyping vs. simulation.
The manuscript should be directed towards the research and development
community and not the management community. Manuscripts should be
22-26 typewritten, double-spaced pages in length. Please do not send
submissions that are significantly shorter or longer than this. The
manuscript must contain original results and should not be submitted
elsewhere while it is being evaluated for acceptance to HICSS-21.
Manuscripts that have already appeared in publication will not be
considered for this conference.
Please send six copies of your manuscript to me before July 20, 1987.
Each paper should have a title page which includes the title of the
paper, the full name of its author(s), affiliation(s), complete
physical and e-mail address(es), and telephone number(s). Each
manuscript is put into a rigorous refereeing process.
. Notifications of accepted papers will be mailed to the author on or
before September 7, 1987.
. Final papers in camera-ready form will be due by October 19, 1987.
Your participation is invited as author, referee or both. Please
contact me by e-mail or otherwise.
------------------------------
Date: 20 April 87 16:03-PDT
From: VARDI%ALMVMA.BITNET@WISCVM.WISC.EDU
Subject: Conference - Theoretical Aspects of Reasoning about Knowledge
Call for Papers
The Second Conference on
THEORETICAL ASPECTS OF REASONING ABOUT KNOWLEDGE
March 6-9, 1988, Monterey, California
The 2nd Conference on Theoretical Aspects of Reasoning about
Knowledge, sponsored by the International Business Machines
Corporation and the American Association for Artificial
Intelligence, will be held March 6-9, 1988, at the Asilomar
Conference Center in Monterey, California. While traditionally
research in this area was mainly done by philosophers and
linguists, reasoning about knowledge has been shown recently to
be of great relevance to computer science and economics. The aim
of the conference is to bring together researchers from these
various disciplines with the intent of furthering our theoretical
understanding of reasoning about knowledge.
Some suggested, although not exclusive, topics of interest are:
Semantic models for knowledge and belief
Resource-bounded reasoning
Minimal knowledge proof systems
Analyzing distributed systems via knowledge
Knowledge acquisition and learning
Knowledge and commonsense reasoning
Knowledge, planning, and action
Knowledge in economic models
You are invited to submit ten copies of a detailed abstract (not
a complete paper) to the program chair:
Moshe Y. Vardi
IBM Research
Almaden Research Center K53-802
650 Harry Rd.
San Jose, CA 95120-6099, USA
Telephone: (408) 927-1784
Electronic address: vardi@ibm.com, vardi@almvma.bitnet
Submissions will be evaluated on the basis of significance,
originality, and overall quality. Each abstract should 1)
contain enough information to enable the program committee to
identify the main contribution of the work; 2) explain the
importance of the work - its novelty and its practical or
theoretical implications; and 3) include comparisons with and
references to relevant literature. Abstracts should be no longer
than ten double-spaced pages.
Program Committee:
J. Barwise (Stanford University)
P. van Emde Boas (University of Amsterdam)
H. Kamp (University of Texas at Austin)
K. Konolige (SRI International)
Y. Moses (Weizmann Institute of Science)
S. Rosenschein (SRI International)
T. Tan (University of Chicago)
M. Vardi (IBM Almaden Research Center)
The deadline for submission of abstracts is August 31, 1987.
Authors will be notified of acceptance by November 1, 1987
(authors who supply an electronic address might be notified
earlier). The accepted papers will be due by December 15, 1987.
Proceedings will be distributed at the conference, and will be
subsequently available for purchase through the publisher.
We hope to allow enough time between the talks for private
discussions and small group meetings. In order to ensure that
the conference remains relatively small, attendance will be
limited to invited participants and authors of accepted papers.
Support for the conference has been received from IBM and AAAI
for partial subsidy of participants' expenses; applications for
further support are pending.
------------------------------
End of AIList Digest
********************
∂01-Jun-87 2010 LAWS@Stripe.SRI.Com AIList Digest V5 #135
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 1 Jun 87 20:05:36 PDT
Date: Mon 1 Jun 1987 17:33-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #135
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 2 Jun 1987 Volume 5 : Issue 135
Today's Topics:
Bindings - NL-KR the List,
Theory - Philosophy and Computational Complexity,
Applications - Computer Grading and the Law & Solid Geometry &
The Synthesizer Generator
----------------------------------------------------------------------
Date: Fri, 29 May 87 17:11 EDT
From: Brad Miller <miller@ACORN.CS.ROCHESTER.EDU>
Subject: NL-KR the list...
Is now available on USENET in group comp.ai.nlang-know-rep as part of the
massive USENET project to have all arpa lists forwarded to their own groups.
If you can receive this group and would prefer to read the digests there,
please send a message to nl-kr-request@cs.rochester.edu so I can remove you
from the separate mailing list.
Brad Miller
nl-kr moderator
nl-kr-request@cs.rochester.edu
[I have been forwarding the recent comp.ai linguistics discussion
to the NL-KR list (instead of to the Arpanet AIList digest). Now
that NL-KR is available via Usenet, I would suggest that the discussion
move there. In that way the Usenet participants will not be missing
out on the cogent repies of the NL-KR linguists. I assume that your
submissions should go to nl-kr@cs.rochester.edu and that you can then
read all of the replies on comp.ai.nlang-know-rep. -- KIL]
------------------------------
Date: Mon, 1 Jun 87 09:18:28 EDT
From: "William J. Rapaport" <rapaport%buffalo.csnet@RELAY.CS.NET>
Subject: philosophy and computational complexity
A good _philosophical_ reference is:
Christopher Cherniak, "Computational Complexity and the Universal Acceptance
of Logic," _Journal of Philosophy_ 81 (1984) 739-758.
William J. Rapaport
Assistant Professor
Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260
(716) 636-3193, 3180
uucp: ..!{allegra,decvax,watmath,rocksanne}!sunybcs!rapaport
csnet: rapaport@buffalo.csnet
bitnet: rapaport@sunybcs.bitnet
------------------------------
Date: Mon 1 Jun 87 13:31:58-PDT
From: PAT <HAYES@SPAR-20.ARPA>
Subject: Re: Philosophy, AI, and Complexity Theory
In reply to Ray Lister: the best overview is probably Hector Levesques
Computers and Thought lecture delivered at the last IJCAI.
Pat Hayes
------------------------------
Date: Sun, 29 Mar 87 03:15:44 cst
From: Laurence Leff <leff%smu.csnet@RELAY.CS.NET>
Subject: Computer Grading and the Law
I propose the attached comment to Mr. Craig's Volume 5 #87 submission
to ailist. In order to allow Mr. Craig an opportunity to either
ammend his statement peacefully or to rebut my criticism, I request
that Dr. Laws hold this until Mr. Craig has had an opportunity to
respond.
[He has apparently chosen not to, and Laurence has now asked
me to forward this to the list. -- KIL]
tektronix!videovax!dmc, Donald Craig, wrote in Volume 5, number 87
about his concern of student's essays being graded by machine.
He also states "In law I have the right to be judged by a jury
of my peers." drawing an analogy between a jury trial and a court case.
The first concern is unfounded and the second statement is an
overgeneralizaton.
In a criminal case involving over six months of imprisonment you have
the right to a jury trial. However, in criminal cases involving small
penalties, the states may pass laws allowing convictions without
a jury. (Source: the Criminal Procedure issue of Georgetown Law Review.)
In a suit in equity, i. e. someone wants an injunction against you or
a declaratory action, you do not have the right to a jury trial.
In administrative cases, you do not have the right to a jury trial.
(Source: "Administrative Law" by Davis, another law book)
However, there must be
"notice" and "hearing" if "life, liberty or property" is to be denied.
"Property" has been interpreted by the courts to include such things
as food stamp benefits (722 F 2d 933), driver licenses and high school
diplomas (Debra P. v. Turlington 644 F 2d 397).
After addressing the overbroad statement, we now address the substantive
concern: can computers grade essays without some human in the loop.
We find that legally, they cannot and furthermore we see the importance
of an "explanation facility", a subject that has come up recently in
AILIST.
The issue of computers making judgements came up in Foggs versus
Block, 722 F2d 933 (1983). In this case, the Commissioner
reduced people's Food Stamp allottment due to a change
in Statute. A computer program reduced the benefits and the card
so announcing gave information regarding the required hearing.
However, this notice was considered inadequate because insufficient
information was provided to determine if an error was made.
Thus any expert system making decisions impinging upon what the courts
view as "property" must provide adequate explanation and must also
provide some form of hearing procedure. Furthermore, some explanation
of the hearing procedure must be provided so that people could take
advantage of it.
Although, there would be no legal problem with a first pass determination
of the grade on a student's essay by computer program, it is clear that
some human must be available to hear a student's objections and furthermore,
that computer program must in some way indicate how the grade was determined.
In the case you mentioned, a first pass grading could be done by
computer as long as there was some procedure for complaints to be made
to a human being with an appropriate hearing.
(Due to the concepts
of ripeness, it may be necessary that the grade for the course/quarter
etc. was recorded since the error made by the computer on one essay
may not be sufficient to change the final recorded grade. However, if the
erroneous grading occurred often enough or was serious enough,
the student would eventually have a complaint that could be heard.)
------------------------------
Date: Sun, 31 May 1987 14:56 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Re: Solid Geometry
[...]
Here are some references on converting from 2-D views to constructive
solid geometry references.
The difficulty is that
simply going from three views along orthogonal axis to a 3-D
physical description
of the problem is ambiguous. That is true, even in the presence of
the "hidden line" information that would not be available from a camera.
In fact, for a given wire-frame (set of edges of the object), there are
many possible corresponding solid objects.
%A H. Yoshiura
%A Kikuo Fujimura
%A T. L. Kunii
%T Top-Down Construction of 3-D Mechanical Object Shapes from
Engineering Drawings
%J COMPUTER
%D December 1984
%P 32-40
%K AIME
%W 14D
%A M. Idesawa
%T A System to Generate a Solid Figure from Three View
%J BJSME
%V 16
%P 216-225
%N 92
%D FEB 1973
%K CADCAM
%W 05J
%A M. A. Wesley
%A G. Markowsky
%T Fleshing OUt Projections
%J IBM J. Research and Development
%V 25
%N 6
%D NOV 1981
As mentioned in AILIST, there are two main methods of modeling objects
in CAD/CAM: boundary representations and constructive solid geometry
systems. CSG based systems provide some mechanism for converting
to boundary representation as this is needed for such functions as
display. This can be done in worst case O(N ** 3) time for the two-D case
where N is the number of two dimensional objects and O(N ** 4)
for three-D. However, the average case is linear!
For an extremely clear discussion of these issues, see Tilove's
thesis which is TM-38 from the PADL group.
Going back from boundary representation to CSG is fairly straightforward.
Looking at the problems of conversion from a canonical form perspective
or cases where the object is represented parametrically is discussed in my
papers.
The argument that CSG systems cannot be put on micros is bogus.
First of all Cubicomp has been selling a commercial CSG based system
for micros for years. Second of all the original research versions of
CSG done by the PADL group was done on an 11/40 containing 28K 16 bit words
which is much more limited than an IBM-PC.
------------------------------
Date: Fri, 22 May 87 08:35:19 PDT
From: Tim Teitelbaum
<synrels%gvax.cs.cornell.edu@Forsythe.Stanford.EDU>
Subject: The Synthesizer Generator
[Forwarded from the Stanford bboard by Laws@STRIPE.SRI.COM.]
Introducing the Synthesizer Generator:
a tool for creating editors
Thomas Reps Tim Teitelbaum
Computer Science Department Computer Science Department
University of Wisconsin Cornell University
Madison, WI 53706 Ithaca, NY 14853
1. What is the Synthesizer Generator
The Synthesizer Generator is a tool for creating editing
environments for complex objects. The editor designer
prepares a specification that includes rules defining a
language's abstract syntax, context-sensitive relationships,
display format, and concrete input syntax. From this
specification, the Generator creates a full-screen editor
for manipulating objects according to these rules.
2. Who might want to use the Synthesizer Generator?
The Synthesizer Generator can be used by researchers who
need to construct an editing environment for objects that
can be described by a grammar. The Generator has been suc-
cessfully used to create a Pascal editor with full static
semantic checking, editors for C and Fortran 77, and many
editors for program verification and proof editing. It has
also been used to construct WYSIWYG editors for right-
justified text and mathematical formulae.
Using the Synthesizer Generator is much faster than
producing a hand-crafted editor, just as using a compiler
compiler is faster than writing a compiler. The Generator
maintains abstract representations for objects and incor-
porates algorithms for propagating context-sensitive infor-
mation through the objects being manipulated. It also pro-
vides the many mundane features that any editor must have,
such as binding of key sequences to generic commands, creat-
ing and manipulating buffers for edited objects, multiple
windows, etc., that would otherwise distract the editor
designer from his primary interest. The relative ease of
generating editors makes the Generator ideal for prototype
development and experimental use.
3. Are there serious applications beyond program editors?
Applications of the Synthesizer Generator are not limited to
editors for programming languages. At Cornell the Generator
is being used to implement environments for formal reasoning
that allow users to interactively construct proofs. Proofs
are represented as trees whose nodes correspond to inference
rules, while proof correctness is represented by context-
sensitive constraints between the nodes of the tree. Two
approaches to building such environments have been investi-
gated: in one the environment designer hand-tailors a Syn-
thesizer specification for a particular formal system [Reps
and Alpern]; in the other, the Synthesizer Generator is used
to implement an environment for defining formal systems that
allows a user to interactively define a particular logic and
to conduct formal reasoning in that logic.
[Reps and Alpern] Reps. T. and Alpern, B. "Interactive Proof
Checking," Eleventh POPL, 1984, 36-45.
4. How does it work?
The Synthesizer Generator is particularly well suited for
creating editors that enforce the syntax and static seman-
tics of objects that can be described in a particular
language. Each object to be edited is represented as a con-
sistently attributed derivation tree. When these objects
are modified, some of the attributes may no longer have con-
sistent values; incremental analysis is performed by updat-
ing attribute values throughout the tree in response to
modifications. If an editing operation modifies an object
in such a way that context-dependent constraints are
violated, the attributes that indicate satisfaction of con-
straints will receive new values; thus, these attributes can
be used to annotate the display in order to provide the user
with feedback about the existence of errors.
Editor specifications are written in the Synthesizer
Specification Language (SSL), which is based on the concepts
of a term algebra and an attribute grammar, although certain
features are tailored to the application domain of
language-based editors.
The Synthesizer Generator has two components:
a) a translator that takes an SSL specification as input,
and produces grammar tables as output, and
b) an editor kernel that consists of an attributed-tree
data-type and a driver for interactively manipulating
attributed trees; the kernel takes input from the key-
board and executes appropriate operations on the
current tree.
A shell program handles the details of invoking the transla-
tor and producing a language-based editor from the resulting
tables.
5. How to get a copy of the Generator
The Generator is written in C and runs under Berkeley UNIX
on VAX computers, Sun workstations (using SunWindows), and
the IBM PC/RT. Porting to other versions of UNIX is
straightforward. We are in the process of porting the Gen-
erator to XWindows. Editors generated with the Synthesizer
Generator will work on any crt terminal described in the
UNIX termcap database. A keyboard description file speci-
fies the layout of special function keys used by the gen-
erated editors. The distribution, which is available for
$200.00, consists of:
a) Source and object code for the SSL translator and edi-
tor kernel.
b) A collection of demonstration editors and their specif-
ications, including a Pascal editor with full static-
semantic checking and several proof editors.
c) A copy of The Synthesizer Generator Reference Manual.
6. References
The Synthesizer Specification Language is described in:
Reps, T. and Teitelbaum, T. The Synthesizer Genera-
tor. In Proceedings of the ACM SIGSOFT/SIGPLAN
Software Engineering Symposium on Practical Software
Development Environments, Pittsburgh, Penn., Apr.
23-25, 1984. (Appeared as joint issue: SIGPLAN No-
tices (ACM) 19, 5 (May 1984), and Soft. Eng. Notes
(ACM) 9, 3 (May 1984), 42-48).
A complete manual is available:
Reps, T. and Teitelbaum, T. The Synthesizer Genera-
tor Reference Manual. Department of Computer Sci-
ence, Cornell University, Ithaca, NY, 14853, August,
1985.
A description of the theory underlying the Generator may be
found in:
Reps, Thomas W. Generating Language-Based Environ-
ments, The MIT Press, 1984.
To request further information about acquiring a copy of the
system, please respond with the name of your organization and
your postal address to
ARPA: synrels@gvax.cs.cornell.edu
UUCP: {rochester, allegra}!cornell!synrels
Bitnet: synrels@crnlcs.Bitnet
USMail: Prof. Tim Teitelbaum
Synthesizer Generator Distribution
Dep't of Computer Science, Upson Hall
Cornell University
Ithaca, NY 14853
USA
We will send you the terms of the distribution and copies
of the distribution agreement.
------------------------------
End of AIList Digest
********************
∂01-Jun-87 2316 LAWS@Stripe.SRI.Com AIList Digest V5 #136
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 1 Jun 87 23:15:49 PDT
Date: Mon 1 Jun 1987 20:31-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #136
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 2 Jun 1987 Volume 5 : Issue 136
Today's Topics:
Bibliography - Leff ai.bib50TR
----------------------------------------------------------------------
Date: Sun, 31 May 1987 14:56 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: ai.bib50TR
%A Ganesh C. Gopalakrishnan
%A Mandayam K. Srivas
%A David R. Smith
%T Hierarchical Design of VLSI Systems Using Algebraic Specifications and
Temporal Logic: On Automatic Synthesis of Controllers for VLSI Modules
From Their Functional Specifications
%I Department of Computer Science, SUNY at Stony Brook
%D Jan 1986
%K AA04 AI11
%R TR 86/01
%A Sanjay Manchanda
%A Suzanne Dietrich
%T Storing and Accessing Relations on Disk in a Prolog Database System
%I Department of Computer Science, SUNY at Stony Brook
%D JAN 1986
%R TR 86/08
%K AA09 T02
%A Michael Kifer
%A R. Lozinskii
%T Framework for an Efficient Implementation of Deductive Databases
%I Department of Computer Science, SUNY at Stony Brook
%D FEB 1986
%R TR 86/04
%K AA09
%A Saumya K. Debray
%T Mode Inference and Abstract Interpretation in Logic Programs
%I Department of Computer Science, SUNY at Stony Brook
%D FEB 1986
%R TR 86/05
%K AI11
%A Michael Kifer
%A E. Lozinskii
%T Can We Implement Logic as a Database System
%I Department of Computer Science, SUNY at Stony Brook
%D FEB 1986
%R TR 86/06
%K AI11 AA09
%A Ganesh C. Goplakrishnan
%A David Smith
%A Mandayam K. Srivas
%T From Algebraic Specifications to Correct VLSI Circuits
%I Department of Computer Science, SUNY at Stony Brook
%D JUN 1986
%R 86/13
%K AA04
%A Saumya K. Debray
%A Prateek Mishra
%T Denotational and Operational Semantics for Prolog
%I Department of Computer Science, SUNY at Stony Brook
%D JUL 1986
%R 86/15
%K T02 AA08
%A Sanjay Manchanda
%A David Scott Warren
%T Toward a Logical Theory of Database Updates
%I Department of Computer Science, SUNY at Stony Brook
%D JUL 1986
%R 86/19
%K AI11 AA09
%A R. Ramesh
%A R. M. Verma
%A T. Krishnaprasad
%A I. V. Ramakrishnan
%T Term Matching on Parallel Computer
%I Department of Computer Science, SUNY at Stony Brook
%D AUG 1986
%R 86/20
%K AI11 H03
%A Sanjay Manchanda
%A Soumitra Sengupta
%A David Scott Warren
%T Concurrent Updates in a Prolog Database Systems
%I Department of Computer Science, SUNY at Stony Brook
%D Dec 1986
%R 86/28
%K AA09 T02
%A Jieh Hsiang
%A Michael Rusinowitch
%T ON Word Problems in Equational Theories
%I Department of Computer Science, SUNY at Stony Brook
%D DEC 1986
%R 86/29
%K AI14
%A Anita Wasilewska
%T Definable Sets in Knowledge Representation Systems
%I Department of Computer Science, SUNY at Stony Brook
%D DEC 1986
%R 86/31
%K AI16
%A Anita Wasilewski
%T On Automatic Learning
%I Department of Computer Science, SUNY at Stony Brook
%D DEC 1986
%R 86/34
%K AI04
%A Chilukuri K. Mohan
%A Mandayam K. Srivas
%A Deepak Kapurm
%T On Proofs in System of Equations and Inequations
%I Department of Computer Science, SUNY at Stony Brook
%D JAN 1987
%R 87/02
%K AI14
%A Alexander Waibel
%T Prosody and Speech Recognition (Thesis)
%I Carnegie Mellon Computer Sciences
%R CMU-CS-86-162
%D 1986
%K AI05
%A Maurice P. Herlihy
%A Jeannette M. Wing
%T Axioms for Concurrent Objects
%I Carnegie Mellon Computer Sciences
%R CMU-CS-86-154
%D 1986
%K AA08
%A Michael C. Browne
%T An Improved Algorithm for the Automatic Verification of Finite
State Systems Using Temporal Logic
%I Carnegie Mellon Computer Sciences
%R CMU-CS-86-156
%D 1986
%K AA08
%A Andrew W. Appel
%A Guy J. Jacobson
%T The World's Fastest Scrabble Program
%I Carnegie Mellon Computer Sciences
%D 1986
%R CMU-CS-86-153
%K AA17 AI03
%A H. T. Kung
%A Jon A. Webb
%T Mapping Image Processing Operations onto a Linear Systolic Machine
%I Carnegie Mellon Computer Sciences
%D 1986
%R CMU-CS-86-137
%K H03 AI06 Warp FFT Hough Transform connected component labeling relaxation
%A Katsushi Ikeuchi
%T Generating an Interpretation Tree From a CAD Model to Represent
Object Configurations for Bin-Picking Trees
%I Carnegie Mellon Computer Sciences
%D 1986
%R CMU-CS-86-144
%K AI07 AA26
%A P. Helman
%A R. Veroff
%T Designing Deductive Databases
%I University of New Mexico Computer Sciences
%D 1986
%R CS86-5
%K AA09
%A James R. Slagle
%A Michael R. Wick
%A Marius O. Poliac
%T Agness: A Generalized Network-Based Expert System Shell
%I University of Minnesota, Computer Science Department
%R CSci TR86-48
%D 1986
%K T03
%A Valdis Berzins
%A Jeff Petty
%T The DB Lisp Code Analyzer
%I University of Minnesota, Computer Science Department
%R CSci TR 86-56
%D 1986
%K T01
%A Jik H. Chang
%A Oscar H. Ibarra
%A Ting-Chuen Pong
%A Stephen M. Sohn
%T Two-Dimensional Convolution on a Pyramid Computer
%I University of Minnesota, Computer Science Department
%R CSci TR87-1
%D 1987
%K AI06 H03
%A Ting-Chuen Pong
%T Matching Topographic Structures in Stereo Vision
%I University of Minnesota, Computer Science Department
%R CSci TR87-2
%D 1987
%K AI06
%T Recent Developments in NIKL
%A Thomas Kaczmarek
%A Raymond Bates
%A Gabriel Robins
%R ISI/RS-86-167
%I USC/Information Sciences Institute
%D November 1986
%K AI16
%X
NIKL (a New Implementation of KL-ONE) is one of the members of the KL-ONE
family of knowledge representation languages. NIKL has been in use for
several years and our experiences have led us to define and implement various
extensions to the language, its support environment and the implementation.
Our experiences are particular to the use of NIKL. However, the requirements
that we have discovered are relevant to any intelligent system that must
reason about terminology. This article reports on the extensions that we have
found necessary based on experiences in several different testbeds. The
motivations for the extensions and future plans are also presented.
%T A Logical-Form and Knowledge-Base Design for Natural Language Generation
%A Norman Sondheimer
%A Bernhard Nebel
%R ISI/RS-86-169
%D November 1986
%I USC/Information Sciences Institute
%K AI02
%X This paper presents a technique for interpreting output demands by a natural
language sentence generator in a formally transparent and efficient way.
These demands are stated in a logical language. A network knowledge base
organizes the concepts of the application domain into categories known to the
generator. The logical expressions are interpreted by the generator using the
knowledge base and a restricted, but efficient, hybrid knowledge
representation system. The success of this experiment has led to plans for
the inclusion of this design in both the evolving Penman natural language
generator and the Janus natural language interface.
%T Rhetorical Structure Theory:
Descripton and Construction of Text
%A William C. Mann
%A Sandra Thompson
%R ISI/RS-86-174
%I USC/Information Sciences Institute
%D October 1986
%X Rhetorical Structure Theory (RST) is a theory of text structure that is
being extended to serve as a theoretical basis for computational text
planning. Text structure in RST are hierarchic, built on small patterns
called schemas. The schemas which compose the structural hierarchy of a
text describe the functions of the parts rather than their form
characteristics. Relations between text parts, comparable to conjunctive
relations, are a prominent part of RST's definitional machinery.
.sp
sp
Recent work on RST has put it onto a new definitional basis. This paper
describes the current status of descriptive RST, along with efforts to
create a constructive version for use as a basis for programming a text
planner.
%T Automatic Compilation of Logical Specifications into Efficient Programs
%A Donald Cohen
%R ISI/RS-86-175
%D November 1986
%I USC/Information Sciences Institute
%K AA08
%X We describe an automatic programmer, or "compiler" which accepts as input a
predicate calculus specification of a set to generate or a condition to test,
along with a description of the underlying representation of the data. This
compiler searches a space of possible algorithms for the one that is expected
to be most efficient. We describe the knowledge that is and is not available
to this compiler, and its corresponding capabilities and limitations. This
compiler is now regularly used to produce large programs.
%T Towards Explicit Integration of Knowledge in Expert Systems
%A Jack Mostow
%A Bill Swartout
%R ISI/RS-86-176
%D November 1986
%I USC/Information Sciences Institute
%K AI16 O04 AA01 AI01
%X The knowledge integration problem arises in rule-based expert systems when
two or more recommendations made by right-hand sides of rules must be
combined. Current expert systems address this problem either by engineering
the rule set to avoid it, or by using a single integration technique built
into the interpreter, e.g., certainty factor combination. We argue that
multiple techniques are needed and that their use -- and underlying
assumptions -- should be made explicit. We identify some of the techniques
used in MYCIN's therapy selection algorithm to integrate the diverse goals it
attempts to satisfy, and suggest how knowledge of such techniques could be
used to support construction, explanation, and maintenance of expert systems.
%A M. Fanty
%T Context-free Parsing in Connectionist Networks
%I University of Rochester Computer Science Department
%D NOV 1985
%R TR 174
%K H03 O06
%X algorithm to convert any context-free grammar into a connectionist
network
.br
br
30 pages $1.25
%A D. H. Ballard
%T Interpolation Coding: A Representation for Numbers in Neural Nets
%I University of Rochester Computer Science Department
%D MAY 1986
%R TR 175
%K O04 H03 O06
%X also discusses a method of combining evidence in neural nets
.br
br
30 pages $1.25
%A J. Aloimonos
%A A. Basu
%T Determining the Translation of a Rigidly Moving Surface Without
Correspondence
%I University of Rochester Computer Science Department
%D JAN 1986
%R TR176
%K AI06
%X deal withs three dimensional translation of a textured object and uses
four cameras
.br
br
20 pages, $1.00
%A J. Aloimonos
%A I. Rigoutsos
%T Determining the Three-Dimensional Motion of a Surface Patch Without
Correspondence, Under Perspective Projection: (i) Planar Surfaces
(ii) Curved Surfaces
%I University of Rochester Computer Science Department
%D DEC 1985
%R TR 178
%K AI06 stereo 3-D
%X 35 pages, $1.50
%A J. F. Allen
%A P. J. Hayest
%T A Common-Sense Theory of Time
%I University of Rochester Computer Science Department
%D FEB 1987
%R TR 180
%K AI16
%X 32 pages, $1.50
.br
br
.br
br
Includes discussion of an axiomatization of time subsuming Allen's
interval-based theory.
%A D. B. Sher
%T Optimal
Likelihood Generators for Edge Detection Under Gaussian Additive Noise
%I University of Rochester Computer Science Department
%D AUG 1986
%R TR 185
%K O04 AI06
%X 9 pages, $0.75
%A D. Baldwin
%T A Model for Automatic Design of Digital Circuits
%I University of Rochester Computer Science Department
%D JUL 1986
%R TR 188
%K AA04
%X 25 pages $1.25
.br
br
discusses partitioning of design tasks into algorithmic and knowledge-based
parts
%A J. A. Feldman
%T Neural Representation of Conceptual Knowledge
%I University of Rochester Computer Science Department
%D JUN 1986
%R TR 189
%K AI12 AI16
%X 35 pages, $1.50
.br
br
discusses holographic models
%A R. P. Loui
%T A Presumptive System of Defeasible Inference
%I University of Rochester Computer Science Department
%D MAY 1986
%R TR 190
%K AI15
%X 20 pages, $1.25
%A R. P. Loui
%T Real Rules of Inference: Acceptance and Non-Monotonicity in AI
%I University of Rochester Computer Science Department
%D SUMMER 1986
%R TR 191
%K AI15
%X 59 pages $2.25
%A D. Sher
%T Evidence Combination Using Likelihood Generators
%I University of Rochester Computer Science Department
%D JAN 1987
%R TR 192
%K O04 AI16
%X 27 pages, $1.25
%A A. Mukherjee
%T Self-calibration Strategies for Robot Manipulators
%I University of Rochester Computer Science Department
%D SEP 1986
%R TR 193
%K AI07
%X 105 pages, $3.75, PH. D. Thesis
%A L. Hartman
%T Generating Motor Behavior
%I University of Rochester Computer Science Department
%D OCT 1986
%R TR 195
%K AI09 naive physics
%X 31 pages $1.50
.br
br
planning in a block world under naive physics axiomitization
%A S. Hollbach
%T Tinker Toy Recognition From 2D Connectivity
%I University of Rochester Computer Science Department
%D OCT 1986
%R TR 196
%K AI06
%X 22 pages, $1.25
%A D. Sher
%T Advanced Likelihood Generators for Boundary Detection
%I University of Rochester Computer Science Department
%D JAN 1987
%R TR 197
%K AI06 O04
%X 50 pages, $2.00
%A I. Rigoutsis
%T Homotopies: A Panacea or Just Another Method?
%I University of Rochester Computer Science Department
%D DEC 1986
%R TR 201
%K AI06 O06
%X discusses applications of a method for solving non-linear equations
and its applicability to computer vision.
%A Marek W. Lugowski
%T Computational Metabolism
%I Indiana University Computer Science Department
%R 200
%K AI16 AI08 AI06 AI04 dynamical locally-coupled bottom-up architecture
%X A new architecture for programming of dynamical systems. It consists of
a tessellation into processors which undergo pairwise swaps. Processors
come in several types; each type recognizes certain other ones. Recognition
events result either in processor state change or a 2-processor swap. Model
combines cellular automaton and connectionist featrures with probabilistic
computation. Intended application: representation and computation of metaphors.
%A Jacek Leszczylowski
%A David Schmidt
%T A Logic for Program Derivation and Verification
%R TR-CS-86-2
%I Kansas State University, Computing and Information Sciences Department
%K AI10 AI11 AA08
%A J. R. B. Cockett
%A J. Herrera
%T Prime Rule Based Methodologies Give Inadequate Control
%R CS-85-60
%I University of Tennessee - Knoxville, Computer Science Department
%K AI01 AA09
%A Janusz Kacprzyk
%A Andrzej Ziolkowski
%T Database Querying Schemes with Fuzzy Linguistic Quantifiers
%R CS-86-62
%I University of Tennessee - Knoxville, Computer Science Department
%K O04 AI02 AA09
%A Janusz Kacprzyk
%T Enhancing Algorithmic/Procedural "Human Consistency" of Control
Models by Using Some Representation of Common Sense Knowledge
%R CS-86-63
%I University of Tennessee - Knoxville, Computer Science Department
%K O04 AI13
%A Janusz Kacprzyk
%A Jerzy Holubiec
%T Towards a More Realistic Modeling of International Economic
Cooperation via Fuzzy Mathematical Programming and Cooperative Games
%R CS-86-64
%K AA11 O04
%I University of Tennessee - Knoxville, Computer Science Department
%A Janusz Kacprzyk
%A Cezary Iwanski
%T A Generalization of Discounted Multistage Decision Making and
Control Through Fuzzy Linguistic Quantifies: An Attempt to
Introduce Commonsense Knowledge
%R CS-86-66
%K O04 AI13
%I University of Tennessee - Knoxville, Computer Science Department
%A Stanley H. Smith
%A Mehmet Celenk
%T A New, Systematic Method for Color Image Analysis II. Computer
Implementation and Results
%R Tech. Rep. EE 8610
%I Stevens Institute of Technology, Electrical Engineering and
Computer Science Departments
%D MAR 1986
%K natural sceens AI06
%A Divyendu Sinha
%T Operations on Unimodal Possibility Distributions that Characterize
the Gray-Values of Images in the Fuzzy Settings Part I
%R Tech Rep. EECS 8614
%D MAY 1986
%I Stevens Institute of Technology, Electrical Engineering and
Computer Science Departments
%K AI06 O04
%A Divyendu Sinha
%T Operations on Unimodal Possibility Distributions that Characterize
the Gray-Values of Images in the Fuzzy Settings Part II
%R Tech Rep. EECS 8615
%D MAY 1986
%I Stevens Institute of Technology, Electrical Engineering and
Computer Science Departments
%K AI06 O04
%A Harrison E. Rowe
%A Jung G. Shin
%A Ta-Shing Chu
%T Radio Imaging of Launch Vehicles and Payloads
%I Stevens Institute of Technology, Electrical Engineering and
Computer Science Departments
%D JUN 1986
%R TECH. Rep. EECS 8617
%K AI06 AA27
%X discussed problems in receiving radio images such
as rain attenuation, clouds, etc.
%A John S. Conery
%T Closed Environments: Partitioned Memory Representation for Parallel Logic
Programming
%I Computer and InformationScience Department, University of Oregon
%C Eugene, Oregon
%R CIS-TR-86-02
%K AI11 H03
%A Kent A. Stevens
%A Daniel P. Lulich
%T Artifacts at the Limit of Resolution
%I Computer and Information Science Department, Univerisity of Oregon
%C Eugene, Oregon
%R CIS-TR-86-04
%K AI06 AA10 AA01
%X A visual illusion which appears at the limit of resolution is used to
investigate perceived artifacts of the convolution by Gaussian filters.
Evidence is provided that implicate the smallest size operator at the
retina and that suggest that the perceived shape of intensity changes
is influenced by artifacts induced by the operator.
%A Kent A. Stevens
%A Allen Brookes
%T Integrating Stereopsis with Monocular Interpretations of Planar Surfaces
%I Computer and Information Science Department, Univerisity of Oregon
%C Eugene, Oregon
%R CIS-TR-86-05
%K AI06 AA10 AA01
%A Kent A. Stevens
%A Allen Brookes
%T Probing Depth in Monocular Images
%I Computer and Information Science Department, Univerisity of Oregon
%C Eugene, Oregon
%R CIS-TR-86-06
%K AI06 AA10 AA01
%A Stephen Fickas
%T Automating the Analysis Process
%I Computer and Information Science Department, Univerisity of Oregon
%C Eugene, Oregon
%R CIS-TR-08
%K AA08
%X discusses the automation of requirements analysis
%A John Conery
%T Backward Execution in Nondeterministic AND-Parallel Systems
%I Computer and Information Science Department, Univerisity of Oregon
%C Eugene, Oregon
%R CIS-TR-86-09
%K H03 AI10
%A Kent A. Stephens
%A Allen Brooks
%T Detecting Structure by Symbolic Constructions on Tokens
%I Computer and Information Science Department, Univerisity of Oregon
%C Eugene, Oregon
%R CIS-TR-86-10
%K AI06
%X discusses the interpretation of dot patterns, comparison of feature
detection structure-detection and energy-summation systems.
%A Allen Brookes
%A Kent A. Stevens
%T The Analogy Between Stereo Depth and Brightness Contrast
%I Computer and Information Science Department, Univerisity of Oregon
%C Eugene, Oregon
%R CIS-TR-86-11
%K AI06 AI08 AA01 AA10
%A Virginia M. Lo
%A David Chen
%T Intelligent Scheduling in Distributed Computing Systems
%R CIS-TR-86-14
%I Computer and Information Science Department, Univerisity of Oregon
%C Eugene, Oregon
%K H03 AI01
%X applies expert system technology to task migration on distribution
systems including dealing with out of date system load tables
%A Kent A. Stevens
%A Allen Brookes
%T Theory of Depth Reconstruction in Stereopsis
%I Computer and Information Science Department, Univerisity of Oregon
%C Eugene, Oregon
%R CIS-TR-86-15
%K AI06 AI08 AA01 AA10
------------------------------
End of AIList Digest
********************
∂02-Jun-87 0205 LAWS@Stripe.SRI.Com AIList Digest V5 #137
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 2 Jun 87 02:05:16 PDT
Date: Mon 1 Jun 1987 20:35-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #137
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 2 Jun 1987 Volume 5 : Issue 137
Today's Topics:
Bibliography - Leff ai.bib49TR
----------------------------------------------------------------------
Date: Sun, 31 May 1987 14:56 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: ai.bib49TR
%A Fil Fuma
%A Erick Krotkov
%A John Summers
%T The Pennsylvania Active Camera System
%I University of Pennsylvania
%R MS-CIS-86-15
%K AI06
%A Tim Finin
%A Aravind K. Joshi
%A Bonnie Lynn Webber
%T Natural Language Interactions with Artificial Experts
%I University of Pennsylvania
%R MS-CIS-86-16
%K AI01 AI02 O01
%A Dale A. Miller
%A Gopalan Nadathur
%T Higher-Order Logic Programming
%I University of Pennsylvania
%R MS-CIS-86-17
%K AI10 T02
%A Eric Krotkov
%T Focusing
%I University of Pennsylvania
%R MS-CIS-86-22
%K AI06
%X automatic focusing of a computer controlled camera
%A Rusena Bajcsy
%A Eric Krotkov
%A Max Mintz
%T Models of Errors and Mistakes in Machine Perception
%I University of Pennsylvania
%R MS-CIS-86-26
%K AI06 stereo
%A Aravind K. Joshi
%A Bonnie L. Webber
%A Ralph M. Weischedel
%T Some Aspects of Default Reasoning in Interactive Discourse
%I University of Pennsylvania
%R MS-CIS-86-27
%K AI02
%A Yuen-Wah Eva Ma
%A Ramesh Krishnamurti
%A Bhagirath Narahari
%A Dennis G. Shea
%A Kwang-shi Shu
%T High Performance Special-Purpose Computer Architectures for Robotics
Applications
%I University of Pennsylvania
%R MS-CIS-86-28
%K H03 AI06 AI07
%A Dale A. Miller
%A Gopalan Nadathur
%T Some Uses of Higher Order Logic in Computational Linguistics
%I University of Pennsylvania
%R MS-CIS-86-31
%K AI10 AI02
%A Robert Rubinoff
%T Adapting Mumble: Experience with Natural Language Generation
%I University of Pennsylvania
%R MS-CIS-86-32
%K text generation
%K AI10 T02
%A Ethel Schuster
%T Towards a Computational Model of Anaphora in Discourse: References to
Events and Actions
%R MS-CIS-86-34
%I University of Pennsylvania
%K AI02
%A Tim Finin
%A David Drager
%T $GUMS sub 1$: A General User Modeling System
%R MS-CIS-86-35
%I University of Pennsylvania
%K AI08 O01 AA15
%A Robert Kass
%A Ron Katriel
%A Tim Finin
%T Breaking the Primitive Concept Barrier
%R MS-CIS-86-36
%I University of Pennsylvania
%K AI16 KL-ONE
%X describes extensions to KL-ONE
%A Anthony S. Kroch
%A Aravind K. Joshi
%T Analyzing Extraposition in A Tree Adjoining Grammar
%R MS-CIS-86-37
%I University of Pennsylvania
%K AI02
%A Martha Elizabeth Pollack
%T Inferring Domain Plans in Question-Answering
%R MS-CIS-86-40
%I University of Pennsylvania
%K AI08 O01
%A Brant A. Cheikes
%T Research in Artificial Intelligence at the University of Pennsylvania
%R MS-CIS-86-41
%I University of Pennsylvania
%K AT09 AI16
%A Susan B. Davidson
%A Mark M. Winkler
%T Conflict Resolution in Class Conflict Graph Analysis
%R MS-CIS-86-43
%I University of Pennsylvania
%K conflict resolution AI16
%A Jean H. Gallier
%A Stan Raatz
%T Extending SLD-Resolution to Equational Horn Clauses Using E-Unification
%I University of Pennsylvania
%R MS-CIS-86-44
%K AI10
%A Dale Miller
%A Amy Felty
%T An Integration of Resolution and Natural Deduction Theorem Proving
%I University of Pennsylvania
%R MS-CIS-86-47
%K AI11
%A Sharon A. Stansfield
%T A Rudimentary Active Multimodal, Intelligent System for Object
Categorization
%I University of Pennsylvania
%R MS-CIS-86-48
%K AI06
%A Mark Turner
%T Texture Discrimination by Gabor Functions
%I University of Pennsylvania
%R MS-CIS-86-51
%K AI06
%A Megumi Kameyama
%T A Property-Sharing Constraint in Centering
%I University of Pennsylvania
%R MS-CIS-86-52
%K AI02 pronoun resolution
%A Dale Miller
%T A Theory of Modules for Logic Programming
%I University of Pennsylvania
%R MS-CIS-86-53
%K AI10
%A Claire Socolovsky Caine
%T An Expert System for Marine Umbrella Liability Insurance Underwriting
%I University of Pennsylvania
%R MS-CIS-86-54
%K AA06
%A Gerald P. Stoloff
%T Lanpick -- An Expert System for Recommendation of Local Area Network
Hardware and Software Products
%I University of Pennsylvania
%R MS-CIS-86-55
%K AA08
%A Franc Solina
%T Object Recognition Using Function Based Category Models
%I University of Pennsylvania
%R MS-CIS-86-56
%K AI06
%A Robert Kaas
%T The Role of User Modelling in Intelligent Tutoring System
%I University of Pennsylvania
%R MS-CIS-86-58
%K AA07 AI08
%A Jean H. Gallier
%A Stan Raatz
%T Refutation Methods for Horn Clauses with Equality Based on Unification
%I University of Pennsylvania
%R MS-CIS-86-59
%K AI10
%A Megumi Kameyama
%T Japanese Zero Pronominal Bindings: Where Syntax and Discourse Meet
%I University of Pennsylvania
%R MS-CIS-86-60
%K AI02
%A Robert Kaas
%A Tim Finin
%T The Role of User Models in Question Answering Systems
%I University of Pennsylvania
%R MS-CIS-86-63
%K AI01 AI08 personal investment AA06
%A Aravind K. Joshi
%T An Introduction to Tree Adjoining Grammars
%I University of Pennsylvania
%R MS-CIS-86-64
%K AI06 AT08
%A Alex Pelin
%A Jean Gallier
%T Solving Word Problems in Free Algebras Using Complexity Functions
%I University of Pennsylvania
%R MS-CIS-86-65
%K AI11
%A Jugal Kalita
%A Sunish Shende
%T Generation of Natural Language Text Describing a System of
Asynchronous, Concurrent Processes
%I University of Pennsylvania
%R MS-CIS-86-66
%A Hugh F. Durrant-Whyte
%T Integration, Coordination and Control of Multi-Sensor Robot Systems
%I University of Pennsylvania
%R MS-CIS-86-67
%K AI06 AI07 blackboard AI01
%A Greg Hager
%A Hugh F. Durrant-Whyte
%T Information and Multi-Sensor Coordination
%I University of Pennsylvania
%R MS-CIS-86-68
%K AI07 AI06 H03
%A Tim Finin
%T NFL- A Novices Frame Language
%I University of Pennsylvania
%R MS-CIS-86-71
%K AT18 T01 T03
%A Bonnie Lynn Webber
%T Two Steps Closer to Event Reference
%I University of Pennsylvania
%R MS-CIS-86-74
%K AI02 AI16
%A Greg Hagar
%T Active Reduction of Uncertainty in Multi-Sensor Systems
%I University of Pennsylvania
%R MS-CIS-86-76
%K H03 O04
%A Lokendra Shastri
%T Massive Parallelism in Artificial Intelligence
%I University of Pennsylvania
%R MS-CIS-86-77
%K H03
%A Lokendra Shastri
%A Raymond L. Wairous
%T Learned Phonetic Discrimination Using Connectionistic Networks
%I University of Pennsylvania
%R MS-CIS-86-78
%K H03 AI05
%A Linda Ness
%T Reducing Linear Recursion to Transitive Closure
%I University of Texas at Austin, Department of Computer Sciences
%R TR-86-25
%K AA09 AI10
%D NOV 1986
%X shows how to deal with a recursively expressed logic program that
is designed to query a database
%A David A. Schmidt
%A Jacek Leszczylowski
%T On Developing a Logic for Program Derivation and Verification
%I Iowa State University Computer Science Department
%R TR#86-16
%D NOV 1986
%K AA08 AI10 intuitionistic type theory predicate calculus
%A James M. Bieman
%A Albert L. Baker
%A Paul M. Clites
%A David A. Gustafson
%A Austin C. Melton
%T A Standard Representation of Imperative Language Programs
%I Iowa Sate University Computer Science Department
%R TR #86-17
%D NOV 1986
%K AA08
%A Ken-Chih Liu
%A Rajshekhar Sunderraman
%T Applying an Extended Relational Model to Indefinite Deductive Databases
%I Iowa State University Computer Science Department
%R TR #86-18
%D NOV 1986
%K AI10 AA09
%A Jacek Leszczylowski
%A Jan Maluszynski
%T Logic Programming with External Procedures: Introducing S-Unification
%I Iowa State University Computer Science Department
%R TR #86-21
%D DEC 1986
%K AI10
%A Chen
%A Chi
%A Ost
%A Sabbaugh
%A Spring
%T Scheme Graphics Reference Manual
%I Indiana University Computer Science Department
%R TR 144
%D 1984
%K T01
%A Daniel P. Friedman
%A Pee-Hong Chen
%T Prototyping Data Flow by Translation Into Scheme
%I Indiana University Computer Science Department
%R TR 147
%D 1983
%K T01
%A Mitchell Wand
%T A Semantic Algebra for Logic Programming
%I Indiana University Computer Science Department
%R TR 148
%D August 1983
%K AI10
%A Kent Dybvig
%T C-Scheme Reference Manual
%I Indiana University Computer Science Department
%R TR 149
%D SEP 1983
%K T01
%A J. Barnden
%T On Short-Term Information-Processing in Connectionist Theories
%I Indiana University Computer Science Department
%R TR 152
%D JAN 1984
%K H03
%A D. Friedman
%A C. Hayes
%A E. Kohlbecker
%A M. Wand
%T Scheme 84 Interim Reference Manual
%R TR 153
%D JUN 1985
%I Indiana University Computer Science Department
%K T01
%A E. Kohlbecker
%T eu-Prolog: Reference Manual and Report
%R TR 155
%D APR 1984
%I Indiana University Computer Science Department
%K T02
%A C. D. Halpern
%T An Implementation of 2-Lisp
%R TR 160
%D JUN 1984
%I Indiana University Computer Science Department
%K T01
%A L. D. Sabbagh
%T Scheme as an Interactive Graphics Programming Environment
%R TR 166
%D FEB 1985
%I Indiana University Computer Science Department
%K T01
%A J. A. Barnden
%T Representations of Intensions, Representations as Intensions,
and Propositional Attitudes
%R TR 172
%D JUN 1985
%I Indiana University Computer Science Department
%K AI02 AI16
%A Johnathan Rees
%A W. D. Clinger
%T Revised Report on Scheme
%R TR 174
%D AUG 1986
%I Indiana University Computer Science Department
%K AI06
%$ 6.00
%A M. W. Lugowski
%T Why Artificial Intelligence is Necessarily Ad Hoc: One's Thinking/Approach/
Model/Solution Rides on One's Metaphors
%R TR 176
%D AUG 1985
%I Indiana University Computer Science Department
%K AI16
%$ 2.00
%A S. C. Kwasny
%A J. Dalby
%A R. Port
%T Rules for Automatic Mapping Between Fast and Slow Speech
%R TR 175
%D JUL 1985
%I Indiana University Computer Science Department
%K AI05
%A Matthias Felleisen
%T Transliterating Prolog into Scheme
%R TR 182
%D OCT 1985
%I Indiana University Computer Science Department
%K T01 T02
%A Christopher T. Haynes
%T Logic Continuations
%R TR 183
%D NOV 1985
%I Indiana University Computer Science Department
%K AI10
%A John A. Barnden
%T Imputations and Explications: Representational Problems in Treatments
of Propositional Attitudes
%R TR 187
%D JAN 1986
%I Indiana University Computer Science Department
%K AI16
%A Erich J. Smythe
%T The Pleasures of SINN: A System for Programming Connectionist Models
%R TR189
%D FEB 1986
%I Indiana University Computer Science Department
%K FEB 1986
%A Matthias Felleisen
%A Daniel P. Friedman
%T Control Operators, the SECD-Machine and the $lambda$-calculus
%R TR 197
%D JUN 1986
%I Indiana University Computer Science Department
%K T01
%A Eugene E. Kohlbecker
%T Syntactic Extensions in the Programming Language Lisp
%R TR 199
%D AUG 1986
%I Indiana University Computer Science Department
%K T01
%$ 12.00 (Ph. D. Dissertation)
%A Matthias Felleisen
%T A Final Scheme-Word on Landin's J-Operator
%R TR 205
%D NOV 1986
%I Indiana University Computer Science Department
%K T01
%A Bipin Indurykha
%T Analogies and Metaphors: An Interdisciplinary Perspective
%R BUCS Tech Report #86-012
%D DEC 1986
%I Boston University Department of Computer Science
%K AI08 AI16 AI02
%A Michael Siegel
%T Automatic Rule Derivation for Semantic Query Optimization
%R BUCS Tech Report #86-013
%D DEC 1986
%I Boston University Computer Science Department
%K AA09 AI01
%A Leonard Uhr
%T Toward a Computational Information-Processing Model of Object
Perception
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR651
%D JUL 1986
%K AI08 AI06
%X describes what is known and is necessary for development of a model
of visual perception in humans as well as those points of information
that are lacking.
%A Matthew J. Thazhuthaveetil
%T A Structured Memory Access Architecture for LISP
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR658
%D AUG 1986
%K H02 T01
%A Udi Manber
%T Using Mathematical Induction to Design Computer Algorithms
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR660
%D AUG 1986
%K AA08 AI11
%A M. A. Sridhar
%T Efficient Algorithms for Multiple Pattern Matching
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR661
%D AUG 1986
%K O06
%A Charles V. Steward
%A Charles R. Dyer
%T A Scheduling Algorithm for the Pipelined Image-Processing Engine
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR664
%D SEP 1986
%K AI06 H03
%A Nian Li
%A Leonard Uhr
%T Comparative Timings for a Neuron Recognition Program on Serial and
Pyramid Computers
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR665
%D SEP 1986
%K AA10 AI06 H03
%X a system to recognize neurons in photomicrographs
%A Gilbert Verghese
%A Shekhar Mehta
%A Charles R. Dyer
%T Image Processing Algorithms for the Pipelined Image-Processing Engine
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR668
%D SEP 1986
%K local peak detection median filtering thinning Hough transform photometric
stereo AI06 O06 H03
%A Mitali Bhattacharyya
%A David Cohrs
%A Barton Miller
%T Implementation of a Visual UNIX Process Connector
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR677
%D DEC 1986
%X An environment for connecting several UNIX processes. Not specifically
AI related
%A Ze-Nian Li
%A Leonard Uhr
%T Pyramid Vision Using Key Features to Integrate Image-Driven Bottom-Up
and Model-Driven Top Down Processes
%I University of Wisconsin-Madison, Computer Sciences Department
%D DEC 1986
%R TR678
%K H03 AI06
%A Charles R. Dyer
%T Multiscale Image Understanding
%I University of Wisconsin-Madison, Computer Sciences Department
%R TR679
%D DEC 1986
%K texture AI06
%A G. T. Toussaint
%T Computational Geometry and Morphology
%I McGill University, School of Computer Science
%R TR-SOCS-86.3
%D FEB 1986
%K AA10 AI06 O06
%X applications of such algorithms as hulls, medial axis, geodesic
and visibility for polygons to understanding biological shape and shape
change.
%A R. De Mori
%A L. Lam
%A M. Gilloux
%T Learning and Plan Refinement in a Knowledge-Based System for Automatic
Speech Recognition
%R TR-SOCS-86.14
%I McGill University, School of Computer Science
%D MAY 1986
%K AI09 AI04 AI05
%X experimental work on recognition of connected letters by 100 speakers
%A Heedong Ko
%A Kunwoo Lee
%T Toward a Practical Planning System for Assembly Tasks
%R Department of Computer Science File 957
%I University of Illinois at Urbana-Champaign
%D SEP 1986
%K AA26
%A Carl Thomas Uhrik
%T A Rule Exerciser for Knowledge Base Enhancement in Expert Systems
%R Department of Computer Science File 969
%I University of Illinois at Urbana-Champaign
%D SEP 1986
%K AI01 O04 AA23 AA10
%X The system has been applied to soybean diagnosis and monkey behavior
discrimination
%A Kenneth D. Forbus
%A Dedre Gentner
%T Learning Physical Domains: Toward a Theoretical Framework
%R Department of Computer Science File 1247
%I University of Illinois at Urbana-Champaign
%D DEC 1986
%K AI08 AI04
%A Steven Greenbaum
%T Input Transformations and Resolution Implementation Techniques for
Theorem Proving in First-Order Logic
%R Department of Computer Science File 1298
%I University of Illinois at Urbana-Champaign
%D SEP 1986
%K AI11
%X the aim is opposed to solve small sized problem with little or no
human guidance as opposed to other systems which are designed to
solve large problems with human guidance. Uses priority-based search
strategy, discrimination networks and Knuth-Bendix method
%A Brian Falkenhainer
%T An Examination of the Third State in the Analogy Process: Verification-
Based Analogical Learning
%R Department of Computer Science File 1302
%I University of Illinois at Urbana-Champaign
%D OCT 1986
%K AI04 qualitative models liquid flow and heat flow
%A Y-L. Steve
%A Daniel D. Gajski
%T LES: A Layout Expert System
%R Department of Computer Science File 1308
%I University of Illinois at Urbana-Champaign
%D NOV 1986
%K AA04
%X A layout system that is competitive with human designers
%A Krish Purswani
%A Larry Rendell
%T A Probabilistic Reasoning-Based Approach to Machine Learning
%R Department of Computer Science File 1311
%I University of Illinois at Urbana-Champaign
%D DEC 1986
%K AI03 O04
%A Yoram Ofer Moses
%T Knowledge in a Distributed Environment
%D MAR 1986
%R STAN-CS-86-1120
%I Stanford University Computer Science
%K H03
%X Discusses the effects of unreliable communications on coordination
of an expert system, the Byzantine agreement problem and the "cheating
wives" puzzle
.br
br
15.00 104 pages
%A Glenn Douglas Rennels
%T A Computational Model of Reasoning from the Clinical Literature
%D JUN 1986
%I Stanford University Computer Science
%R STAN-CS-86-1122
%K AA01 AI01
%X discusses getting information from the clinical literature into
an AI system for patient care. Example problem is "breast cancer
management options."
.br
br
244 pages 15.00
%A H. Penny Nii
%T Blackboard Systems
%D JUN 1986
%I Stanford University Computer Science
%R STAN-CS-86-1123
%X general review of black board systems
.br
br
86 pages, 10.00
%A Daniel J. Scales
%T Efficient Matching Algorithms for the SOAR/OPS5 Production System
%D JUN 1986
%I Stanford University Computer Science
%R STAN-CS-86-1124
%K T03 AI01
%X 50 pages 10.00
%A Eric Schoen
%T The CAOS System
%D MAR 1986
%I Stanford University Computer Science
%R STAN-CS-86-1125
%K H03 O03
%X a real time Lisp distributed system for signal interpretations
.br
br
69 pages 10.00
%A Byron Davies
%T CAREL: A Visible Distributed Lisp
%D MAR 1986
%R STAN-CS-86-1126
%I Stanford University Computer Science
%K H02 H03 T01
%X A system programming language that runs on the TI Explorer that
includes real time display of the processor activity and data
communications; useful as an educational tool
.br
br
15 pages 5.00
%A Yonathan Malachi
%T A Timely Resolution
%D MAR 1986
%R STAN-CS-86-1127
%I Stanford University Computer Science
%K AI11 AI10 T01 T02 H03 TABLOG unification
%X 15.00 145 pages
%A Evan R. Cohn
%A Ramsey W. Haddad
%T Beta Operations: Efficient Implementation of a Primitive Parallel Operation
%D AUG 1986
%R STAN-CS-86-1129
%I Stanford University Computer Science
%K H03
%X The Beta Operation can be performed in O(log N + log **2 M) time
on a hypercube where N is the size of the input and M is the size
of the output.
.br
br
5.00, 18 pages
%A Vishvjit S. Nalwa
%A Thomas O. Binford
%T On Detecting Edges
%R STAN-CS-86-1130
%D MAR 1986
%I Stanford University Computer Science
%K AI06
%X Proposed method will localize edges to within a thilrd of a pixel
if step-size over noise ratio > 2.5
.br
br
50 pages 10.00
%A Yehoshua Sagiv
%T Optimizing Datalog Programs
%R STAN-CS-86-1132
%D MAR 1986
%I Stanford University Computer Science
%K AI10
%X Prolog programs without function symbols are optimized. Also defines
a new form of equivalence under which such programs can be compared.
.br
br
30 pages, 50.00
%A Richard James Treitel
%T Sequentialization of Logic Programs
%R STAN-CS-86-1135
%D NOV 1986
%I Stanford University Computer Science
%K AI10
%X 16 pages 15.00
%A Harold Brown
%A Erich Schoen
%A Bruce Delogi
%T An Experiment in Knowledge-based Signal Understanding Using Parallel
Architectures
%R STAN-CS-86-1136
%D OCT 1986
%I Stanford University Computer Science
%K H03 AA18 T01
%X System was tested on radar emissions from air craft
.br
br
36 pages 5.00
------------------------------
End of AIList Digest
********************
∂03-Jun-87 2316 LAWS@Stripe.SRI.Com AIList Digest V5 #138
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 Jun 87 23:16:30 PDT
Date: Wed 3 Jun 1987 20:28-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #138
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 4 Jun 1987 Volume 5 : Issue 138
Today's Topics:
Queries - Uncertainty in ART & Expert Systems for Debugging and Porting &
Sources for June AI Expert & AAAI at Seattle &
Common LISP on PRIME 50 & Connectionist AI Grad Schools,
Education - AI Graduate Schools,
Philosophy - Computational Complexity,
Binding - Walter Bunch,
Funding - Travel Funding,
Education - Computer Grading and the Law,
Theory - Linguistic Precision & Symbol Grounding
----------------------------------------------------------------------
Date: 1 Jun 87 16:02:51 GMT
From: ihnp4!alberta!calgary!arcsun!greg@ucbvax.Berkeley.EDU (Greg Sidebottom)
Subject: Request for information: uncertainty in ART
I am using ART (from INFERENCE) and I am interested in implementing a
mechanism for dealing with uncertainty. I would like to hear from anybody
who has addressed this problem.
Thanks in advance
Greg
--
Greg Sidebottom, Alberta Research Council
3rd Floor, 6815 8 Street N.E.
Calgary, Alberta CANADA T2E 7H7
(403) 297-2677
UUCP: ...!{ubc-vision, alberta}!calgary!arcsun!greg
------------------------------
Date: 3 Jun 87 03:15:49 GMT
From: eric@eddie.mit.edu (Eric Van Tassell)
Subject: Expert Systems, Debugging and Porting
Hi,
Does anyone have any experience in building expert systems to
assist in porting large C (or any language) programs to new hardware
and OS environments? I am interested in building a system to aid in
porting and debugging a 100K line relational database and 4GL. Please
e-mail to me any info you think might be relevant. (Success, failure,
elation, bitter dejection, or utter frustration) Thanks in advance.
Eric Van Tassell
eric@eddie.mit.edu
------------------------------
Date: 1 Jun 87 20:52:20 GMT
From: tektronix!tekcrl!tekchips!stever@ucbvax.Berkeley.EDU (Steve
Rehfuss)
Subject: sources for June AI Expert
Can someone send me the source code posted for the June issue of AI Expert?
I actually just want the prolog benchmark stuff, if you happen to have it
separated out.
Sorry about this, it expired before I knew I wanted it.
Thanks,
Steve R
stever%tekchips.tek.com@relay.cs.net
------------------------------
Date: 3 Jun 87 10:10:00 EST
From: "LIZ_FONG" <fong@icst-ise>
Reply-to: "LIZ_FONG" <fong@icst-ise>
Subject: Information on AAAI at Seattle
Can some one send me info on AAAI at Seattle on July 13-17
E. Fong <fong@icst-ecf.arpa>
------------------------------
Date: 3 Jun 87 18:35:56 GMT
From: necntc!primerd!doug@ames.arpa (Douglas Rand)
Subject: Common LISP on PRIME 50 Series
I'm interested in people's reaction to Lucid's CL on the Prime. Are people
even aware that this exists?
Doug Rand (...!mit-eddie!primerd!doug, doug@primerd.prime.com)
--
Douglas Rand, Prime Computer Inc. (decvax!necntc!primerd!doug)
-> The above opinions are mine alone and are not influenced by narcotics,
my employer, my cat or the clothes I wear.
------------------------------
Date: 25 May 87 20:00:48 GMT
From: speech2.cs.cmu.edu!yamauchi@pt.cs.cmu.edu (Brian Yamauchi)
Subject: Connectionist AI Grad Schools
I will be graduating from Carnegie-Mellon next May, with a BS in applied
math/computer science, and I am planning to attend graduate school with the
goal of a PhD in computer science.
My field of interest is artificial intelligence, specifically, connectionist
artificial intelligence. I am currently consdiering Carnegie-Mellon, MIT,
Caltech, Stanford, UCSD, and the University of Rochester. Are there any
other universities that I should be considering? Are there any universities
conducting connectionist AI research that I have missed?
I would greatly appreciate any information that anyone could provide. Also,
I would be interested in hearing any opinions about the relative merits of
the computer science graduate programs at these universities, both in
general and relative to my specific interests.
Thanks in advance,
Brian Yamauchi
Brian Yamauchi ARPANET: yamauchi@speech2.cs.cmu.edu
Carnegie-Mellon University
Computer Science Department
------------------------------
Date: 2 Jun 87 02:48:13 GMT
From: decvax!dartvax!takis@ucbvax.Berkeley.EDU (Takis Metaxas)
Subject: Re: Need info on grad schools with a good AI program
From my experience, I can point out to you two schools with
some projects in AI: Brown Univ. in Prov.,RI has speciality in
natural language representation, and Carnegie-Mellon in searching.
Good luck with the field you have chosen...
[See back issues of AI Magazine and the SIGART Newsletter for
descriptions of many graduate programs. -- KIL]
------------------------------
Date: Tue, 2 Jun 87 04:43:53 EDT
From: Jim Hendler <hendler@brillig.umd.edu>
Subject: Re: philosophy and computational complexity
I second the suggestion of the Cherniak paper. If you want a more complete
work try
CHristopher Cherniak, Minimal Rationaliy
I believe it is MIT Press 87.
------------------------------
Date: 1 Jun 87 09:56:12 GMT
From: mcvax!ukc!its63b!hwcs!aimmi!walt@seismo.css.gov (Walter Bunch)
Subject: Conceptual Information Research
When I made my original posting, my .signature address was incorrect. Thanks
to those who got their response to me anyway. Our address changed recently.
Sorry for the trouble.
--
Walter Bunch, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
UUCP: walt@uk.ac.hw.cs
ARPA: walt%cs.hw.ac.uk@cs.ucl.ac.uk
JANET: walt@uk.ac.hw.cs "Is that you, Dave?"
------------------------------
Date: Tue, 2 Jun 87 15:24:37 BST
From: "G. Joly" (Birkbeck) <gjoly@Cs.Ucl.AC.UK>
Subject: Travel Funding.
With reference to the articles on information on financial
support to travel to Milan for IJCAI-87, the following are
possible sources of support.
(1) Royal Society (U.K. residents and Ph.D. status only).
(2) British Computer Society (members only).
(3) AI and Simulation of Behaviour (members only).
(4) AAAI (members only?).
In the case of (1) above, the passing date has already gone,
but the information may be of use in the future. Most
professional bodies seem to have some funds available to
their own members.
I am not 100% sure of all of the above, but hope this short
list is a start (does anyone have a larger collection?).
Gordon Joly,
Computer Science,
Birkbeck College,
Malet Street,
LONDON WC1E 7HX.
+44 1 631 6468
ARPA: gjoly@cs.ucl.ac.uk
BITNET: UBACW59%uk.ac.bbk.cu@AC.UK
UUCP: ...!seismo!mvcax!ukc!bbk-cs!gordon
------------------------------
Date: Wed, 3 Jun 87 10:48:31 PDT
From: Neil Hunt <spar!hunt@decwrl.DEC.COM>
Subject: Re: Computer Grading and the Law
In V5 #135, Laurence Leff <leff%smu.csnet@RELAY.CS.NET>
makes a point about computer grading of student essays.
He proposes that using computers to grade essays on a first
pass, with "some procedure for complaints to be made to a
human being with an appropriate hearing" and that the com-
puter "must in some way indicate how the grade was deter-
mined".
I think that he has missed the point of earlier discussions
expressing concern over the educational consequences of hav-
ing students orient their efforts towards pleasing a machine
rather than a human grader. I believe that the real lesson
that students would learn in this situation, is that it is
much simpler to write their essays in a style that would
satisfy the mechanical grader than to pursue rectification
of their grades by requesting a hearing with a human. In
fact, most students would probably soon discover how to beat
the machine at its own game, writing in a style which would
be unacceptable to a human grader, but which a machine with
rules of a limited scope might grade highly.
The opposite side of the coin, however, as most students are
aware, is that human graders all have their own preferences
and foibles. Students do learn to avoid certain techniques
and foster others just because their human graders seem to
dislike the former and like that latter, even if these feel-
ings are not representative of all graders. The advantage of
human involvement is that the scope of the human includes an
understanding of this very problem, thereby providing a curb
on the possibility of either the teacher or the student
exploiting the situation too far.
Of course, the problem is a characteristic of our society,
as one's work is always judged by people with prejudices and
biases. I believe that before we introduce additional com-
puterised agents of judgement, we should have a good under-
standing of all the problems they might pose.
This is not to say that mechanical style checkers do not
have their place. Perhaps all students should have the
option of using such a tool before submitting their work to
the human grader, but they should be encouraged to under-
stand its limitations as well as its strengths, and avoid
falling into the trap of assuming that if the machine liked
their essay, that the intended readership would also like
it.
Perhaps it is a little premature to be considering the
legality of using computerised grading systems. I am sure
that there are many legal options available to teachers and
graders which we would not expect them to utilise if they
were not effective teaching and learning tools. I think that
the desirability of using such an option should be
established before time is wasted debating whether it is
legal.
Neil/.
These are my own opinions and not those of my employer etc.
------------------------------
Date: 2 Jun 87 00:39:52 GMT
From: hoptoad!laura@ucbvax.Berkeley.EDU (Laura Creighton)
Reply-to: hoptoad!laura@ucbvax.Berkeley.EDU (Laura Creighton)
Subject: Re: framing problems
In article <8705280722.AA09419@ucbvax.Berkeley.EDU> DAVIS@EMBL.BITNET writes:
>
>I'd like to briefly say that perhaps an even more astounding problem
>than that proposed by Stevan Harnad is that connected with the means by
>which literate, intelligent and interested persons can totally obscure
>the central core of an idea by the use of unnecessarily obtuse jargon.
>
>If we're going to discuss the more philosphical end of AI (*yes please!*),
>then we don't *have* to throw everyone else off the track by bogging
>down the chat in a maze of terms intended to have *such* a precise meaning
>as to prevent anyone but the author from truly grasping the intended meaning.
Precision is a good thing. If one can say precisely what one means then
one will not be misunderstood. This, alas, is a pipe dream. There
is no way to say precisely what one means -- what one says does not
have precise meaning embedded in the words or the relationships between
the words. Rather, one shares a linguistic context with one's
audience. This means that the serach for precision is never ending.
Right now there are a good number of people who want to talk about
``psychic energy'' and ``interpersonal energy'' and the like.
Reguardless of what these people mean by these terms, it is clear that
they do not mean m c-squared. The search for precision continues.
--
(C) Copyright 1987 Laura Creighton - you may redistribute only if your
recipients may.
``One must pay dearly for immortality: one has to die several
times while alive.'' -- Nietzsche
Laura Creighton
ihnp4!hoptoad!laura utzoo!hoptoad!laura sun!hoptoad!laura
------------------------------
Date: 2 Jun 87 12:54:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: physical invertibility and symbol grounding
S. Harnad writes:
> Now I conjecture that it is this physical invertibility -- the possibility
> of recovering all the original information -- that may be critical in
> cognitive representations. I agree that there may be information loss in
> A/A transformations (e.g., smoothing, blurring or loss of some
> dimensions of variation), but then the image is simply *not analog in
> the properties that have been lost*! It is only an analog of what it
> preserves, not what it fails to preserve.....
>
> A strong motivation for giving invertibility a central role in
> cognitive representations has to do with the second stage of A/D
> conversion: symbolization. The "symbol grounding problem" that has
> been under discussion here concerns the fact that symbol systems
> depend for their "meanings" on only one of two possibilities: One is
> an interpretation supplied by human users -- "`Squiggle' means `animal' and
> `Squoggle' means `has four legs'" -- and the other is a physical, causal
> connection with the objects to which the symbols refer. ....
>
> The reason the invertibility must be physical rather than merely
> formal or conceptual is to make sure the system is grounded rather
> than hanging by a skyhook from people's mental interpretations.
I wonder why the grounding is to depend on invertibility rather than
causation and/or resemblance? Isn't it true that physically distinct
kinds of light (eg. #1 red-wavelength and green-wavelength vs.
#2 yellow-wavelength) can cause completely indistinguishable
sensations (ie subjective yellow)? Is this not, then, a non-invertible,
but nonetheless grounded sensation? When I experience something as
yellow, I have no way short of spectroscopy of knowing what the
"real" physical characteristics are of the light. Nonetheless,
I know what "yellow" means, as do young children, scientifically
naive people, etc.
I don't have a ready-made candidate to substitute for invertibility as a
basis for symbol-grounding, although I suspect, as mentioned above,
that causation and resemblance are lurking around somewhere.
But how can invertibility serve if in fact our sensations are, in general,
not invertible?
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: Tue, 2 Jun 87 13:48:51 pdt
From: ladkin@kestrel.ARPA (Peter Ladkin)
Subject: symbol grounding
stevan harnad writes guardedly:
> perhaps there was an element of incoherence in all but the most
> technical and restricted of signal-analytic candidates.
for the record, my suggestion was not signal-analytic, and no-one
showed any element of technical incoherence. however, it was met
with resounding uninterest, since it was a distinction from logic.
since most people want an inherent distinction, i.e. one that
maintains under translations and coding, my suspicion is still that
technical logic and complexity theory, not signal processing, is the
place to look for a solution.
peter ladkin
ladkin@kestrel.arpa
------------------------------
End of AIList Digest
********************
∂10-Jun-87 0244 LAWS@Stripe.SRI.Com AIList Digest V5 #139
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Jun 87 02:44:45 PDT
Date: Wed 10 Jun 1987 00:13-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #139
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 10 Jun 1987 Volume 5 : Issue 139
Today's Topics:
Conference - AAAI's Preregistration Deadline,
Binding - Number Theory Net,
Queries - Small Expert Systems & Speech Data Compression &
Dominoes & Hofstadter's Waking Up From the Boolean Dream,
Theory - Applying AI Models to Biology
----------------------------------------------------------------------
Date: Thu, 4 Jun 87 10:23:18 PDT
From: AAAI <AAAI-OFFICE@SUMEX-AIM.STANFORD.EDU>
Subject: AAAI's Preregistration Deadline
The AAAI would like to remind those individuals interested in attending
AAAI-87 in Seattle, July 13-17, that the preregistration deadline of Friday,
June 12, draws very near. If you would like registration materials, please
call or send us a msg with your name and mailing address. Thanks!
AAAI
445 Burgess Drive
Menlo Park, CA 94025
(415) 328-3123
AAAI-Office@sumex-aim.stanford.edu
------------------------------
Date: 5 Jun 1987 16:45:12-EDT (Friday)
From: "Victor S. Miller" <VICTOR%YKTVMX.BITNET@forsythe.stanford.edu>
Reply-to: THEORYNT%YKTVMX.BITNET@forsythe.stanford.edu
Subject: Number Theory Net
[Forwarded from the Stanford bboard.]
Announcing Number Theory Net
I would like to start a separate network for Number Theorists
around the world. This would be similar in principle to Theory Net (and
probably have some overlap). The purpose of NumberTheory Net would be
to help communication among those who work in number theory. Appropriate
submissions would be: problems, solutions, queries, notification of
address changes, announcement of results, etc. For now, all submissions
will be handled by the same userids as for TheoryNet: TheoryNet@ibm.com
or theorynt@yktvmx.bitnet for submissions, and TheoryNet-Request@ibm.com
or theorynt@yktvmx.bitnet for administrative matters (e.g. additions or
deletions to the subscriber list, requests for back submissions, etc.).
All contributions should be clearly labeled as being for NumberTheoryNet.
I think that it should be useful and enlightening.
Victor S. Miller -- moderator
------------------------------
Date: 5 Jun 87 13:52:47 GMT
From: salveter@bu-cs.bu.edu (Sharon Salveter)
Subject: Need small expert system for research
I am directing a research project on knowledge transfer for expert
systems. Essentially, we are trying to automate the function of
the knowledge engineer in classification-type expert systems. We
are looking for small (fewer than 1000 rules) existing expert systems
to use as our domains and testbeds/benchmarks. If you have such a system
that you would like to donate to research, please contact me.
Sharon Salveter Computer Science Boston University
------------------------------
Date: 2 Jun 87 22:10:53 GMT
From: imagen!auspyr!dlb!dana!rap@ucbvax.Berkeley.EDU (Rob Peck)
Subject: Speech Data Compression
I am interested in finding some kind of data compression algorithm
that is suitable for compressing speech data. As I understand it,
human speech has a great deal of redundancy to it, i.e. repetitions
of virtually the same waveforms over a period of time, as well
as slow changes in many cases from one waveform to the next.
However, if one takes a set of audio samples of a spoken word,
the samples will not fall in the right spots to show up any such
redundancy. Thus, for a simplistic compression algorithm that
looks for repeated sequences, no opportunity to compress would
be noticed.
Could someone point me to the appropriate literature? Or is there
some public domain source code that is already available for this?
The code needn't be fast on the analysis and compression. On
playback, it should be pretty easy to expand, though. That is,
play so many repetitions of this waveform at this sampling rate,
then do this next one (or better still, adjust the current waveform
until it looks like this new one, as a slewing to the new output...
that'd be neat).
I've read a little about FFT's, but once calculated, I have no
idea how to use it or if it gives me remotely what I am looking
for here.
Please EMAIL directly to me. I will summarize any interesting
responses to the Net. Thanks very much.
Rob Peck ...ihnp4!hplabs!dana!rap
------------------------------
Date: 8 Jun 87 19:46:16 GMT
From: ai!gautier@rsch.wisc.edu (Jorge Gautier)
Subject: WANTED: references on the game of dominoes
I am looking for references on computer implementations of the game of
dominoes. I suspect there are many variations on the rules for this game,
but any pointers to papers, commercial products, Ph.D. theses :-), etc.
would be much appreciated. Please reply by mail.
Jorge Gautier
gautier@ai.wisc.edu
"America is waiting for a message of some sort or another."
------------------------------
Date: Tue, 09 Jun 87 11:26:42 n
From: DAVIS%EMBL.BITNET@wiscvm.wisc.edu
Subject: digging up the garbage....
Ok, here's a quick query for old timers on the AIList (no prizes KIL for
being the first in line). Did the list ever show much of a response to
Doug Hofstadter's "Waking up From the Boolean Dream or, Subcognition as
Computation" ? Yes, yes - I know thats it a wet, cloudy, amorphous piece
of writing, utterly unpublishable in any journal beginning with the
name "Transactions of....", but nevertheless, Hoftstadter's criticism
of 'traditional' AI ("high church computationalism") still seems well in
place amidst the countless "has anyone seen expert system EXSYS yet ?"
and "any clues on dealing with uncertainty within the context of a
WHITEWASH based frame-solving fourth generation language ?" that
dominate the list......
I don't want to dig up the past, but if it hasn't happened before, are there
any defenders of the EXSYS/4GL/"fuzzy reasoning"/etc., etc., approach willing to
correct my impressions of the right direction for movement ?
Or even just give me a few recent, decent rebuffs to Hofstadter's viewpoint ?
yours in statistical emergence,
paul davis
"i wash my own clothes, i wash my own hair, i wash my own opinions"
nb: but my employers provide the washing machine, the shower & the computer.
davis@embl.bitnet
------------------------------
Date: 6 Jun 87 01:38:26 GMT
From: mnetor!yetti!unicus!craig@seismo.css.gov (Craig D. Hubley)
Subject: Taking AI models and applying them to biology...
Forgive the wide cross posting, net.gods, but I am interested in gathering
an opinion from biological and artifical intelligence people on a model
that arises from AI but has (possibly) biological implications:
Foreword or WHY I'M WRITING THIS.
--------------------------------
I was semi-surprised in recent months to discover that cognitive psychology,
far from developing a bold new metaphor for human thinking, has (to a degree)
copied at least one metaphor from third-generation computer science.
This description of the human memory system, though cloaked in vaguer terms,
corresponds more or less one-to-one with the traditional computer
architecture we all know and love. To wit:
- senses have "iconic" and "echo" memories analogous to buffers.
- short term memory holds information that is organized for quick
processing, much like main storage in a computing system.
- long term memory holds information in a sort of semantic
association network where large related pieces of information
reside, similar to backing or "archived" computing storage.
At least this far, this theory appears to owe a lot to computer science.
Granted, there is lots of empirical evidence in favour, but we all know
how a little evidence can go far too far towards developing an analogy.
What I think we may need are good parallel connectionist computing models
for the social sciences to copy, rather than these old ones that we are
beginning to fuse and modify and discard. After all, engineering can
construct and test artifacts much quicker than psychologists can. And
investigate their insides and their performance as well...
The Point or WHAT I'M THINKING ABOUT
------------------------------------
Single cells are constructed according to instructions resident
in their own DNA. When their reproductive process fails, they
die, become cancerous, etc...
In computing terms, a self-reproducing program messes up the code
and therefore fails to function (it does not reproduce). Or, it may
continue to reproduce a flawed cell (cancer...).
But a biological mechanism such as, say, a muscle or a brain is
a massively parallel system consisting of many many redundant cells,
each of which is capable of performing (at least almost) the same
function.
So many many parts would have to fail before the effect was enough
to endanger the system as a whole. That is, it degrades gracefully.
This effect has been observed in parallel sensing systems, which
use several low-resolution phased fields that redundantly cover
the same area. Removing one such field results in a loss of
resolution, but not utter failure to detect a stimulus. Details
in Geoffrey Hinton and others... (Byte AI issue, 1985?)
At some point of degradation, the whole parallel system will collapse.
Or an aged human being will die of a cold.
The Question or WHAT DO YOU THINK?
----------------------------------
Apparently, all human organ weights begin to decline shortly after puberty.
The cumulative effect of this seeming reduction of resources isn't felt so
strongly until middle-age, when we become more susceptible to disease.
So far, this is just a statement of the nature of parallel systems.
But does it hold up as a theory of aging?
- Is mitosis sufficiently prone to failure to account for organ decline?
- Statistically, one would expect exponential distribution for
failure of single cells, the rate dependent on mitosis failure,
and perhaps modified by other cell-killing factors
- Does organ failure, medically, occur at the point where
a parallel processing system, mathematically, would fail?
I've heard that mammal cells appear to suffer a "hard" reproductive limit
of 52 mitosis operations, and that meiosis "resets this counter" to 0.
- any comment on this, bio-med types? Is it true?
- Would a theory assuming a simple variable or random "counter" in each cell
limiting its reproductive span better explain aging (programmed cells...)
It doesn't seem so... regardless of the origin of the failure, the observed
degradation of the system as a whole would still follow this pattern.
The upshot of this is that a potentially useful life science model may have
just materialized in artificial intelligence.
The main flaw that I can see in it is that a cell is complex mechanism in
and of itself, and so the success/failure of each might be subject to
many factors in parallel as well. That is, it might not fail the way a
short subroutine would were it copied badly, which is the gist of this.
But then one might find a lower level where the parts were sufficiently
monolithic that the analogy held.
This seems to kick the butt of the good old 'Entropy' theory... cop-out.
Incompentent nineteenth century philosophers leaned heavily on entropy.
Comments? Flames? The name of a good shrink?
Musing,
Craig.
------------------------------
Date: 10 Jun 87 02:49:55 GMT
From: hao!boulder!pell@husc6.harvard.edu (Anthony Pelletier)
Subject: Re: Taking AI models and applying them to biology...
(Craig D. Hubley) writes:
(cognative psycology)
>far from developing a bold new metaphor for human thinking, has (to a degree)
>copied at least one metaphor from third-generation computer science.
>
one of the things that has always amused me is that, to the extent that
I understand the structuring of computers, it seems that the cell
and the computer scientists have come up with similar solutions to
many of the same questions. This is particularly true when one looks
at information flow in the cell. I feel comfortable in assuming that
the cell had little help from the CS types in solving problems of information
flow.
It is likely to be true that contemporaries of in different scientific
fields play with each other's ideas. This is why "Nature" insists on being so
broad and why F.H.C.C. can get work.
But I should stay more to the point.
>The Question or WHAT DO YOU THINK?
>----------------------------------
>Apparently, all human organ weights begin to decline shortly after puberty.
>The cumulative effect of this seeming reduction of resources isn't felt so
>strongly until middle-age, when we become more susceptible to disease.
>- Is mitosis sufficiently prone to failure to account for organ decline?
>
>I've heard that mammal cells appear to suffer a "hard" reproductive limit
>of 52 mitosis operations, and that meiosis "resets this counter" to 0.
>
It would seem to me that the step that is likely to give the cell trouble
is not mitosis but DNA replication. If a whole chromosome lost or
non-disjoined, that cell is in some serious trouble. Progressive
accumulation mistakes through replication and general maintanence seems a more
likely culprit.
I confess that once the topic turns to outside the single cell or involves
more than, say, two cells, I am hopelssly lost.
So the question of aging is outside my capabilities. This will not, of course,
stop me from volenteering the following:
I have never liked the "hard-wired-number-of-mitosis" model.
I am not sure why; it just seems implausible, or worse yet, unecessary.
Supposedly "immortal" cells, like bacteria, actually have a rather high death
rate in the population (try doing a particle count then plating them out to see
how many are actually able to continue dividing).
Their apparent immortality is the result of unrestrained growth.
I suspect the failure rate is similar between bacteria and individual cells
of a metazoan. The difference may be simply that a metazoan cannot tolerate
unrestrained growth of cell populations. The cells are forced to stop
dividing when in contact with other cells. they can be induced to re-enter
the cycle by growth factors released, for example, when the skin is cut.
I would guess that if one coupled the limitations on growth necessary to
be a metazoan with accumulated errors, both during replication and
simple maitanence, one could explain gradual breakdown of tissue without
invoking the "hard-wire" model.
oh well, I've gone on too long already.
tony (few degrees are worth remembering--and none are worth predicting)
Pelletier
Molecular etc. Bio
Boulder, Co. 80309-0347
P.S. I think alot about information flow problems and would enjoy
discussions on that...if anyone wants to chat.
------------------------------
End of AIList Digest
********************
∂10-Jun-87 0507 LAWS@Stripe.SRI.Com AIList Digest V5 #141
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Jun 87 05:07:01 PDT
Date: Wed 10 Jun 1987 00:29-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #141
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 10 Jun 1987 Volume 5 : Issue 141
Today's Topics:
Theory - The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 5 Jun 87 17:12:10 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem
In reply to my objection that
>> invertibility has essentially *nothing* to do with the difference
>> between analog and digital representation according to anybody's
>> intuitive use of the terms
Stevan Harnad (harnad@mind.UUCP) writes in message <792@mind.UUCP>:
>There are two stages of A/D even in the technical sense. ... Unless the
>original signal is already discrete, the quantization phase involves a
>loss of information. Some regions of input variation will not be retrievable
>from the quantized image. The transformation ... cannot be inverted so as to
>recover the entire original signal.
Well, what I think is interesting is not preserving the signal itself but
rather the *information* that the signal carries. In this sense, an analog
signal conveys only a finite amount of information and it can in fact be
converted to digital form and back to analog *without* any loss.
But in any case the point I've been emphasizing remains: the A/A
transformations you envisage are not going to be perfect (no "skyhooks" now,
remember?), so preservation or loss of information alone won't distinguish an
(intuitively) A/A from an A/D transfomation. I think the following reply to
this point only muddies the waters:
> I agree that there may be information loss in
>A/A transformations (e.g., smoothing, blurring or loss of some
>dimensions of variation), but then the image is simply *not analog in
>the properties that have been lost*! It is only an analog of what it
>preserves, not what it fails to preserve.
You can take this line if you like, but notice that the same is true of a
*digitized* image -- in your terms, it is "analog" in the information it
preserves and not in the information lost. This seems to me to be a very
unhappy choice of terminology!
Both analog and digitizing transformations must preserve *some* information.
If all you're *really* interested in is the quality of being (naturally)
information-preserving (i.e. physically invertible), than I'd strongly
recommend you just use one of these terms and drop the misleading use of
"analog", "iconic", and "digital".
> The "symbol grounding problem" that has
>been under discussion here concerns the fact that symbol systems
>depend for their "meanings" on only one of two possibilities: One is
>an interpretation supplied by human users... and the other is a physical,
>causal connection with the objects to which the symbols refer.
>The surprising consequence is that a "dedicated system" -- one that is
>hard-wired to its transducers and effectors... may be significantly different
>from the very *same* system as an isolated symbol-manipulating module,
>cut off from its peripherals ...
With regard to this "symbol grounding problem": I think it's been
well-understood for some time that causal interaction with the world is a
necessary requirement for artificial intelligence. Recall that in his BBS
reply to Searle, Dennett dismissed Searle's initial target -- the "bedridden"
form of the Turing test -- as a strawman for precisely this reason. (Searle
believes his argument goes through for causally embedded AI programs as well,
but that's another topic.)
The philosophical rationale for this requirement is the fact that some causal
"grounding" is needed in order to determine a semantic interpretation. A
classic example is due to Georges Rey: it's possible that a program for
playing chess could, when compiled, be *identical* to one used to plot
strategy in the Six Day War. If you look only at the formal symbol
manipulations, you can't distinguish between the two interpretations; it's
only by virtue of the causal relations between the symbols and the world that
the symbols could have one meaning rather than another.
But although everyone agrees that *some* kind of causal grounding is
necessary for intentionality, it's notoriously difficult to explain exactly
what sort it must be. And although the information-preserving
transformations you discuss may play some role here, I really don't see how
this challenges the premises of symbolic AI in the way you seem to think it
does. In particular you say that:
>The potential relevance of the physical invertibility criterion
>would only be to cognitive modeling, especially in the constraint that
>a grounded symbol system must be *nonmodular* -- i.e., it must be hybrid
>symbolic/nonsymbolic.
But why must the arrangement you envision must be "nonmodular" ? A system
may contain analog and digital subsystems and still be modular if the
subsytems interact solely via well-defined inputs and outputs.
More importantly -- and this is the real motivation for my terminological
objections -- it isn't clear why *any* (intuitively) analog processing need
take place at all. I presume the stance of symbolic AI is that sensory input
affects the system via an isolable module which converts incoming stimuli
into symbolic representations. Imagine a vision sub-system that converts
incoming light into digital form at the first stage, as it strikes a grid of
photo-receptor surfaces, and is entirely digital from there on in. Such a
system is still "grounded" in information-preserving representations in the
sense you require.
In short, I don't see any *philosophical* reason why symbol-grounding
requires analog processing or a non-modular structure.
Anders Weinstein
BBN Labs
------------------------------
Date: 7 Jun 87 18:25:00 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
aweinste@Diamond.BBN.COM (Anders Weinstein)
of BBN Laboratories, Inc., Cambridge, MA writes:
> [regarding invertibility, information preservation and the A/D
> distinction]: what I think is interesting is not preserving the
> signal itself but rather the *information* that the signal carries.
> In this sense, an analog signal conveys only a finite amount of
> information and it can in fact be converted to digital form and back
> to analog *without* any loss.
This is an important point and concerns a matter that is at the heart
of the symbolic/nonsymbolic issue: What you're saying is appropriate for
ordinary communication theory and communication-theoretic
applications such as radio signals, telegraph, radar CDs, etc. In all these
cases the signal is simply a carrier that encodes information which is
subsequently decoded at the receiving end. But in the case of human
cognition this communication-theoretic model -- of signals carrying
messages that are encoded/decoded on either end -- may not be
appropriate. (Formal information theory has always had difficulties
with "content" or "meaning." This has often been pointed out, and I take
this to be symptomatic of the fact that it's missing something as a
candidate model for cognitive "information processing.")
Note that the communication-theoretic, signal-analytic view has a kind of
built-in bias toward digital coding, since it's the "message" and not
the "medium" that matters. But what if -- in cognition -- the medium
*is* the message? This may well be the case in iconic processing (and
the performances that it subserves, such as discrimination, similarity
judgment, matching, short-term memory, mental rotation, etc.): It may
be the structure or "shape" of the physical signal (the stimulus) itself that
matters, not some secondary information or message it carries in coded
form. Hence the processing may have to be structure- or shape-preserving
in the physical analog sense I've tried to capture with the criterion
of invertibiliy.
> a *digitized* image -- in your terms... is "analog" in the
> information it preserves and not in the information lost. This
> seems to me to be a very unhappy choice of terminology! Both analog
> and digitizing transformations must preserve *some* information.
> If all you're *really* interested in is the quality of being
> (naturally) information-preserving (i.e. physically invertible),
> than I'd strongly recommend you just use one of these terms and drop
> the misleading use of "analog", "iconic", and "digital".
I'm not at all convinced yet that the sense of iconic and analog that I am
referring to is unrelated to the signal-analytic A/D distinction,
although I've noted that it may turn out, on sufficient analysis, to be
an independent distinction. For the time being, I've acknowledged that
my invertibility criterion is, if not necessarily unhappy, somewhat
surprising in its implications, for it implies (1) that being analog
may be a matter of degree (i.e., degree of invertibility) and (2) even
a classical digital system must be regarded as analog to a degree if
one is considering a larger "dedicated" system of which it is a
hard-wired (i.e., causally connected) component rather than an
independent (human-interpretation-mediated) module.
Let me repeat, though, that it could turn out that, despite some
suggestive similarities, these considerations are not pertinent to the
A/D distinction but, say, to the symbolic/nonsymbolic distinction --
and even that only in the special context of cognitive modeling rather than
signal analysis or artificial intelligence in general.
> With regard to [the] "symbol grounding problem": I think it's been
> well-understood for some time that causal interaction with the world
> is a necessary requirement for artificial intelligence...
> The philosophical rationale for this requirement is the fact that
> some causal "grounding" is needed in order to determine a semantic
> interpretation... But although everyone agrees that *some* kind of
> causal grounding is necessary for intentionality, it's notoriously
> difficult to explain exactly what sort it must be. And although the
> information-preserving transformations you discuss may play some role
> here, I really don't see how this challenges the premises of symbolic
> AI in the way you seem to think it does.
As far as I know, there have so far been only two candidate proposals
to overcome the symbol grounding problem WITHOUT resorting to the kind
of hybrid proposal I advocate (i.e., without giving up purely symbolic
top-down modules): One proposal, as you note, is that a pure
symbol-manipulating system can be "grounded" by merely hooking it up
causally in the "right way" to the outside world with simple (modular)
transducers and effectors. I have conjectured that this strategy
will not work in cognitive modeling (and I have given my supporting
arguments elsewhere: "Minds, Machines and Searle"). The strategy may work
in AI and conventional robotics and vision, but that is because these
fields *do not have a grounding problem*! They're only trying to generate
intelligent *pieces* of performance, not to model the mind in *all* its
performance capacity. Only cognitive modeling has a symbol grounding
problem.
The second nonhybrid way to try to ground a purely symbolic system in
real-world objects is by cryptology. Human beings, knowing already at least
one grounded language and its relation to the world, can infer the meanings
of a second one [e.g., ancient cuneiform] by using its internal formal
structure plus what they already know: Since the symbol permutations and
combinations of the unknown system (i.e., its syntactic rules) are constrained
to yield a semantically interpretatable system, sometimes the semantics can be
reliably and uniquely decoded this way (despite Quine's claims about the
indeterminacy of radical translation). It is obvious, however, that such
a "grounding" would be derivative, and would depend entirely on the
groundedness of the original grounded symbol system. (This is equivalent
to Searle's "intrinsic" vs. "derived intentionality.") And *that* grounding
problem remains to be solved in an autonomous cognitive model.
My own hybrid approach is simply to bite the bullet and give up on the
hope of an autonomous symbolic level, the hope on which AI and symbolic
functionalism had relied in their attempt to capture mental function.
Although you can get a lot of clever performance by building in purely
symbolic "knowledge," and although it had seemed so promising that
symbol-strings could be interpreted as thoughts, beliefs, and mental
propositions, I have argued that a mere extension of this modular "top-down"
approach, hooking up eventually with peripheral modules, simply won't
succeed in the long run (i.e., as we attempt to approach an asymptote of
total human performance capacity, or what I've called the "Total Turing Test")
because of the grounding problem and the nonviability of the two
"solutions" sketched above (i.e., simple peripheral hook-ups and/or
mediating human cryptology). Instead, I have described a nonmodular
hybrid representational system in which symbolic representations are
grounded bottom-up in nonsymbolic ones (iconic and categorical).
Although there is a symbolic level in such a system, it is not quite
the autonomous all-purpose level of symbolic AI. It trades its autonomy
for its groundedness.
> [W]hy must the arrangement you envision be "nonmodular"? A system
> may contain analog and digital subsystems and still be modular if
> the subsystems interact solely via well-defined inputs and outputs.
I'll try to explain why I believe that a successful mind-model (one
able to pass the Total Turing Test) is unlikely to consist merely of a
pure symbol-manipulative module connected to input/output modules.
A pure top-down symbol system just consists of physically implemented
symbol manipulations. You yourself describe a typical example of
ungroundedness (from Georges Rey):
> it's possible that a program for playing chess could,
> when compiled, be *identical* to one used to plot
> strategy in the Six Day War. If you look only at the
> formal symbol manipulations, you can't distinguish between
> the two interpretations; it's only by virtue of the causal
> relations between the symbols and the world that the symbols
> could have one meaning rather than another.
Now consider two cases of "fixing" the symbol interpretations by
grounding the causal relations between the symbols and the world. In
(1) a "toy" case -- a circumscribed little chunk of performance such as
chess-playing or war-games -- the right causal connections could be
wired according to the human encryption/decryption scheme: Inputs and
outputs could be wired into their appropriate symbolic descriptions.
There is no problem here, because the toy problems are themselves
modular, and we know all the ins and outs. But none but the most
diehard symbolic functionalist would want to argue that such a simple
toy model was "thinking," or even doing anything remotely like what we
do when we accomplish the same performance. The reason is that we are
capable of doing *so much more* -- and not by an assemblage of endless
independent modules of essentially the same sort as these toy models,
but by some sort of (2) integrated internal system. Could that "total"
system be just an oversized toy model -- a symbol system with its
interpretations "fixed" by a means analogous to these toy cases? I am
conjecturing that it is not.
Toy models don't think. Their internal symbols really *are*
meaningless, and hence setting them in the service of generating a toy
performance just involves hard-wiring our intended interpretations
of its symbols into a suitable dedicated system. Total (human-capacity-sized)
models, on the other hand, will, one hopes, think, and hence the
intended interpretations of their symbols will have to be intrinsic in
some deeper way than the analogy with the toy model would suggest, at
least so I think. This is my proposed "nonmodular" candidate:
Every formal symbol system has both primitive atomic symbols and composite
symbol-strings consisting of ruleful combinations of the atoms. Both
the atoms and the combinations are semantically interpretable, but
from the standpoint of the formal syntactic rules governing the symbol
manipulations, the atoms could just as well have been undefined or
meaningless. I hypothesize that the primitive symbols of a nonmodular
cognitive symbol system are actually the (arbitrary) labels of object
categories, and that these labels are reliably assigned to their referents
by a nonsymbolic representational system consisting of (i) iconic (invertible,
one-to-one) transformations of the sensory surface and (ii) categorical
(many-to-few) representations that preserve only the features that suffice to
reliably categorize and label sensory projections of the objects in
question. Hence, rather than being primitive and undefined, and hence
independent of interpretation, I suggest that the atoms of cognitive
symbol systems are grounded, bottom-up, in such a categorization
mechanism. The higher-order symbol combinations inherit the bottom-up
constraints, including the nonsymbolic representations to which they
are attached, rather than being an independent top-down symbol-manipulative
module with its connections to an input/output module open to being
fixed in various extrinsically determined ways.
> it isn't clear why *any* (intuitively) analog processing need
> take place at all. I presume the stance of symbolic AI is that
> sensory input affects the system via an isolable module which converts
> incoming stimuli into symbolic representations. Imagine a vision
> sub-system that converts incoming light into digital form at the
> first stage, as it strikes a grid of photo-receptor surfaces, and is
> entirely digital from there on in. Such a system is still "grounded"
> in information-preserving representations in the sense you require.
> In short, I don't see any *philosophical* reason why symbol-grounding
> requires analog processing or a non-modular structure.
It is exactly this modular scenario that I am calling into question. It
is not clear at all that a cognitive system must conform to it. To get a
device to be able to do what we can do we may have to stop thinking in
terms of "isolable" input modules that go straight into symbolic
representations. That may be enough to "ground" a conventional toy
system, but, as I've said, such toy systems don't have a grounding problem
in the first place, because nobody really believes they're thinking. To get
closer to life-size devices -- devices that can generate *all* of our
performance capacity, and hence may indeed be thinking -- we may have to
turn to hybrid systems in which the symbolic functions are nonmodularly
grounded, bottom-up, in the nonsymbolic ones. The problem is not a
philosophical one, it's an empirical one: What looks as if it's likely
to work, on the evidence and reasoning available?
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
End of AIList Digest
********************
∂10-Jun-87 1219 LAWS@Stripe.SRI.Com AIList Digest V5 #140
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Jun 87 12:15:20 PDT
Date: Wed 10 Jun 1987 00:22-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #140
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 10 Jun 1987 Volume 5 : Issue 140
Today's Topics:
AI Tools - ID3 vs C4 & Expert Systems for CAD,
Comment - Precision in Writing,
Theory - Complexity Theory &
Applying AI Models to Biology &
Symbol Grounding and Physical Invertibility
----------------------------------------------------------------------
Date: 4 Jun 87 13:04:17 GMT
From: reiter@endor.harvard.edu (Ehud Reiter)
Subject: Re: ID3 vs C4
In article <114@upba.UUCP> damon@upba.UUCP (Damon Scaggs) writes:
>I understand that Ross Quinlan, author of the ID3 classification algorithm
>has developed a better version with the designation C4. I am looking for
>any papers or references about this new algorithm as well as any comments
>about what it does better.
The best reference I've seen on statistical algorithms for learning decision
trees is
CLASSIFICATION AND REGRESSION TREES
by L. Breiman, J. Friedman, R. Olshen, C. Stone
Wadsworth Press, 1984
The book makes no specific mention of ID3 or C4, but it gives much more
detail about this class of learning algorithms than I've seen in any of
Quinlan's papers.
I'm posting this reponse to the net because I really do think this is a
superb book.
Ehud Reiter
reiter@harvard (ARPA,BITNET,UUCP)
reiter@harvard.harvard.EDU (new ARPA)
------------------------------
Date: 4 Jun 87 19:16:24 GMT
From: bolasov@athena.mit.edu (Benjamin I Olasov)
Reply-to: aphrodite!bolasov@RUTGERS.EDU (Benjamin I Olasov)
Subject: Re: Wanted: Information on current work in Expert Systems
for CAD
In article <8705300459.AA08391@ucbvax.Berkeley.EDU> SPANGLER@gmr.COM writes:
>I am beginning a survey of the current status of work in applying Expert
>Systems technology to Computer Aided Design. This survey is being done
>for the Knowledge Engineering group at General Motors.
>
>I would greatly appreciate any descriptions of or references to research
>in this area, as well as information on what CAD expert systems and
>expert system shells are available for purchase.
>
> -- Scott Spangler, spangler@gmr.com
> -- Advanced Engineering Staff, GM
I just finished writing a master's thesis on just this topic, however
it focuses primarily on applications for architectural practice,
especially design with a structural pre-cast concrete panel system.
You may also write or send e-mail to Professor Sriram in the Civil
Engineering Department here at MIT who has written an expert system
for structural design called DESTINY. His e-mail address is
sriram@athena.mit.edu- mine is bolasov@aphrodite.mit.edu or
Olasov@MIT-MULTICS.ARPA.
Good luck!
Ben
------------------------------
Date: Tue, 09 Jun 87 11:26:05 n
From: DAVIS%EMBL.BITNET@wiscvm.wisc.edu
Subject: precision in writing
I have no wish to make a big deal out of this point, but I feel that Laura
Creighton's remarks on precision in writing/expression must be dealt with.
She writes:
> Precision is a good thing. If one can say precisely what one means then
> one will not be misunderstood. This, alas, is a pipe dream. There
> is no way to say precisely what one means -- what one says does not
> have precise meaning embedded in the words or the relationships between
> the words. Rather, one shares a linguistic context with one's
> audience. This means that the serach for precision is never ending.
I'm afraid that there is a gross difference between the precise delineation
of an idea, and over-precise word usage. To be sure, all of human activity
is constantly capable of generating new words, and new uses for old words
(radical! barf! hack! bug!) - but this alone does not justify the
`jargonising' of debate. I believe that if two (or more) people wish to
debate any issue, then they have a responsibility to do so on as much common
ground as humanly possible. You think that Bertrand Russel was any less
capable of a meaningful debate on various aspects of philosphy/cognition
because he didn't have access to computerese ? The delineation of an idea
is capable of being precise through carefully chosen analogy and metaphor.
Such a route is actually better than jargonising since the writer/speaker
stands a better chance of getting the audience to appreciate the *core*
of an idea, rather than sit back satisfied that they *think* they understand
his words......
Sorry to go on on this one, but so much of the debate in and around
AI/cognitive science/philosphy of mind gets bogged down by people jargonising
their positions, which forces replies to first hack through the cloud
that surrounds potentially good (or bad) opinions.
yours for jargon free AI,
paul davis
"i wash my own clothes, i wash my own hair, i wash my own opinions"
nb: but my employers provide the washing machine, the shower & the computer
davis@embl.bitnet
------------------------------
Date: 3 Jun 87 17:15:21 GMT
From: mcvax!botter!klipper!biep@seismo.css.gov (J. A. "Biep" Durieux)
Subject: What philosophical problems does complexity theory yield?
Suppose P != NP. Then some things will take a long time to compute.
But so what?
Suppose someone finds out not all problems can be solved in constant
time. Now that comes as a philosophical shock, of course. That has
lots of implications.
But once one has overcome that shock, finding that some problems cannot
be solved in linear time may be annoying, but now since the possibility
of constant time already has been destroyed, it's no great news.
As, one by one, all sorts of upper bounds on exponents prove false, and
finally it seems polynomial time isn't good at all, one gets even bored
by all those variations on the same theme, not? So what exactly is so
exciting about that polynomial limit?
About constant time solutions: Seemingly linear-time solutions can often be
turned into constant-time solutions by applying parallelism. This is the
way the universe is able to simulate itself, however big it (object) may
be or grow. I don't know of what complexity the collapsing of a wave-
function would be supposed that all "time-space-points" of it worked
parallelly on it.
But, isn't anything which cannot be turned into a constant-time process
philosophically annoying? Why just hassling about non-polynomial time
solutions? Am I missing something? (Shouldn't I have asked that at the
beginning of this article? :-))
--
Biep. (biep@cs.vu.nl via mcvax)
Popper tells us how science ought to be done - Kuhn tells us how it *is* done.
And I ... I read neither.
------------------------------
Date: 4 Jun 87 16:09:44 GMT
From: ramesh@cvl.umd.edu (Ramesh Sitaraman)
Subject: Re: What philosophical problems does complexity theory yield?
In article <789@klipper.cs.vu.nl> biep@cs.vu.nl (J. A. "Biep" Durieux) writes:
>But, isn't anything which cannot be turned into a constant-time process
>philosophically annoying? Why just hassling about non-polynomial time
>solutions? Am I missing something? (Shouldn't I have asked that at the
>beginning of this article? :-))
>--
Yes, you are missing the point !!
The difference between a polynomial and non-polynomial solution for
a problem is the difference between structure and a complete lack
of it. If P not = NP we would have shown that some problems can be
solved only by something similar to a dumb exhaustive search over
the solution space i.e. there is not enough structure in the
problem to constrain its solutions.
Graph theorists have found eulerian circuits very interesting
and there have been very strong theorems proved about graphs
with this property. However, the seemingly similar problem
of Hamiltonian circuits have almost no characterisation inspite
of dilligent efforts for the past 100 years or so. The theory of
NP-completeness explains this anomaly. Eulerian circuit can be
solved in linear time while Hamiltonian circuit is NP-complete !!!
Ramesh
(Defn:
Eulerian ckt: A circuit passing through all edges of a graph
without repeating an edge.
Hamiltonian ckt: A circuit passing through all the vertices
of a graph without repeating a vertex.
)
------------------------------
Date: 6 Jun 87 20:52:53 GMT
From: umnd-cs!umn-cs!moll@ucbvax.Berkeley.EDU (Rick Moll)
Subject: Re: What philosophical problems does complexity theory yield?
In article <789@klipper.cs.vu.nl> biep@cs.vu.nl (J. A. "Biep" Durieux) writes:
>Suppose P != NP. Then some things will take a long time to compute.
>But so what?
>As, one by one, all sorts of upper bounds on exponents prove false, and[...]
You seem to be implying that if P=NP then *all* problems can be solved in
polynomial time. This is certainly not so. Given any computable function
f(x), one can construct (by diagonalization) a problem which can be solved,
but cannot be solved in time f(n) on a Turing machine. I believe
the same proof would work for parallel machines.
>About constant time solutions: Seemingly linear-time solutions can often be
>turned into constant-time solutions by applying parallelism. [...]
Note that P=NP is stated as a problem about Turing machines (or sometimes
single processor random access machines). Any problem in the class NP
can definately be solved in polynomial time is one is allowed to use an
arbitrary number (varying with the size of the problem instance) of
processors.
------------------------------
Date: 7 Jun 87 00:28:36 GMT
From: chiaraviglio@husc4.harvard.edu (lucius chiaraviglio)
Subject: Re: Taking AI models and applying them to biology...
In article <622@unicus.UUCP> craig@unicus.UUCP (Craig D. Hubley) writes:
>I've heard that mammal cells appear to suffer a "hard" reproductive limit
>of 52 mitosis operations, and that meiosis "resets this counter" to 0.
>
>- any comment on this, bio-med types? Is it true?
>- Would a theory assuming a simple variable or random "counter" in each cell
>limiting its reproductive span better explain aging (programmed cells...)
Random failure may be a significant factor in aging, but a hard limit
on the number of times a cell may divide before it self-destructs has been
observed in tissue culture, where the cells are for the most part not
dependant on each other. Those cells which manage to get past the hard limit
are abnormal (although not necessarily cancerous) in ways beyond their mere
ability to keep dividing after they were supposed to self-destruct. I don't
remember most of the details of this, but I do remember that they tend to
become tetraploid (I think also aneuploid) due to an increase in the rate of
mitotic failure.
-- Lucius Chiaraviglio
lucius%tardis@harvard.harvard.edu
seismo!tardis.harvard.edu!lucius
------------------------------
Date: 9 Jun 87 00:02:19 GMT
From: pixar!davel@ucbvax.Berkeley.EDU (David Longerbeam)
Subject: Re: Taking AI models and applying them to biology...
In article <622@unicus.UUCP>, craig@unicus.UUCP (Craig D. Hubley) writes:
>
> This description of the human memory system, though cloaked in vaguer terms,
> corresponds more or less one-to-one with the traditional computer
> architecture we all know and love. To wit:
[description deleted]
> At least this far, this theory appears to owe a lot to computer science.
> Granted, there is lots of empirical evidence in favour, but we all know
> how a little evidence can go far too far towards developing an analogy.
One of my philosophy professors in college offered the observation that
models for the human mind have always seemed to correspond to the most
advanced form of technology at that given point in history. He could
recall that when he was young, this technology was the combustion engine,
and lo, the cognitive psychologists' model at that time was the combustion
engine.
Of course, this technology is now the digital computer, and many psychologists,
linguists and computer scientists use it as a model to explain activites
of the human mind. Some go so far as to say that intelligence is nothing
more than the result of following the same sorts of syntactical rules as
performed by a computer!
But I stray...
I wanted to point out that you didn't give the source of the above model/
comparison, and that if it is not entirely empirical in nature, it
may be a case of "use the latest technology as the best model".
--
David Longerbeam || The opinions expressed above
Pixar || are not to be contrued as the
San Rafael, CA || opinions, stated or otherwise,
ucbvax!pixar!davel (415) 499-3600 || of Pixar.
------------------------------
Date: 5 Jun 87 04:45:45 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: symbol grounding and physical invertibility
John Cugini <Cugini@icst-ecf.arpa> asks:
> (1) I wonder why the grounding is to depend on invertibility rather than
> causation and/or resemblance?
>
> (2) Isn't it true that physically distinct
> kinds of light (eg. #1 red-wavelength and green-wavelength vs.
> #2 yellow-wavelength) can cause completely indistinguishable
> sensations (ie subjective yellow)? Is this not, then, a non-invertible,
> but nonetheless grounded sensation?
(1) According to my view, invertibility (and perhaps inversion)
captures just the relevant features of causation and resemblance that
are needed to ground symbols. The relation is between the proximal
projection (of a distal object) onto the sensory surfaces -- let's
call it P -- and an invertible transformation of that projection [I(P)].
The latter is what I call the "iconic representation." Note that the
invertibility is with the sensory projection, *not* the distal object. I
don't believe in distal magic. My grounding scheme begins at the
sensory surfaces ("skin and in"). No "wider" metaphysical causality is
involved, just narrow, local causality.
Of course the story is more complicated, because iconic
representations are not sufficient to ground a symbol referring to
an object. They're not even enough to allow a device to reliably pick
out the object and give it the right name (i.e., to categorize or
identify it). "Categorical representations" are needed next, but these
are no longer invertible into the sensory projection. They are
feature-filters preserving only the (proximal) properties of the object's
sensory projection that reliably distinguish the object (let's say
it's an "X") from the other objects that it can be confused with
(i.e., relevant "non-X's" in the particular context of confusable
alternatives sampled to date). Then finally the labels ("X," "non-X")
can be used as the primitive symbols in a (now *grounded*) symbol
system, to be combined and otherwise syntactically manipulated into
meaningful composite symbol-strings (descriptions).
(2) Your question about indistinguishable but distinct colors mistakes my
grounding scheme for a "wide" metaphysical grounding scheme -- one
where the critical "causality" would be in the relation between distal
objects and our internal representations of them, whereas mine is a narrow,
skin-and-in grounding proposal. I have dubbed this view
"approximationism," and, without going into details (for which you may
want to consult the CP book or a reprint of the theoretical chapter),
the essence of the idea is that internal representations are
always approximate rather than "exact," in two important senses. The
iconic representation is approximate up to its grain of resolution
(the "jnd" or "just-noticeable-difference"): Think of it as a Principle
of the "Iconic Identity of Iconic Indiscernibles": What you can't tell
apart is the same to you.
The categorical representations are approximate in an even more important
sense: The only features the category filter picks out are the ones
that are needed in order to identify the confusable alternatives in
the context you have sampled to date. Hence an X is just what your
current, approximate, provisional context-dependent feature-filter picks
out reliably from among the X's and Non-X's you have encountered so far:
"The Categorical Identity of Unsorted or Unsortable Members" (i.e.,
X's are identically X's unless and until reliably identified or identifiable
otherwise).
Since this is not a "wide" grounding, there is nothing oracular or
omniscient or metaphysical about what the X is that this picks out.
There is no God's-eye view from which you can say what X's "really"
are. There's just the mundane historical fact -- available to an
outside observer, if there is one -- about what the actual distal objects
were whose proximal projections you were sampling. Those furnished your
context, and your fallible, context-dependent representations will
always be approximate relative to those objects.
In conclusion, the only differences in the object that are reflected
in the iconic and categorical representations are the ones present in
the proximal projection of the alternatives sampled to date
(and preserved by the category-feature filter). The representations
are approximate (i.e., indifferent) with respect to any further distal
differences. Symbolic discourse may serve to further tighten the
approximation, but even that cannot be "exact," if for no other
reason than that there's always a tomorrow, in which the
context may be widened and the current representation may have to be
revised. -- But that's another story, and no longer concerns the
grounding problem but what's called "inductive risk."
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
End of AIList Digest
********************
∂15-Jun-87 0107 LAWS@Stripe.SRI.Com AIList Digest V5 #142
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Jun 87 01:07:23 PDT
Date: Sun 14 Jun 1987 22:45-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #142
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 15 Jun 1987 Volume 5 : Issue 142
Today's Topics:
Program - Cognitive Science at Occidental College,
Seminars - Universal Plans: Emergent Goal Structures (SRI) &
Abductive Reasoning in Multifault Diagnostic Systems (UPenn) &
Potential Histories and Inertial Theories (SU) &
Controlling Execution of Logic Programs (MCC),
Conferences - OOPSLA-87 &
Architectures for Intelligent Interfaces
----------------------------------------------------------------------
Date: 04 Jun 87 09:00:45 PST
From: oxy!traiger@csvax.caltech.edu (Saul P. Traiger)
Subject: Program - Cognitive Science at Occidental College
Occidental College, a liberal arts college which enrolls approximately
1600 students, is pleased to announce a new Program in Cognitive
Science. The Program offers an undergraduate major and minor in Cognitive
Science. Faculty participating in this program include members of the
departments of mathematics, linguistics, psychology, and philosophy.
The program is the result of one of the most exciting developments in
higher education today, namely the interaction among philosophers,
mathematicians, psychologists, linguists, and computer scientists. This
interaction is the result of common interests in cognitive science.
Computer architecture is now as likely to be discussed in a philosophy or
psychology seminar as it is in a computer science course. Shared
interests in cognitive science lead to the development and adoption of an
interdepartmental program in cognitive science at Occidental College.
The undergraduate major in Cognitive Science at Occidental College
includes courses in mathematics, philosophy, psychology and linguistics.
Instruction in mathematics introduces students to computer languages,
discrete mathematics, logic, and the mathematics of computation.
Philosophy offerings cover the philosophy of mind, with emphasis on
computational models of the mind, the theory of knowledge, the philosophy
of science, and the philosophy of language. Psychology courses include
basic psychology, learning, perception, and cognition. Courses in
linguistics provide a theoretical foundation in natural languages, their
acquisition, development, and structure.
For more information about Occidental College's Cognitive Science Program
please contact:
Professor Saul Traiger
Cognitive Science Program
1600 Campus Road
Occidental College
Los Angeles, CA 90041
ARPANET: oxy!traiger@CSVAX.Caltech.EDU
BITNET: oxy!traiger@hamlet
CSNET: oxy!traiger%csvax.caltech.edu@RELAY.CS.NET
UUCP: ....{seismo, rutgers, ames}!cit-vax!oxy!traiger
------------------------------
Date: Thu, 11 Jun 87 11:29:04 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Universal Plans: Emergent Goal Structures (SRI)
EXECUTING UNIVERSAL PLANS:
EMERGENT GOAL STRUCTURES & THEIR USES
Marcel Schoppers (MARCEL@ADS.COM)
Advanced Decision Systems
11:00 AM, MONDAY, June 15
SRI International, Building E, Room EJ228
``Universal plans'' are designed for execution in unpredictable state spaces,
refusing to over-commit to a specific future course of events, and deliberately
making no assumptions about how situations might follow one another. Instead,
plan synthesis becomes the goal-directed selection of reactions to possible
situations; plans become inherently conditional; and plan execution classifies
the current situation so as to respond with the selected reaction. Consequently
there is no inherent distinction between expected and unexpected events; the
concepts of success & failure are irrelevant for both synthesis and execution;
and "error recovery" needs no special mechanisms beyond those already present
for normal execution.
After introducing the Universal Plan representation, this talk will show how at
any given instant, plan predicates can be interpreted as goals of achievement
or of maintenance, and that this interpretation can be used to reconstruct a
four-fold typing of events (of success, failure, serendipity and sabotage). In
other words, intentions emerge from the interaction of plan with environment
(the environment has a large hand in determining the agent's goals at each
moment), and the notions of success and failure are not primitive but
perceived (relative to the agent's goals).
The Universal Plan representation also indicates precisely which conditions
must be monitored at each instant to enable detection of all events of each
type. Two benefits follow; I will only mention them briefly. First, we can
get complexity estimates for detecting all serendipity and sabotage events,
and can produce informed strategies to alleviate sensing costs. Second, the
goal structure at each moment in time contains all the information required
to choose an appropriate action, thus facilitating incremental synthesis.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Thu, 11 Jun 87 14:13:25 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Abductive Reasoning in Multifault Diagnostic
Systems (UPenn)
ABDUCTIVE REASONING in MULTIPLE-FAULT DIAGNOSTIC SYSTEMS
Gary Morris
Computer and Information Science
University of Pennsylvania
Philadelphia PA
Abductive reasoning involves generating explanations for observed
facts or symptoms -- i.e. diagnosis. Diagnosis is more difficult,
both theoretically and practically, when more than one disorder or
fault may occur simultaneously in the system beign diagnosed. Five
approaches to this problem are reviewed and contrasted:
- Binary Choice Bayesian (Ben-Bassat: the MEDAS system)
- Sequential Bayesian (Pople: INTERNIST)
- Causal Model Reasoning (Patil: ABEL)
- Parsimonious Set Covering (Reggia & Nau: various systems)
- "Diagnosis From First Principles" (Reiter, deKleer: various)
Finally, an emerging convergence of these methods is described.
Friday, June 12, 3:30 pm
Room 554 Moore
------------------------------
Date: 01 Jun 87 1605 PDT
From: Vladimir Lifschitz <VAL@SAIL.STANFORD.EDU>
Subject: Seminar - Potential Histories and Inertial Theories (SU)
[Forwarded from the Stanford bboard.]
Yoav Shoham asked me to send a nice little poem to this mailing list:
With logics that are monotonic
Relations are nice but platonic
It's when you permit
Just models that fit
That things become most erotonic
Yoav will also speak at our seminar on a related subject:
POTENTIAL HISTORIES AND INERTIAL THEORIES
Yoav Shoham
Thursday, June 4, 4:15pm
Bldg. 160, Room 161K
In previous talks I never managed to get to my solution to the
extended-prediction problem (which is my name for the problem
subsuming the frame problem, a name that, shall we say, never
quite caught). I'll describe the intuitive concept of a potential
history, which has a strong McDermott-like persistence flavor.
I'll then embed the concept formally within the logic of
chronological ignorance. I'll identify a class of theories, called
inertial theories, which extend causal theories, and yet which
a. are expressive enough to capture the notion of potential
histories, and b. have the "unique model" and easy computability
properties.
My intention is this time to go into some detail. I'm still
not sure I have enough material for an hour, and if I don't
I'll ask the audience some questions on TMS's.
------------------------------
Date: Mon 1 Jun 87 11:04:12-CDT
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - Controlling Execution of Logic Programs (MCC)
Madhur Kohli
Department of Computer Science
University of Maryland
June 4 - 10:30am
ACA Conference Room 2.806
Controlling the Execution of Logic Programs
The performance of a logic programming system is dictated by the
control strategy of its problem solving component. This talk
describes a methodology for the specification and utilization of
control knowledge for logic programs.
We describe a control specification system developed as an
experimental tool for the study of control issues in problem
solving. Analysis of the control behavior of several sequential
problem solvers and PRISM, a parallel logic programming system, is
used to identify parameters to express control decisions and points
at which they apply. These results form the basis for the
definition of a control language to specify the control behavior of
problem solvers. The language is expressive enough to specify many
general and specialized top-down execution schemes for both
sequential and parallel problem solvers. A compiler has been
developed to generate an interpreter which implements the specified
control strategy. Experimental results show that the generated
interpreters provide an order of magnitude improvement over
meta-interpretation of the control specification.
Madhur Kohli
June 4 - 10:30
ACA Conference Room 2.806
------------------------------
Date: 5 Jun 87 18:50:31 GMT
From: ut-sally!home.csnet!im4u!ti-csl!fordyce@seismo.CSS.GOV (David
Fordyce)
Subject: Conference - OOPSLA-87
Article-I.D.: home.444
OBJECT-ORIENTED DATABASE WORKSHOP: Implementation Aspects
To be held in conjunction with the
Object-oriented Programming Systems,
Languages and Applications (OOPSLA-87) Conference
October 5, 1987
Orlando, Florida
Object-oriented database systems combine the streangths of
object-oriented programming systems and data models, and database
systems. This half-day workshop will be held on Monday morning, October
5, 1987. The goal of the workshop is to study the implementation
aspects of object-oriented database systems. The workshop will focus on
issues such as object fault management, storage management (buffering,
prefetching, clustering, etc.), object persistence, object sharing,
transactions on objects, concurrency control, recovery, and performance
issues.
The workshop panel will consist of: Timothy Andrewes (Ontologic), Umesh
Dayal (Computer Corporation of America), Prof. David Maier (Oregon
Graduate Center and Servio Logic), Patrick O'Brien (Digital Equipment
Corporation), Prof. Lawrence Rowe (University of California at
Berkeley), Prof. Alfred Spector (Carnegie-Mellon University), David
Wells (Texas Instruments), and Prof. Stan Zdonik (Brown University).
In the first 90 minutes, each panel member will present his position.
This will be followed by questions from the workshop participants and
discussions.
To encourage vigorous interactions and exchange of ideas between the
participants, the workshop will be limited to 50 qualified participants.
If you are interested in attending the workshop, please submit three
copies of a single page abstract to the workshop chairman describing
your work related to the implementation issues of object-oriented
database systems. The workshop participants will be selected based on the
relevance and significance of their work described in the abstract.
There will be no proceedings for the workshop.
Abstracts should be submitted to the workshop chairman by August 1,
1987. Selected participants will be notified by September 1, 1987
Workshop Chairman:
Dr. Satish M. Thatte
Manager, Database Systems Branch
Artificial Intelligence Laboratory
Texas Instruments Incorporated
P.O. Box 226015, M/S 238
Dallas, TX 75266
Phone: (214)-995-0340
CSNet: Thatte@TI-CSL
--
Regards, David
------------------------------
Date: Fri, 5 Jun 87 09:42:22 PDT
From: wiley!sherman@lll-lcc.ARPA (Sherman Tyler)
Subject: Conference - Architectures for Intelligent Interfaces
Call for Participation
Workshop on
Architectures for Intelligent Interfaces:
Elements and Prototypes
March 29 - April 1, 1988, Monterey, California
Sponsored by AAAI
Objective: The term ``Intelligent Interface'' characterizes the set
of computer-human interfaces which employ AI to enhance the
transactional nature of the interface. The goal of the workshop is to
explore ways in which AI techniques (e.g., knowledge representation,
inference mechanisms, and heuristic search) can be used to provide the
adaptability and reasoning capabilities required for a more
intelligent human-machine interaction.
Some possible areas for focused discussions might include:
* Models (user, system, task) - adapting the dialogue to the
current context of the interaction, considering the
particular user, the target system, and the high-level task
under execution;
* Channels of Communication - allowing users to communicate
intentions with a minimum of learning and effort, using
Natural Language, Graphics, and the integration of mixed
modalities of input;
* Planning - for recognizing user plans and their implied
goals, generating plans to meet those goals, and planning how
to best display the resulting information to communicate the
result of the executed action;
* Interface-Building Tools - using artificial intelligence
techniques to support developers in designing and
constructing interfaces.
Attendance: In order to provide an intellectually stimulating
environment conducive to interaction and exchange of ideas, the
attendance will be limited to approximately 35 participants. The
ideal participant is an individual who is actively addressing
theoretical, research, and/or implementation issues relevant to
Intelligent Interfaces (with a bias toward those who have dealt with
implementation issues at some level). Limited financial assistance
will be available for graduate students who are invited to
participate.
Review Process: The submitted abstracts and autobiographies will be
reviewed by the program committee. Invitation will be based upon
relevance of the work to the goals of the workshop, and on the basis
of significance, originality, and scientific quality.
Workshop Organization: The workshop organizers are J. Sullivan
(Lockheed AI Center) and S. Tyler (Lockheed AI Center). The program
committee consists of J. Mackinlay (Xerox PARC), R. Neches
(USC Information Sciences Institute), E. Rissland (University of
Massachusetts), and N. Sondheimer (USC Information Sciences Institute).
Submission: A detailed eight page abstract and a one page
biographical sketch (six copies of each) should be submitted by
September 1, 1987. Invitations for participation will be extended by
October 16, 1987, with complete papers due by December 18, 1987.
Publication of the proceedings is planned, therefore the quality of
the papers is important.
Submit abstracts to: Joseph W. Sullivan or Sherman W. Tyler,
O/90-06 B/259, Lockheed AI Center, 2710 Sand Hill Rd., Menlo Park, CA
94025, (415) 354-5200, wiley!joe@lll-lcc.arpa or
wiley!sherman@lll-lcc.arpa
------------------------------
End of AIList Digest
********************
∂15-Jun-87 0259 LAWS@Stripe.SRI.Com AIList Digest V5 #143
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Jun 87 02:59:44 PDT
Date: Sun 14 Jun 1987 23:18-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #143
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 15 Jun 1987 Volume 5 : Issue 143
Today's Topics:
Journal Issues - Neural Networks (IEEE Computer) &
Smolensky on Connectionism (BBS) &
Laming on Sensory Analysis (BBS),
Conference - Genetic Algorithms
----------------------------------------------------------------------
Date: 8 June 1987, 16:25:07 EDT
From: Bruce Shriver <SHRIVER@ibm.com>
Subject: Journal Issue - Neural Networks
Call for Papers and Referees
Special Issue of Computer Magazine
on Neural Networks
The March, 1988 issue of Computer magazine will be devoted
to a wide range of topics in Neural Computing. Manuscripts
that are either tutorial, survey, descriptive, case-study,
applications-oriented or pedagogic in nature are immediately
sought in the following areas:
o Neural Network Architectures
o Electronic and Optical Neurocomputers
o Applications of Neural Networks in Vision, Speech
Recognition and Synthesis, Robotics, Image Process-
ing, and Learning
o Self-Adaptive and Dynamically Reconfigurable Systems
o Neural Network Models
o Neural Algorithms and Models of Computation
o Programming Neural Network Systems
INSTRUCTIONS FOR SUBMITTING MANUSCRIPTS
Manuscripts should be no more than 32-34 typewritten,
double-spaced pages in length including all figures and ref-
erences. No more than 12 references should be cited. Papers
must not have been previously published nor currently sub-
mitted for publication elsewhere. Manuscripts should have a
title page that includes the title of the paper, full name
of its author(s), affiliation(s), complete physical and
electronic address(es), telephone number(s), a 200 word ab-
stract, and a list of keywords that identify the central is-
sues of the manuscript's content.
DEADLINES
o A 200 word abstract on the manuscript is due as soon
as possible.
o Eight (8) copies of the full manuscript is due by
August 30, 1987.
o Notification of acceptance is November 1, 1987.
o Final version of the manuscript is due no later than
December 1, 1987.
SEND SUBMISSIONS AND QUESTIONS TO
Bruce D. Shriver
Editor-in-Chief, Computer
IBM T. J. Watson Research Center
P. O. Box 704
Yorktown Heights, NY 10598
Phone: (914) 789-7626
Electronic Mail Addresses:
arpanet: shriver@ibm.com
bitnet: shriver at yktvmh
compmail+: b.shriver
------------------------------
Date: 5 Jun 87 18:14:46 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Smolensky on Connectionism: BBS Call for Commentators
The following is the abstract of a forthcoming article on which BBS
[Behavioral and Brain Sciences -- An international, interdisciplinary
Journal of Open Peer Commentary, published by Cambridge University Press]
invites self-nominations by potential commentators.
(Please note that the editorial office must exercise selectivity among the
nominations received so as to ensure a strong and balanced cross-specialty
spectrum of eligible commentators. The procedure is explained after
the abstract.)
-----
On the Proper Treatment of Connectionism
Paul Smolensky
Institute of Cognitive Science
University of Colorado
Boulder CO 80309-0430
A set of hypotheses is formulated for a connectionist
approach to cognitive modeling. These hypotheses are
shown to be incompatible with the hypotheses embodied
in traditional cognitive models. The connectionist
models considered are massively parallel numerical com-
putational systems that are a kind of continuous dynam-
ical system. The numerical values in the system
correspond semantically to fine-grained features below
the level of the concepts used to describe the task
domain. The level of analysis is intermediate between
that of symbolic cognitive models and neural models.
The explanations of behavior provided are like those in
traditional physical sciences, unlike the explanations
provided by symbolic models.
Higher-level analyses of these connectionist models
reveal subtle relations to symbolic models. Fundamen-
tally parallel connectionist memory and linguistic
processes are hypothesized to give rise to processes
that are describable at a higher level as sequential
rule application. At the lower level, computation has
the character of massively parallel satisfaction of
numerical constraints; at the higher level this can
lead to competence characterizable by hard rules. Per-
formance will typically deviate from competence since
behavior is achieved not by interpreting hard rules but
by satisfying soft constraints. The result is a picture
in which traditional and connectionist theoretical con-
structs collaborate intimately to provide an under-
standing of cognition.
-----
This is an experiment in using the Net to find eligible commentators
for articles in the Behavioral and Brain Sciences (BBS), an
international, interdisciplinary journal of "open peer commentary,"
published by Cambridge University Press, with its editorial office in
Princeton NJ.
The journal publishes important and controversial interdisciplinary
articles in psychology, neuroscience, behavioral biology, cognitive science,
artificial intelligence, linguistics and philosophy. Articles are
rigorously refereed and, if accepted, are circulated to a large number
of potential commentators around the world in the various specialties
on which the article impinges. Their 1000-word commentaries are then
co-published with the target article as well as the author's response
to each. The commentaries consist of analyses, elaborations,
complementary and supplementary data and theory, criticisms and
cross-specialty syntheses.
[...] Eligible individuals who judge that they
would have a relevant commentary to contribute should contact the editor at
the e-mail address indicated at the bottom of this message, or should
write by normal mail to:
Stevan Harnad
Editor
Behavioral and Brain Sciences
20 Nassau Street, Room 240
Princeton NJ 08542
(phone: 609-921-7771)
Potential commentators should send their names, addresses, a description of
their general qualifications and their basis for seeking to comment on
this target article in particular to the address indicated earlier or
to the following e-mail address:
{seismo, psuvax1, bellcore, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.princeton.edu
[Subscription information is available from Harry Florentine at
Cambridge University Press: 800-221-4512]
[Contact Harnad for further discussion of eligibility, application
procedures, journal circulation, etc. -- KIL]
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 10 Jun 87 04:42:54 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Laming on Sensory Analysis: BBS Multiple Book Review
The following is the abstract of a book that will be multiply reviewed in BBS
[Behavioral and Brain Sciences -- An international, interdisciplinary
Journal of Open Peer Commentary, published by Cambridge University Press].
Self-nominations by potential reviewers/commentators are invited. Please note
that the editorial office must exercise selectivity among the nominations
received so as to ensure a strong and balanced cross-specialty spectrum of
eligible commentators. The procedure is explained after the abstract.
-----
SENSORY ANALYSIS
Donald Laming
Department of Experimental Psychology
University of Cambrdige
Cambridge CB2 3EB ENGLAND
ABSTRACT
Sensory analysis is that initial, preconscious stage of
perception at which features (edges, temporal discon-
tinuities, and periodicities) are picked out from the
random fluctuations that characterize the physical
stimulation of sensory receptors. Sensory analysis may
be studied by means of signal-detection, psychometric-
function and threshold experiments, and my book, SEN-
SORY ANALYSIS, presents a succinct, quasi-quantitative
account of the phenomena revealed thereby. This account
covers all five sensory modalities, emphasizing the
similarities between them.
A succinct account depends on identifying simple prin-
ciples of wide generality, of which the most fundamen-
tal are that (a) sensory discriminations are differen-
tially coupled to the physical stimuli and that (b)
small stimuli are subject to a square-law transform
which makes them less detectable than they would other-
wise be. These two principles are established by com-
parisons between different configurations of two
stimulus levels to be discriminated; they are realized
within a simple physical-analogue model which affords
certain low-level comparisons with neurophysiological
observation. That physical-analogue model consists of a
sequence of elementary operations on the stimulus con-
stituting a stage of sensory processing. The concate-
nation of two of three stages in cascade accommodates
an increased range of experimental phenomena, espe-
cially the detection of sinusoidal gratings.
My BBS precis is organized in three parts: Part I sur-
veys SENSORY ANALYSIS as economically as may be, begin-
ning from the simplest, most fundamental ideas and
working towards phenomena of increasing complexity. A
rather short Part II reviews the most important alter-
native models addressed to some part or other of the
phenomena surveyed. Finally, a very short Part III con-
tributes some metatheoretic remarks on the function of
a theory of sensory discrimination.
Potential commentators/reviewers should send their names, addresses, a
description of their general qualifications and their basis for seeking to
review this book in particular to the following USmail or Email address:
Stevan Harnad, Editor
Behavioral and Brain Sciences
20 Nassau Street, Room 240
Princeton NJ 08542
(phone: 609-921-7771)
{seismo, psuvax1, bellcore, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.princeton.edu
[See previous solicitations in AIList for the full blurb. -- KIL]
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: Fri, 12 Jun 87 15:40:35 edt
From: John Grefenstette <gref@nrl-aic.ARPA>
Subject: Conference - Genetic Algorithms
Second International Conference on
Genetic Algorithms and Their Applications
July 28-31, 1987
MIT
Cambridge, Massachusetts
Sponsored By
American Association for Artificial Intelligence
Naval Research Laboratory
Bolt Beranek and Newman, Inc.
Genetic algorithms are adaptive search techniques based on
principles derived from natural population genetics, and are
currently being applied to a variety of difficult problems in
science, engineering, and artificial intelligence. Topics for
discussion will include:
Fundamental research on genetic algorithms
Machine learning using genetic algorithms
Implementation techniques,
especially on parallel processors
Relationships to connectionism and other
search and learning techniques
Application of genetic algorithms
Conference Committee:
John H. Holland University of Michigan
(Conference Chair)
Lashon B. Booker Navy Center for Applied Research in AI
Dave Davis Bolt Beranek and Newman, Inc.
Kenneth A. De Jong George Mason University
David E. Goldberg University of Alabama
John J. Grefenstette Navy Center for Applied Research in AI
(Program Chair)
Stephen F. Smith Carnegie-Mellon Robotics Institute
Stewart W. Wilson Rowland Institute for Science
(Local Arrangements)
The registration fee is $120 ($175 after June 15) and
includes admission to all sessions, the Conference Proceedings,
a Welcoming Reception, and all coffee breaks and lunches.
The Conference Banquet is $30 additional per person. The
Registration fee for students is $60. For registration forms
and information concerning local arrangements, contact:
Conference Services Office
Room 7-111
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139
(617) 253-1703
For copies of the Conference Proceedings, contact:
Lawrence Erlbaum Associates, Publishers
365 Broadway
Hillsdale, New Jersey 07642
CONFERENCE PROGRAM
TUESDAY, JULY 28, 1987
5:00 - 9:00 REGISTRATION
7:00 - 9:00 WELCOMING RECEPTION
7:00 - 9:00 TUTORIAL (if sufficient interest)
WEDNESDAY, JULY 29, 1987
8:00 REGISTRATION
9:00 OPENING REMARKS
9:20 - 10:40 GENETIC SEARCH THEORY
Finite Markov chain analysis of genetic algorithms
David E. Goldberg and Philip Segrest
An analysis of reproduction and crossover in a
binary-coded genetic algorithm
Clayton L. Bridges and David E. Goldberg
Reducing bias and inefficiency in the selection algorithm
James E. Baker
Altruism in the bucket brigade
Thomas H. Westerdale
10:40 - 11:00 COFFEE BREAK
11:00 - 12:00 ADAPTIVE SEARCH OPERATORS I
Schema recombination in pattern recognition problems
Irene Stadnyk
An adaptive crossover distribution mechanism for
genetic algorithms
J. David Schaffer and Amy Morishima
Genetic algorithms with sharing for multimodal
function optimization
David E. Goldberg and Jon Richardson
12:00 - 2:00 LUNCH
2:00 - 3:20 REPRESENTATION ISSUES
The ARGOT strategy: adaptive representation genetic
optimizer technique
Craig G. Shaefer
Nonstationary function optimization using genetic
algorithms with dominance and diploidy
David E. Goldberg and Robert E. Smith
Genetic operators for high-level knowledge representations
H. J. Antonisse and K. S. Keller
Tree structured rules in genetic algorithms
Arthur S. Bickel and Riva Wenig Bickel
3:20 - 3:40 COFFEE BREAK
3:40 - 5:00 KEYNOTE ADDRESS
Genetic algorithms and classifier systems: foundations
and future directions
John H. Holland
7:00 - 9:00 BUSINESS MEETING
THURSDAY, JULY 30, 1987
9:00 - 10:20 ADAPTIVE SEARCH OPERATORS II
Greedy genetics
G.E. Liepins, M.R. Hilliard, Mark Palmer
and Michael Morrow
Incorporating heuristic information into genetic search
Jung Y. Suh and Dirk Van Gucht
Using reproductive evaluation to improve genetic
search and heuristic discovery
Darrell Whitley
Toward a unified thermodynamic genetic operator
David J. Sirag and Paul T. Weisser
10:20 - 10:40 COFFEE BREAK
10:40 - 12:00 CONNECTIONISM AND PARALLELISM I
Toward the evolution of symbols
Charles P. Dolan and Michael G. Dyer
SUPERGRAN: a connectionist approach to learning,
integrating genetic algorithms and graph induction
Deon G. Oosthuizen
Parallel implementation of genetic algorithms in a
classifier system
George G. Robertson
Punctuated equilibria: a parallel genetic algorithm
J.P. Cohoon, S.U. Hegde, W.N. Martin and D. Richards
12:00 - 2:00 LUNCH
2:00 - 3:20 PARALLELISM II
A parallel genetic algorithm
Chrisila B. Pettey, Michael R. Leuze and John J. Grefenstette
Genetic learning procedures in distributed environments
Adrian V. Sannier II and Erik D. Goodman
Parallelisation of probabilistic sequential search algorithms
Prasanna Jog and Dirk Van Gucht
Parallel genetic algorithms for a hypercube
Reiko Tanese
3:20 - 3:40 COFFEE BREAK
3:40 - 5:00 CREDIT ASSIGNMENT AND LEARNING
Bucket brigade performance: I. Long sequences of classifiers
Rick L. Riolo
Bucket brigade performance: II. Default hierarchies
Rick L. Riolo
Multilevel credit assignment in a genetic learning system
John J. Grefenstette
On using genetic algorithms to search program spaces
Kenneth A. De Jong
6:30 - 10:00 CLAM BAKE
FRIDAY, JULY 31, 1987
9:00 - 10:20 APPLICATIONS I
A genetic system for learning models of consumer choice
David Perry Greene and Stephen F. Smith
A study of permutation crossover operators on the
traveling salesman problem
I.M. Oliver, D.J. Smith and J. R. C. Holland
A classifier based system for discovering scheduling heuristics
M.R. Hilliard, G.E. Liepins, Mark Palmer,
Michael Morrow and Jon Richardson
Using the genetic algorithm to generate LISP source code
to solve the prisoner's dilemma
Cory Fujiko and John Dickinson
10:20 - 10:40 COFFEE BREAK
10:40 - 12:00 APPLICATIONS II
Optimal determination of user-oriented clusters:
an application for the reproductive plan
Vijay V. Raghavan and Brijesh Agarwal
The genetic algorithm and biological development
Stewart W. Wilson
Genetic algorithms and communication link speed design:
theoretical considerations
Lawrence Davis and Susan Coombs
Genetic algorithms and communication link speed design:
constraints and operators
Susan Coombs and Lawrence Davis
12:00 - 2:00 LUNCH
2:00 - 3:20 PANEL DISCUSSION: GA's and AI
3:20 - 3:40 COFFEE BREAK
3:40 - 5:00 INFORMAL DISCUSSION AND FAREWELL
------------------------------
End of AIList Digest
********************
∂15-Jun-87 0440 LAWS@Stripe.SRI.Com AIList Digest V5 #144
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Jun 87 04:39:59 PDT
Date: Sun 14 Jun 1987 23:29-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #144
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 15 Jun 1987 Volume 5 : Issue 144
Today's Topics:
Queries - Smalltalk-80 Implementations & AI Grad Schools &
Machine Emotion Research & Neural Network Processors in High Technology &
ML programming & ICOT Prolog,
Theory - Complexity Theory,
AI Tools - The ISI Grapher
----------------------------------------------------------------------
Date: 10 Jun 87 18:34:19 GMT
From: ihnp4!alberta!sask!kusalik@ucbvax.Berkeley.EDU (Tony Kusalik)
Subject: request for info on Smalltalk-80 implementations
We are looking for a version of Smalltalk-80 for
SUN-3's. We have contacted Berkeley about BSII,
but the blurb that came back states
"It [BSII] has not been updated to run on SUN 3 or to run
under the X window system, although others have made these
changes"
Anyone know who these "others" might be? I.e.
can anyone out there point me in the direction of
a Smalltalk-80 system for SUN-3's?
The Berkeley blurb mentions a SUN implementation done
by L. Peter Deutsch and Allan M. Schiffman. Does anyone
know of addresses (Email or snail-mail) for them?
Tony Kusalik
kusalik@sask.bitnet
...!{ihnp4,alberta}!sask!kusalik
------------------------------
Date: 8 Jun 87 13:59:44 GMT
From: spe@SPICE.CS.CMU.EDU (Sean Engelson)
Subject: AI grad schools?
Can anyone give me any `inside' information on graduate CS-AI PhD
programs? I know of a number of schools with such programs; I am
interested in the opinions of people who have been involved in such
programs, either as students or as professors. My main interests are
in machine learning, analogical and common-sense reasoning, and
natural language processing.
Thank you,
--
Credo, ergo absurdum est.
LISP ::=
((())((Lots(())))(()(()(of(((Idiotic)())()()(Silly(()))()(Parentheses))))))
----------------------------------------------------------------------
Sean Philip Engelson I have no opinions.
Carnegie-Mellon University Therefore my employer is mine.
Computer Science Department
----------------------------------------------------------------------
ARPA: spe@spice.cs.cmu.edu
UUCP: {harvard | seismo | ucbvax}!spice.cs.cmu.edu!spe
------------------------------
Date: 12 Jun 87 02:03:39 GMT
From: dartvax!uvm-gen!emerson.UUCP@seismo.css.gov (Tom "Oliver W.
Jones" Emerson)
Subject: Machine emotion research
I would like information regarding emotion research in intelligent
computers, including references if possible.
If there is suffecient interest, I will report the contents of replies
to the net.
Thanx in advance,
Tom E.
------------------------------
Date: 12 Jun 87 15:40:00 EDT
From: LANTZ@RED.RUTGERS.EDU
Subject: Neural network processors in High Technology
The May issue of High Technology has an(other) article on
neural networks. Would someone please send me the names and addresses
of the four companies mentioned in the article. Thanks.
Brian
------------------------------
Date: 9 Jun 87 19:36:37 GMT
From: uunet!steinmetz!philabs!sbcs!sbstaff2!allen@seismo.css.gov (
Allen Leung)
Subject: ML programming, anybody?
Is there any one out there doing serious programming and/or research
in ML (Meta Language)? I would like to hear from you.
Don't trust me,
I'm just an undergrad.
Allen Leung,
SUNY at Stony Brook.
------------------------------
Date: 11 Jun 87 18:12:40 GMT
From: mit-vax!jouvelot@eddie.mit.edu (Pierre Jouvelot)
Subject: Re: ML programming, anybody?
In article <665@sbstaff2.UUCP> allen@sbstaff2.UUCP ( Allen Leung) writes:
>
> Is there any one out there doing serious programming and/or research
> in ML (Meta Language)? I would like to hear from you.
>
Yes (I guess) !!
I used it as an executable specification language for the semantic
parallelization of imperative programs during my PhD research in France
(I'm currently a PostDoc in MIT/LCS Programming Research Group). The
overall program is about 3500 lines of ML code (with a few others in
FranzLisp and MLYacc). The overall idea is described in my POPL'87 paper
"Semantic Parallelization: A Practical Exercise in Abstract Interpretation"
where both the theory (abstract interpretation) and practice (use of ML)
are introduced (for courageous people, there is also my PhD thesis ... written
in french :-)
Note that I used the Cambridge/INRIA Version which is older and
slightly different from SML. The main problem I had was related to
the lack of "real" separate-compilation facility. This should
disappear with newer versions that introduce modules. Besides this, ML is
a very fine language which should have a more widespread use.
Pierre
--
Pierre Jouvelot
Room NE43-403 ARPA: jouvelot@xx.lcs.mit.edu
Lab for Computer Science USENET: decvax!mit-vax!jouvelot
MIT (or mcvax!litp!pj)
545, Technology Square
Cambridge, MA 02139
USA
------------------------------
Date: Thu, 11 Jun 87 08:31:20 EDT
From: elsaesser%mwcamis@mitre.arpa
Subject: Say, what ever happened to ... ICOT Prolog?????
It seems ages ago that the 5th generation project was going to
reinvent AI in a Prolog "engine" that was to do 10 gazillion "
LIPS". Anyone know what happened? I mean, if you can make so many
"quality" cars (sans auto transmission, useful A/C, paint that can take
rain and sun, etc.), why can't you make a computer that runs an NP-complete
applications language in real time??? Simi-seriously, what is the status
of the 5th generation project, anyone got an update?
chris (elsaesser%mwcamis@mitre.arpa)
[See the June IEEE Spectrum, "Next-Generation Race Bogs Down", Karen
Fitzgerald and Raul Wallich, pp. 28-33, for a review. The
Japanese effort is doing well enough in its parallel architecture
development and is making some progress in "knowledge programming",
but has dropped VLSI technology and made little headway in AI and
knowledge representation. Competitive efforts in the U.S. and
Europe have also had the most success in hardware. The real question
now is whether the 5th-generation push has given Japan the kind of
computer-science infrastructure that it needs to compete and perhaps
pull out ahead in algorithm development. My guess is that it has not
(because the software part of the effort was too small). An interesting
sign of change, though, is the Japanese government's invitation to
Western universities to set up branches in Japan. I assume that
Japanese leaders will always come from Tyodai or Kyodai, but perhaps
computer scientists will be educated in a different tradition. -- KIL]
------------------------------
Date: 10 Jun 87 08:33:39 GMT
From: mcvax!botter!klipper!biep@seismo.css.gov (J. A. "Biep" Durieux)
Subject: Re: What philosophical problems does complexity theory yield?
In article <789@klipper.cs.vu.nl> biep@cs.vu.nl (J. A. "Biep" Durieux) writes:
>But, isn't anything which cannot be turned into a constant-time process
>philosophically annoying? Why just hassling about non-polynomial time
>solutions? Am I missing something?
In article <2258@cvl.umd.edu> ramesh@cvl.UUCP (Ramesh Sitaraman) writes:
>Yes, you are missing the point !!
>
>The difference between a polynomial and non-polynomial solution for
>a problem is the difference between structure and a complete lack
>of it.
Thanks a lot, this sounds much more relevant than just computation time.
But, isn't finding the smallest element of a set solvable only by "dumb
exhaustive search" either? Are people having that much trouble with such a
linear algorithm too?
Also, thanks for including the defs! Such things make the net a whole lot
more readable.
But: please don't put your mail address on the "Follow-up-to: " line.
I'm having a terrible time getting this article out!
Inews
feeding
time
------------------------------
Date: Sat, 13 Jun 87 13:35:12 PDT
From: Gabriel Robins <gabriel@vaxa.isi.edu>
Subject: The ISI Grapher
Greetings,
Due to the considerable interest drawn by the ISI Grapher so far, I am
posting this abstract summarizing its function and current status. Interested
parties may obtain further information by directly sending EMail to
"gabriel@vaxa.isi.edu" or by writing to:
Gabriel Robins
Intelligent Systems Division
Information Sciences Institute
4676 Admiralty Way
Marina Del Rey, Ca 90292-6695
If you want documentation in hardcopy, please include your U.S. Mail address.
Gabe
----------------------------------------------------------------------
The ISI Grapher
June, 1987
Gabriel Robins
Intelligent Systems Division
Information Sciences Institute
The ISI Grapher is a set of functions that convert an arbitrary graph
structure (or relation) into an equivalent pictorial representation and
displays the resulting diagram. Nodes and edges in the graph become boxes and
lines on the workstation screen, and the user may then interact with the
Grapher in various ways via the mouse and the keyboard.
The fundamental motivation which gave birth to the ISI Grapher is the
observation that graphs are very basic and common structures, and the belief
that the ability to quickly display, manipulate, and browse through graphs may
greatly enhance the productivity of a researcher, both quantitatively and
qualitatively. This seems especially true in knowledge representation and
natural language research.
The ISI Grapher is both powerful and versatile, allowing an
application-builder to easily build other tools on top of it. The ISI NIKL
Browser is an example of one such tool. The salient features of the ISI
Grapher are its portability, speed, versatility, and extensibility. Several
additional applications were already built on top of the ISI Grapher,
providing the ability to graph lists, flavors, packages, divisors, functions,
and Common-Loops classes.
Several basic Grapher operations may be user-controlled via the specification
of alternate functions for performing these tasks. These operations include
the drawing of nodes and edges, the selection of fonts, the determination of
print-names, pretty-printing, and highlighting operations. Standard
definitions are already provided for these operations and are used by default
if the application-builder does not override them by specifying his own
custom-tailored functions for performing the same tasks.
The ISI Grapher now spans about 100 pages of CommonLisp code. The 120-page
ISI Grapher manual is available; this manual describes the general ideas, the
interface, the application-builder's back-end, the algorithms, the
implementation, and the data structures. The ISI Grapher presently runs on
both Symbolics (6 & 7) and TI Explorer workstations.
If you are interested in more information, the sources themselves, or just
the documentation/manual, please feel free to forward your U.S. Mail address to
"gabriel@vaxa.isi.edu" or write to "Gabriel Robins, c/o Information Sciences
Institute, 4676 Admiralty Way, Marina Del Rey, Ca 90292-6695."
------------------------------
End of AIList Digest
********************
∂15-Jun-87 0712 LAWS@Stripe.SRI.Com AIList Digest V5 #145
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Jun 87 07:12:00 PDT
Date: Sun 14 Jun 1987 23:45-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #145
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 15 Jun 1987 Volume 5 : Issue 145
Today's Topics:
Query - Why Did The $6,000,000 Man Run So Slowly?,
Science - Applying AI Models to Biology
----------------------------------------------------------------------
Date: Fri, 12 Jun 87 00:51:41 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: why did the $6,000,000 man run so slowly?
Why did the six million dollar man run so slowly?
Some time ago, Pat Hays posted a message in which he asked people for
explanations for the fact that Dr. Who's tardis is bigger on the
inside than it appears to be from the outside. He was trying, of
course, to discover something about our common sense model of the
physical world.
I have a similar question which might shed some light on our common
sense notions of time and actions: why did the six million dollar man
run so slowly? As you recall, the six million dollar man (from the
popular TV show in the early '70's) had bionic legs which enabled him
to run at super-human speeds. However, when the producers wanted to
show him doing this, they slowed down the image of him running. That
is, to depict him running at incredibly fast speeds, they showed an
image of him moving in "slow motion".
Id like to collect explanations for this fact.
Tim.
------------------------------
Date: 12 Jun 87 20:51:51 GMT
From: ihnp4!homxb!houxm!hou2d!avr@ucbvax.Berkeley.EDU (Adam V. Reed)
Subject: Re: Why did the six-million dollar man run so slowly?
Slow motion is commonly used in TV (and before that, newsreel) reports
to represent very fast motion (e.g. in horse races and other sports
events). My guess is that this originated through use of free "photo
finish" footage, originally filmed for the use of sport-event judges,
in early movie newsreels. If my guess is right, the representation of
fast movement with slow-motion footage uses a learned but highly
familiar mental association.
Adam Reed (hou2d!adam)
------------------------------
Date: 13 Jun 87 03:16:03 GMT
From: code@sphinx.uchicago.edu (paul robinson wilson)
Subject: Re: Why did the six-million dollar man run so slowly?
In article <1431@hou2d.UUCP> avr@hou2d.UUCP (Adam V. Reed) writes:
>Slow motion is commonly used in TV (and before that, newsreel) reports
>to represent very fast motion (e.g. in horse races and other sports
>events). My guess is that this originated through use of free "photo
>finish" footage, originally filmed for the use of sport-event judges,
>in early movie newsreels. If my guess is right, the representation of
>fast movement with slow-motion footage uses a learned but highly
>familiar mental association.
I think it may be more subtle than that. There is a general tendency for
effective, competent motion to be smooth and for large motions to be
relatively slow. A long-legged runner runs more "slowly" than a short-legged
one, but covers more ground. A jaguar moves fluidly and less hurriedly than
its usual prey, making large bounds seemingly effortlessly. By contrast,
the little kid trying to keep up with the big kids moves its legs very fast.
Naturally, if we saw speeded-up film of the $ 6 Meg man, we'd think he looked
comical, with his legs moving very rapidly, like a small (impotent) creature's.
Slow-motion, however, looks smooth and graceful, revealing the grace with
which we all move, but seldom notice. Our ability to appreciate this
(intended) effect without the accompanying (unintended) impression of his
moving quite slowly, however, may in fact depend on our "being used to it"
from television sports, etc. We appreciate the obvious grace while suspending
our judgement about speed.
The _right_ way to show it, I guess, would have been to have Lee Majors
bound 20 ft. (or thereabouts) at a time, and quickly. Besides being a bit
difficult to accomplish, it's also a little hard on the skeletal structure.
They would have gone through stuntmen at quite a clip :-).
(By the way, I believe Lee Majors is a rather short guy, and would have looked
especially comical in sped-up film, coveing significant ground, with normal
stuff to gauge him against.)
| Paul R. Wilson ph.: (312) 947-0740 uucp: ...!ihnp4!uicbert!wilson |
| Electronic Mind Control Lab if no answer: ...ihnp4!gargoyle!sphinx!code |
| UIC EECS Dept. (M/C 154) arpa: uicbert!wilson@uxc.cso.uiuc.edu |
| P.O.Box 4348 Chicago,IL 60680 |
------------------------------
Date: 13 Jun 87 06:18:52 GMT
From: pattis@june.cs.washington.edu (Richard Pattis)
Subject: Re: Why did the six-million dollar man run so slowly?
I've thought that the slowdown was not from the perspective of the viewer,
but from the perspective of the the $6M man. The viewer, viewing from the
frame of the $6M man, is moving so fast that everything else seems slowed
down.
------------------------------
Date: 13 Jun 87 17:49:31 GMT
From: super.upenn.edu!linc.cis.upenn.edu!mayerk@RUTGERS.EDU (Kenneth Mayer)
Subject: Re: Why did the six-million dollar man run so slowly?
Occaisionally, the producers _did_ show Lee Majors in a speeded up shot. The
effect was comical. (As I recall, there was this old farmer watching from the
porch of his house as Mr. $6million sprinted across his field.) I like the
cougar metaphor. Wildlife films of such an animal in normal speed are choppy,
incredibly brief, and usuall ends with the felling of the prey. In slow-mo
we get a chance to see the beautiful detail of the predator flying by.
From a cinematic viewpoint, the camera director/special effects director had
to do something to show that Steve Austin wasn't simply jogging across a field
like the rest of us. Slowing the file speed (and speeding up apparent time)
looks comical, like an old Keystone Cops film. Stretching out the time line
increases tension. The viewer gets a chance to examine more detail per sec.
of real time. Exactly the way a novel will be incredibly brief during
transitions, and excrutiatingly deatailed during climaxes. (I just finished
reading Misery, by Stephen King. For a good reflective look at a writer's art,
packaged in a really good thriller, borrow this book from the library for a
summer weekend reader.)
Kenneth Mayer mayerk@eniac.seas.upenn.edu
------------------------------
Date: 10 Jun 87 09:33:34 GMT
From: nosc!humu!uhccux!todd@sdcsvax.ucsd.edu (The Perplexed Wiz)
Subject: Re: Taking AI models and applying them to biology...
In article <836@pixar.UUCP> davel@pixar.UUCP (David Longerbeam) writes:
>In article <622@unicus.UUCP>, craig@unicus.UUCP (Craig D. Hubley) writes:
>> This description of the human memory system, though cloaked in vaguer terms,
>> corresponds more or less one-to-one with the traditional computer
>> architecture we all know and love. To wit:
> [description deleted]
>> At least this far, this theory appears to owe a lot to computer science.
>> Granted, there is lots of empirical evidence in favour, but we all know
>> how a little evidence can go far too far towards developing an analogy.
>One of my philosophy professors in college offered the observation that
>models for the human mind have always seemed to correspond to the most
>advanced form of technology at that given point in history. He could
It's true that theories of cognition often reflect the current popular
technology. But before we start arguing current theories as reflections
of computer science and physiology, I suggest we at least have some
common starting point for our discussion.
I don't want to suggest that you need a Ph.D. in Cognitive Psychology
to discuss the subject, but you might want to consider reading one
of the many intro texts on the subject before leaping to any speculations
(wild or otherwise :-).
An intro text I often recommend to people with a more than casual
interest in cognition is:
Anderson, John (1985).
Cognitive Psychology and Its Implications. (2nd edition)
New York: W.H. Freeman and Co.
[The 1st edition also has much to recommend it. It was written from
a psychological viewpoint, and introduces vocabulary and concepts that
may be unfamiliar to computer scientists. The 2nd edition was rewritten
with an AI (or cognitive psychology!) vocabulary, hence risks echoing the
preconceptions of the field instead of contributing fresh insights. -- KIL]
If you are interested in a historical perspective of psychological
research, I suggest you take a peek at:
Hearst, Eliot (Ed.) (1979).
The First Century of Experimental Psychology.
Hillsdale, New Jersey: Lawrence Erlbaum Associates, Pub.
And finally, though I don't always agree with what Richard Gregory has
to say, I always enjoy hearing or reading his ideas and theories. His
"Mind in Science" is an interesting speculative book.
Gregory, Richard (1981).
Mind in Science: A History of Explanations in
Psychology and Physics.
Cambridge: Cambridge University Press
Well, I hope we at least have some common reference point now...
Todd Ogasawara
"With a good wind behind me and and a lot of luck...
Ph.D. in Psychology later this year :-)"
--
Todd Ogasawara, U. of Hawaii Computing Center
UUCP: {ihnp4,seismo,ucbvax,dcdwest}!sdcsvax!nosc!uhccux!todd
ARPA: uhccux!todd@nosc.MIL
INTERNET: todd@uhccux.UHCC.HAWAII.EDU
------------------------------
Date: Wed, 10 Jun 87 09:51 EDT
From: Seth Steinberg <sas@bfly-vax.bbn.com>
Subject: Borrowing from Biology [Half in Jest]
Actually, the biologists have been borrowing from the history of the
Roman Empire. Cincinatus comes down from his farm and codifies the
laws for the Republic and creates a nearly perfect mechanism which
starts taking over the Mediterranean basin. By providing for a means
of succession (read "DNA replication"), the Empire is able to achieve
higher levels of organization. Unfortunately, the military (read "the
immune system"), slowly grows in strength as the Empire expands and
finally reaches a limit to its expansion and spends the next millenium
rotting away in Byzantium.
Theories about entropy are about complex systems in general, not just
the behavior of energy in steam engines. Biologists have latched onto
them to account for aging in organisms and to explain the epochs of
evolution. (Why aren't there any new phyla being created?) If you've
ever tried to make a major change in a decade old program think of what
the biologists are up against with their billion year old kludges.
Last month, an article in Scientific American described a glucose
complex based aging mechanism, arguing that many aging effects could be
caused by very slow chemical reactions induced by the operating
environment. Next month we may discover an actual internal counter
within each cell. It is quite probable that there are dozens of
mechanisms at work. With 90% of the genome encoding for garbage,
elegant design is more of a serendipity than the norm.
Seth Steinberg
sas@bbn.com
P.S. Did you notice the latest kludge? They've found a gene whose DNA
complement also encodes a gene! Kind of like a 68000 program you can
execute if you put a logical complement on each instruction fetch.
Neat, huh?
------------------------------
Date: 12 Jun 87 16:08:04 GMT
From: hao!boulder!eddy@ames.arpa (Sean Eddy)
Subject: Re: Taking AI models and applying them to biology...
In article <1331@sigi.Colorado.EDU> pell@boulder.Colorado.EDU writes:
>It would seem to me that the step that is likely to give the cell trouble
>is not mitosis but DNA replication. If a whole chromosome lost or
>non-disjoined, that cell is in some serious trouble. Progressive
>accumulation mistakes through replication and general maintanence seems a more
>likely culprit.
"General maintenance" is a very important thing to bring up. It seems
to me that replication/mitosis can't be the whole story in aging. One
must also propose other models because there are cells that do not
divide after a certain point, yet still age and die. Neurons are the
classic example; not only do they not divide, they cannot even
be replaced (in humans) if damaged.
- Sean Eddy
- MCD Biology; U. of Colorado at Boulder; Boulder CO 80309
- eddy@boulder.colorado.EDU !{hao,nbires}!boulder!eddy
-
- "So what. Big deal."
- - Emilio Lazardo
------------------------------
Date: 13 Jun 87 23:03:16 GMT
From: mcvax!lambert@seismo.css.gov (Lambert Meertens)
Subject: Re: Taking AI models and applying them to biology...
In article <836@pixar.UUCP> davel@pixar.UUCP (David Longerbeam) writes:
> In article <622@unicus.UUCP>, craig@unicus.UUCP (Craig D. Hubley) writes:
|
| > This description of the human memory system, though cloaked in vaguer terms,
| > corresponds more or less one-to-one with the traditional computer
| > architecture we all know and love. To wit:
|
| [description deleted]
|
| > At least this far, this theory appears to owe a lot to computer science.
| > Granted, there is lots of empirical evidence in favour, but we all know
| > how a little evidence can go far too far towards developing an analogy.
|
| One of my philosophy professors in college offered the observation that
| models for the human mind have always seemed to correspond to the most
> advanced form of technology at that given point in history.
I find the connection between models of human memory as developed in
cognitive psychology and existing computer architectures rather tenuous.
The main similarity appears to be that several levels of memory can be
discerned, but the suggested analogy in function is a bit far-fetched.
It is perhaps worth pointing out that much of the current models in
cognitive psychology can already be found in the pioneering work of Otto
Selz (Muenchen, 1881 - Auschwitz, 1943), antedating the computer era.
--
Lambert Meertens, CWI, Amsterdam; lambert@cwi.nl
------------------------------
Date: Thu, 11 Jun 87 13:48:05 BST
From: Graham Higgins <gray%hplb.csnet@RELAY.CS.NET>
Subject: Re: Taking AI models and applying them to biology...
In article <622@unicus.UUCP>, craig@unicus.UUCP (Craig D. Hubley) writes:
> I was semi-surprised in recent months to discover that cognitive psychology,
> far from developing a bold new metaphor for human thinking, has (to a degree)
> copied at least one metaphor from third-generation computer science.
Psychology freely borrows *any* models that will help it get a grip on
characterising and explaining the phenomena of cognition. Over the years,
analogies of the workings of the mind have been constructed from : windmills,
hydraulic systems, telephone switching exchanges and latterly, the computer (or
more properly, information-processing devices). The one thing that all these
analogies have in common is that they draw on the technological state-of-the-art
of the time. (The "internal combustion engine" analogy is a new one to me).
David Longerbeam's comment about the requirement for empiricism is valid in this
instance. Donald Hebb assumed a separation of STM and LTM in a 1949 paper (and
that's going back quite some time, only a year after Shockley's invention of the
transistor). It is unlikely that the computer-architecture construct of
"archived storage" played any part in Hebb's dichotomising of human memory. It
appears that this is one example of a model developed within cognitive
psychology, independently of developments in computer architecture. (I'm not
well-versed in comp.sci. history - but it seems reasonable to conjecture that
Hebb was unaware of the notions of "archived storage" when he was developing his
dichotomisation).
> This description of the human memory system, though cloaked in vaguer terms,
> corresponds more or less one-to-one with the traditional computer
> architecture we all know and love ...
>
> - senses have "iconic" and "echo" memories analogous to buffers.
> - short term memory holds information that is organized for quick
> processing, much like main storage in a computing system.
> - long term memory holds information in a sort of semantic
> association network where large related pieces of information
> reside, similar to backing or "archived" computing storage.
I think that this is somewhat of an over-simplification. There are quite a few
phenomena arising from studies of "iconic", "echoic", "short-term" and
"long-term" areas of human memory which do not fit so tamely into a
computer-architecture model. Thus, there has *not* been uncritical acceptance of
either that the "iconic" and "echoic" aspects of memory are passive or that
memory can be simply dichotomised into into STM and LTM sections. In the absence
of anything better, the analogies will do for now, but there are too many
phenomena which don't fit in to these analogies for them to anything but
convenient for the moment.
One of the disciplinary traits actively promoted in psychology (be it cognitive,
social, experimental, etc.) is a high degree of circumspection. (There is a
tradition that one never sees a one-armed psychologist - "on one hand .... and
on the other ... "). Thus models and analogies *can* be freely borrowed from
other areas and exploited for what they offer, for as long as they exhibit some
level of descriptive utility. It is instructive to note that contemporary
cognitive psychologists no longer use windmills or telephone exchanges (or even
the internal combustion engine) as analogies of the workings of the mind. These
particular analogies have outlived their usefulness and have been discarded (I
hope!).
Graham Higgins || The opinions expressed above
Hewlett-Packard Labs || are not to be contrued as the
Bristol, U.K. || opinions, stated or otherwise,
gjh@hplb.csnet +44 272 799910 xt 4060 || of Hewlett-Packard
------------------------------
End of AIList Digest
********************
∂16-Jun-87 0300 LAWS@Stripe.SRI.Com AIList Digest V5 #146
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Jun 87 02:53:19 PDT
Date: Mon 15 Jun 1987 23:20-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #146
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 16 Jun 1987 Volume 5 : Issue 146
Today's Topics:
Theory - The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 9 Jun 87 22:12:32 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem
In article <812@mind.UUCP> Stevan Harnad <harnad@mind.UUCP> replies:
With regard physical invertibility and the A/D distinction:
>
>> a *digitized* image -- in your terms... is "analog" in the
>> information it preserves and not in the information lost. This
>> seems to me to be a very unhappy choice of terminology!
>
> For the time being, I've acknowledged that
>my invertibility criterion is, if not necessarily unhappy, somewhat
>surprising in its implications, for it implies (1) that being analog
>may be a matter of degree (i.e., degree of invertibility) and (2) even
>a classical digital system must be regarded as analog to a degree ...
Grumble. These consequences only *seem* surprising if we forget that you've
redefined "analog" in a non-standard manner; this is precisely I why I keep
harping on your terminology. Compare them with what you're really saying:
"physical invertibility is a matter of degree" or "a classical digital system
still employs physically invertible representations" -- both quite humdrum.
With regard to the symbolic AI approach to the "symbol-grounding problem":
>
>One proposal, as you note, is that a pure symbol-manipulating system can be
>"grounded" by merely hooking it up causally in the "right way" to the outside
>world with simple (modular) transducers and effectors. ... I have argued
>that [this approach] simply won't succeed in the long run (i.e., as we
>attempt to approach an asymptote of total human performance capacity ...)
>...In (1) a "toy" case ... the right causal connections could be wired
>according to the human encryption/decryption scheme: Inputs and outputs could
>be wired into their appropriate symbolic descriptions. ... But none but the
>most diehard symbolic functionalist would want to argue that such a simple
>toy model was "thinking," ... The reason is that we are capable of
>doing *so much more* -- and not by an assemblage of endless independent
>modules of essentially the same sort as these toy models, but by some sort of
>(2) integrated internal system. Could that "total" system be just an
>oversized toy model -- a symbol system with its interpretations "fixed" by a
>means analogous to these toy cases? I am conjecturing that it is not.
I think your reply may misunderstand the point of my objection. I'm not
trying to defend the intentionality of "toy" programs. I'm not even
particularly concerned to *defend* the symbolic approach to AI (I personally
don't even believe in it). I'm merely trying to determine exactly what your
argument against symbolic AI is.
I had thought, perhaps wrongly, that you were claiming that the
interpretations of systems conceived by symbolic AI system must somehow
inevitably fail to be "grounded", and that only a system which employed
"analog" processing in the way you suggest would have the causal basis
required for fixing an interpretation. In response, I pointed out first that
advocates of the symbolic approach already understand that causal commerce
with the environment is necessary for intentionality: they envision the use
of complex perceptual systems to provide the requisite "grounding". So it's
not as though the symbolic approach is indifferent to this issue. And your
remarks against "toy" systems and "hard-wiring" the interpretations of the
inputs are plain unfair -- the symbolic approach doesn't belittle the
importance or complexity of what perceptual systems must be able to do. It is
in total agreement with you that a truly intentional system must be capable
of complex adaptive performance via the use of its sensory input -- it just
hypothesizes that symbolic processing is sufficient to achieve this.
And, as I tried to point out, there is just no reason that a modular,
all-digital system of the kind envisioned by the symbolic approach could not
be entirely "grounded" BY YOUR OWN THEORY OF "GROUNDEDNESS": it could employ
"physically inevertible" representations (only they would be digital ones),
from these it could induct reliable "feature filters" based on training (only
these would use digital rather than analog techniques), etc. I concluded that
the symbolic approach appears to handle your so-called "grounding problem"
every bit as well as any other method.
Now comes the reply that you are merely conjecturing that analog processing
may be required to realize the full range of human, as opposed to "toy",
performance -- in short, you think the symbolic approach just won't work.
But this is a completely different issue! It has nothing to do with some
mythical "symbol grounding" problem, at least as I understand it. It's just
the same old "intelligent-behavior-generating" problem which everyone in AI,
regardless of paradigm, is looking to solve.
From this reply, it seems to me that this alleged "symbol-grounding problem"
is a real red-herring (it misled me, at least). All you're saying is that
you suspect that mainstream AI's symbol system hypothesis is false, based on
its lack of conspicuous performance-generating sucesses. Obviously everyone
must recognize that this is a possibility -- the premise of symbolic AI is,
after all, only a hypothesis.
But I find this a much less interesting claim than I originally thought --
conjectures, after all, are cheap. It *would* be interesting if you could
show, as, say, the connectionist program is trying to, how analog processing
can work wonders that symbol-manipulation can't. But this would require
detailed research, not speculation. Until then, it remains a mystery why your
proposed approach should be regarded as any more promising than any other.
Anders Weinstein
BBN Labs
------------------------------
Date: 10 Jun 87 21:28:23 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
aweinste@Diamond.BBN.COM (Anders Weinstein) of BBN Laboratories, Inc.,
Cambridge, MA writes:
> There's no [symbol] grounding problem, just the old
> behavior-generating problem
Before responding to the supporting arguments for this conclusion, let
me restate the matter in what I consider to be the right way. There is:
(1) the behavior-generating problem (what I have referred to as the problem of
devising a candidate that will pass the Total Turing Test), (2) the
symbol-grounding problem (the problem of how to make formal symbols
intrinsically meaningful, independent of our interpretations), and (3)
the conjecture (based on the existing empirical evidence and on
logical and methodological considerations) that (2) is responsible for
the failure of the top-down symbolic approach to solve (1).
>>my [SH's] invertibility criterion is, if not necessarily unhappy, somewhat
>>surprising in its implications, for it implies that (1) being analog may
>>be a matter of degree (i.e., degree of invertibility) and that (2) even
>>a classical digital system must be regarded as analog to a degree ...
>
> These consequences only *seem* surprising if we forget that you've
> redefined "analog" in a non-standard manner... you're really saying:
> "physical invertibility is a matter of degree" or "a classical digital
> system still employs physically invertible representations" -- both
> quite humdrum.
You've bypassed the three points I brought up in replying to your
challenge to my invertibility criterion for an analog transform the
last time: (1) the quantization in standard A/D is noninvertible, (2) a
representation can only be analog in what it preserves, not in what it
fails to preserve, and, in cognition at any rate, (3) the physical
shape of the signal may be what matters, not the "message" it
"carries." Add to this the surprising logical consequence that a
"dedicated" digital system (hardwired to its peripherals) would be
"analog" in its invertible inputs and outputs according to my
invertibility criterion, and you have a coherent distinction that conforms
well to some features of the classical A/D distinction, but that may prove
to diverge, as I acknowledged, sufficiently to make it an independent,
"non-standard" distinction, unique to cognition and neurobiology. Would it be
surprising if classical electrical engineering concepts did not turn
out to be just right for mind-modeling?
> I [AW] had thought, perhaps wrongly, that you were claiming that the
> interpretations of systems conceived by symbolic AI system must somehow
> inevitably fail to be "grounded", and that only a system which employed
> "analog" processing in the way you suggest would have the causal basis
> required for fixing an interpretation.
That is indeed what I'm claiming (although you've completely omitted
the role of the categorical representations, which are just as
critical to my scheme, as described in the CP book). But do make sure you
keep my "non-standard" definition of analog in mind, and recall that I'm
talking about asymptotic, human-scale performance, not toy systems.
Toy systems are trivially "groundable" (even by my definition of
"analog") by hard-wiring them into a dedicated input/output
system. But the problem of intrinsic meaningfulness does not arise for
toy models, only for devices that can pass the Total Turing Test (TTT).
[The argument here involves showing that to attribute intentionality to devices
that exhibit sub-TTT performance is not justified in the first place.]
The conjecture is accordingly that the modular solution (i.e., hardwiring an
autonomous top-down symbolic module to conventional peripheral modules
-- transducers and effectors) will simply not succeed in producing a candidate
that will be able to pass the Total Turing Test, and that the fault
lies with the autonomy (or modularity) of the symbolic module.
But I am not simply proposing an unexplicated "analog" solution to the
grounding problem either, for note that a dedicated modular system *would*
be analog according to my invertibility criterion! The conjecture is
that such a modular solution would not be able to meet the TTT
performance criterion, and the grounds for the conjecture are partly
inductive (extrapolating symbolic AI's performance failures), partly
logical and methodological (the grounding problem), and partly
theory and data-driven (psychophysical findings in human categorical
perception). My proposal is not that some undifferentiated,
non-standard "analog" processing must be going on. I am advocating a
specific hybrid bottom-up, symbolic/nonsymbolic rival to the pure
top-down symbolic approach (whether or not the latter is wedded to
peripheral modules), as described in the volume under discussion
("Categorical Perception: The Groundwork of Cognition," CUP 1987).
> advocates of the symbolic approach already understand that causal
> commerce with the environment is necessary for intentionality: they
> envision the use of complex perceptual systems to provide the
> requisite "grounding". So it's not as though the symbolic approach
> is indifferent to this issue.
This is the pious hope of the "top-down" approach: That suitably
"complex" perceptual systems will meet for a successful "hook-up"
somewhere in the middle. But simply reiterating it does not mean it
will be realized. The evidence to date suggests the opposite: That the
top-down approach will just generate more special-purpose toys, not a
general purpose, TTT-scale model of human performance capacity. Nor is
there any theory at all of what the requisite perceptual "complexity"
might be: The stereotype is still standard transducers that go from physical
energy via A/D conversion straight into symbols. Nor does "causal
commerce" say anything: It leaves open anything from the modular
symbol-cruncher/transducer hookups of the kind that so far only seem
capable of generating toy models, to hybrid, nonmodular, bottom-up
models of the sort I would advocate. Perhaps it's in the specific
nature of the bottom-up grounding that the nature of the requisite
"complexity" and "causality" will be cashed in.
> your remarks against "toy" systems and "hard-wiring" the
> interpretations of the inputs are plain unfair -- the symbolic
> approach doesn't belittle the importance or complexity of what
> perceptual systems must be able to do. It is in total agreement
> with you that a truly intentional system must be capable of complex
> adaptive performance via the use of its sensory input -- it just
> hypothesizes that symbolic processing is sufficient to achieve this.
And I just hypothesize that it isn't. And I try to say why not (the
grounding problem and modularity) and what to do about it (bottom-up,
nonmodular grounding of symbolic representations in iconic and categorical
representations).
> there is just no reason that a modular, all-digital system of the
> kind envisioned by the symbolic approach could not be entirely
> "grounded" BY YOUR OWN THEORY OF "GROUNDEDNESS": it could employ
> "physically inevertible" representations (only they would be digital
> ones), from these it could induct reliable "feature filters" based on
> training (only these would use digital rather than analog techniques),
> etc. ... the symbolic approach appears to handle your so-called
> "grounding problem" every bit as well as any other method.
First of all, as I indicated earlier, a dedicated top-down symbol-crunching
module hooked to peripherals would indeed be "grounded" in my sense --
if it had TTT-performance power. Nor is it *logically impossible* that
such a system could exist. But it certainly does not look likely on the
evidence. I think some of the reasons we were led (wrongly) to expect it were
the following:
(1) The original successes of symbolic AI in generating intelligent
performance: The initial rule-based, knowledge-driven toys were great
successes, compared to the alternatives (which, apart from some limited
feats of Perceptrons, were nonexistent). But now, after a generation of
toys that show no signs of converging on general principles and growing
up to TTT-size, the inductive evidence is pointing in the other direction:
More ad hoc toys is all we have grounds to expect.
(2) Symbol strings seemed such hopeful candidates for capturing mental
phenomena such as thoughts, knowledge, beliefs. Symbolic function seemed
like such a natural, distinct, nonphysical level for capturing the mind.
Easy come, easy go.
(3) We were persuaded by the power of computation -- Turing
equivalence and all that -- to suppose that computation
(symbol-crunching) just might *be* cognition. If every (discrete)
thing anyone or anything (including the mind) does is computationally
simulable, then maybe the computational functions capture the mental
functions? But the fact that something is computationally simulable
does not entail that it is implemented computationally (any more than
behavior that is *describable* as ruleful is necessarily following an
explicit rule). And some functions (such as transduction and causality)
cannot be implemented computationally at all.
(4) We were similarly persuaded by the power of digital coding -- the
fact that it can approximate analog coding as closely as we please
(and physics permits) -- to suppose that digital representations were
the only ones we needed to think about. But the fact that a digital
approximation is always possible does not entail that it is always
practical or optimal, nor that it is the one that is actually being
*used* (by, say, the brain). Some form of functionalism is probably
right, but it certainly need not be symbolic functionalism, or a
functionalism that is indifferent to whether a mental function or
representation is analog or digital: The type of implementation may
matter, both to the practical empirical problem of successfully
generating performance and to the untestable phenomenological problem of
capturing qualitative subjective experience. And some functions (let
me again add), such as transduction and (continuous) A/A, cannot be
implemented purely symbolically at all.
A good example to bear in mind is Shepard's mental rotation
experiments. On the face of it, the data seemed to suggest that
subjects were doing analog processing: In making same/different
judgments of pairs of successively presented 2-dimensional projections
of 3-dimensional, computer-generated, unfamiliar forms, subjects' reaction
times for saying "same" when one stimulus was in a standard orientation and
the other was rotated were proportional to the degree of rotation. The
diehard symbolists pointed out (correctly) that the proportionality,
instead of being due to the real-time analog rotation of a mental icon, could
have been produced by, say, (1) serially searching through the coordinates
of a digital grid on which the stimuli were represented, with more distant
numbers taking more incremental steps to reach, or by (2) doing
inferences on formal descriptions that became more complex (and hence
time-consuming) as the orientation became more eccentric. The point,
though, is that although digital/symbolic representations were indeed
possible, so were analog ones, and here the latter would certainly seem to be
more practical and parsimonious. And the fact of the matter -- namely,
which kinds of representations were *actually* used -- is certainly
not settled by pointing out that digital representations are always
*possible.*
Maybe a completely digital mind would have required a head the size of
New York State and polynomial evolutionary time in order to come into
existence -- who knows? Not to mention that it still couldn't do the
"A" in the A/D...
> [you] reply that you are merely conjecturing that analog processing
> may be required to realize the full range of human, as opposed to "toy",
> performance -- in short, you think the symbolic approach just won't
> work. But this... has nothing to do with some mythical "symbol
> grounding" problem, at least as I understand it. It's just
> the same old "intelligent-behavior-generating" problem which everyone
> in AI, regardless of paradigm, is looking to solve... All you're
> saying is that you suspect that mainstream AI's symbol system
> hypothesis is false, based on its lack of conspicuous
> performance-generating successes. Obviously everyone must recognize
> that this is a possibility -- the premise of symbolic AI is, after
> all, only a hypothesis.
I'm not just saying I think the symbolic hypothesis is false. I'm
saying why I think it's false (ungroundedness) and I'm suggesting an
alternative (a bottom-up hybrid).
> But I find this a much less interesting claim than I originally
> thought -- conjectures, after all, are cheap. It *would* be
> interesting if you could show, as, say, the connectionist program
> is trying to, how analog processing can work wonders that
> symbol-manipulation can't. But this would require detailed research,
> not speculation. Until then, it remains a mystery why your proposed
> approach should be regarded as any more promising than any other.
Be patient. My hypotheses (which are not just spontaneous conjectures,
but are based on an evaluation of the available evidence, the theoretical
alternatives, and the logical and methodological problems involved)
will be tested. They even have a potential connectionist component (in
the induction of the features subserving categorization), although
connectionism comes in for criticism too. For now it would seem only
salutary to attempt to set cognitive modeling in directions that
differ from the unprofitable ones it has taken so far.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 11 Jun 87 15:24:22 GMT
From: ihnp4!homxb!houxm!houdi!marty1@ucbvax.Berkeley.EDU
(M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <828@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> aweinste@Diamond.BBN.COM (Anders Weinstein) of BBN Laboratories, Inc.,
> Cambridge, MA writes:
>
> > There's no [symbol] grounding problem, just the old
> > behavior-generating problem
>
> ..... There is:
> (1) the behavior-generating problem (what I have referred to as the problem of
> devising a candidate that will pass the Total Turing Test), (2) the
> symbol-grounding problem (the problem of how to make formal symbols
> intrinsically meaningful, independent of our interpretations), and (3) ...
Just incidentally, what is the intrinsic meaning of "intrinsically
meaningful"? The Turing test is an objectively verifiable criterion.
How can we objectively verify intrinsic meaningfulness?
> .... Add to this the surprising logical consequence that a
> "dedicated" digital system (hardwired to its peripherals) would be
> "analog" in its invertible inputs and outputs according to my
> invertibility criterion, .....
Using "analog" to mean "invertible" invites misunderstanding, which
invites irrelevant criticism.
Human (in general, vertebrate) visual processing is a dedicated
hardwired digital system. It employs data reduction to abstract such
features as motion, edges, and orientation of edges. It then forms a
map in which position is crudely analog to the visual plane, but
quantized. This map is sufficiently similar to maps used in image
processing machines so that I can almost imagine how symbols could be
generated from it.
By the time it gets to perception, it is not invertible, except with
respect to what is perceived. Noninvertibility is demonstrated in
experiments in the identification of suspects. Witnesses can report
what they perceive, but they don't always perceive enough to invert
the perceived image and identify the object that gave rise to the
perception. If you don't agree, please give a concrete, objectively
verifiable definition of "invertibility" that can be used to refute my
conclusion.
If I am right, human intelligence itself relies on neither analog nor
invertible symbol grounding, and therefore artificial intelligence
does not require it.
By the way, there is an even simpler argument: even the best of us can
engage in fuzzy thinking in which our symbols turn out not to be
grounded. Subjectively, we then admit that our symbols are not
intrinsically meaningful, though we had interpreted them as such.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
End of AIList Digest
********************
∂16-Jun-87 1202 LAWS@Stripe.SRI.Com AIList Digest V5 #147
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Jun 87 12:01:47 PDT
Date: Mon 15 Jun 1987 23:23-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #147
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 16 Jun 1987 Volume 5 : Issue 147
Today's Topics:
Theory - Symbol Grounding and Physical Invertibility
----------------------------------------------------------------------
Date: 11 Jun 87 21:15:31 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem
In article <828@mind.UUCP> Stevan Harnad <harnad@mind.UUCP> writes
>
>> There's no [symbol] grounding problem, just the old
>> behavior-generating problem
> There is:
>(1) the behavior-generating problem (what I have referred to as the problem of
>devising a candidate that will pass the Total Turing Test), (2) the
>symbol-grounding problem (the problem of how to make formal symbols
>intrinsically meaningful, independent of our interpretations), and (3)
>the conjecture (based on the existing empirical evidence and on
>logical and methodological considerations) that (2) is responsible for
>the failure of the top-down symbolic approach to solve (1).
It seems to me that in different places, you are arguing the relation between
(1) and (2) in both directions, claiming both
(A) The symbols in a purely symbolic system will always be
ungrounded because such systems can't generate real performance;
and
(B) A purely symbolic system can't generate real performance because
its symbols will always be ungrounded.
That is, when I ask you why you think the symbolic approach won't work, one
of your reasons is always "because it can't solve the grounding problem", but
when I press you for why the symbolic approach can't solve the grounding
problem, it always turns out to be "because I think it won't work." I think
we should get straight on the priority here.
It seems to me that, contra (3), thesis (A) is the one that makes perfect
sense -- in fact, it's what I thought you were saying. I just don't
understand (B) at all.
To elaborate: I presume the "symbol-grounding" problem is a *philosophical*
question: what gives formal symbols original intentionality? I suppose the
only answer anybody knows is, in brief, that the symbols must be playing a
certain role in what Dennett calls an "intentional system", that is, a system
which is capable of producing complex, adaptive behavior in a rational way.
Since such a system must be able to respond to changes in its environment,
this answer has the interesting consequence that causal interaction with the
world is a *necessary* condition for original intentionality. It tells us
that symbols in a disconnected computer, without sense organs, could never be
"grounded" or intrinsically meaningful. But those in a machine that can
sense and react could be, provided the machine exhibited the requisite
rationality.
And this, as far as I can tell, is the end of what we learn from the "symbol
grounding" problem -- you've got to have sense organs. For a system that is
not causally isolated from the environment, the symbol-grounding problem now
just reduces to the old behavior-generating problem, for, if we could just
produce the behavior, there would be no question of the intentionality of the
symbols. In other words, once we've wised up enough to recognize that we must
include sensory systems (as symbolic AI has), we have completely disposed of
the "symbol grounding" problem, and all that's left to worry about is the
question of what kind of system can produce the requisite intelligent
behavior. That is, all that's left is the old behavior-generating problem.
Now as I've indicated, I think it's perfectly reasonable to suspect that the
symbolic approach is insufficient to produce full human performance. You
really don't have to issue any polemics on this point to me; such a suspicion
could well be justified by pointing out the triviality of AI's performance
achievements to date.
What I *don't* see is any more "principled" or "logical" or "methodological"
reason for such a suspicion; in particular, I don't understand how (B) could
provide such a reason. My system can't produce intelligent performance
because it doesn't make its symbols meaningful? This statement has just got
things backwards -- if I could produce the behavior, you'd have to admit that
its symbols had all the "grounding" they needed for original intentionality.
In sum, apart from the considerations that require causal embedding, I don't
see that there *is* any "symbol-grounding" problem, at least not any problem
that is any different from the old "total-performance generating" problem.
For this reason, I think your animadversions on symbol grounding are largely
irrelevant to your position -- the really substantial claims pertain only to
"what looks like it's likely to work" for generating intelligent behavior.
On a more specific issue:
>
>You've bypassed the three points I brought up in replying to your
>challenge to my invertibility criterion for an analog transform the
>last time: (1) the quantization in standard A/D is noninvertible,
Yes, but *my* point has been that since there isn't necessarily any more loss
here than there is in a typical A/A transformation, the "degree of
invertibility" criterion cross-cuts the intuitive A/D distinction.
Look, suppose we had a digitized image, A, which is of much higher resolution
than another analog one, B. A is more invertible since it contains more
detail from which to reconstruct the original signal, but B is more
"shape-preserving" in an intuitive sense. So, which do you regard as "more
analog"? Which does your theory think is better suited to subserving our
categorization performance? If you say B, then invertibility is just not what
you're after.
Anders Weinstein
BBN Labs
------------------------------
Date: 12 Jun 87 08:16:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: symbol grounding and physical invertibility
S. Harnad replies:
> According to my view, invertibility (and perhaps inversion)
> captures just the relevant features of causation and resemblance that
> are needed to ground symbols. The relation is between the proximal
> projection (of a distal object) onto the sensory surfaces -- let's
> call it P -- and an invertible transformation of that projection [I(P)].
> The latter is what I call the "iconic representation." Note that the
> invertibility is with the sensory projection, *not* the distal object. I
> don't believe in distal magic. My grounding scheme begins at the
> sensory surfaces ("skin and in"). No "wider" metaphysical causality is
> involved, just narrow, local causality.
Well, OK, glad you clarified that - I think there are issues here
about the difference between grounding symbols in causation emanating
from distal objects vs. grounding them in proximal sensory surfaces -
(optical illusions, hallucinations, etc.) but let's pass over that
for now.
It still doesn't seem clear why invertibility should be necessary
for grounding (although it may be sufficient). Frinstance, suppose
we humans, or a robot, had four kinds of color receptors lurking
behind our retinas (retinae?), which responded to red, green,
blue and yellow wavelengths. And further suppose that stimulating
the yellow receptors alone produced the same iconic representation
as stimulating the red and green ones - ie both were experienced
as plain old yellow, nor could the experiencer in any way
distinguish between the yellows caused by the two different
stimulations. (A fortiori, the experiencer would certainly not
have more than one categorical representation, nor symbol for
such experiences.) In short, suppose that some information was
lost on the way in from the sensory surface, so we had a many
to one (hence non-invertible) mapping.
Would you then want to say that the symbol "yellow" was not grounded
for such a being?
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: 12 Jun 87 15:52:40 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
marty1@houdi.UUCP (M.BRILLIANT) of AT&T Bell Laboratories, Holmdel writes:
> Human visual processing is neither analog nor invertible.
Nor understood nearly well enough to draw the former two conclusions,
it seems to me. If you are taking the discreteness of neurons, the
all-or-none nature of the action potential, and the transformation of
stimulus intensity to firing frequency as your basis for concluding
that visual processing is "digital," the basis is weak, and the
analogy with electronic transduction strained.
As the (unresolved) discussion of the logical basis of the A/D distinction
last year indicated, nature itself may not be continuous, but
quantized. This would make continuity-based definitions of A/D moot.
If discrete photons strike discrete photoreceptors, then discontintuity
is transforming into discontinuity. Yet the question can still be
asked: Is the transformation preserving physical properties such as
intensity and spatial relations by transforming them to physical
properties that are isomorphic to them (e.g., intensity to frequency,
and spatial adjacency to spatial adjacency) as opposed to merely
"standing for" them in some binary code?
There is also the question of postsynaptic potentials, which, unlike
the all-or-none action potentials, are graded (to within the
pharmacological quantum of a neurotransmitter packet). What if
significant aspects of vision are coded at that level as fields or
gradients and their interactions? Or at the level of local or distributed
patterns of connectivity? Or at the chemical level? We don't even know
how to match up the various resolution-levels or "grains" of the inputs and
transformations involved: light quanta, neural quanta, psychophysical
quanta. What is discrete and above-threshold at one level may become
blurred, "continuous" and below-threshold at another.
> what is the intrinsic meaning of "intrinsically meaningful"?
> The Turing test is an objectively verifiable criterion. How can
> we objectively verify intrinsic meaningfulness?
We cannot objectively verify intrinsic meaningfulness. The Turing test
is the only available criterion. Yet we can make inferences about it
(for example, that it is unlikely to be present in a thermostat or
lisp code running on a vax). And we have some direct (but subjective)
evidence that it exists in at least one case (namely, our own): We
know the difference between looking up a meaning in an English/English
dictionary versus a Chinese/Chinese dictionary (if we are nonspeakers
of Chinese): The former symbols are meaningful and the latter are
not. We also know that we could "ground" an understanding of Chinese
(by translation) in our prior understanding of English; and we assume
that our understanding of English is grounded in our prior perceptual
learning and understanding of categories in the real world of
objects. Objective evidence of this perceptual grounding is provided
by our ability to discriminate, manipulate, categorize, name and
describe real-world objects and our ability to produce and respond to
names and descriptions meaningfully (i.e., all Turing criteria).
So the empirical question becomes the following: Is a device that has
nothing but symbols and can only manipulate them on the basis of their
shape more likely to be like our own (intrinsically grounded) case, or
more like the Chinese/Chinese dictionary, whose meanings can only be
derived by the mediation of an intrinsically grounded system like our own?
But the issue is ultimately empirical. The logical and methodological
considerations can really only serve to motivate pursuing one empirical
hypothesis rather than another (e.g., top-down symbolic vs. bottom-up
hybrid). The final arbiter is the Total Turing Test. If a pure symbolic
module linked to transducers and effectors turns out to be able to
generate all of our performance capacity then the grounding problem and
intrinsic intentionality was a red herring. As I make clear in the
paper "Minds, Machines and Searle," this is an empirical, not a
logical question. But on the evidence to date, this outcome looks
highly unlikely, and the obstacle seems to be the problem of bottom-up
grounding of symbols in nonsymbolic representations and in the real world
of objects.
> Using "analog" to mean "invertible" invites misunderstanding,
> which invites irrelevant criticism.
I have tried to capture with the invertibility criterion certain
features that may be important (perhaps even unique) to the case of
cognitive modeling -- features that fail to be captured by the
conventional electrical engineering criteria. I have acknowledged all
along that the physically invertible/noninvertible distinction may
turn out to be independent of the A/D distinction, although the
overlap looks significant. And I'm doing my best to sort out the
misunderstandings and irrelevant criticism...
> Human (in general, vertebrate) visual processing is a dedicated
> hardwired digital system. It employs data reduction to abstract such
> features as motion, edges, and orientation of edges. It then forms a
> map in which position is crudely analog to the visual plane, but
> quantized. This map is sufficiently similar to maps used in image
> processing machines so that I can almost imagine how symbols could be
> generated from it.
I am surprised that you state this with such confidence. In
particular, do you really think that vertebrate vision is well enough
understood functionally to draw such conclusions? And are you sure
that the current hardware and signal-analytic concepts from electrical
engineering are adequate to apply to what we do know of visual
neurobiology, rather than being prima facie metaphors?
> By the time it gets to perception, it is not invertible, except with
> respect to what is perceived. Noninvertibility is demonstrated in
> experiments in the identification of suspects. Witnesses can report
> what they perceive, but they don't always perceive enough to invert
> the perceived image and identify the object that gave rise to the
> perception. If you don't agree, please give a concrete, objectively
> verifiable definition of "invertibility" that can be used to refute my
> conclusion. If I am right, human intelligence itself relies on neither
> analog nor invertible symbol grounding, and therefore artificial
> intelligence does not require it.
I cannot follow your argument at all. Inability to categorize and identify
is indeed evidence of a form of noninvertibility. But my theory never laid
claim to complete invertibility throughout. (For the disadvantages of
"total invertibility," see Luria's "The Mind of a Mnemonist," or, for a more
literary depiction of the same problem, Borges's "Funes the Memorious." Both
are discussed in a chapter of mine entitled "Metaphor and Mental Duality"
in Simon & Sholes [eds] book "Language, Mind and Brain," Academic Press 1978.
See also the literature on eidetic imagery.] Categorization and identification
itself *requires* selective non-invertibility: within-category differences
must be ignored and diminished, while between-category differences must
be selected and enhanced.
Although I do my best, it is not always possible to get all the relevant
background material for these Net discussions onto the Net. Sometimes I
must reluctantly refer discussants to a fuller text elsewhere. In
principle, though, I'm prepared to re-present any particular piece of
relevant material here. This particular misunderstanding, though,
sounds like it would call for the exposition of my entire theory of
categorization, which I am reluctant to impose on the entire Net
without a wider demand. So let me just say that invertibility is my
provisional criterion for what counts as an analog transformation, and
that I have claimed that symbolic representations must be grounded in
nonsymbolic ones, which include both invertible (iconic) and
noninvertible (categorical) representations.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: Sun 14 Jun 87 16:42:34-PDT
From: Ken Laws <Laws@Stripe.SRI.Com>
Reply-to: AIList-Request@STRIPE.SRI.COM
Subject: [mind!harnad@princeton.edu (Stevan Harnad): Re: The symbol
grounding problem]
Date: 12 Jun 87 15:52:40 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
If discrete photons strike discrete photoreceptors, then discontintuity
is transforming into discontinuity. Yet the question can still be
asked: Is the transformation preserving physical properties such as
intensity and spatial relations by transforming them to physical
properties that are isomorphic to them (e.g., intensity to frequency,
and spatial adjacency to spatial adjacency) as opposed to merely
"standing for" them in some binary code?
This makes me uncomfortable. Consider a "hash transformation" that
maps a set of "intuitively meaningful" numeric symbols to a set of
seemingly random binary codes. Suppose that the transformation
can be computed by some [horrendous] information-preserving
mapping of the reals to the reals. Now, the hash function satisfies
my notion of an analog transformation (in the signal-processing sense).
When applied to my discrete input set, however, the mapping does not
seem to be analog (in the sense of preserving isomorphic relationships
between pairs -- or higher orders -- of symbolic codes). Since
information has not been lost, however, it should be possible to
define "relational functions" that are analogous to "adjacency" and
other properties in the original domain. Once this is done, surely
the binary codes must be viewed as isomorphic to the original symbols
rather than just "standing for them".
The "information" in a signal is a function of your methods for
extracting and interpreting the information. Likewise the "analog
nature" of an information-preserving transformation is a function
of your methods for decoding the analog relationships.
We should also keep in mind that information theorists have advanced
a great deal since the days of Shannon. Perhaps they have too limited
(or general!) a view of information, but they have certainly considered
your problem of decoding signal shape (as opposed to detecting modulation
patterns). I regret that I am not familiar with their results, but
I am sure that methods for decoding both discrete and continuous
information in continuous signals are well studied. Not that all
the answers are in -- vision workers like myself are well aware that
there can be [obvious] information in a signal that is impossible to
extract without a good model of the generating process.
-- Ken
------------------------------
End of AIList Digest
********************
∂16-Jun-87 1724 LAWS@Stripe.SRI.Com AIList Digest V5 #148
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Jun 87 17:24:40 PDT
Date: Mon 15 Jun 1987 23:37-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #148
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 16 Jun 1987 Volume 5 : Issue 148
Today's Topics:
Theory - The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 15 Jun 87 13:23:35 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem (Reply to Ken Laws on ailist)
Ken Laws <Laws@Stripe.SRI.Com> on ailist@Stripe.SRI.Com writes:
> Consider a "hash transformation" that maps a set of "intuitively
> meaningful" numeric symbols to a set of seemingly random binary codes.
> Suppose that the transformation can be computed by some [horrendous]
> information-preserving mapping of the reals to the reals. Now, the
> hash function satisfies my notion of an analog transformation (in the
> signal-processing sense). When applied to my discrete input set,
> however, the mapping does not seem to be analog (in the sense of
> preserving isomorphic relationships between pairs -- or higher
> orders -- of symbolic codes). Since information has not been lost,
> however, it should be possible to define "relational functions" that
> are analogous to "adjacency" and other properties in the original
> domain. Once this is done, surely the binary codes must be viewed
> as isomorphic to the original symbols rather than just "standing for
> them".
I don't think I disagree with this. Don't forget that I bit the bullet
on some surprising consequences of taking my invertibility criterion
for an analog transform seriously. As long as the requisite
information-preserving mapping or "relational function" is in the head
of the human interpreter, you do not have an invertible (hence analog)
transformation. But as soon as the inverse function is wired in
physically, producing a dedicated invertible transformation, you do
have invertibility, even if a lot of the stuff in between is as
discrete, digital and binary as it can be.
I'm not unaware of this counterintuitive property of the invertibility
criterion -- or even of the possibility that it may ultimately do it in
as an attempt to capture the essential feature of an analog transform in
general. Invertibility could fail to capture the standard A/D distinction,
but may be important in the special case of mind-modeling. Or it could
turn out not to be useful at all. (Although Ken Laws's point seems to
strengthen rather than weaken my criterion, unless I've misunderstood.)
Note, however, that what I've said about the grounding problem and the role
of nonsymbolic representations (analog and categorical) would stand
independently of my particular criterion for analog; substituting a more
standard one leaves just about all of the argument intact. Some of the prior
commentators (not Ken Laws) haven't noticed that, criticizing
invertibility as a criterion for analog and thinking that they were
criticizing the symbol grounding problem.
> The "information" in a signal is a function of your methods for
> extracting and interpreting the information. Likewise the "analog
> nature" of an information-preserving transformation is a function
> of your methods for decoding the analog relationships.
I completely agree. But to get the requisite causality I'm looking
for, the information must be interpretation-independent. Physical
invertibility seems to give you that, even if it's generated by
hardwiring the encryption/decryption (encoding/decoding) scheme underlying
the interpretation into a dedicated system.
> Perhaps [information theorists] have too limited (or general!)
> a view of information, but they have certainly considered your
> problem of decoding signal shape (as opposed to detecting modulation
> patterns)... I am sure that methods for decoding both discrete and
> continuous information in continuous signals are well studied.
I would be interested to hear from those who are familiar with such work.
It may be that some of it is relevant to cognitive and neural modeling
and even the symbol grounding problems under discussion here.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 12 Jun 87 18:14:08 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
aweinste@Diamond.BBN.COM (Anders Weinstein)
of BBN Laboratories, Inc., Cambridge, MA writes:
> [1] [The only thing] we learn from the "symbol grounding" problem [is
> that] you've got to have sense organs.
> [2] For a system that is not causally isolated from the environment,
> the symbol-grounding problem now just reduces to the old
> behavior-generating problem, for, if we could just produce the behavior,
> there would be no question of the intentionality of the symbols...
> [3] [But claiming that a] system can't produce intelligent
> performance *because* it doesn't make its symbols meaningful... has
> just got things backwards -- if I could produce the behavior, you'd
> have to admit that its symbols had all the "grounding" they needed
> for original intentionality.
> [4] For this reason, I think your animadversions on symbol
> grounding are largely irrelevant to your position -- the really
> substantial claims pertain only to "what looks like it's likely to
> work" for generating intelligent behavior.
[1] No, we don't merely learn that you need sense organs from the symbol
grounding problem; we also learn that the nature of those sense organs,
and their functional inter-relation with whatever else is going on
downstream, may not be as simple as one might expect. The relation may
be non-modular. It may not be just a matter of a simple hookup between
autonomous systems -- sensory and symbolic -- as it is in current toy models.
I agree that the symbol grounding problem does not logically entail
this further conclusion, but it, together with the data, does suggest
it, and why it might be important for generating successful performance.
[2] I completely agree that a system that could pass the Total Turing
Test using nothing but an autonomous symbolic module hooked to simple
transducers would not be open to question about its "intrinsic
intentionality" (at least not from groundedness considerations of the
kind I've been describing here). But there's nothing circular about
arguing that skepticism about the possibility of successfully passing
the Total Turing Test with such a system is dictated in part by
grounding considerations. The autonomy of the symbolic level can be
the culprit in both respects. It can be responsible for the performance
failures *and* for the lack of intrinsic intentionality.
[3] Nor is there anything "backwards" about blaming the lack of
intrinsic intentionality for performance failures. Rather, *you* may be
engaging in counterfactual conditionals here.
[4] The symbol grounding problem can hardly be irrelevant to my
substantive hypotheses about what may work, since it is not only the
motivation for them, but part of the explanation of why and how they
may work.
> since there isn't necessarily any more loss [in A/D] than there is
> in a typical A/A transformation, the "degree of invertibility"
> criterion cross-cuts the intuitive A/D distinction.... suppose we
> had a digitized image, A, which is of much higher resolution
> than another analog one, B. A is more invertible since it contains
> more detail from which to reconstruct the original signal, but B is
> more "shape-preserving" in an intuitive sense. So, which do you regard
> as "more analog"? Which does your theory think is better suited to
> subserving our categorization performance? If you say B, then
> invertibility is just not what you're after.
First, if A, the digital representation, is part of a dedicated
system, hardwired to inputs and outputs, and the input stimuli are
invertible, then, as I've said before, the whole system would be "analog"
according to my provisional criterion, perhaps even more analog than
B. If A is not part of a dedicated, physically invertible system, the
question is moot, since it's not analog at all. With equal
invertibility, it is an empirical question which is better suited to
subserve cognition in general, and probably depends on optimality and
capacity considerations. Finally, categorization performance in particular
calls for much more than invertibility, as I've indicated before. Only iconic
representations are invertible. Categorical reprsentations require
selective *noninvertibility*. But that is another discussion...
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 12 Jun 87 21:36:13 GMT
From: ihnp4!homxb!houxm!houdi!marty1@ucbvax.Berkeley.EDU
(M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <6521@diamond.BBN.COM>, aweinste@Diamond.BBN.COM (Anders
Weinstein) writes:
> ....
> (A) The symbols in a purely symbolic system will always be
> ungrounded because such systems can't generate real performance;
> ...
> It seems to me that .... thesis (A) is the one that makes perfect
> sense ....
>
> ..... I think it's perfectly reasonable to suspect that the
> symbolic approach is insufficient to produce full human performance....
What exactly is this "purely" symbolic approach? What impure approach
might be necessary? "Purely symbolic" sounds like a straw man: a
system so purely abstract that it couldn't possibly relate to the real
world, and that nobody seriously trying to mimic human behavior would
even try to build anything that pure.
To begin with, any attempt to "produce full human performance" must
involve sensors, effectors, and motivations. Does "purely symbolic"
preclude any of these? If not, what is it in the definition of a
"purely symbolic" approach that makes it inadequate to pull these
factors together?
(Why do I so casually include motivations? I'm an amateur actor. Not
even a human can mimic another human without knowing about motivations.)
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 12 Jun 87 22:19:48 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem
In article <837@mind.UUCP> Stevan Harnad (harnad@mind.UUCP) writes:
> But there's nothing circular about
>arguing that skepticism about the possibility of successfully passing
>the Total Turing Test with such a system is dictated in part by
>grounding considerations. The autonomy of the symbolic level can be
>the culprit in both respects. It can be responsible for the performance
>failures *and* for the lack of intrinsic intentionality.
I'm afraid I still don't understand this. You write here as if these are
somehow two *different* things. I don't see them that way, and hence find
circularity. That is, I view intentionality as a matter of rational
behavior. For me, the behavior is primary, and the notion of "symbol
grounding" or "intrinsic intentionality" is conceptually derivative; and I
thought from your postings that you shared this frankly behavioristic
philosophy.
Baldly put, here is the only plausible theory I know of "symbol grounding":
X has intrinsic intentionality (is "grounded") iff X can pass the TTT.
If you have a better theory, I'd like to hear it, but until then I believe
that TTT-behavior is the very essence of intrinsic intentionality.
Note that since it's the behavior that has conceptual priority, it makes
sense to say that failure on the behavior front is, in a philosophical sense,
the *reason* for a failure to make intrinsic intentionality. But to say the
reverse is vacuous: failure to make intrinsic intentionality just *is the
same thing* as failure to produce full TTT performance. I don't see that
you can significantly distinguish these two failings.
So what could it come to to say that symbolic AI must inevitably choke on the
grounding problem? Since grounding == behavioral capability, all this claim
can mean is that symbolic AI won't be able to generate full TTT performance.
I think, incidentally, that you're probably right in this claim. However, I
also think that the supposed "symbol-grounding problem" *is* irrelevant. From
my point of view, it's just a fancy alternative name for the real issue, the
behavior-generating problem.
>[4] The symbol grounding problem can hardly be irrelevant to my
>substantive hypotheses about what may work, since it is not only the
>motivation for them, but part of the explanation of why and how they
>may work.
I still don't see how it explains anything. The grounding problem *reduces*
to the behavior problem, not the other way around. To say that your approach
is better grounded is only to say that it may work better (ie. generate TTT
performance); there's just no independent content to the claim of
"groundedness". Or do you have some non-behavioral definition of intrinsic
intentionality that I haven't yet heard?
Anders Weinstein
BBN Labs
------------------------------
Date: 13 Jun 87 19:59:12 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
aweinste@Diamond.BBN.COM (Anders Weinstein)
of BBN Laboratories, Inc., Cambridge, MA writes:
> X has intrinsic intentionality (is "grounded") iff X can pass the TTT.
> I thought from your postings that you shared this frankly behavioristic
> philosophy... So what could it come to to say that symbolic AI must
> inevitably choke on the grounding problem? Since grounding == behavioral
> capability, all this claim can mean is that symbolic AI won't be able
> to generate full TTT performance. I think, incidentally, that you're
> probably right in this claim. However,...To say that your approach
> is better grounded is only to say that it may work better (ie.
> generate TTT performance); there's just no independent content to the
> claim of "groundedness". Or do you have some non-behavioral definition
> of intrinsic intentionality that I haven't yet heard?
I think that this discussion has become repetitious, so I'm going to
have to cut down on the words. Our disagreement is not substantive.
I am not a behaviorist. I am a methodological epiphenomenalist.
Intentionality and consciousness are not equivalent to behavioral
capacity, but behavioral capacity is our only objective basis for
inferring that they are present. Apart from behavioral considerations,
there are also functional considerations: What kinds of internal
processes (e.g., symbolic and nonsymbolic) look as if they might work?
and why? and how? The grounding problem accordingly has functional aspects
too. What are the right kinds of causal connections to ground a
system? Yes, the test of successful grounding is the TTT, but that
still leaves you with the problem of which kinds of connections are
going to work. I've argued that top-down symbol systems hooked to
transducers won't, and that certain hybrid bottom-up systems might. All
these functional considerations concern how to ground symbols, they are
distinct from (though ultimately, of course, dependent on) behavioral
success, and they do have independent content.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 14 Jun 87 19:45:33 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem
In article <1163@houdi.UUCP> marty1@houdi.UUCP (M.BRILLIANT) writes:
>> (A) The symbols in a purely symbolic system ...
>
>What exactly is this "purely" symbolic approach? What impure approach
>might be necessary? "Purely symbolic" sounds like a straw man ...
The phrase "purely symbolic" was just my short label for the AI strategy that
Stevan Harnad has been criticizing. Yes this strategy *does* encompass the
use of sensors and effectors and (maybe) motivations. Sorry if the term was
misleading, I was only using it as pointer; consult Harnad's postings for a
fuller characterization.
------------------------------
End of AIList Digest
********************
∂16-Jun-87 2047 LAWS@Stripe.SRI.Com AIList Digest V5 #149
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Jun 87 20:46:47 PDT
Date: Mon 15 Jun 1987 23:42-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #149
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 16 Jun 1987 Volume 5 : Issue 149
Today's Topics:
Theory - The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 14 Jun 87 15:13:34 GMT
From: ihnp4!homxb!houxm!houdi!marty1@ucbvax.Berkeley.EDU
(M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <843@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
>
> Intentionality and consciousness are not equivalent to behavioral
> capacity, but behavioral capacity is our only objective basis for
> inferring that they are present. Apart from behavioral considerations,
> there are also functional considerations: What kinds of internal
> processes (e.g., symbolic and nonsymbolic) look as if they might work?
> and why? and how? The grounding problem accordingly has functional aspects
> too. What are the right kinds of causal connections to ground a
> system? Yes, the test of successful grounding is the TTT, but that
> still leaves you with the problem of which kinds of connections are
> going to work. I've argued that top-down symbol systems hooked to
> transducers won't, and that certain hybrid bottom-up systems might. All
> these functional considerations concern how to ground symbols, they are
> distinct from (though ultimately, of course, dependent on) behavioral
> success, and they do have independent content.
Harnad's terminology has proved unreliable: analog doesn't mean
analog, invertible doesn't mean invertible, and so on. Maybe
top-down doesn't mean top-down either.
Suppose we create a visual transducer feeding into an image
processing module that could delineate edges, detect motion,
abstract shape, etc. This processor is to be built with a
hard-wired capability to detect "objects" without necessarily
finding symbols for them.
Next let's create a symbol bank, consisting of a large storage
area that can be partitioned into spaces for strings of
alphanumeric characters, with associated pointers, frames,
anything else you think will work to support a sophisiticated
knowledge base. The finite area means that memory will be
limited, but human memory can't really be infinite, either.
Next let's connect the two: any time the image processor finds
an object, the machine makes up a symbol for it. When it finds
another object, it makes up another symbol and links that symbol
to the symbols for any other objects that are related to it in
ways that it knows about (some of which might be hard-wired
primitives): proximity in time or space, similar shape, etc. It
also has to make up symbols for the relations it relies on to
link objects. I'm over my head here, but I don't think I'm
asking for anything we think is impossible. Basically, I'm
looking for an expert system that learns.
Now we decide whether we want to play a game, which is to make
the machine seem human, or whether we want the machine to
exhibit human behavior on the same basis as humans, that is, to
survive. For the game, the essential step is to make the
machine communicate with us both visually and verbally, so it
can translate the character strings it made up into English, so
we can understand it and it can understand us. For the survival
motivation, the machine needs a full set of receptors and
effectors, and an environment in which it can either survive or
perish, and if we built it right it will learn English for its
own reasons. It could also endanger our survival.
Now, Harnad, Weinstein, anyone: do you think this could work,
or do you think it could not work?
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 14 Jun 87 14:15:55 GMT
From: ihnp4!homxb!houxm!houdi!marty1@ucbvax.Berkeley.EDU
(M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <835@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> marty1@houdi.UUCP (M.BRILLIANT) of AT&T Bell Laboratories, Holmdel writes:
>
> > Human visual processing is neither analog nor invertible.
>
> Nor understood nearly well enough to draw the former two conclusions,
> it seems to me. If you are taking the discreteness of neurons, the
> all-or-none nature of the action potential, and the transformation of
> stimulus intensity to firing frequency as your basis for concluding
> that visual processing is "digital," the basis is weak, and the
> analogy with electronic transduction strained.
No, I'm taking more than that as the basis. I don't have any
names handy, and I'm not a professional in neurobiology, but
I've seen many articles in Science and Scientific American
(including a classic paper titled something like "What the
frog's eye tells the frog's brain") that describe the flow of
visual information through the layers of the retina, and through
the layers of the visual cortex, with motion detection, edge
detection, orientation detection, etc., all going on in specific
neurons. Maybe a neurobiologist can give a good account of what
all that means, so we can guess whether computer image
processing could emulate it.
> > what is the intrinsic meaning of "intrinsically meaningful"?
> > The Turing test is an objectively verifiable criterion. How can
> > we objectively verify intrinsic meaningfulness?
>
> We cannot objectively verify intrinsic meaningfulness. The Turing test
> is the only available criterion. Yet we can make inferences...
I think that substantiates Weinstein's position: we're back to
the behavior-generating problem.
> ....: We
> know the difference between looking up a meaning in an English/English
> dictionary versus a Chinese/Chinese dictionary (if we are nonspeakers
> of Chinese): The former symbols are meaningful and the latter are
> not.
Not relevant. Intrinsically, words in both languages are
equally meaningful.
> > Using "analog" to mean "invertible" invites misunderstanding,
> > which invites irrelevant criticism.
>
> ..... I have acknowledged all
> along that the physically invertible/noninvertible distinction may
> turn out to be independent of the A/D distinction, although the
> overlap looks significant. And I'm doing my best to sort out the
> misunderstandings and irrelevant criticism...
Then please stop using the terms analog and digital.
>
> > Human (in general, vertebrate) visual processing is a dedicated
> > hardwired digital system. It employs data reduction to abstract such
> > features as motion, edges, and orientation of edges. It then forms a
> > map in which position is crudely analog to the visual plane, but
> > quantized. This map is sufficiently similar to maps used in image
> > processing machines so that I can almost imagine how symbols could be
> > generated from it.
>
> I am surprised that you state this with such confidence. In
> particular, do you really think that vertebrate vision is well enough
> understood functionally to draw such conclusions? ...
Yes. See above.
> ... And are you sure
> that the current hardware and signal-analytic concepts from electrical
> engineering are adequate to apply to what we do know of visual
> neurobiology, rather than being prima facie metaphors?
Not the hardware concepts. But I think some principles of
information theory are independent of the medium.
> > By the time it gets to perception, it is not invertible, except with
> > respect to what is perceived. Noninvertibility is demonstrated in
> > experiments in the identification of suspects. Witnesses can report
> > what they perceive, but they don't always perceive enough to invert
> > the perceived image and identify the object that gave rise to the
> > perception....
> > .... If I am right, human intelligence itself relies on neither
> > analog nor invertible symbol grounding, and therefore artificial
> > intelligence does not require it.
>
> I cannot follow your argument at all. Inability to categorize and identify
> is indeed evidence of a form of noninvertibility. But my theory never laid
> claim to complete invertibility throughout.....
First "analog" doesn't mean analog, and now "invertibility"
doesn't mean complete invertibility. These arguments are
getting too slippery for me.
> .... Categorization and identification
> itself *requires* selective non-invertibility: within-category differences
> must be ignored and diminished, while between-category differences must
> be selected and enhanced.
Well, that's the point I've been making. If non-invertibility
is essential to the way we process information, you can't say
non-invertibility would prevent a machine from emulating us.
Anybody can do hand-waving. To be convincing, abstract
reasoning must be rigidly self-consistent. Harnad's is not.
I haven't made any assertions as to what is possible. All
I'm saying is that Harnad has come nowhere near proving his
assertions, or even making clear what his assertions are.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 15 Jun 87 01:43:55 GMT
From: berleant@sally.utexas.edu (Dan Berleant)
Subject: Re: The symbol grounding problem
It is interesting that some (presumably significant) visual processing
occurs by graded potentials without action potentials. Receptor cells
(rods & cones), 'horizontal cells' which process the graded output of
the receptors, and 'bipolar cells' which do further processing, use no
action potentials to do it. This seems to indicate the significance of
analog processing to vision.
There may also be significant invertibility at these early stages of
visual processing in the retina: One photon can cause several hundred
sodium channels in a rod cell to close. Such sensitivity suggests a need
for precise representation of visual stimuli which suggests the
representation might be invertible.
Furthermore, the retina cannot be viewed as a module, only loosely
coupled to the brain. The optic nerve, which does the coupling, has a
high bandwidth and thus carries much information simultaneously along
many fibers. In fact, the optic nerve carries a topographic
representation of the retina. To the degree that a topographic
representation is an iconic representation, the brain thus receives an
iconic representation of the visual field.
Furthermore, even central processing of visual information is
characterized by topographic representations. This suggests that iconic
representations are important to the later stages of perceptual
processing. Indeed, all of the sensory systems seem to rely on
topographic representations (particularly touch and hearing as well as
vision).
An interesting example in hearing is direction perception. Direction
seems to be, as I understand it, found by processing the difference in
time from when a sound reaches one ear to when it reaches the other, in
large part. The resulting direction is presumably an invertible
representation of that time difference.
Dan Berleant
UUCP: {gatech,ucbvax,ihnp4,seismo,kpno,ctvax}!ut-sally!berleant
ARPA: ai.berleant@r20.utexas.edu
------------------------------
Date: 14 Jun 87 15:03:51 GMT
From: harwood@cvl.umd.edu (David Harwood)
Subject: Re: The symbol grounding problem
In article <843@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
(... replying to Anders Weinstein ...who wonders "Where's the beef?" in
Steve Harnad's conceptual and terminological salad ...; uh - let me be first
to prophylactically remind us - lest there is any confusion and forfending
that he should perforce of intellectual scruple must need refer to his modest
accomplishments - Steve Harnad is editor of Behavioral and Brain Sciences,
and I am not, of course. We - all of us - enjoy reading such high-class
stuff...;-)
Anyway, Steve Harnad replies to A.W., re "Total Turing Tests",
behavior, and the (great AI) "symbol grounding problem":
>I think that this discussion has become repetitious, so I'm going to
>have to cut down on the words.
Praise the Lord - some insight - by itself, worthy of Pass of
the "Total Turing Test."
>... Our disagreement is not substantive.
>I am not a behaviorist. I am a methodological epiphenomenalist.
I'm not a behaviorist, you're not a behaviorist, he's not a
behaviorist too ... We are all methodological solipsists hereabouts
on this planet, having already, incorrigibly, failed the "Total Turing
Test" for genuine intergalactic First Class rational beings, but so what?
(Please, Steve - this is a NOT a test - I repeat - this is NOT a test of
your philosophical intelligence. It is an ACTUAL ALERT of your common
sense, not to mention, sense of humor. Please do not solicit BBS review of
this thesis...
>... Apart from behavioral considerations,
>there are also functional considerations: What kinds of internal
>processes (e.g., symbolic and nonsymbolic) look as if they might work?
>and why? and how? The grounding problem accordingly has functional aspects
>too. What are the right kinds of causal connections to ground a
>system? Yes, the test of successful grounding is the TTT, but that
>still leaves you with the problem of which kinds of connections are
>going to work. I've argued that top-down symbol systems hooked to
>transducers won't, and that certain hybrid bottom-up systems might. All
>these functional considerations concern how to ground symbols, they are
>distinct from (though ultimately, of course, dependent on) behavioral
>success, and they do have independent content.
>--
>
>Stevan Harnad (609) - 921 7771
>{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
>harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
You know what is the real problem with your postings - it's
what I would call "the symbol grounding problem". You want to say obvious
things in the worst possible way, otherwise say abstract things in the
worst possible way.. And ignore what others say. Also, for purposes of
controversial public discussion, ignore scientific 'facts' (eg about
neurologic perceptual equivalence), and standard usage of scientific
terminology and interpretation of theories. (Not that these are sacrosanct.)
It seems to me that your particular "symbol grounding problem"
is indeed the the sine qua non of the Total Turing Test for "real"
philosophers of human cognition. As I said, we are all methodological
solipsists hereabouts. However, if you want AI funding from me - I want to
see what real computing system, using your own architecture and object code
of at least 1 megabytes, has been designed by you. Then we will see how
your "symbols" are actually grounded, using the standard, naive but effective
denotational semantics for the "symbols" of your intention, qua "methodological
epiphenomensist."
David Harwood
------------------------------
Date: 15 Jun 87 03:32:07 GMT
From: berleant@sally.utexas.edu (Dan Berleant)
Subject: Re: The symbol grounding problem
In article <835@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>We cannot objectively verify intrinsic meaningfulness. The Turing test
>is the only available criterion.
Yes, the Turing test is by definition subjective, and also subject to
variable results from hour to hour even from the same judge.
But I think I disagree that intrinsic meaningfulness cannot be
objectively verified. What about the model theory of logic?
Dan Berleant
UUCP: {gatech,ucbvax,ihnp4,seismo,kpno,ctvax}!ut-sally!berleant
ARPA: ai.berleant@r20.utexas.edu
------------------------------
End of AIList Digest
********************
∂16-Jun-87 2332 LAWS@Stripe.SRI.Com AIList Digest V5 #150
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Jun 87 23:32:32 PDT
Date: Mon 15 Jun 1987 23:45-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #150
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 16 Jun 1987 Volume 5 : Issue 150
Today's Topics:
Binding - comp.theory Newsgroup,
Theory - Information Flow & The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 11 Jun 87 21:17:29 GMT
From: ramesh@cvl.umd.edu (Ramesh Sitaraman)
Subject: New newsgroup: comp.theory
To those of you haven't already noticed ....
A new news group "comp.theory" has commenced. This group presumably
deals with all aspects of the Theoretcial Computer Science
including Complexity theory, Algorithm analysis, Logic and
theory of computation, denotational semantics, computational
geometry etc etc etc.
Make merry,
Ramesh
------------------------------
Date: Wed 10 Jun 87 12:31:39-EDT
From: Albert Boulanger <ABOULANGER@G.BBN.COM>
Subject: Re: Information flow discussions
Anthony Pelletier writes:
P.S. I think alot about information flow problems and would enjoy
discussions on that...if anyone wants to chat.
For a real "juicy" discussion of information flow in non-linear
systems see:
"Strange Attractors, Chaotic Behavior, and Information Flow"
Robert Shaw, Z. Naturforsch, 36a, 80-112 1981
This discusses the information flow characteristics of non-linear
systems in order to gain insight on how non-linear systems self-organize.
(This self-organization aspect of non-linear dynamical systems
is an aspect of neural networks. See for example Kohonen's work
on self-organizing feature maps in "Self-Organization and
Associative Memory" Springer-Verlag 1984. This feature map stuff
is a type of unsupervised learning.)
Albert Boulanger
BBN Labs
------------------------------
Date: 15 Jun 87 02:37:00 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
In two consecutive postings marty1@houdi.UUCP (M.BRILLIANT)
of AT&T Bell Laboratories, Holmdel wrote:
> the flow of visual information through the layers of the retina,
> and through the layers of the visual cortex, with motion detection,
> edge detection, orientation detection, etc., all going on in specific
> neurons... Maybe a neurobiologist can give a good account of what
> all that means, so we can guess whether computer image
> processing could emulate it.
As I indicated the last time, neurobiologists don't *know* what all
those findings mean. It is not known how features are detected and by
what. The idea that single cells are doing the detecting is just a
theory fragment, and one that has currently fallen on hard times. Rivals
include distributed networks (of which the cell is just a component),
or spatial frequency detectors, or coding at some entirely different
level, such as continuous postsynaptic potentials, local circuits,
architectonic columns or neurochemistry. Some even think that the
multiple analog retinas at various levels of the visual system (12 on
each side, at last count) may have something to do with feature
extraction. One cannot just take current neurophysiological data and
replace the nonexistent theory by preconceptions from machine vision
-- especially not by way of justifying the machine-theoretic concepts.
>> >[SH:] my theory never laid claim to complete invertibility
>> >throughout.
>
> First "analog" doesn't mean analog, and now "invertibility"
> doesn't mean complete invertibility. These arguments are
> getting too slippery for me... If non-invertibility is essential
> to the way we process information, you can't say non-invertibility
> would prevent a machine from emulating us.
I have no idea what proposition you think you were debating here. I
had pointed out a problem with the top-down symbolic approach to
mind-modeling -- the symbol grounding problem -- which suggested that
symbolic representations would have to be grounded in nonsymbolic
representations. I had also sketched a model for categorization that
attempted to ground symbolic representations in two nonsymbolic kinds
of representations -- iconic (analog) representations and categorical
(feature-filtered) representations. I also proposed a criterion for
analog transformations -- invertibility. I never said that categorical
representations were invertible or that iconic representations were
the only nonsymbolic representations you needed to ground symbols. Indeed,
most of the CP book under discussion concerns categorical representations.
> All I'm saying is that Harnad has come nowhere near proving his
> assertions, or even making clear what his assertions are...
> Harnad's terminology has proved unreliable: analog doesn't mean
> analog, invertible doesn't mean invertible, and so on. Maybe
> top-down doesn't mean top-down either...
> Anybody can do hand-waving. To be convincing, abstract
> reasoning must be rigidly self-consistent. Harnad's is not.
> I haven't made any assertions as to what is possible.
Invertibility is my candidate criterion for an analog transform. Invertible
means invertible, top-down means top-down. Where further clarification is
needed, all one need do is ask.
Now here is M. B. Brilliant's "Recipe for a symbol-grounder" (not to be
confused with an assertion as to what is possible):
> Suppose we create a visual transducer... with hard-wired
> capability to detect "objects"... Next let's create a symbol bank
> Next let's connect the two... I'm over my head here, but I don't
> think I'm asking for anything we think is impossible. Basically,
> I'm looking for an expert system that learns... the essential step
> is to make the machine communicate with us both visually and verbally,
> so it can translate the character strings it made up into English, so
> we can understand it and it can understand us. For the survival
> motivation, the machine needs a full set of receptors and
> effectors, and an environment in which it can either survive or
> perish, and if we built it right it will learn English for its
> own reasons. Now, Harnad, Weinstein, anyone: do you think this
> could work, or do you think it could not work?
Sounds like a conjecture about a system that would pass the TTT.
Unfortunately, the rest seems far too vague and hypothetical to respond to.
If you want me to pay attention to further postings of yours, stay
temperate and respectful as I endeavor to do. Dismissive rhetoric will not
convince anyone, and will not elicit substantive discussion.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 15 Jun 87 05:21:36 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
berleant@ut-sally.UUCP (Dan Berleant) of U. Texas CS Dept., Austin, Texas
has posted this welcome reminder:
> the retina cannot be viewed as a module, only loosely
> coupled to the brain. The optic nerve, which does the coupling, has a
> high bandwidth and thus carries much information simultaneously along
> many fibers. In fact, the optic nerve carries a topographic
> representation of the retina. To the degree that a topographic
> representation is an iconic representation, the brain thus receives an
> iconic representation of the visual field.
> Furthermore, even central processing of visual information is
> characterized by topographic representations. This suggests that iconic
> representations are important to the later stages of perceptual
> processing. Indeed, all of the sensory systems seem to rely on
> topographic representations (particularly touch and hearing as well as
> vision).
As I mentioned in my last posting, at last count there were 12 pairs
of successively higher analog retinas in the visual system. No one yet
knows what function they perform, but they certainly suggest that it
is premature to dismiss the importance of analog representations in at
least one well optimized system...
> Yes, the Turing test is by definition subjective, and also subject to
> variable results from hour to hour even from the same judge.
> But I think I disagree that intrinsic meaningfulness cannot be
> objectively verified. What about the model theory of logic?
In earlier postings I distinguished between two components of the
Turing Test. One is the formal, objective one: Getting a system to generate
all of our behavioral capacities. The second is the informal,
intuitive (and hence subjective) one: Can a person tell such a device
apart from a person? This version must be open-ended, and is no better
or worse than -- in fact, I argue that is identical to -- the
real-life turing-testing we do of one another in contending with the
"other minds" problem.
The subjective verification of intrinsic meaning, however, is not done
by means of the informal turing test. It is done from the first-person
point of view. Each of us knows that his symbols (his linguistic ones,
at any rate) are grounded, and refer to objects, rather than being
menaningless syntactic objects manipulated on the basis of their shapes.
I am not a model theorist, so the following reply may be inadequate, but it
seems to me that the semantic model for an uninterpreted formal system
in formal model-theoretic semantics is always yet another formal
object, only its symbols are of a different type from the symbols of the
system that is being interpreted. That seems true of *formal* models.
Of course, there are informal models, in which the intended interpretation
of a formal system corresponds to conceptual or even physical objects. We
can say that the intended interpretation of the primitive symbol tokens
and the axioms of formal number theory are "numbers," by which we mean
either our intuitive concept of numbers or whatever invariant physical
property quantities of objects share. But such informal interpretations
are not what formal model theory trades in. As far as I can tell,
formal models are not intrinsically grounded, but depend on our
concepts and our linking them to real objects. And of course the
intrinsic grounding of our concepts and our references to objects is
what we are attempting to capture in confronting the symbol grounding
problem.
I hope model theorists will correct me if I'm wrong. But even if the
model-theoretic interpretation of some formal symbol systems can truly
be regarded as the "objects" to which it refers, it is not clear that
this can be generalized to natural language or to the "language of
thought," which must, after all, have Total-Turing-Test scope, rather
than the scope of the circumscribed artificial languages of logic and
mathematics. Is there any indication that all that can be formalized
model-theoretically?
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
End of AIList Digest
********************
∂18-Jun-87 0256 LAWS@Stripe.SRI.Com AIList Digest V5 #152
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 18 Jun 87 02:55:57 PDT
Date: Thu 18 Jun 1987 00:07-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #152
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 18 Jun 1987 Volume 5 : Issue 152
Today's Topics:
Queries - Nano-Engineering & AI Research in Network Management &
K-B Expert Systems for Manufacturing &
Information Management in Software Engineering & Unix Lisps in C,
AI Tools - ID3 vs C4 & Smalltalk-80 & ML,
Comments - AI Models in Biology
----------------------------------------------------------------------
Date: 16 Jun 1987 09:10-EDT
From: DAVSMITH@A.ISI.EDU
Subject: Nano-Engineering
The recent discussion of the $6M man reminded me of an oddity
which someone out there in Net-land might be able to clarify. Early
one morning on NPR (National Public Radio) I was surprised to hear
a feature from someone at the MIT AI Lab entitled Nano-Engineering.
I hasten to add that it was several months ago, but _not_ on April 1st,
although the following synopsis may lead you to believe such. The
general thesis was a genetic engineering exercise whereby a little genetic
robot would be created to "assemble" genes. The really intersting
part was the observation that since these things would naturally be
very small, their first assignment would be to assemble clones of themselves.
Recall that I said this was early in the morning, but I did check
with another NPR fan in our office who also heard the same feature.
Can anyone confirm (a) that this was perpetrated and (b) that
it came from MIT?
David Smith - DAVSMITH@A.ISI.EDU
------------------------------
Date: 16 Jun 87 21:33:30 GMT
From: dvorak@im4u.utexas.edu (Daniel L. Dvorak)
Subject: AI research in network management
This is a brainstorming exercise, folks --- all ideas are welcome.
I'm trying to select a PhD research topic in artificial intelligence
that is applicable to network management (of data or voice networks)
or, more liberally, the management of distributed computing environments.
Network management, roughly, is concerned with the operation, administration
and maintenance of communication networks, whether it be the campus network
here at The University of Texas at Austin or the nationwide telephone network.
The term encompasses issues such as congestion control, fault diagnosis,
capacity planning, security, availability, etc.
My questions for you are:
-- What are the important unsolved (or poorly solved) problems here
that might yield to AI? Please be specific.
-- What AI research issues should be tested in this domain?
-- Are there any papers that you would recommend to me?
--
-----
Dan Dvorak UUCP: {harvard,ihnp4,seismo}!ut-sally!im4u!dvorak
(512) 472-6671 ARPA: dvorak@im4u.utexas.edu
------------------------------
Date: 16 Jun 87 13:31:30 GMT
From: pt!andrew.cmu.edu!dg1v+@cs.rochester.edu (David Greene)
Subject: K-B Expert Sys for Manufacturing
Could anyone tell me where I might obtain the following proceedings:
Knowledge-Based Expert Systems for Manufacturing. Proceedings
of the Winter Annual Meeting of the American Society of
Mechanical Engineers (ASME), S. C-Y. Lu and R. Komanduri
(eds.), Anaheim (CA), December 7-12, 1986.
Please leave mail for:
dg1v@andrew.cmu.edu David Greene
GSIA
Carnegie Mellon Univ.
Pittsburgh, PA 15213
------------------------------
Date: 16 Jun 87 17:41:17 GMT
From: pollux.usc.edu!garg@OBERON.USC.EDU (Pankaj Garg)
Subject: Information management in software engg.
Hi,
I am doing a survey on information management in the development, use,
and maintenance of large scale software systems. I know about several
efforts, but would like to be comprehensive, hence this posting.
If you know of any efforts in databases, information science, or
knowledge representation, in this direction, please let me know.
I can post summaries to those interested.
regards...
...pankaj
US MAIL: Computer Science Department
Sal 200
University of Southern California
Los Angeles, CA 90089-0782
E-Mail: garg@pollux.usc.edu or garg@cse.usc.edu
Phone: (213)743-7995, 735-2843
------------------------------
Date: Wed, 17 Jun 87 13:21:22 BST
From: A system manager <root%maths.qmc.ac.uk@Cs.Ucl.AC.UK>
Subject: Unix Lisps in C?
I am seeking information about Unix lisps written entirely in
(hopefully not VAX-specific) C. Pointers to such beasts would be
gratefully received. Anybody who wants a copy of information thus
obtained should let me know - I will be happy to forward it.
Malcolm MacCallum (mm@maths.qmc.ac.uk)
Relays: UKACRL (Bitnet), ucl-cs (arpa)
------------------------------
Date: 14 Jun 87 21:05:39 GMT
From: mcvax!ukc!stc!praxis!gerry@seismo.css.gov (Gerry Wolff)
Subject: Re: ID3 vs C4
In article <114@upba.UUCP> damon@upba.UUCP (Damon Scaggs) writes:
>I understand that Ross Quinlan, author of the ID3 classification algorithm
>has developed a better version with the designation C4. I am looking for
>any papers or references about this new algorithm as well as any comments
>about what it does better.
I can't speak for C4 but I will claim, immodestly, that an inductive
learning program I wrote (and reported) a few years ago is, in certain
respects, more sophisticated than ID3. In particular, it integrates
the learning of segmental structure with the learning of disjunctive
(class) structure. The program (called SNPR) also has the ability
to generalize structures and to correct overgeneralizations
*without correction by a 'teacher' or the provision of 'negative'
samples*.
The reference is: Wolff J G (1982). Language acquisition, data
compression and generalization. Language & Communication 2, 57-89.
*-----------------------------------------------------------------------*
| Dr Gerry Wolff | Phone: (44) 225 335855 |
| Praxis Systems plc | UUCP: gerry@praxis.co.uk |
| 20 Manvers Street | Telex: 445848 PRAXIS G |
| Bath | Facsimile Groups 2 & 3 |
| BA1 1PX | (44) 225 65205 |
| UK | |
*-----------------------------------------------------------------------*
------------------------------
Date: Mon, 15 Jun 87 16:04:21 PDT
From: "William J. Fulco" <lcc.bill@CS.UCLA.EDU>
Subject: Smalltakl-80 for Sun 3 (and others)
I saw a really nice system, (I mean REALLY nice - with good color support)
from Xerox PARC marketing spinoff at the 1986 AAAI show. It was running
on a Sun 3/260 and it really sizzles.....
I believe they are going to show this and some other versions (a la Mac)
at the U of WA/Seattle AAAI '87 show July. I'll be there, Mac II in hand,
drooling !!!!!
I have been waiting (2 months) paitently for information from:
ParcPlace Systems
3330 Coyote Hill Road
Palo Alto, CA 94304
(415) 859-1000
(bill)
P.S. I would be interested in any implementations you find out about.
------------------------------
Date: 16 Jun 87 01:14:50 GMT
From: mcvax!diku!carllp@seismo.css.gov (Carl-Lykke Pedersen)
Subject: Re: ML programming, anybody?
Yes, we are some people at diku (datalogisk institut ved
K|benhavns Universitet -> Coputer Science Department at
the University of Copenhagen) who are trying to work with SML.
We are supposed to make a user-manual for the implementation -
but ....
Right now I'm working with a self-interpreter to SML, and it
seems to be ok.
We are using a version from Edingburgh. It's rather old, but we
have some problems in getting a newer version.
Regards
Carl-Lykke
------------------------------
Date: 11 Jun 87 16:10:31 GMT
From: ptsfa!hoptoad!academ!uhnix1!uhnix2!bchso@ames.arpa (Dan
Davison)
Subject: Re: Taking AI models and applying them to biology...
In article <1331@sigi.Colorado.EDU> pell@boulder.Colorado.EDU (Anthony
Pelletier) writes:
>P.S. I think alot about information flow problems and would enjoy
>discussions on that...if anyone wants to chat.
Do you know about the "Matrix of Biological Knowledge Workshop" in Santa Fe, NM
July 13-August 14 this year? One of the subjects is "information flow from
DNA to cells" lead by Dickerson of UCLA, Hershman, also UCLA, and Smith from
MBCRR at Harvard.
For information, contact Ms. Ginger Richardson at The Santa Fe Institute,
P.O. Box 9020, Santa Fe, N.M. 87504-9020; phone 505-984-8800.
dr. dan davison/ Dept of Biochemical and Biophysical Sciences/ U. of Houston
bitnet: bchs6\@uhupvm1.bitnet | 4800 Calhoun/ Houston, Tx 77004
arpanet: davison\@sumex-aim.stanford.edu|uucp:...rice!academ!uhnix1!uhnix2!bchso
------------------------------
Date: 15 Jun 87 13:06:19 GMT
From: edwards@unix.macc.wisc.edu (mark edwards)
Subject: Re: Taking AI models and applying them to biology...
In article <7416@boring.cwi.nl> lambert@cwi.nl (Lambert Meertens) writes:
:| > This description of the human memory system, though cloaked in
vaguer terms,
:| > corresponds more or less one-to-one with the traditional computer
:| > architecture we all know and love. To wit:
:|
:| [description deleted]
:|
:| > At least this far, this theory appears to owe a lot to computer science.
:| > Granted, there is lots of empirical evidence in favour, but we all know
:| > how a little evidence can go far too far towards developing an analogy.
:The main similarity appears to be that several levels of memory can be
:discerned, but the suggested analogy in function is a bit far-fetched.
:
:It is perhaps worth pointing out that much of the current models in
:cognitive psychology can already be found in the pioneering work of Otto
:Selz (Muenchen, 1881 - Auschwitz, 1943), antedating the computer era.
What? You cite facts from the pre-computer age? Shame shame. Don't
you know that life began with the creation of the computer, as well
as all the other sciences! With out the computer all other life would
cease to exist!
Its a sad fact that the above holds true for many computer scientist
especially those in AI. Many still believe the sacred words AI were
really coined in the late fifties, and that LISP and Liebnitz have
no connection. When infact my prof. has given references from a latin
book dating back to the 13th century, with the latin words for AI.
The state of the art of computer science is in bad shape when the
computer wheel must be re-invented every year because th CS people refuse
to read any book that seemingly has nothing to do with CS or computers.
Thanks for the reference. I may be the only one who benefits from
it, because those CS'ers practicing the art would certainly declare it
blasphemous and maybe just short of heresy.
I may be stoned for this.....
mark
--
edwards@unix.macc.wisc.edu
{allegra, ihnp4, seismo}!uwvax!uwmacc!edwards
UW-Madison, 1210 West Dayton St., Madison WI 53706
------------------------------
Date: 15 Jun 87 03:47:26 GMT
From: ihnp4!alberta!mnetor!utzoo!utgpu!utcsri!utegc!utai!tjhorton@ucbv
ax.Berkeley.EDU
Subject: Re: Taking AI models and applying them to biology...
>lambert@cwi.nl (Lambert Meertens) writes:
>It is perhaps worth pointing out that much of the current models in
>cognitive psychology can already be found in the pioneering work of Otto
>Selz (Muenchen, 1881 - Auschwitz, 1943), antedating the computer era.
1943 was at least 7 years after Turing published his paper
(fifty years ago, last November) and 5 years after Shannon
published his thesis about information theory. Although I
don't know Selz, his life definitely spanned into the dawn
of the "computer era". It's interesting - do these models
of his pre-date these "computeresque" notions?
Timothy J Horton <tjhorton@utai.toronto.edu>
------------------------------
Date: 16 Jun 87 18:04:06 GMT
From: pyramid!prls!philabs!aecom!diaz@decwrl.dec.com (Dizzy Dan)
Subject: Re: Taking AI models and applying them to biology...
In article <395@uhnix2.UUCP>, bchso@uhnix2.UUCP (Dan Davison) writes:
> Do you know about the "Matrix of Biological Knowledge Workshop" in Santa Fe,
> NM
> July 13-August 14 this year? One of the subjects is "information flow from
> DNA to cells" lead by Dickerson of UCLA, Hershman, also UCLA, and Smith from
> MBCRR at Harvard.
>
> For information, contact Ms. Ginger Richardson at The Santa Fe Institute,
> P.O. Box 9020, Santa Fe, N.M. 87504-9020; phone 505-984-8800.
>
Sorry gang, but applications for the Matrix Workshop were due in April.
If you are interested, the Santa Fe Institute may be able to put you in
touch with some of the faculty running the workshops.
--
5'gtacggagc dn/dx = Dan Diaz (philabs!aecom!diaz)
Department of Molecular Biology & Snake Oil Dynamics
Albert Slimestein College of Medicine ctataacagcta 3'
------------------------------
End of AIList Digest
********************
∂18-Jun-87 1623 LAWS@Stripe.SRI.Com AIList Digest V5 #151
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 18 Jun 87 16:23:28 PDT
Date: Wed 17 Jun 1987 23:58-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #151
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 18 Jun 1987 Volume 5 : Issue 151
Today's Topics:
Seminars - Mechanization of Programmer's Knowledge (MCC) &
Partial Order Programming (MCC) &
AI at Vanderbilt & Comparative Induction (NASA Ames) &
Default Reasoning and Stereotypes in User Modelling (UPenn),
Conference - Last Call for AAAI-87 Volunteers &
CADE-9: Automated Deduction &
Office Knowledge &
Second Eurographics Workshop on Intelligent CAD Systems
----------------------------------------------------------------------
Date: Mon 15 Jun 87 14:12:25-CDT
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - Mechanization of Programmer's Knowledge (MCC)
Please join the AI group for the following speaker:
ON THE MECHANIZATION OF PROGRAMMER'S KNOWLEDGE
Henryk Jan Komorowski
Harvard University
June 17 - 10:00
MCC Balcones Auditorium
What do programmers with experience in writing programs know and how
can this knowledge be mechanized so it can be used by a computer? This
talk presents an informal overview of the foundations of mechanical
support for software design. The goal of the mechanization is to
provide an intelligent assistant for the programmer that can uncover
flaws in the design rather than automatically generate programs. What
programmer knows is divided into knowledge of data structures,
recursive schemata, assimilation rules, and the process of designing a
program which is similar to extension of a theory. A prototype system
now implemented provides salient advice, despite its limited
knowledge-base.
June 17 - 10:00
MCC Balcones Auditorium
------------------------------
Date: Mon 15 Jun 87 14:50:06-CDT
From: Ellie Huck <AI.ELLIE@MCC.COM>
Subject: Seminar - Partial Order Programming (MCC)
Please join the AI Group for the following speaker:
PARTIAL ORDER PROGRAMMING
D. Stott Parker
UCLA Computer Science Department
June 19 - 10:00
MCC Balcones Auditorium
We introduce a declarative programming paradigm that describes
computation with partial orders. A partial order program corresponds
to a collection of constraints
u >= C(u)
where >= is a partial order on a domain of `objects' and `values',
u is an object, and C(u) is an object or a value.
Semantics of such a program consist of assignments of values to the
objects u that satisfy the inequalities. When C is a monotone and
continuous function, fixpoint semantics of the program may be
obtained easily and naturally.
The partial order programming paradigm has interesting properties:
(1) It generalizes various computational paradigms (logic,
functional, object-oriented, and others) in a clean way.
(2) It takes thorough advantage of known results for continuous
functionals on partial orders, providing a clear semantics
for the paradigm.
(3) It presents a framework that may be more generally acceptable
for dealing with `cognitive' computation problems, including
natural language processing and knowledge representation.
(4) It coincides with recent work on relaxation solution of a
variety of problems including consistent labelling, path
problems, and linear algebraic systems.
June 19 - 10:00
MCC Balcones Auditorium
------------------------------
Date: Tue, 16 Jun 87 15:15:50 PDT
From: JARED%PLU@ames-io.ARPA
Subject: Seminars - AI at Vanderbilt & Comparative Induction (NASA
Ames)
NASA, Ames Research Center
Intelligent Systems Forum
TWO SPEAKERS:
Dr. Arthur J. Brodersen
Center for Intelligent Systems
Vanderbilt University
Expert Systems Research at Vanderbilt University
Abstract:
The current research activities at the Center for Intelligent Systems
at Vanderbilt University will be discussed. The current research
activities include knowledge-based systems for test technologies,
intelligent tutorial systems for simulation tools, training systems,
knowledge retrieval systems, and diagnositic and repair systems.
David Hartzband
Digital Equipment Corporation
Chief Scientist, Artificial Intelligence Technology Group
and
Visiting Scholar, Stanford University
Comparative Induction Methods for Problem Solving and
(Some) Learning}
Date: Thursday, June 18, 1987
Time: 2:00 to 4:30 PM
Location: Bldg. 245, Space Science Auditorium
Inquires: David Jared, (415) 694-6525, jared@ames-pluto.arpa
VISITORS ARE WELCOME: Register and obtain vehicle pass at Ames Visitor
Reception Building (N-253) or the Security Station near Gate 18. Do not
use the Navy Main Gate.
Non-citizens (except Permanent Residents) must have prior approval from the
Director's Office one week in advance. Submit requests to the point of
contact indicated above. Non-citizens must register at the Visitor
Reception Building. Permanent Residents are required to show Alien
Registration Card at the time of registration.
------------------------------
Date: 15 Jun 87 12:15:25 EDT
From: Marcella.Zaragoza@isl1.ri.cmu.edu
Subject: Seminar - Default Reasoning and Stereotypes in User
Modelling (UPenn)
SPECIAL SEMINAR
SPEAKER: Timothy Finin
Computer and Information Science
University of Pennsylvania, Philadelphia, PA
WHEN: Thursday, June 18, 1987, 10:00 am
WHERE: Doherty Hall 3313
TOPIC: DEFAULT REASONING AND STEREOTYPES IN USER MODELLING
This talk discusses the application of various kinds of default reasoning in
systems which must maintain a model of its users. In particular, we
describe a general architecture of a domain independent system for building
and maintaining long term models of individual users. The user modelling
system is intended to provide a well defined set of services for an
application system which is interacting with various users and has a need to
build and maintain models of them. As the application system interacts with
a user, it can acquire knowledge of him and pass that knowledge on to the
user model maintenance system for incorporation. We describe a prototype
general user modelling system (hereafter called GUMS1 which we have
implemented in Prolog. This system satisfies some of the desirable
characteristics we discuss.
------------------------------
Date: 16 Jun 87 20:18:07 GMT
From: feifer@locus.ucla.edu
Subject: Conference - Last call for AAAI-87 volunteers
Due to some last minute cancellations we have a few
openings for volunteers for AAAI-87.
Please see the original posting below for more information.
If interested, please respond immediately.
ANNOUNCEMENT:
Student Volunteers Needed for
Artificial Intelligence Conference
AAAI-87
AAAI-87 (American Association on Artificial Intelligence) will
be held July 13-17, 1987 in beautiful Seattle, Washington.
Student volunteers are needed to help with local arrangements
and staffing of the conference. To be eligible for a Volunteer
position, an individual must be an undergraduate or graduate
student in any field at any college or university.
This is an excellent opportunity for students to participate in
the conference. Volunteers receive FREE registration at AAAI-87,
conference proceedings, "STAFF" T-shirt, and are invited to the
volunteer party. More importantly, by participating as a volunteer,
you become more involved and meet students and researchers with
similar interests.
Volunteer responsibilities are varied, including conference
preparation, registration, staffing of sessions and tutorials
and organizational tasks. Each volunteer will be assigned
twelve (12) hours.
If you are interested in participating in AAAI-87 as a Student
Volunteer, apply by sending the following information:
Name
Electronic Mail Address
USMail Address
Telephone Number(s)
Dates Available
Student Affiliation
Advisor's Name
to:
feifer@locus.ucla.edu
or
Richard Feifer
UCLA
Center for the Study of Evaluation
145 Moore Hall
Los Angeles, California 90024
Thanks, and I hope you join us this year!
Richard Feifer
Student Volunteer Coordinator
AAAI-87 Staff
- Richard
------------------------------
Date: Mon, 15 Jun 87 20:07:49 cdt
From: stevens@anl-mcs.ARPA (Rick L. Stevens)
Subject: Conference - CADE-9: Automated Deduction
Preliminary Announcement and Call for Papers
9th International Conference on Automated
Deduction
May 23-26, 1988
CADE-9 will be held at Argonne National Laboratory (near
Chicago) in celebration of the 25th anniversary of the
discovery of the resolution principle at Argonne in the sum-
mer of 1963. Papers are invited in the following or related
fields:
Theorem Proving Logic Programming
Unification Deductive Databases
Term Rewriting ATP for Non-Standard Logics
Program Verification Inference Systems
The Program Committee includes:
Peter Andrews Hans-Jorgen Ohlbach
W.W. Bledsoe Ross Overbeek
Alan Bundy William Pase
Seif Haridi Jorg Siekmann
Larry Henschen Jim Williams
Jean-Louis Laissez Mark Stickel
Dallas Lankford
Ewing Lusk
Michael MacRobbie
Papers should be sent to arrive before November 23rd, 1987
to
Ewing Lusk and Ross Overbeek, chairmen
CADE-9
Mathematics and Computer Science Division
Argonne National Laboratory
Argonne, IL 60439
------------------------------
Date: Mon, 15 Jun 87 17:17:53 edt
From: rba@flash.bellcore.com (Robert B. Allen)
Subject: Conference - Office Knowledge
Office Knowledge: Representation, Management and Utilization
University of Toronto
IFIP WG8.4 Workshop Program
For information contact: Fred Lochovsky, fred@csri.toronto.edu
Monday, August 17th, 1987
8:00-9:00 Registration
9:00-9:15 Workshop Opening Remarks
9:15-10:45 Session: Invited Talk
Objects and Things. D. Tsichritzis, Universite de Geneve,
Switzerland
11:15-12:45 Session: Supporting Organizational Activities
Ubik: A System for Conceptual and Organizational Development.
P. de Jong, MIT, U.S.A.
KNOOM - KNowledge Oriented Office Model Representation of
Knowledge in the Office. M. Hofmann, Universitaet Wien,
Austria
OTM: A Language for Representing Concurrent Office Tasks.
J. Hogg, University of Toronto, Canada
2:00-3:30 Session: Invited Talk
Representing Office Work with Goals and Constraints.
W.B. Croft, University of Massachusetts, U.S.A.
4:00-5:30 Session: Representing, Querying and Generating
Office Objects
Time Management in the Office-net System. R. Maiocchi,
R. Zicari, Politecnico di Milano, Italy, M. Fugini,
Universita di Brescia, Italy
Towards a Graphic Query Interface for Complex Objects.
G. Lausen, Universitaet Mannheim, West Germany, A. Oberweis,
Technische Hochschule Darmstadt, West Germany
Knowledge Representation and Utilization in Automatic Office
Form Generation. K. Watabe, K. Tsuruoka, NEC Corporation,
Japan
5:30-6:30 Reception
6:30-7:30 Demonstration
Meta-Data for Automating the Management of Office Information.
R.E.A. Mason, A. Benjamin, J.R. Tessier, Online People Inc.,
Canada
_________________________________________________________________
Tuesday, August 18th, 1987
9:00-10:30 Session: Invited Talk
Organizational Semantics. C. Hewitt, MIT, U.S.A.
11:00-12:30 Session: Problem Solving
An Office Environment to Support Problem Solving.
P.W.G. Bots, H.G. Sol, Delft University of Technology,
Netherlands
Generic Knowledge in Office Activities. A.A. Araya,
M.J. Stefik, Xerox PARC, U.S.A.
EXPERTNET: An Approach to Resource Sharing on a Network of
Workstations. A. Allam, Northern Telecom Canada Ltd.,
Canada, G.M. White, University of Ottawa, Canada
2:00-3:30 Session: Text and Pictures
Semantics and Conceptual Modelling of Documents. F. Barbic,
S. Daneluzzi, F. Garzotto, S. Mainetti, P. Paolini,
Politecnico di Milano, Italy
Knowledge-Based Text Processing in Office Environments: The
Text Condensation System TOPIC. U. Hahn, Universitaet
Passau, West Germany, U. Reimer, Universitaet Konstanz, West
Germany
Knowledge Base for Storage and Retrieval of Pictures.
B. Beetz, SEL Research Center, West Germany
4:00-5:30 Session: Poster Session
Artificial Intelligence and Organizational Design: Prospects
of Integrating Two Perspectives. U. Frank, Universitaet
Mannheim, West Germany
Intermediate Knowledge Representation for Extended Office
Systems. E.S. Cordingley, University of Surrey, England
Intelligent Interfaces for Office Information Systems.
B.C. Desai, Concordia University, Canada, C. Frasson,
J. Vaucher, Universite de Montreal, Canada
Managing Office Knowledge through Conceptual Structures.
G. Berg-Cross, Advanced Decision Systems, U.S.A.
Picture Management on Optical Disks: A Practical Approach on
Micro-computers. S. Miranda, N. Le Thanh, A.C. Salgado,
E. Borelli-Vittori, Universite de Nice, France
Managing Replicas in Distributed Telephone/Address
Directories. H.M. Gladney, IBM Almaden Research Center,
U.S.A.
7:30 Banquet
_________________________________________________________________
Wednesday, August 19th, 1987
9:00-10:30 Session: Invited Talk
NICK: Intelligent Computer Supported Cooperative Work.
C. Ellis, MCC, U.S.A.
11:00-12:30 Session: Office Communication
Solving the Connection Problem. M.S. Mazer, University of
Toronto, Canada
Viewing Communication as a Problem Solving Activity: An
Enrichment Towards Supporting Cooperative Office Work.
C.C. Woo, F.H. Lochovsky, University of Toronto, Canada
CHAOS: A Knowledge-Based System for Conversing Inside Offices.
F. De Cindio, C. Simone, R. Vassallo, A. Zanaboni,
Universita di Milano, Italy
2:00-3:30 IFIP WG8.4 Business Meeting
------------------------------
Date: Mon, 15 Jun 87 17:29:16 +0200
From: mcvax!cwi.nl!tomi@seismo.CSS.GOV (Tetsuo Tomiyama)
Reply-to: mcvax!cwi.nl!tomi@seismo.CSS.GOV
Subject: Conference - Second Eurographics Workshop on Intelligent CAD
Systems
Call For Papers
SECOND EUROGRAPHICS WORKSHOP ON INTELLIGENT CAD SYSTEMS
-Implementational Issues-
APRIL 12-15, 1988, THE NETHERLANDS
Organized by
CENTRE FOR MATHEMATICS AND COMPUTER SCIENCE (CWI), AMSTERDAM
Sponsored by
EUROGRAPHICS
AIM AND SCOPE
This is the second workshop of a series of three
Eurographics workshops on Intelligent CAD Systems which have
the following main topics;
- 1st, 1987: Theoretical and methodological aspects.
- 2nd, 1988: Implementational issues.
- 3rd, 1989: Practical experiences and evaluation.
Since applying knowledge engineering to CAD systems seems
very promising to solve the problems of conventional CAD
systems, it has drawn attention from not only CAD
researchers but also AI researchers. The first workshop
which was held on April 21-24, 1987, in the Netherlands,
aimed at discussing the results and problems in this highly
interesting field. We have realized that ad hoc approaches
will eventually result in increased complexity of CAD
applications and that we need a robust theoretical basis for
development.
This second workshop in 1988 is planned to discuss
implementational issues and to clarify problems associated
with developing intelligent CAD systems based on those
theoretical and methodological considerations. The scope of
the workshop includes, but is not limited to;
1) Role of theories to implement intelligent CAD
systems.
2) Implementations of theories for intelligent CAD
systems.
3) Architecture of intelligent CAD systems.
4) Techniques and tools to implement intelligent CAD
systems.
5) Acquisition and maintenance of design knowledge.
6) Innovative and large-scale implementations of
intelligent CAD systems.
7) Problems and future tasks in implementations of
intelligent CAD systems.
We are especially interested in reports telling how
theoretical work influenced implementations.
SCHEDULE FOR THE SECOND WORKSHOP
November 1, 1987: Deadline for extended abstracts and
position papers.
December 1987: Notification of acceptance for presentation.
February 1988: Acceptance of participation.
April 12-15, 1988: Workshop (Full papers are submitted just
before the workshop).
May 1988: Deadline for final manuscripts for publication.
SERIES SCHEDULE
Approximately 15 reviewed papers will be presented in this
second workshop. Participants will be limited to about 50
based on invitation. Intended authors and participants are
invited to submit extended abstracts or position papers.
The results of this series of three workshops will be
published by Springer-Verlag as Eurographics Seminar Books.
The report on the first workshop held in April 1987,
"Intelligent CAD Systems 1: Theoretical and Methodological
Aspects," will be published in August 1987.
This series of workshop is being organized under cooperation
with IFIP Working Group 5.2 Workshops on Intelligent CAD
Systems but with different scopes.
ORGANIZATION
Co-Chairmen
P.J.W. ten Hagen (CWI, NL)
T. Tomiyama (The University of Tokyo, J)
Technical Secretary
P.J. Veerkamp (CWI, NL)
Workshop Secretary
E. Both (CWI, NL)
Program Committee
A.M. Agogino (University of California, Berkeley, USA)
V. Akman (CWI, NL)
F. Arbab (University of Southern California, USA)
P. Bernus (Hungarian Academy of Sciences, H)
A. Bijl (University of Edinburgh, UK)
J. Encarnacao (TH Darmstadt, D)
S.J. Fenves (Carnegie Mellon University, USA)
D. Gossard (MIT, USA)
F. Kimura (The University of Tokyo, J)
T. Kjellberg (Royal Institute of Technology, S)
G.A. Kramer (Schlumberger Palo Alto Research, USA)
M. Mac an Airchinnigh (University of Dublin, IRL)
K. MacCallum (University of Strathclyde, UK)
S. Murthy (IBM Thomas J. Watson Research, USA)
F.J. Schramel (Philips, NL)
D. Sriram (MIT, USA)
W. Strasser (Universitaet Tuebingen, D)
T. Takala (Technical University of Helsinki, SF)
F. Tolman (TNO, NL)
INFORMATION
Please submit 5 copies of an extended abstract or a position
paper up to 1,000 words (figures and references do not
count) on A4 sheets before November 1, 1987, to: (Submission
by electric mail is accepted)
Ms. Elisabeth Both
Centre for Mathematics and Computer Science
Kruislaan 413, 1098 SJ Amsterdam, The Netherlands
Telephone: (overseas) +31-20-592-4171
(from the Netherlands) 020-592-4171
Telex: 12571 mactr nl
Electric Mail: pauljan@cwi.nl (Internet, Bitnet),
...!mcvax!pauljan (Usenet)
The extended abstract or position paper should contain the
following information:
- Name, Address (Postal, Phone, Telex, E-mail), Keywords,
References.
- Statements on how you define "design" and "intelligent
CAD systems."
------------------------------
End of AIList Digest
********************
∂20-Jun-87 0032 LAWS@Stripe.SRI.Com AIList Digest V5 #153
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 20 Jun 87 00:32:32 PDT
Date: Fri 19 Jun 1987 22:02-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #153
To: AIList@STRIPE.SRI.COM
AIList Digest Saturday, 20 Jun 1987 Volume 5 : Issue 153
Today's Topics:
Queries - Computer Composition of Music &
AI in Criminal Investigation &
Expert Systems in Process Control,
AI Tools - Unix LISPs in C,
Speculation - Nanotechnology,
Psychology - Why Did The $6,000,000 Man Run So Slowly?
----------------------------------------------------------------------
Date: 17 Jun 87 19:50:07 GMT
From: pwa-b!mmintl!johnt@gr.utah.edu (John Tangney)
Subject: Computer composition of music
Composing music -- procedurally:
Until 1981 I had been doing some research on computer composition
of music. I have now taken up where I left off. Even back then
I was not up to date with the latest advances. A lot must have
happened in this field since then.
I want to contact people who know something about composing by
computer. Some of the researchers I read about (like Max
Mathews, Lejaren Hiller, Iannis Xenakis, Stephen Smoliar to name
a few off the top of my head) must still be out there. Also,
people like myself, who do this in their spare time, must have
ideas, suggestions, sources of information. What about journals,
books, papers on the subject?
If anyone in net.land knows anything about computer composition
of music, or knows anyone who does, then I beg you to let me
know. E-mail is most sensible. Who knows? Maybe we could end
up with our own news.group! A phone call or Snailmail reply
would be most welcome too.
John Tangney ...inhp4!philabs!pwa-b!mmintl!johnt
52 Oakland Ave, East Hartford, CT 06108. Phone: (203) 522-2116
------------------------------
Date: 19 Jun 87 08:21 PDT
From: gaska.pasa@Xerox.COM
Subject: Use of AI in Criminal Investigation
Does any one have any pointers to papers, books, persons, etc. that deal
with the use of AI in criminal investigation and forensic science? Any
and all leads will be greatly appreciated.
Len Gaska
GASKA@PASA.XEROX.COM
------------------------------
Date: 18 Jun 1987 11:58:37 EST
From: Herve.Lambert@PS3.CS.CMU.EDU
Subject: Expert Systems in Process Control
I have to find some literature about actually operational expert systems in
process control. All I know is the example of PICON used at a Texaco's
refinery. Any informations, pointers very much aprreciated...
If I get interesting enough info, and if some people express the desire to
have the result of my query posted, I will do so...
Thanks in advance
- Herve
Net-address: herve@ps3.cs.cmu.edu
[How about this blurb from Business Week, "The 'Renaissance Man' of
Expert Systems?", Emily T. Smith, May 11, 1978, p. 141:
The trouble with using so-called expert system computer programs
in the factory is that very few manufacturing operations involve
only one realm of expertise. It's tough enough getting two experts
in the same field to agree, let alone a gaggle of experts from
different disciplines. So Major Stephen R. LeClair, head of
research in artificial intelligence for manufacturing at the
Materials Laboratory at Wright-Patterson Air Force Base, decided
it was time to devise a new type of expert system -- one that
could embrace multiple "domains" of expertise, automatically
resolve any conflicts, and "learn" from the process.
In its first real-world test, LeClair's multiexpert knowledge
system (MKS) recently turned in a stunning performance. It
discovered, on its own, that the accepted guidelines for curing
complex plastics composites are all wet. The aerospace industry
has been taking 12 hours to bake a 256-layer, graphite-reinforced
lamination used for airframe parts. By synthesizing the knowledge
from various fields, MKS came up with a complicated scheme for
curing the composite in less than three hours. No one believed
it could work, but it does. LeClair asserts that MKS may similarly
confound convential wisdom in other process-control applications.
The same page has another short report about a system that measures
rough gemstones (other than diamonds), plans the optimal cuts, and
cuts the stones. It reduces wasted stone by 10%, cost by 70%,
and makes marginal stones useable. -- KIL]
------------------------------
Date: Fri, 19 Jun 87 12:11:16 EDT
From: dml@nadc.arpa (D. Loewenstern)
Subject: Unix LISPs in C
In response to your request for Unix LISPs written entirely in C, I
believe I can recommend Kyoto Common Lisp. It has no real editor (it
shells out to vi!!) but it implements nearly the entirety of Common
LISP. The compiler translates to C, then invokes the C compiler. I
know of VAX, ECLIPSE, and Sun versions. Write to:
IBUKI
399 Main Street
Los Altos, CA 94022
David Loewenstern
Naval Air Development Center
code 7013
Warminster, PA 18974-5000
<dml@nadc.arpa>
------------------------------
Date: Thu 18 Jun 87 17:21:23-CDT
From: Jonathan Slocum <AI.Slocum@MCC.COM>
Subject: nanomachinery
The book "Engines of Creation," by one K. Eric Drexler, describes this
technology and discusses the societal ramifications of its introduction.
Whether one believes in the possibility of such things or not (Drexler
is a persuasive advocate), it makes for good reading in my opinion. He
was (is?), I believe, associated with MIT in some way (don't have the
book with me, so can't refer to the jacket) -- perhaps a student??
-Jonathan Slocum
------------------------------
Date: 18 Jun 87 07:35:44 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Nano-Engineering
Date: 16 Jun 1987 09:10-EDT
From: DAVSMITH@A.ISI.EDU
The recent discussion of the $6M man reminded me of an oddity
which someone out there in Net-land might be able to clarify. Early
one morning on NPR (National Public Radio) I was surprised to hear
a feature from someone at the MIT AI Lab entitled Nano-Engineering.
* * *
Can anyone confirm (a) that this was perpetrated and (b) that
it came from MIT?
Its proponents call it Nanotechnology. The most well known spokesman
seems to be Eric Drexler, who has written a book about it called
"Engines of Creation." I think it's from MIT Press. Below I have
included an announcement of a two day symposium that was held during
IAP (Independent Activities Period, known as "January" to the world
outside MIT). As you can see from the header of the
message, there is a mailing list called nanotechnology@oz.ai.mit.edu,
or, from outside MIT a better bet would be to try
nanotechnology@ai.ai.mit.edu.
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
Date: Fri, 16 Jan 87 02:35 EST
From: Christopher Fry <cfry@OZ.AI.MIT.EDU>
Subject: Nanotechnology Symposium
To: nanotechnology@OZ.AI.MIT.EDU, MACROMOLECULES-MIT@OZ.AI.MIT.EDU,
ROBOTICS-SEMINARS@OZ.AI.MIT.EDU, *BBOARD@OZ.AI.MIT.EDU
Exploring Nanotechnology
An IAP 87 Symposium
All technology rests ultimately on our ability to arrange atoms.
Foreseeable technological advances will enable us to build devices
to atomic specifications. This "nanotechnology" will have profound
consequences, forcing a reevaluation of our expectations regarding the next
several decades. In the symposium, we will explore paths to the
development of nanotechnology, consequences of the technology in
various disciplines, and we will critically examine the premises of
these assertions via panel discussions which will include experts
in several fields.
Tuesday, 20 January 1987, 10-250
10:00 - 11:00 am Overview: Eric Drexler (BS '77, MS '79)
will describe various paths to the
development of replicating assembler systems, capable of manufacturing
complex components to atomic specification. Some potential
applications, such as mechanical nanocomputers, and their
consequences will be discussed. We strongly recommend you attend this talk
in order to follow the subsequent discussions in context.
11:05 - 11:45 am Materials Science and Protein Engineering: Kevin Ulmer
will discuss the protein engineering techniques which could be used to
create new alloys and composites. New materials made
to atomic specifications promise order of magnitude improvements in
performance. One consequence is space transportation costs equivalent
to current airline costs.
Noon - 1:00 pm Lunch Break
1:00 - 1:40 pm Panel Discussion I.
A panel of experts will discuss the technical
feasibility of various aspects of nanotechnology, including consideration
of the time frame. A panel moderator will take questions from the
audience.
1:45 - 2:25 pm Economics: David Friedman
will discuss the consequences of
nanotechnology, such as extreme decentralization of the economy.
On-site, personal manufacturing stations could virtually eliminate
mass production. What will happen to our economy during the transition
to this technology?
2:30 - 3:10 pm Society, Technology and Policy: Arthur Kantrowitz
will share his thoughts on
how society may be affected, and what kind of future may be in store
for the human race. How can our government adapt to this new technology
and what legislation, if any, should be enacted to control its development?
3:10 - 3:25 Break.
3:25 - 4:05 pm Thought and Intelligence: Marvin Minsky
will speak on intelligent
systems which could employ Avogadro's number of parallel nanocomputers.
Achieving artificial intelligence by mimicking human brain architecture
is a rapid route to true AI with nanotechnology.
4:10 - 4:40 pm Concluding Points: Eric Drexler
will wrap up by describing life
extension possibilities using cell repair machines.
4:10 - 5:00 pm Panel Discussion II.
A panel of experts will discuss the
societal implications of nanotechnology, including steps we might take
to avoid some of the dangerous consequences of nanotechnology. A panel
moderator will take questions from the audience.
Thursday, 22 January 1987 7:30 - 10:00 pm Advanced Topics:
NE43-773
As an extension to the symposium we will hold a special session
during the regular meeting time of the MIT Nanotechnology
Study Group. We will discuss, in depth, critical issues regarding the
development of nanotechnology such as control of assemblers, guidance
of technology development, and prevention
of abuse. Eric Drexler will be with us. Recommended only for those who
attend the symposium on Tuesday, or who have attended NSG introductory lectures
in the past.
Sponsored by the MIT Nanotechnology Study Group,
the Dept. of Applied Biological Sciences,
the Artificial Intelligence Laboratory,
the Office of the Associate Provost,
the Graduate Student Council,
the Dept. of Materials Science and Engineering,
and the Dept. of Political Science.
Special thanks to the AI Lab for its generous support of this activity.
Contact cfry@@MIT-OZ
------------------------------
Date: 18 Jun 87 08:53:01 CDT (Thu)
From: ernst%home%ti-csl.csnet@RELAY.CS.NET
Subject: Nanotechnology
The "nano-engineering" that David Smith heard about on an
early-morning NPR show is, indeed, no joke. Its chief proponent is
K. Eric Drexler, who describes the theory in his 1985 book _Engines of
Creation_. He is associated with MIT, and he has a stong following
there. In particular, Marvin Minsky wrote the forward to the
above-mentioned book and spoke, along with Eric Drexler and others, at
a recent day-long symposium on nano-technology at MIT.
The idea behind nanotechnology is the creation of tiny machines which
would be built up molecule by molecule by "molecular assemblers",
which would function much like DNA or RNA in fishing for the right
component to add to a structure. Because of their small size, their
manipulators would move a million times a second, resulting in
extraordinarily quick construction. Mechanical nanocomputers (that
is, they would contain tiny gears made of a handful of atoms and such,
on the order of Hillis's mechanical tic-tac-toe player) orders of
magnitude more powerful than current machines but small enough to fit
in dust-speck sized nanomachines would carry instructions and direct
work.
Drexler envisions the construction of assemblers within a few decades
as a result of advances in bioengineering and other sciences. It is a
technology he believes will powerfully leverage off itself: after the
first assembler is built, uncountable trillions more will follow
almost immediately, and scientific breakthroughs in many fields (all
of which will be able to use nanotechnology or its products as a tool)
will be made in days rather than years.
Drexler's book is more about what changes will be made in society with
the advent of nanomachines than their technical aspects; after all, no
one is close to the advances he envisions. He discusses jet engines
built in hours, self-repairing machines, AI workstations of
unprecedented power, and world hypertext systems as well as more
sinister possibilities like the capability to build tiny airborne
surveillance devices or supergerms that could destroy life on earth in
hours.
Although much of the material is hard to believe, I recommed the book
for an interesting mix of philosophy and forward-sighted scientific
thought (or science fiction, call it what you like).
-Michael Ernst
MIT AI Lab Texas Instruments AI Lab
mernst@oz.ai.mit.edu ernst%home%ti-csl@csnet-relay.arpa
...!eddie!mernst
The opinions expressed above are not only not those of my employer,
they may well not be my own.
------------------------------
Date: Mon, 15 Jun 87 14:48 EDT
From: Nichael Cramer <nichael@JASPER.PALLADIAN.COM>
Reply-to: Nichael Cramer <NICHAEL%JASPER@LIVE-OAK.LCS.MIT.EDU>
Subject: Re: Why Did The $6,000,000 Man Run So Slowly?
>>
>> Date: Fri, 12 Jun 87 00:51:41 EDT
>> From: tim@linc.cis.upenn.edu (Tim Finin)
>> Subject: why did the $6,000,000 man run so slowly?
>>
I had always assumed that he ran slowly for the same reason that the
people on "Kung Fu" always fought so slowly; namely that it's
technically much easier to depict graphic, physical motion (and
violence) in this way. You have the first actor throwing punches that
actually connect with the second actor's jaw, except that he's moving
more slowly in real time, and so not crippling the second actor with
every blow. Once you slow this down a lot, the viewer loses all sense
of how much the time is really altered; i.e. the slow motion camera
technique masks the slowed down "acting".
In the present case, slow motion has the effect of distorting your
time sense and allowing the film makers to use other (cheaper?)
methods to suggest high-speed to the viewer, e.g. swooshing sounds or
tense music.
(With regard to these non-visual cues used to suggest high-speed: As
others have pointed out, watch the opening of "Star Trek" with the
sound turned off. The Enterprise, which would normally sweeping
across the screen at Warp N, will, with the usual swooshing sound
missing, simply creep across the screen.)
NICHAEL
------------------------------
Date: 15 Jun 87 19:36:28 GMT
From: tektronix!teklds!zeus!bobr@ucbvax.Berkeley.EDU (Robert Reed)
Subject: Re: Why did the six-million dollar man run so slowly?
Because it was cheaper to take slow motion footage to show SOMETHING was
happening than to make a believable high speed effect. Of course, they
could taken blue screen shots of Steve Austin running normally and
composited in a high speed background, but many of the shots involved his
feet. Making a believable shot under those conditions would have been a lot
more expensive.
It is interesting to note that the recent reunion of the "bionic family"
represented the new generation of bionic technology by having his son blur
(it actually looked like defocused multiple exposures) during the slow
motion "high speed" running shots.
--
Robert Reed, Tektronix CAE Systems Division, bobr@zeus.TEK
------------------------------
Date: Mon, 15 Jun 87 17:15:04 edt
From: amsler@flash.bellcore.com (Robert Amsler)
Subject: Re: AIList Digest V5 #145
Incidentally.... Re: Dr. Who's TARDIS. I've decided most of the
discussions were wrong. Few people considered the function of the
`relative dimensions stabilizer circuits' which are intended to
compensate for dimensional anomalies. It would be QUITE possible to
have the inside view of the TARDIS look either miniturized or like
a small window into a larger room. One should recall that anomalies in
the circuit can cause the TARDIS inhabitants to actually BE smaller
when they emerge. Anyway... wrong discussion. `pop'
Re: bionics. It has been my belief for some time that the mind
operates using movie techniques when examining moving image memories.
That is, we employ cuts, zooms, view angles, props, etc. in such
memory recording and dreams. It would seem reasonable that we have
borrowed this acceptable form of imaging and used it in films--why,
for instance, should a cut between two views be acceptable
cinamatography. Some cinematographic techniques violate our `dream'
view methods. For instance, when one holds the camera at a bad angle
the impact is typically to introduce the concept of the camera into
the film, i.e. one way to show something is being seen through a
camera lens in a film, is to have the camera do bad cinematographic
techniques--ones which make the artificiality of the instrument apparent
(another problem is whenever things get on the lens, such as rain or
ocean spray or dust, etc.)
Now, the speed to slow motion effect is interesting in that I don't
believe it does have a natural human moving image memory counterpart.
We never see things in slow motion ourselves, except as they have
been slowed down by the use of film etc. That indeed explains to me
why this is being discussed in AILIST. I.e. it is an artificial
learned moving-image association. The interesting thing is that is
SEEMS to be possible to introduce this into the visual recording
system for memories in the brain without causing the ``Oh, this is
being shot through a camera'' phenomena.
I suspect what is happening is that this is analogous to the focusing
of attention on the events which happened in a real moving image
memory. That is, if one attempts to reconstruct an event that
happened very quickly in real time after the fact, one will
artificially create something like slow motion.
---- Note: I am NOT saying that we really have moving images in the
brain. It is unclear we have images at ALL; however, the mapping
between what we do have and what we accept in cinematographic
portrayals is an interesting one.
------------------------------
End of AIList Digest
********************
∂20-Jun-87 1842 LAWS@Stripe.SRI.Com AIList Digest V5 #154
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 20 Jun 87 18:42:34 PDT
Date: Sat 20 Jun 1987 16:08-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #154
To: AIList@STRIPE.SRI.COM
AIList Digest Sunday, 21 Jun 1987 Volume 5 : Issue 154
Today's Topics:
Theory - Symbol Grounding and Physical Invertibility
----------------------------------------------------------------------
Date: 16 Jun 87 1559 PDT
From: John McCarthy <JMC@SAIL.STANFORD.EDU>
Subject: Symbol Grounding Problem and Disputes
[In reply to message sent Mon 15 Jun 1987 23:23-PDT.]
This dispute strikes me as unnecessarily longwinded. I imagine that the
alleged point at issue and a few of the positions taken could be
summarized for the benefit of those of us whose subjective probability
that there is a real point at issue is too low to motivate studying the
entire discussion but high enough to motivate reading a summary.
------------------------------
Date: 16 Jun 87 17:41:50 GMT
From: ihnp4!homxb!houxm!houdi!marty1@ucbvax.Berkeley.EDU
(M.BRILLIANT)
Subject: Re: The symbol grounding problem (Reply to Ken Laws on
ailist)
In article <849@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> .... Invertibility could fail to capture the standard A/D distinction,
> but may be important in the special case of mind-modeling. Or it could
> turn out not to be useful at all....
So what do you think is essential: (A) literally analog transformation,
(B) invertibility, or (C) preservation of significant relational
functions?
> ..... what I've said about the grounding problem and the role
> of nonsymbolic representations (analog and categorical) would stand
> independently of my particular criterion for analog; substituting a more
> standard one leaves just about all of the argument intact.....
Where does that argument stand now? Can we restate it in terms whose
definitions we all agree on?
> ..... to get the requisite causality I'm looking
> for, the information must be interpretation-independent. Physical
> invertibility seems to give you that......
I think invertibility is too strong. It is sufficient, but not
necessary, for human-style information-processing. Real people forget
awesome amounts of detail, we misunderstand each other (our symbol
groundings are not fully invertible), and we thereby achieve levels of
communication that often, but not always, satisify us.
Do you still say we only need transformations that are analog
(invertible) with respect to those features for which they are analog
(invertible)? That amounts to limited invertibility, and the next
essential step would be to identify the features that need
invertibility, as distinct from those that can be thrown away.
> Ken Laws <Laws@Stripe.SRI.Com> on ailist@Stripe.SRI.Com writes:
> > ... I am sure that methods for decoding both discrete and
> > continuous information in continuous signals are well studied.
>
> I would be interested to hear from those who are familiar with such work.
> It may be that some of it is relevant to cognitive and neural modeling
> and even the symbol grounding problems under discussion here.
I'm not up to date on these methods. But if you want to get responses
from experts, it might be well to be more specific. For monaural
sound, decoding can be done with Fourier methods that are in principle
continuous. For monocular vision, Fourier methods are used for image
enhancement to aid in human decoding, but I think machine decoding
depends on making the spatial dimensions discontinous and comparing the
content of adjacent cells.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: Wed 17 Jun 87 23:33:01-PDT
From: Ken Laws <Laws@Stripe.SRI.Com>
Subject: Visual Decoding
From: ihnp4!homxb!houxm!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
For monaural
sound, decoding can be done with Fourier methods that are in principle
continuous. For monocular vision, Fourier methods are used for image
enhancement to aid in human decoding, but I think machine decoding
depends on making the spatial dimensions discontinous and comparing the
content of adjacent cells.
Marty is right; one must be specific about the types of signals that are
carrying the information. Information theorists tend to work with
particular types of modulation (e.g., radar returns), but are interested
in the general principles of information transmission. Some of the
spread spectrum work is aimed at concealing evidence of modulation while
still being able to recover the encoded information.
Fourier techniques are particularly appropriate for speech processing
because sinusoidal waveforms (the basis of Fourier analysis) are the
eigenforms of acoustic channels. In other words, the sinusoidal components
of speech are transmitted relatively unharmed, although the phase relationships
between the components can be scrambled. Any process that decodes acoustic
signals must be prepared to deal with a little phase spreading. Other
1-D signals (e.g., spectrographic signatures of chemicals) may be composed
of Gaussian pulses or other basis forms. Yet others may be generated by
differential equations rather than composition or modulation of basis
functions. Decoding generally requires models of the generating process
and of the channel or sensing transformations, particularly if the latter
are invertible.
Images are typically captured in discrete arrays, although we know that
biological retinas are neither limited to one kind of detector/resolution
nor so spatially regular. Discrete arrays are convenient, and the Nyquist
theorem (combined with the limited spatial resolution of typical imaging
systems) gives us assurance that we lose nothing below a specific minimum
frequency -- we can, if we wish, reconstruct the true image intensity at
any point in the image plane, regardless of its relationship to the pixel
centers. (In practice this interpolation is exceedingly difficult and is
almost never done -- but enough pixels are sampled to make interpolation
unnecessary for the types of discrimination we need to perform.) The
discrete pixel grid is often convenient but is not fundamental to the
enterprise of image analysis.
A difficulty in image analysis is that we rarely know the shapes of the
basis functions that carry the information; that, after all, is what we
are trying to determine by parsing a scene into objects. We do have
models of the optical channels, but they are generally noninvertible.
Our models of the generating processes (e.g., real-world scenes) are
exceedingly weak. We have some approaches to decoding these signals,
but nothing approaching the power of the human visual system except in
very special tasks (such as analysis of bubble chamber photographs).
-- Ken
------------------------------
Date: 17 Jun 87 08:02:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: symbol grounding and physical invertibility
I hate to nag but...
In all the high-falutin' philosophical give-and-take (of which, I admit,
I am actually quite fond) there's been no response to a much more
*specific* objection/question I raised earlier:
What if there were a few-to-one transformation between the skin-level
sensors (remember Harnad proposes "skin-and-in" invertibility
as being necessary for grounding) and the (somewhat more internal)
iconic representation. My example was to suppose that #1:
a combination of both red and green retinal receptors and #2 a yellow
receptor BOTH generated the same iconic yellow.
Clearly this iconic representation is non-invertible back out to the
sensory surfaces, but intuitively it seems like it would be grounded
nonetheless - how about it?
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: 17 Jun 87 18:32:20 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem (Reply to Ken Laws on
ailist)
In article <849@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
> As long as the requisite
>information-preserving mapping or "relational function" is in the head
>of the human interpreter, you do not have an invertible (hence analog)
>transformation. But as soon as the inverse function is wired in
>physically, producing a dedicated invertible transformation, you do
>have invertibility, ...
This seems to relate to a distinction between "physical invertibility" and
plain old invertibility, another of your points which I haven't understood.
I don't see any difference between "physical" and "merely theoretical"
invertibility. If a particular physical transformation of a signal is
invertible in theory, then I'd imagine we could always build a device to
perform the actual inversion if we wanted to. Such a device would of course
be a physical device; hence the invertibility would seem to count as
"physical," at least in the sense of "physically possible".
Surely you don't mean that a transformation-inversion capability must
actually be present in the device for it to count as "analog" in your sense.
(Else brains, for example, wouldn't count). So what difference are you trying
to capture with this distinction?
Anders Weinstein
BBN Labs
------------------------------
Date: 17 Jun 87 20:12:22 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
marty1@houdi.UUCP (M.BRILLIANT) asks:
> what do you think is essential: (A) literally analog transformation,
> (B) invertibility, or (C) preservation of significant relational
> functions?
Essential for what? For (i) generating the pairwise same/different judgments,
simlarity judgments and matching that I've called, collectively,
"discrimination", and for which I've hypothesized that there are
iconic ("analog") representations? For that I think invertibility is
essential. (I think that in most real cases what is actually
physically invertible in my sense will also turn out to be "literally
analog" in a more standard sense. Dedicated digital equivalents that
would also have yielded invertibility will be like a Rube-Goldberg
alternative; they will have a much bigger processing cost. But for my
puroposes, the dedicated digital equivalent would in principle serve
just as well. Don't forget the *dedicated* constraint though.)
For (ii) generating the reliable sorting and labeling of objects on the
basis of their sensory projections, which I've called collectively,
"identification" or "categorization"? For that I think only distinctive
features need to be extracted from the sensory projection. The rest need
not be invertible. Iconic representations are one-to-one with the
sensory projection; categorical representations are many-to-few.
But if you're not talking about sensory discrimination or about
stimulus categorization but about, say, (iii) conscious problem-solving,
deduction, or linguistic description, then relation-preserving
symbolic representations would be optimal -- only the ones I advocate
would not be autonomous (modular). The atomic terms of which they were
composed would be the labels of categories in the above sense, and hence they
would be grounded in and constrained by the nonsymbolic representations.
They would preserve relations not just in virtue of their syntactic
form, as mediated by an interpretation; their meanings would be "fixed"
by their causal connections with the nonsymbolic representations that
ground their atoms.
But if your question concerns what I think is nesessary to pass the
Total Turing Test (TTT), I think you need all of (i) - (iii), grounded
bottom-up in the way I've described.
> Where does [the symbol grounding] argument stand now? Can we
> restate it in terms whose definitions we all agree on?
The symbols of an autonomous symbol-manipulating module are
ungrounded. Their "meanings" depend on the mediation of human
interpretation. If an attempt is made to "ground" them merely by
linking the symbolic module with input/output modules in a dedicated
system, all you will ever get is toy models: Small, nonrepresentative,
nongeneralizable pieces of intelligent performance (a valid objective for
AI, by the way, but not for cognitive modeling). This is only a
conjecture, however, based on current toy performance models and the
the kind of thing it takes to make them work. If a top-down symbolic
module linked to peripherals could successfully pass the TTT that way,
however, nothing would be left of the symbol grounding problem.
My own alternative has to do with the way symbolic models work (and
don't work). The hypothesis is that a hybrid symbolic/nonsymbolic
model along the lines sketched above will be needed in order to pass
the TTT. It will require a bottom-up, nonmodular grounding of its
symbolic representations in nonsymbolic representations: iconic
( = invertible with the sensory projection) and categorical ( = invertible
only with the invariant features of category members that are preserved
in the sensory projection and are sufficient to guide reliable
categorization).
> I think invertibility is too strong. It is sufficient, but not
> necessary, for human-style information-processing. Real people
> forget... misunderstand...
I think this is not the relevant form of evidence bearing on this
question. Sure we forget, etc., but the question concerns what it takes
to get it right when we actually do get it right. How do we discriminate,
categorize, identify and describe things as well as we do (TTT-level)
based on the sensory data we get? And I have to remind you again:
categorization involves at least as much selective *non*invertibility
as it does invertibility. Invertibility is needed where it's needed;
it's not needed everywhere, indeed it may even be a handicap (see
Luria's "Mind of a Mnemonist," which is about a person who seems to
have had such vivid, accurate and persisting eidetic imagery that he
couldn't selectively ignore or forget sensory details, and hence had
great difficulty categorizing, abstracting and generalizing; Borges
describes a similar case in "Funes the Memorious," and I discuss the
problem in "Metaphor and Mental Duality," a chapter in Simon & Sholes' (eds.)
"Language, Mind and Brain," Academic Press 1978).
> Do you still say [1] we only need transformations that are analog
> (invertible) with respect to those features for which they are analog
> (invertible)? That amounts to limited invertibility, and the next
> essential step would be [2] to identify the features that need
> invertibility, as distinct from those that can be thrown away.
Yes, I still say [1]. And yes, the category induction problem is [2].
Perhaps with the three-level division-of-labor I've described a
connectionist algorithm or some other inductive mechanism would be
able to find the invariant features that will subserve a sensory
categorization from a given sample of confusable alternatives. That's
the categorical representation.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: Thu, 18 Jun 87 10:08:27 pdt
From: Ray Allis <ray@BOEING.COM>
Subject: The Symbol Grounding Answer
I have enjoyed the ailist's tone of rarified intellectual inquiry,
but lately I have begun to think the form of the question "What is
the solution to the Symbol Grounding Problem" has unduly influenced
the content of the answer, as in "How many angels can dance on the
head of a pin?"
You are solemnly discussing angels and pinheads.
There is no "Symbol Grounding Problem"; the things are *not* grounded.
The only relationship a symbol has with anything is that the physical
effects (electrical and chemical) of its perception in the brain of a
perceiver co-exist with the physical effects of other perceptions, and
are consequently associated in that individual's brain, and therefore
mind. It happens when we direct our baby's attention at a bovine and
clearly enunciate "COW". There is no more "physical invertibility" in
that case than there is between you and your name, and there is no other
physical relationship. And, as we computer hackers are wont to say,
"That's a feature, not a bug". It means we can and do "think" about
things and relationships which may not "exist". (BTW, it's even better!
You are right now using second-level symbols. The visual patterns you
are perceiving on paper or on a display screen are symbols for sounds,
which in turn are symbols for experiences.)
Last year's discussion of the definitions of "analog" and "digital" are
relevant to the present topic. In the paragraph above, the electrical
and chemical effects in the observer's brain are an *analogy* (we
hypothesize) of external "reality". These events are *determined* (we
believe) by that reality, i.e., for each external situation there is one
and only one electro-chemical state of the observer's brain. Now, the
brain effects appear pretty abstracted, or attenuated, so "complete
invertibility" is unlikely, but if we can devise a fancy enough brain,
may be approachable. No such deterministic relationship holds between
external "reality" and symbols. As I noted above, symbols are related
to their referents by totally arbitrary association.
Thus, there is nothing subtle about the distinction between "analog"
and "digital"; they are two profoundly different things. The "digital"
side of an A/D relationship is *symbolic*. The relationship (we humans
create) between a symbol and a quantity is wholly arbitrary. The value
here is that we can use *deductive* relationships in our manipulation
of quantities, rather than, say, pouring water back and forth among a set
of containers to balance our bank account.
I am one of those convinced by such considerations that purely symbolic
means, which includes most everything we do on digital computers, are
*insufficient in principle* to duplicate human behavior. And I have some
ideas about the additional things we need to investigate. (By the way,
whose behavior are we to duplicate? Ghengis Khan? William Shakespeare?
Joe Sixpack? All of the above in one device? The Total Turing Test is
just academic obfuscation of "If it walks like a duck, and quacks like
A duck ...").
------------------------------
Date: 18 Jun 87 18:26:23 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem
In article <861@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
> The atomic terms of which they were
>composed would be the labels of categories in the above sense, and hence they
>would be grounded in and constrained by the nonsymbolic representations.
>They would preserve relations not just in virtue of their syntactic
>form, as mediated by an interpretation; their meanings would be "fixed"
>by their causal connections with the nonsymbolic representations that
>ground their atoms.
I don't know how significant this is for your theory, but I think it's worth
emphasizing that the *semantic* meaning of a symbol is still left largely
unconstrained even after you take account of it's "grounding" in perceptual
categorization. This is because what matters for intentional content is not
the objective property in the world that's being detected, but rather how the
subject *conceives* of that external property, a far more slippery notion.
This point is emphasized in a different context in the Churchland's BBS reply
to Drestke's "Knowledge and the Flow of Information." To paraphrase one of
their examples: primitive people may be able to reliably categorize certain
large-scale atmospheric electrical discharges; nevertheless, the semantic
content of their corresponding states might be "Angry gods nearby" or some
such. Indeed, by varying their factual beliefs we could invent cases where
the semantic content of these states is just about anything you please.
Semantic content is a holistic matter.
Another well-known obstacle to moving from an objective to an intentional
description is that the latter contains an essentially normative component,
in that we must make some distinction between correct and erroneous
classification. For example, we'd probably like to say that a frog has a
fly-detector which is sometimes wrong, rather than a "moving-spot-against-a-
fixed-background" detector which is infallible. Again, this distinction seems
to depend on fuzzy considerations about the purpose or functional role of the
concept in question.
Some of the things you say also suggest that you're attempting to resuscitate
a form of classical empricist sensory atomism, where the "atomic" symbols
refer to sensory categories acquired "by acquaintance" and the meaning of
complex symbols is built up from the atoms "by description". This approach
has an honorable history in philsophy; unfortunately, no one has ever been
able to make it work. In addition to the above considerations, the main
problems seem to be: first, that no principled distinction can be made
between the simple sensory concepts and the complex "theoretical" ones; and
second, that very little that is interesting can be explicitly defined in
sensory terms (try, for example, "chair").
I realize the above considerations may not be relevant to your program -- I
just can't tell to what extent you expect it to shed any light on the problem
of explaining semantic content in naturalistic terms. In any case, I think
it's important to understand why this fundamental problem remains largely
untouched by such theories.
Anders Weinstein
BBN Labs
------------------------------
End of AIList Digest
********************
∂26-Jun-87 1959 LAWS@Stripe.SRI.Com AIList Digest V5 #155
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 26 Jun 87 19:59:24 PDT
Date: Fri 26 Jun 1987 00:08-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #155
To: AIList@STRIPE.SRI.COM
AIList Digest Friday, 26 Jun 1987 Volume 5 : Issue 155
Today's Topics:
Seminars - Acquiring Knowledge from the Outside (Rutgers) &
AI Research at Edinburgh (SRI) &
Nonmonotonic Multiple Inheritance Systems (Bell Labs)
Conference - Advanced Computing Symposium &
European Conference on AI in Medicine
----------------------------------------------------------------------
Date: 18 Jun 87 11:47:53 EDT
From: KALANTARI@RED.RUTGERS.EDU
Subject: Seminar - Acquiring Knowledge from the Outside (Rutgers)
R U T G E R S U N I V E R S I T Y
Department of Computer Science
C O L L O Q U I U M
SPEAKER: Paul Rosenbloom
Stanford University
TITLE: ACQUIRING KNOWLEDGE FROM THE OUTSIDE
SOME RECENT PROGRESS ON LEARNING IN SOAR
DATE: Monday, June 29, 1987
TIME: 10:00 a.m.
PLACE: Hill Center, Room 705
In previous work on learning in Soar we have focused on how the chunking of
internal problem solving can acquire the varieties of knowledge required by a
general problem solver; for example, productions can be acquired which perform
operator retrieval, instantiation, selection, and implementation. One major
form of learning not covered by this previous work is the acquisition of
knowledge from external sources. In this talk I will describe two current
projects which are examining how the techniques utilized in the previous work
can be employed to learn from external knowledge sources. The first project is
working on the acquisition of general search control knowledge from external
advice. This work touches on issues of operationalization, learning
apprentices, analogy, and generalization. The second project is working on the
acquisition of declarative knowledge. This work demonstrates for the first
time in Soar what Dietterich termed "knowledge level learning"; that is, the
acquisition of knowledge not already in the system's deductive closure. One
implication of this demonstration is that explanation-based learning mechanisms
are not inherently limited to symbol level learning. Issues that have arisen
during this work include: how to decouple new facts from the context in which
they were learned, how to be able to distinguish what has been learned from
what hasn't, and how to index declarative information for appropriate
retrieval.
------------------------------
Date: Wed, 24 Jun 87 11:32:42 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - AI Research at Edinburgh (SRI)
AI RESEARCH AT EDINBURGH - PAST, PRESENT, AND FUTURE
Roberto Desimone
University of Edinburgh
2:00 PM, FRIDAY, June 26
SRI International, Building E, Room EK242
This talk will comprise a review of AI research and other AI
activities that have and are being pursued at Edinburgh. I will start
with a short history of the early days of AI in Edinburgh in the 1960s
and 1970s, the transition period in the mid to late 1970s and the
revival in 1980s. Then, I will stress the basic research currently
being conducted within the Dept. of AI at the University of Edinburgh.
Some of the activities conducted within the AI Applications Institute
also in Edinburgh will also be discussed. Finally, some thoughts on
the future of AI research at Edinburgh.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
NOTE: Different time and place
------------------------------
Date: Thu 25 Jun 1987 14:10:08
From: dlm@allegra.csnet
Subject: Seminar - Nonmonotonic Multiple Inheritance Systems (Bell
Labs)
Date: Thursday, July 2
Time: 2:00 PM
Place: AT&T Bell Laboratories MH 3D-473
David S. Touretzky
Computer Science Department
Carnegie Mellon University
A Clash of Intuitions: The Current State of
Nonmonotonic Multiple Inheritance Systems
Early attempts at combining multiple inheritance with nonmonotonic reasoning
were based on straightforward extensions to tree-structured inheritance
systems, and were theoretically unsound. In The Mathematics of Inheritance
Systems, or TMOIS, I described two basic problems that these systems cannot
handle. One involves reasoning with true but redundant assertions; the other
involves ambiguity.
TMOIS provided the definition and analysis of a theoretically sound multiple
inheritance system, accompanied by inference algorithms. Other definitions for
inheritance have since been proposed by Sandewall and by Horty, Thomason, and
Touretzky that are equally sound and intuitive, but do not always agree with
the system defined in TMOIS. At the heart of the controversy is a clash of
intuitions about certain fundamental issues such as skepticism versus
credulity, the direction in which inheritance paths are extended, and classical
versus intuitive notions of consistency. In this talk I will catalog the
issues, map out a design space, and describe interesting properties that result
from certain choices of definitions. Just as there are alternative logics,
there may be no single ``best'' approach to nonmonotonic multiple inheritance.
This is joint work with Richmond Thomason of the University of Pittsburgh and
John Horty of CMU.
Sponsor: Ron Brachman
------------------------------
Date: Thu, 18 Jun 87 13:14:49 pdt
From: Douglas Schuler <douglas@BOEING.COM>
Subject: Conference - Advanced Computing Symposium
DIRECTIONS AND IMPLICATIONS OF ADVANCED COMPUTING
A One Day Symposium - July 12, 1987
University of Washington, Seattle, Washington
PROGRAM
On-Site Registration (8:00 - 9:00)
PLENARY SESSION (9:00 - 10:30)
Robert Kahn and Terry Winograd with Gary Chapman
The featured speakers will discuss the role of funding on computer science
research. How and why are projects selected for funding? What are the
roles of the Department of Defense, civilian agencies and private sources?
Does it matter where research money comes from?
Robert Kahn is the founder of the non-profit Corporation for National
Research Initiatives, in Washington, D.C. Until 1985, Kahn was director of
the Information Processing Techniques Office at the Defense Advanced
Research Projects Agency (DARPA).
Terry Winograd is an associate professor of computer science at Stanford
University. He is author of "Understanding Natural Language", "Language as
a Cognitive Process" and (with Fernando Flores) "Understanding Computers
and Cognition". Winograd is the national president of Computer
Professionals for Social Responsibility (CPSR).
The discussion will be moderated by Gary Chapman, Executive Director of
CPSR. He is co-editor of the book, "Computers in Battle" to be published
this fall. Chapman is a former member U.S. Special Forces.
PARALLEL SESSIONS
FUNDING (11:00 - 12:00)
David Bushnell - The Promise and Reality of ARPANET: A Brief History
Joel Yudken and Barbara Simons - Project on Funding in Computer Science:
A Preliminary Report
AI PROSPECTS I (11:00 - 12:00)
Juergen Koenemann Artificial Intelligence and the Future of Work
Reinhard Keil-Slawik An Ecological Approach to Responsible
Systems Development
LUNCH (12:00 - 1:30)
MILITARY/RELIABILITY (1:30 - 3:00)
Richard Hamlet - Testing for Trustworthiness
David Bella - Fault-tolerant Ballistic Missile Defense
Erik Nilsson - The Costs of Computing Star Wars
EXPERT SYSTEMS (1:30 - 3:00)
Matthew Lewis and Seth Chaikin - Will There Be Teachers in the Classroom
of the Future?
Rolf Engelbrecht - Expert Systems in Medicine - A Technology Assessment
Carole Hafner and Donald Berman - The Potential of AI to Help Solve the
Crisis in Our Legal System
BREAK (3:00 - 3:30)
RESEARCH PRIORITIES (3:30 - 4:30)
Douglas Schuler - A Civilian Computing Initiative: Three Modest Proposals
Jack Beusmans and Karen Wieckert - Artificial Intelligence and the Military
AI PROSPECTS II (3:30 - 4:30)
Susan Landau - The Responsible Use of 'Expert' Systems
K. Eric Drexler - Technologies of Danger and Wisdom
VIDEO
Daressa Computers in Context
CPSR Reliability and Risk
videotape on DBNET (a computer mail network for the deaf-blind)
Registration fees
Regular $50 ____
CPSR Member $30 ____
Student/Low Income $20 ____
Proceedings only (cannot attend symposium) $15 ____
Proceedings will be distributed to symposium registrants on day of
symposium. Lunch is included.
DIAC '87
CPSR/Seattle
P.O. Box 85481
Seattle, WA 98105
Sponsored by Computer Professionals for Social Responsibility
------------------------------
Date: 23 Jun 1987 12:32:28 EST
From: Herve.Lambert@PS3.CS.CMU.EDU
Subject: Conference - European Conference on AI in Medicine
EUROPEAN CONFERENCE on
ARTIFICIAL INTELLIGENCE
in MEDICINE
__________
Marseilles (France), Aug 31st - Sept 3rd
Organized by: AIME, European Society for Artificial Intelligence in Medicine
In cooperation with: IIRIAM, International Institute of Robotics and
Artificial Intelligence of Marseilles.
IRCF, Imperial Cancer Research Fund Laboratories, UK
GSF-MEDIS, Gesellschaft fur Strahlen und
umweltforschung mbH Munchen
Laboratoire d'Informatique Medicale de la Faculte de
Medecine de Marseille.
PROGRAM
_______
WORKSHOP and TUTORIALS
----------------------
Monday, August 31st:
Tutorial 1:
9.00 - 13.00 Acquisition of Knowledge from Medical databases
Gio C.M. Wiederhold, M. Walker, R.L. Blum, Stanford University (USA)
Tutorial 2:
14.00 - 18.00 Methods and Techniques used in Expert Systems
Jan L. Talmon, Henny P.A. Boshuizen, University of Limburg (NL)
Tutorial 3:
14.00 - 18.00 Knowledge representation
Steen Andreassen, University of Aalborg (DK), Mike Wellman, MIT (USA)
Workshop:
9.00 - 13.00 From Mycin to Oncocin
Larry Fagan, Stanford University (USA)
CONFERENCE
----------
Tuesday, September 1st, 1987
9.00 - 9.30 Opening Session
9.30 - 10.30 Invited Keynote speaker: J.H. Van Bemmel, Free University of
Amsterdam
10.30 - 11.00 Break
Session 1: Methodology
11.00 - 11.30 "INTERMED": a medical language interface.
Mery C., Normier B., Orgonowski A. (F)
11.30 - 12.00 Inference engineering through prototyping in Prolog
Van Thilo J., Mulders A. (B)
12.00 - 12.30 The evaluation of clinical decision support systems: a
discussion of the methodology used in the ACORN project.
Wyatt J. (UK)
12.30 - 13.00 Matching patients: an approach to decision support in Liver
transplantation.
Tusch G., Bernauer J., Reichertz P.L. (FRG)
13.00 - 14.00 Lunch
Session 2: Clinical Applications (1)
14.30 - 15.00 An expert system for diagnosis and therapy planning in
patients with peripheral vascular disease.
Talmon J.L., Schijven R.A.J., Kitslaar P.J.E.H.M.,
Penders R. (NL)
15.00 - 15.30 An expert system for the classification of Dizziness and
Vertigo.
Schmid R., Zanocco P., Buizza A., Magenes G., Manfrin M.,
Mira E. (I)
15.30 - 16.00 The SENEX system, a microcomputer-based expert system built by
oncologists for breast cancer management.
Renaud-Salis J.L., Bonichon F., Durand M., Avril A.,
Lagarde C. (F).
16.00 - 16.30 Break
Session 3: Qualitative Reasoning
16.30 - 17.00 The use of QSIM for Qualitative simulation of physiological
systems.
Nicolosi E., Leaning M. (UK)
17.00 - 17.30 Qualitative description of electrophysiologic measurements:
toward automatic data interpretation.
Irler W.J., Antolini R., Kirchner M., Stringa L. (I)
17.30 - 18.00 A qualitative spatial representation for cardiac
Electrophysiology.
Gotts N. (UK)
18.45 Cocktail at the city hall of Marseilles.
Wednesday September 2nd 1987{
Session 4: Knowledge acquisition and representation
9.00 - 9.30 Knowledge acquisition in expert system assisted diagnosis:
a machine learning approach
Funk M., Appel R.D., Roch Ch., Hochstrasse D., Pellegrini Ch.,
Muller A.F., (CH)
9.30 - 10.00 Knowledge representation for cooperative medical systems
Rector A.L. (UK)
10.00 - 10.30 A representation of time for medical expert systems
Hamlet I., Hunter J. (UK)
10.30 - 11.00 Break
Session 5: Management of uncertainty
11.00 - 11.30 TOULMED an inference engine which deals with imprecise and
uncertain aspects of medical knowledge.
Buisson J.C., Farreny H., Prade H., Turnin M.C., Tauber J.P.,
Bayard F. (F)
11.30 - 12.00 Coherent handling of uncertainty via localized computation in
an expert system for therapeutic decision.
Berzuini C., Barosi G., Polino G. (I)
12.00 - 12.30 MUNIN, on the case for probabilities in medical expert systems
a pratical exercise.
Jensen F.V., Andersen S.K., Kjaerulff U., Andreassen S. (DK)
12.30 - 13.00 Rule based expert systems in gynecology: statistical versus
heuristic approach
Riss P.A., Koelbl H., Reinthaller A., Deutinger J. (Austria)
Afternoon: Social Program
Thursday September 3rd
Session 6: Knowledge Engineering tools.
9.00 - 9.30 A radiological expert system for the P.C., design and
Implementation issues.
Horn W., Imhof H., Pfahringer B., Salamonowitz E., (Austria)
9.30 - 10.00 A P.C based shell for clinical information systems with
reasoning capabilities
Wiener F., Groth T. (Israel, Sweden)
10.00 - 10.30 The kernel mechanism for handling assumptions and
justifications and its applications to the biotechnologies
Cherubini M.A., Cerri S.A., Sbarbati R. (I)
10.30 - 11.00 Break
Session 7: General Session
11.00 - 12.00 Invited Lecture
Larry Fagan, Stanford University (USA)
12.00 - 12.30 Man-machine interaction in CHECK
Console L., Fossa M., Torasso P., Molino G., Cravetto G (I)
12.30 - 13.00 The Oxford system of medicine
Fox J., Glowinski A., O'Neil M. (UK)
13.00 - 14.30 Lunch
Session 8: Clinical Applications (2)
14.30 - 15.00 Evaluating the performance of AMEMIA
Quaglini S., Stefanelli M., Barosi G., Berzuini A. (I)
15.00 - 15.30 Computer aided diagnosis and treatment of brachial plexus
injuries.
Jaspers R.B.M., Van der Helm F.C.T. (NL)
15.30 - 16.00 Representation of embryonic development and its anomalies.
Goutal J.M., Philip N., Griffiths M., Ayme S. (F)
16.00 - 16.30 A microcomputer based decision support for lipid desorder.
Fhaircheallaigh D.N., Sinnot M., Grimson J., O'Moore R. (Eire)
16.30 - 17.00 Closing session
Program Committee:
J. Fox, London Chairman
P. Adlassnig, Vienna
R. Engelbrecht, Munich Tutorial
M. Fieschi, Marseille
F. Gremy, Montpellier (F)
T. Groth, Upsalla
A. Hasman, Maastricht
A.L., Rector, Manchester
P.L. reichertz, Hannover
P. Smets, Brussels
M. Stefanelli, Pavia
Organizing committee:
M. Fieschi Chairman
V. Bernadac Organization
P. Dujol
B. Guisiano Social events
M. Joubert Local arrangements
D. Riouall Liaison
M. Roux
G. Soula Exhibition
Additionnal Informations:
Viviane Bernadac
IIRIAM
2 rue Henri Barbusse, CMCI
13241 Marseille Cedex 1 - FRANCE
tel: (33) 91 91 36 72
telex: 440 860
telefax: (33) 91 91 70 24
------------------------------
End of AIList Digest
********************
∂29-Jun-87 0103 LAWS@Stripe.SRI.Com AIList Digest V5 #156
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Jun 87 01:03:32 PDT
Date: Sun 28 Jun 1987 22:22-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #156
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 29 Jun 1987 Volume 5 : Issue 156
Today's Topics:
Theory - Symbol Grounding and Invertibility
----------------------------------------------------------------------
Date: Mon, 22 Jun 87 10:19:59 PDT
From: Neil Hunt <spar!hunt@decwrl.dec.com>
Subject: Symbol grounding and invertibility.
John Cugini <Cugini@icst-ecf.arpa> writes:
> What if there were a few-to-one transformation between the skin-level
> sensors ...
> My example was to suppose that #1:
> a combination of both red and green retinal receptors and #2 a yellow
> receptor BOTH generated the same iconic yellow.
We humans see the world (to a first order at least) through red, green and
blue receptors. We are thus unable to distinguish between light of a yellow
frequency, and a mixture of light of red and green frequencies, and we assign
to them a single token - yellow. However, if our visual apparatus was
equipped with yellow receptors as well, then these two input stimuli
would *appear* quite different, as indeed they are. In this case I think
that it is highly unlikely that we would have the same symbol to
represent the two cases.
Consider a species with only two classes of colour receptors, low
frequency and high frequency, roughly equivalent to our concepts
of red and blue, but with no middle frequency receptors corresponding
to a human concept of green). Creatures of such a species when shown
pure green light would receive reduced levels from the receptors
on each side of green frequency, thus receiving some combination of
blue and red signals. This would be indistinguishable from a mixture
of blue and red, which we call magenta. Such creatures might then
reason (incorrectly) about the possibility of having a middle frequency
receptor, and having a many to one mapping between case #1, pure
green light, and case #2, a mixture of red and blue, and wonder
about how that affects questions of invertibility. As we humans know,
if these creatures had such a visual capability, they would
invent a new symbol for magenta, and there would be no many to one
mapping.
> Clearly this iconic representation is non-invertible back out to the
> sensory surfaces, but intuitively it seems like it would be grounded
> nonetheless - how about it?
The fallacy is that iconic representation described is indeed non invertible,
but it is also clearly not grounded, since if we had yellow receptors,
we would be able to perceive a difference between, and require a new
symbol for one of the new colours.
Neil/.
----- End Forwarded Message -----
------------------------------
Date: 21 Jun 87 22:55:09 GMT
From: ihnp4!homxb!houxm!houdi!marty1@ucbvax.Berkeley.EDU
(M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <6670@diamond.BBN.COM>, aweinste@Diamond.BBN.COM (Anders
Weinstein) writes, with reference to article <861@mind.UUCP>
harnad@mind.UUCP (Stevan Harnad):
>
> Some of the things you say also suggest that you're attempting to resuscitate
> a form of classical empricist sensory atomism, where the "atomic" symbols
> refer to sensory categories acquired "by acquaintance" and the meaning of
> complex symbols is built up from the atoms "by description". This approach
> has an honorable history in philsophy; unfortunately, no one has ever been
> able to make it work. In addition to the above considerations, the main
> problems seem to be: first, that no principled distinction can be made
> between the simple sensory concepts and the complex "theoretical" ones; and
> second, that very little that is interesting can be explicitly defined in
> sensory terms (try, for example, "chair").
>
I hope none of us are really trying to resuscitate classical philosophies,
because the object of this discussion is to learn how to use modern
technologies. To define an interesting object in sensory terms requires
an intermediary module between the sensory system and the symbolic system.
With a chair in the visual sensory field, the system will use hard-coded
nonlinear (decision-making) techniques to identify boundaries and shapes
of objects, and identify the properties that are invariant to rotation
and translation. A plain wooden chair and an overstuffed chair will be
different objects in these terms. But the system might also learn to
identify certain types of objects that move, i.e., those we call people.
If it notices that people assume the same position in association with
both chair-objects, it could decide to use the same category for both.
The key to this kind of classification is that the chair is not defined in
explicit sensory terms but in terms of filtered sensory input.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
P.S. Sorry for the double posting of my previous article.
------------------------------
Date: 20 Jun 87 02:17:09 GMT
From: ihnp4!homxb!houxm!houdi!marty1@ucbvax.Berkeley.EDU
(M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <861@mind.UUCP>, harnad@mind.UUCP writes:
> marty1@houdi.UUCP (M.BRILLIANT) asks:
>
> > what do you think is essential: (A) literally analog transformation,
> > (B) invertibility, or (C) preservation of significant relational
> > functions?
>
Let me see if I can correctly rephrase his answer:
(i) "discrimination" (pairwise same/different judgments) he associates
with iconic ("analog") representations, which he says have to be
invertible, and will ordinarily be really analog because "dedicated"
digital equivalents will be too complex.
(ii) for "identification" or "categorization" (sorting and labeling of
objects), he says only distinctive features need be extracted from the
sensory projection; this process is not invertible.
(iii) for "conscious problem-solving," etc., he says relation-preserving
symbolic representations would be optimal, if they are not "autonomous
(modular)" but rather are grounded by deriving their atomic symbols
through the categorization process above.
(iv) to pass the Total Turing Test he wants all of the above, tied
together in the sequence described.
I agree with this formulation in most of its terms. But some of the
terms are confusing, in that if I accept what I think are good
definitions, I don't entirely agree with the statements above.
"Invertible/Analog": The property of invertibility is easy to visualize
for continuous functions. First, continuous functions are what I would
call "analog" transformations. They are at least locally image-forming
(iconic). Then, saying a continuous transformation is invertible, or
one-to-one, means it is monotonic, like a linear transformation, rather
than many-to-one like a parabolic transformation. That is, it is
unambiguously iconic.
It might be argued that physical sensors can be ambiguously iconic,
e.g., an object seen in a half-silvered mirror. Harnad would argue
that the ambiguity is inherent in the physical scene, and is not
dependent on the sensor. I would agree with that if no human sensory
system ever gave ambiguous imaging of unambiguous objects. What about
the ambiguity of stereophonic location of sound sources? In that case
the imaging (i) is unambiguous; only the perception (ii) is ambiguous.
But physical sensors are also noisy. In mathematical terms, that noise
could be modeled as discontinuity, as many-to-one, as one-to-many, or
combinations of these. The noisy transformation is not invertible.
But a "physically analog" sensory process (as distinct from a digital
one) can be approximately modeled (to within the noise) by a continuous
transformation. The continuous approximation allows us to regard the
analog transformation as image-forming (iconic). But only the
continuous approximation is invertible.
"Autonomous/Modular": The definition of "modular" is not clear to me.
I have Harnad's definition "not analogous to a top-down, autonomous
symbol-crunching module ... hardwired to peripheral modules." The
terms in the definition need defining themselves, and I think there are
too many of them.
I would rather look at the "hybrid" three-layer system and say it does
not have a "symbol-cruncher hardwired to peripheral modules" because
there is a feature extractor (and classifier) in between. The main
point is the presence or absence of the feature extractor.
The symbol-grounding problem arises because the symbols are discrete,
and therefore have to be associated with discrete objects or classes.
Without the feature extractor, there would be no way to derive discrete
objects from the sensory inputs. The feature extractor obviates the
symbol-grounding problem. I consider the "symbol-cruncher hardwired to
peripheral modules" to be not only a straw man but a dead horse.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 26 Jun 87 04:38:02 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
John Cugini <Cugini@icst-ecf.arpa> on ailist@stripe.sri.com writes:
> What if there were a few-to-one transformation between the skin-level
> sensors (remember Harnad proposes "skin-and-in" invertibility
> as being necessary for grounding) and the (somewhat more internal)
> iconic representation. My example was to suppose that #1:
> a combination of both red and green retinal receptors and #2 a yellow
> receptor BOTH generated the same iconic yellow.
> Clearly this iconic representation is non-invertible back out to the
> sensory surfaces, but intuitively it seems like it would be grounded
> nonetheless - how about it?
Invertibility is a necessary condition for iconic representation, not
for grounding. Grounding symbolic representations (according to my
hypothesis) requires both iconic and categorical representations. The
latter are selective, many-to-few, invertible only in the features
they pick out and, most important, APPROXIMATE (e.g., as between
red-green and yellow in your example above). This point has by now
come up several times...
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 26 Jun 87 05:07:40 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem: McCarthy's query
In article 208 of comp.ai.digest: JMC@SAIL.STANFORD.EDU (John McCarthy)
asks:
> I imagine that the alleged point at issue and a few of the positions
> taken could be summarized for the benefit of those of us whose
> subjective probability that there is a real point at issue is too
> low to motivate studying the entire discussion but high enough to
> motivate reading a summary.
The point at issue concerns how symbols in a symbol-manipulative
approach to the modeling of mind can be grounded in something other
than more symbols so that their meanings and their connections to
objects can be independent of people's interpretations of them. One of
the positions taken was that connecting a purely symbolic module to
peripheral (transducer/effector) modules in the right way should be
all you need to ground the symbols. I suggested that all this is
likely to yield is more of the toy models that symbolic AI has produced
until now. To get human-scale (Total Turing Test) performance
capacity, a bottom-up hybrid nonsymbolic/symbolic system may be
needed, one in which the elementary symbols are the names of sensory
categories picked out by inductive (possibly connectionist) feature-filters
(categorical representations) and invertible analogs of sensory projections
(iconic representations). This model is described in "Categorical Perception:
The Groundwork of Cognition" (Cambridge University Press 1987,
S. Harnad, ed., ISBN 0-521-26758-7). Other alternatives that have been
mentioned by others in the discussion included: (1) symbol-symbol "grounding"
is already enough and (2) connectionist nets already generate grounded
"symbols." If you want the entire file, I've saved it all...
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 26 Jun 87 17:19:29 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <914@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> Invertibility is a necessary condition for iconic representation, not
> for grounding. Grounding symbolic representations (according to my
> hypothesis) requires both iconic and categorical representations...
Syllogism:
(a) grounding ... requires ... iconic ... representation....
(b) invertibility is ... necessary ... for iconic representation.
(c) hence, grounding must require invertibility.
Why then does harnad say "invertibility is a necessary condition
for ..., NOT for grounding" (caps mine, of course)?
This discussion is getting hard to follow. Does it have to be carried
on simultaneously in both comp.ai and comp.cog-eng? Could harnad, who
seems to be the major participant, pick one?
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 26 Jun 87 18:03:26 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: The symbol grounding problem: McCarthy's query
Will the proponents of the various views described below, and those
whose revelant views have not been described below, please stand up?
In article <915@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> In article 208 of comp.ai.digest: JMC@SAIL.STANFORD.EDU (John McCarthy)
> asks:
>
> > I imagine that the alleged point at issue and a few of the positions
> > taken could be summarized .....
>
> The point at issue concerns how symbols in a symbol-manipulative
> approach to the modeling of mind can be grounded in something other
> than more symbols so that their meanings and their connections to
> objects can be independent of people's interpretations of them.
> ..... One of
> the positions taken was that connecting a purely symbolic module to
> peripheral (transducer/effector) modules IN THE RIGHT WAY should be
> all you need to ground the symbols.
Caps mine. Position 1 is that the peripherals and the symbolic module
have to be connected in the right way. Harnad's position is that
> .... a bottom-up hybrid nonsymbolic/symbolic system may be
> needed, one in which the elementary symbols are the names of sensory
> categories picked out by inductive (possibly connectionist) feature-filters
> (categorical representations) and invertible analogs of sensory projections
> (iconic representations).....
This looks like a way to connect periperals to a symbolic module. To
the extent that I understand it, I like it, except for the invertibility
condition. If it's the right way, it's a special case of position 1.
Harnad has called the "right way" of position 1 "top-down,"
"hard-wired," and other names, to distance himself from it. I'm not
sure there are any real proponents of position 1 in such a narrow
sense. I support position 1 in the wide sense, and I think Harnad does.
> ..... Other alternatives that have been
> mentioned by others in the discussion included: (1) symbol-symbol "grounding"
> is already enough ....
They don't care about the problem, so either they or we can go away.
They (and I) want this discussion to go to another newsgroup.
> ..... and (2) connectionist nets already generate grounded "symbols."
Is that a variant of Harnad's position, i.e., "(possibly connectionist)"?
I think the real subject of discussion is the definition of some of the
technical terms in Harnad's position, and the identification of which
elements are critical and which might be optional? Might some of the
disagreement disappear if the definitions were more concrete?
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
End of AIList Digest
********************
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∂29-Jun-87 0257 LAWS@Stripe.SRI.Com AIList Digest V5 #157
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Jun 87 02:57:16 PDT
Date: Sun 28 Jun 1987 22:26-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
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Subject: AIList Digest V5 #157
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 29 Jun 1987 Volume 5 : Issue 157
Today's Topics:
Theory - The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 26 Jun 87 19:41:11 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
berleant@ut-sally.UUCP (Dan Berleant) of U. Texas CS Dept., Austin, Texas
writes:
> Are you saying that the categorical representations are to be
> nonsymbolic? The review of human concept representation I recently read
> (Smith and Medin, Categories and Concepts, 1981) came down... hard on
> the holistic theory of concept representation... The alternative
> nonsymbolic approach would be the 'dimensional' one. It seems a
> strongish statement to say that this would be sufficient, to the
> exclusion of symbolic properties... However, the metric
> hypothesis -- that a concept is sufficiently characterized by a point
> in a multi-dimensional space -- seems wrong, as experiments have shown.
Categorical representations are the representations of purely SENSORY
categories, and I am indeed saying that they are to be NONsymbolic.
Let me also point out that the theory I am putting forward represents
a direct challenge to the Roschian line of category research in which
the book you cite belongs. To put it very briefly, I claim that that
line of experimental and theoretical work is not really investigating
the representations underlying the capacity to categorize at all; it is
only looking at the fine tuning of category judgments. The experiments
are typically not addressing the question of how it is that a device
or organism can successfully categorize the inputs in question in the
first place; instead it examines (1) how QUICKLY or EASILY subjects do it,
(2) how TYPICAL (of the members of the category in question) subjects rate
the inputs to be and (3) what features subjects INTROSPECT that they are
using. This completely bypasses the real question of how anyone or anything
actually manages to accomplish the categorization at all.
Let me quickly add that there is nothing wrong with reaction-time
experiments if they suggest hypotheses about the basic underlying
mechanism, or provide ways of testing them. But in this case -- as in
many others in experimental cognitive psychology -- the basic
mechanisms are bypassed and the focus is on fine-tuning questions
that are beside the point (or premature) -- if, that is, the objective
is to explain how organisms or devices actually manage to generate
successful categorization performance given the inputs in question. As
an exercise, see where the constructs you mention above -- "holistic,"
"dimensional," or "metric" representations -- are likely to get you if
you're actually trying to get a device to categorize, as we do.
There is also an "entry point" problem with this line of research,
which typically looks willy-nilly at higher-order, abstract
categories, as well as "basic level" object categories (an incoherent
concept, in my opinion, except as an arbitrary default level), and
even some sensory categories. But it seems obvious that the question
of how the higher-order categories are represented is dependent on how
the lower-order ones are represented, the abstract ones on the
concrete ones, and perhaps all of these depend on the sensory ones.
Moreover, often the inputs used are members of familiar, overlearned
categories, and the task is a trivial one, not engaging the mechanisms
that were involved in their acquisition. In other experiments,
artificial stimuli are used, but it is not clear how representative
these are of the category acquisition process either.
Finally, and perhaps most important: In bypassing the problem of
categorization capacity itself -- i.e., the problem of how devices
manage to categorize as correctly and successfully as they do, given
the inputs they have encountered -- in favor of its fine tuning, this
line of research has unhelpfully blurred the distinction between the
following: (a) the many all-or-none categories that are the real burden
for an explanatory theory of categorization (a penguin, after all, be it
ever so atypical a bird, and be it ever so time-consuming for us to judge
that it is indeed a bird, is, after all, indeed a bird, and we know
it, and can say so, with 100% accuracy every time, irrespective of
whether we can successfully introspect what features we are using to
say so) and (b) true "graded" categories such as "big," "intelligent,"
etc. Let's face the all-or-none problem before we get fancy...
> To discuss "invariant features... sufficient to guide reliable
> categorization" sounds like the "classical" theory (as Smith & Medin
> call it) of concept representation: Concepts are represented as
> necessary and sufficient features (i.e., there are defining features,
> i.e. there is a boolean conjunction of predicates for a concept). This
> approach has serious problems, not the least of which is the inability
> of humans to describe these features for seemingly elementary concepts,
> like "chair", as Weinstein and others point out. I contend that a
> boolean function (including ORs as well as ANDs) could work, but that
> is not what was mentioned. An example might be helpful: A vehicle must
> have a steering wheel OR handlebars. But to remove the OR by saying,
> a vehicle must have a means of steering, is to rely on a feature which
> is symbolic, high level, functional, which I gather we are not allowing.
It certainly is the "classical" theory, but the one with the serious
problems is the fine-tuning approach I just described, not the quite
reasonable assumption that if 100% correct, all-or-none categorization
is possible at all (without magic), then there must be a set of features
in the inputs that is SUFFICIENT to generate it. I of course agree
that disjunctive features are legitimate -- but whoever said they
weren't? That was another red herring introduced by this line of
research. And, as I mentioned, "the inability of humans to describe
these features" is irrelevant. If they could do it, they'd be
cognitive modelers! We must INFER what features they're using to
categorize successfully; nothing guarantees they can tell us.
(If by "Weinstein" you mean "Wittgenstein" on "games," etc., I have to remind
you that Wittgenstein did not have the contemporary burden of speaking
in terms of internal mechanisms a device would have to have in order to
categorize successfully. Otherwise he would have had to admit that
"games" are either (i) an all-or-none category, i.e., there is a "right" or
"wrong" of the matter, and we are able to sort accordingly, whether or
not we can introspect the basis of our correct sorting, or (ii) "games"
are truly a fuzzy category, in which membership is arbitrary,
uncertain, or a matter of degree. But if the latter, then games are
simply not representative of the garden-variety all-or-none
categorization capacity that we exercise when we categorize most
objects, such as chairs, tables, birds. And again, there's nothing
whatsoever wrong with disjunctive features.)
Finally, it is not that we are not "allowing" higher-order symbolically
described features. They are the goal of the whole grounding project.
But the approach I am advocating requires that symbolic descriptions
be composed of primitive symbols which are in turn the labels of sensory
categories, grounded in nonsymbolic (iconic and categorical) representations.
> [Concerning model-theoretic "grounding":] The more statements
> you have (that you wish to be deemed correct), the more the possible
> meanings of the terms will be constrained. To illustrate, consider
> the statement FISH SWIM. Think of the terms FISH and SWIM as variables
> with no predetermined meaning -- so that FISH SWIM is just another way
> of writing A B. What variable bindings satisfy this? Well, many do...
> Now consider the statement FISH LIVE, where FISH and LIVE are variables.
> Now there are two statements to be satisfied. The assignment to the
> variable LIVE restricts the possible assignments to the variable SWIM...
> Of course, we have many many statements in our minds that must be
> simultaneously satisfied, so the possible meanings that each word name
> can be assigned is correspondingly restricted. Could the restrictions be
> sufficient to require such a small amount of ambiguity that the word
> names could be said to have intrinsic meaning?... footnote: This
> leaves unanswered the question of how the meanings themselves are
> grounded. Non-symbolically, seems to be the gist of the discussion,
> in which case logic would be useless for that task even in an
> "in principle" capacity since the stuff of logic is symbols.
I agree that there are constraints on the correlations of symbols in a
natural language, and that the degrees of freedom probably shrink, in
a sense, as the text grows. That is probably the basis of successful
cryptography. But I still think (and you appear to agree) that even if
the degrees of freedom are close to zero for a natural language's
symbol combinatons and their interpretations, this still leaves the
grounding problem intact: How are the symbols connected to their
referents? And what justifies our interpretation of their meanings?
With true cryptography, the decryption of the symbols of the unknown
language is always grounded in the meanings of the symbols of a known
language, which are in turn grounded in our heads, and their
understanding of the symbols and their relation to the world. But
that's the standard DERIVED meaning scenario, and for cognitive
modeling we need INTRINSICALLY grounded symbols. (I do believe,
though, that the degrees-of-freedom constraint on symbol combinations
does cut somewhat into Quine's claims about the indeterminacy of
radical translation, and ESPECIALLY for an intrinsically grounded
symbol system.)
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 26 Jun 87 22:17:16 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
aweinste@Diamond.BBN.COM (Anders Weinstein) of BBN Laboratories, Inc.,
Cambridge, MA writes:
> I don't see any difference between "physical" and "merely theoretical"
> invertibility... Surely you don't mean that a transformation-inversion
> capability must actually be present in the device for it to count as
> "analog" in your sense. (Else brains, for example, wouldn't count).
I think this is partly an empirical question. "Physically possible"
invertibility is enough for an analog transformation, but actual
physical invertibility may be necessary for an iconic representation
that can generate all of our discrimination capacities. Avoiding
"merely theoretical" invertibility is also part of avoiding any reliance
on mediation by our theoretical interpretations in order to get an
autonomous, intrinsically grounded system.
> the *semantic* meaning of a symbol is still left largely unconstrained
> even after you take account of it's "grounding" in perceptual
> categorization. This is because what matters for intentional content
> is not the objective property in the world that's being detected, but
> rather how the subject *conceives* of that external property, a far
> more slippery notion... primitive people may be able to reliably
> categorize certain large-scale atmospheric electrical discharges;
> nevertheless, the semantic content of their corresponding states might
> be "Angry gods nearby" or some such.
I agree that symbol grounding cannot be based on the "objective
property" that's being detected. Categorical representations in my
grounding model are approximate. All they do is sort and label the confusable
alternatives that have been sampled, using the provisional features
that suffice to generate reliable sorting performance according to the feedback
that defines "right" and "wrong." There is always a context of
confusable alternatives, and which features are used to sort reliably
is always a "compared to what?" matter. The exact "objective property" they
pick out is never an issue, only whether they can generate reliable
asymptotic categorization performance given that sample and those
feedback constraints. The representation is indifferent to whether
what you are calling "water," is really "twin-water" (with other
objective properties), as long as you can sort it "correctly" according
to the feedback (say, from the dictates of thirst, or a community of
categorizing instructors).
As to what people "conceive" themselves to be categorizing: My model
is proposed in a framework of methodological epiphenomenalism. I'm
interested in what's going on in people's heads only inasmuch as it is
REALLY generating their performance, not just because they think or
feel it is. So, for example, in criticizing the Roschian approach to
categorization in my reply to Dan Berleant I suggested that it was
irrelevant what features subjects BELIEVED they were using to
categorize, say, chairs; what matters is what features they (or any
organism or device in a similar input situation) really ARE using.
[This does not contradict my previous point about the irrelevance of
"objective properties." "Features" refers to properties of the
proximal projection on the device's sense receptors, whereas
"properties" would be the essential characteristics of distal objects
in the world. Feature detectors are blind to distal differences that
are not preserved in the proximal projection.]
On the other hand, "Angry gods nearby" is not just an atomic label for
"thunder" (otherwise it WOULD be equivalent to it in my model -- both
labels would pick out approximately the same thing); in fact, it is
decomposable, and hence has a different meaning in virtue of the
meanings of "angry" and "gods." There should be corresponding internal
representational differences (iconic, categorical and symbolic) that
capture that difference.
> Another well-known obstacle to moving from an objective to an
> intentional description is that the latter contains an essentially
> normative component, in that we must make some distinction between
> correct and erroneous classification. For example, we'd probably
> like to say that a frog has a fly-detector which is sometimes wrong,
> rather than a "moving-spot-against-a- fixed-background" detector
> which is infallible. Again, this distinction seems to depend on fuzzy
> considerations about the purpose or functional role of the concept
> in question... [In his reply on this point to Dan Berleant,
> Weinstein continues:] the philosophical problem is to say why any
> response should count as an *error* at all. What makes it wrong?
> I.e. who decides which "concept" -- "fly" or "moving-spot..." -- the
> frog is trying to apply? The objective facts about the frog's
> perceptual abilities by themselves don't seem to tell you that in
> snapping out its tongue at a decoy, it's making a *mistake*. To
> say this, an outside interpreter has to make some judgement about what
> the frog's brain is trying to accomplish by its detection of moving
> spots. And this makes the determination of semantic descriptions a
> fuzzy matter.
I don't think there's any problem at all of what should count as an "error"
for my kind of model. The correctness or incorrectness of a label is
always determined by feedback -- either ecological, as in evolution
and daily nonverbal learning, or linguistic, where it is conventions
of usage that determine what we call what. I don't see anything fuzzy about
such a functional framework. (The frog's feedback, by the way,
probably has to do with edibility, so (i) "something that affords eating"
is probably a better "interpretation" of what it's detecting. And, to
the extent that (ii) flies and (iii) moving spots are treated indifferently by
the detector, the representation is approximate among all three.
The case is not like that of natives and thunder, since the frog's
"descriptions" are hardly decomposable. Finally, there is again no
hope of specifying distal "objective properties" ["bug"/"schmug"] here
either, as approximateness continues to prevail.)
> Some of the things you say also suggest that you're attempting to
> resuscitate a form of classical empricist sensory atomism, where the
> "atomic" symbols refer to sensory categories acquired "by acquaintance"
> and the meaning of complex symbols is built up from the atoms "by
> description". This approach has an honorable history in philosophy;
> unfortunately, no one has ever been able to make it work. In addition
> to the above considerations, the main problems seem to be: first,
> (1) that no principled distinction can be made between the simple
> sensory concepts and the complex "theoretical" ones; and second,
> (2) that very little that is interesting can be explicitly defined in
> sensory terms (try, for example, "chair")...[In reply to Berleant,
> Weinstein continues:] Of course *some* concepts can be acquired by
> definition. However, the "classical empiricist" doctrine is committed
> to the further idea that there is some privileged set of *purely
> sensory* concepts and that all non-sensory concepts can be defined in
> terms of this basis. This is what has never been shown to work. If you
> regard "juice" as a "primitive" concept, then you do not share the
> classical doctrine. (And if you do not, I invite you try giving
> necessary and sufficient conditions for juicehood.)
You're absolutely right that this is a throwback to seventeenth-century
bottom-upism. In fact, in the CP book I call the iconic and
categorical representations the "acquaintance system" and the symbolic
representations the "description system." The only difference is that
I'm only claiming to be giving a theory of categorization. Whether or
not this captures "meaning" depends (for me at any rate) largely on
whether or not such a system can successfully pass the Total Turing
Test. It's true that no one has made this approach work. But it's also
true that no one has tried. It's only in today's era of computer
modeling, robotics and bioengineering that these mechanisms will begin
to be tested to see whether or not they can deliver the goods.
To reply to your "two main problems": (1) Even an elementary sensory
category such as "red" is already abstract once you get beyond the
icon to the categorical representation. "Red" picks out the
electromagnetic wave-lengths that share the feature of being above and
below a certain threshold. That's an abstraction. And in exchange for
generating a feature-detector that reliably picks it out, you get a
label -- "red" -- which can now enter into symbolic descriptions (e.g.,
"red square"). Categorization is abstraction. As soon as you've left
the realm of invertible icons, you've begun to abstract, yet you've
never left the realm of the senses. And so it goes, bottom up, from
there onward.
(2) As to sensory "definitions": I don't think this is the right thing
to look for, because it's too hard to find a valid "entry point" into
the bottom-up hierarchy. I doubt that "chair" or "juice" are sensory
primitives, picked out purely by sensory feature detectors. They're
probably represented by symbolic descriptions such as "things you can
sit on" and "things you can drink," and of course those are just the
coarsest of first approximations. But the scenario looks pretty
straightforward: Even though it's flexible enough to be revised to
include a chair (suitably homegenized) as a juice and a juice (for a
bug?) as a chair, it seems very clear that it is the resources of (grounded)
symbolic description that are being drawn upon here in picking out
what is and is not a chair, and on the basis of what features.
The categories are too interrelated (and approximate, and provisional) for
an exhaustive "definition," but provisional descriptions that will get
you by in your sorting and labeling -- and, more important, are
revisable and updatable, to tighten the approximation -- are certainly
available and not hard to come by. "Necessary and sufficient conditions for
juicehood," however, are a red herring. All we need is a provisional
set of features that will reliably sort the instances as environmental and
social feedback currently dictates. Remember, we're not looking for
"objective properties" or ontic essences -- just something that will
guide reliable sorting according to the contingencies sampled to date.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
End of AIList Digest
********************
-------
∂29-Jun-87 0451 LAWS@Stripe.SRI.Com AIList Digest V5 #158
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Jun 87 04:51:33 PDT
Date: Sun 28 Jun 1987 22:30-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
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Subject: AIList Digest V5 #158
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 29 Jun 1987 Volume 5 : Issue 158
Today's Topics:
Theory - The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 27 Jun 87 01:09:41 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem: McCarthy's query
marty1@houdi.UUCP (M.BRILLIANT) of AT&T Bell Laboratories, Holmdel writes:
> But a "physically analog" sensory process (as distinct from a digital
> one) can be approximately modeled (to within the noise) by a continuous
> transformation. The continuous approximation allows us to regard the
> analog transformation as image-forming (iconic). But only the
> continuous approximation is invertible.
I have no quarrel with this, in fact I make much the same point --
that iconic representations are approximate too -- in the chapter
describing the three kinds of representation. Is there any reason for
expecting I would object?
> the "hybrid" three-layer system... does not have a "symbol-cruncher
> hardwired to peripheral modules" because there is a feature extractor
> (and classifier) in between. The main point is the presence or
> absence of the feature extractor... The symbol-grounding problem
> arises because the symbols are discrete, and therefore have to be
> associated with discrete objects or classes. Without the feature
> extractor, there would be no way to derive discrete objects from the
> sensory inputs. The feature extractor obviates the symbol-grounding
> problem.
The problem certainly is not just that of discrete symbols needing to pick
out discrete objects. You are vastly underestimating the problem of
sensory categorization, sensory learning, and the relation between
lower and higher-order categories. Nor is it obvious that symbol manipulation
can still be regarded as just symbol manipulation when the atomic symbols
are constrained to be the labels of sensory categories. That's a
bottom-up constraint, and symbolic AI normally expects to float down
onto its sensors top-down. Imagine if your "setq" statements were
constrained by what your elementary symbols were connected to, and their
respective causal interrelations with other nonsymbolic sensory representations
and their associated labels.
> Why does Harnad say "invertibility is a necessary condition
> for iconic representations..., NOT for grounding"
Because the original statement of mine that you quote was a reply to a
query about whether ALL representations had to be invertible for grounding.
(It was accompanied by alleged counterexamples -- grounded but noninvertible
percepts.) My reply indicated that only iconic ones had to be invertible,
but that both iconic and categorical (noninvertible) ones were needed to
ground symbols.
> Position 1 [on the symbol grounding problem] is that the peripherals
> and the symbolic module have to be connected in the right way. Harnad's
> position is... a special case of position 1.
I'm afraid not. I don't think there will be independent peripheral
modules and symbolic modules suitably interconnected in the hybrid
device that passes the Total Turing Test. I think a lot of what we
consider cognition will be going on in the nonsymbolic iconic and categorical
systems (discrimination, categorization, sensory learning and
generalization) and that symbol manipulation will be constrained in
ways that don't leave it in any way analogous to the notion of an
independent functional module, operating on its own terms (as in
standard AI), but connected at some critical point with the
nonsymbolic modules. When I spoke earlier of the "connections" of the
atomic symbols I had in mind something much more complexly
interdigitated and interdependent than can be captured by anything
that remotely resembles position 1. Position 1 is simply AI's pious
hope that a pure "top-down" approach can expect to meet up with a
bottom-up one somewhere in between. Mine is not a special case of
this; it's a rival.
> "...and (2) connectionist nets already generate grounded "symbols." Is
> that a variant of Harnad's position, i.e., "(possibly connectionist)"?
No. In my model connectionistic processes are just one possible
candidate for the mechanism that finds the features that will reliably
pick out a learned category. They would just be a component in the
categorical representational system. But there are much more ambitious
connectionistic views than that, for example, that connectionism can
usurp the role of symbolic representations altogether or (worse) that
they ARE symbolic (in some yet to be established sense). As far as I'm
concerned, the latter would entail a double grounding problem for
connectionism, the first to ground its interpretation of its states as
symbolic states, and then to ground the interpretations of the
symbolic states themselves (which is the standard symbol grounding problem).
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 27 Jun 87 14:32:42 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem: Correction re.
Approximationism
In responding to Cugini and Brilliant I misinterpreted a point that
the former had made and the latter reiterated. It's a point that's
come up before: What if the iconic representation -- the one that's
supposed to be invertible -- fails to preserve some objective property
of the sensory projection? For example, what if yellow and blue at the
receptor go into green at the icon? The reply is that an analog
representation is only analog in what it preserves, not in what it fails
to preserve. Icons are hence approximate too. If all retinal squares,
irrespective of color, go into gray icons, I have icons of the
squareness, but not of the colors. Or, to put it another way, the
grayness is approximate as between all the actual colors (and gray).
There is no requirement that all the features of the sensory
projection be preserved in icons; just that some of them should be --
enough to subserve our discrimination capacities. This is analogous to
the fact that the sensory projection itself need not (and does not,
and cannot) preserve all of the properties of the distal object. To
those it fails to preserve -- and that we cannot detect by instruments
or inference -- we are fated to remain "blind." But none of this
information loss in either sensory projections or icons (or, for that
matter, categorical representations) compromises groundedness. It just
means that our representations are doomed to be approximations.
Finally, it must be recalled that my grounding scheme is proposed in a
framework of methodological epiphenomenalism: It only tries to account
for performance capacity (discrimination, identification,
description), not qualitative experience. So "what it is like to see
yellow" is not part of my evidential burden: just what it takes to
discriminate, identify and describe colors as those who see yellow do...
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 27 Jun 87 13:22:19 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <917@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> ... blurred the distinction between the
> following: (a) the many all-or-none categories that are the real burden
> for an explanatory theory of categorization (a penguin, after all, be it
> ever so atypical a bird, ... is, after all, indeed a bird, and we know
> it, and can say so, with 100% accuracy every time, ....
> ... and (b) true "graded" categories such as "big," "intelligent," ...
> ......
> "games" are either (i) an all-or-none category, i.e., there is a "right" or
> "wrong" of the matter, and we are able to sort accordingly, ...
> ... or (ii) "games"
> are truly a fuzzy category, in which membership is arbitrary,
> uncertain, or a matter of degree. But if the latter, then games are
> simply not representative of the garden-variety all-or-none
> categorization capacity that we exercise when we categorize most
> objects, such as chairs, tables, birds....
Now, much of this discussion is out of my field, but (a) I would like
to share in the results, and (b) I understand membership in classes
like "bird" and "chair."
I learned recently that I can't categorize chairs with 100% accuracy.
A chair used to be a thing that supported one person at the seat and
the back, and a stool had no back support. Then somebody invented a
thing that supported one person at the seat, the knees, but not the
back, and I didn't know what it was. As far as my sensory
categorization was concerned at the time, its distinctive features were
inadequate to classify it. Then somebody told me it was a chair. Its
membership in the class "chair" was arbitrary. Now a "chair" in my
lexicon is a thing that supports the seat and either the back or the
knees.
Actually, I think I perceive most chairs by recognizing the object
first as a familiar thing like a kitchen chair, a wing chair, etc., and
then I name it with the generic name "chair." I think Harnad would
recognize this process. The class is defined arbitrarily by inclusion
of specific members, not by features common to the class. It's not so
much a class of objects, as a class of classes....
If that is so, then "bird" as a categorization of "penguin" is purely
symbolic, and hence is arbitrary, and once the arbitrariness is defined
out, that categorization is a logical, 100% accurate, deduction. The
class "penguin" is closer to the primitives that we infer inductively
from sensory input.
But the identification of "penguin" in a picture, or in the field, is
uncertain because the outlines may be blurred, hidden, etc. So there
is no place in the pre-symbolic processing of sensory input where 100%
accuracy is essential. (This being so, there is no requirement for
invertibility.)
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 28 Jun 87 17:52:03 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: The symbol grounding problem: Against Rosch & Wittgenstein
marty1@houdi.UUCP (M.BRILLIANT) of AT&T Bell Laboratories, Holmdel asks:
> Why require 100% accuracy in all-or-none categorizing?... I learned
> recently that I can't categorize chairs with 100% accuracy.
This is a misunderstanding. The "100% accuracy" refers to the
all-or-none-ness of the kinds of categories in question. The rival
theories in the Roschian tradition have claimed that many categories
(including "bird" and "chair") do not have "defining" features. Instead,
membership is either fuzzy or a matter of degree (i.e., percent), being
based on degree of similarity to a prototype or to prior instances, or on
"family resemblances" (as in Wittgenstein on "games"), etc.. I am directly
challenging this family of theories as not really providing a model for
categorization at all. The "100% accuracy" refers to the fact that,
after all, we do succeed in performing all-or-none sorting and
labeling, and that membership assignment in these categories is not
graded or a matter of degree (although our speed and "typicality
ratings" may be).
I am not, of course, claiming that noise does not exist and that errors
may not occur under certain conditions. Perhaps I should have put it this way:
Categorization preformance (with all-or-none categories) is highly reliable
(close to 100%) and MEMBERSHIP is 100%. Only speed/ease of categorization and
typicality ratings are a matter of degree. The underlying representation must
hence account for all-or-none categorization capacity itself first,
then worry about its fine-tuning.
This is not to deny that even all-or-none categorization may encounter
regions of uncertainty. Since ALL category representations in my model are
provisional and approximate (relative to the context of confusable
alternatives that have been sampled to date), it is always possible that
the categorizer will encounter an anomalous instance that he cannot classify
according to his current representation. The representation must
hence be revised and updated under these conditions, if ~100% accuracy
is to be re-attained. This still does not imply that membership is
fuzzy or a matter of degree, however, only that the (provisional
"defining") features that will successfully sort the members must be revised
or extended. The approximation must be tightened. (Perhaps this is
what happened to you with your category "chair.") The models for the
true graded (non-all-or-none) and fuzzy categories are, respectively,
"big" and "beautiful."
> The class ["chair," "bird"] is defined arbitrarily by inclusion
> of specific members, not by features common to the class. It's not so
> much a class of objects, as a class of classes.... If that is so,
> then "bird" as a categorization of "penguin" is purely symbolic, and
> hence is arbitrary, and once the arbitrariness is defined
> out, that categorization is a logical, 100% accurate, deduction.
> The class "penguin" is closer to the primitives that we infer
> inductively [?] from sensory input... But the identification of
> "penguin" in a picture, or in the field, is uncertain because the
> outlines may be blurred, hidden, etc. So there is no place in the
> pre-symbolic processing of sensory input where 100% accuracy is
> essential. (This being so, there is no requirement for invertibility.)
First, most categories are not arbitrary. Physical and ecological
contraints govern them. (In the case of "chair," this includes the
Gibsonian "affordance" of whether they're something that can be sat
upon.) One of the constraints may be social convention (as in
stipulations of what we call what, and why), but for a
categorizer that must learn to sort and label correctly, that's just
another constraint to be satisfied. Perhaps what counts as a "game" will
turn out to depend largely on social stipulation, but that does not make
its constraints on categorization arbitrary: Unless we stipulate that
"gameness" is a matter of degree, or that there are uncertain cases
that we have no way to classify as "game" or "nongame," this category
is still an all-or-none one, governed by the features we stipulate.
(And I must repeat: Whether or not we can introspectvely report the features
we are actually using is irrelevant. As long as reliable, consensual,
all-or-none categorization performance is going on, there must be a set of
underlying features governing it -- both with sensory and more
abstract categories. The categorization theorist's burden is to infer
or guess what those features really are.)
Nor is "symbolic" synonymous with arbitrary. In my grounding scheme,
for example, the primitive categories are sensory, based on
nonsymbolic representations. The primitive symbols are then the names
of sensory categories; these can then can go on to enter into combinations
in the form of symbolic descriptions. There is a very subtle "entry-point"
problem in investigating this bottom-up quasi-hierarchy, however:
Is a given input sensory or symbolic? And, somewhat independently, is
its categorization mediated by a sensory representation or a symbolic
one (or both, since there are complicated interrelations [especially
inclusion relations] between them, including redundancies and sometimes
even incoherencies)? The Roschian experimental and theoretical line of
work I am criticizing does not attempt to sort any of this out, and no
wonder, because it is not really modeling categorization performance
in the first place, just its fine tuning.
As to invertibility: I must again repeat, an iconic representation is
only analog in the properties of the sensory projection that it
preserves, not those it fails to preserve. Just as our successful
all-or-none categorization performance dictates that a reliable
feature set must have been selected, so our discrimination performance
dictates the minimal resolution capacity and invertibility there must be
in our iconic representations.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: Sun 28 Jun 87 15:27:22-PDT
From: Ken Laws <Laws@Stripe.SRI.Com>
Subject: Fuzzy Symbolism
From: mind!harnad@princeton.edu (Stevan Harnad)
Finally, and perhaps most important: In bypassing the problem of
categorization capacity itself -- i.e., the problem of how devices
manage to categorize as correctly and successfully as they do, given
the inputs they have encountered -- in favor of its fine tuning, this
line of research has unhelpfully blurred the distinction between the
following: (a) the many all-or-none categories that are the real burden
for an explanatory theory of categorization (a penguin, after all, be it
ever so atypical a bird, and be it ever so time-consuming for us to judge
that it is indeed a bird, is, after all, indeed a bird, and we know
it, and can say so, with 100% accuracy every time, irrespective of
whether we can successfully introspect what features we are using to
say so) and (b) true "graded" categories such as "big," "intelligent,"
etc. Let's face the all-or-none problem before we get fancy...
Is a mechanical rubber penguin a penguin? Is a dead or dismembered
penguin a penguin? How about a genetically damaged or altered penguin?
When does an penguin embryo become a penguin? When does it become a
bird? I think your example depends on circularities inherent in our
use of natural language. I can't unambiguously define the class of
penguins, so how can I be 100% certain that every penguin is a bird?
If, on the other hand, we are dealing only in abstractions, and the
only "penguin" involved is a idealized living adult penguin bird, then
the question is a tautology. We would then be saying that we are 100%
certain that our abstraction satisfies its own sufficient conditions --
and even that could change if scientists someday discover incontrovertible
evidence that penguins are really fish.
In short, every category is a graded one except for those that we
postulate to be exact as part of their defining characteristics.
After writing the above, I saw the following reply:
I am not, of course, claiming that noise does not exist and that errors
may not occur under certain conditions. Perhaps I should have put it
this way: Categorization preformance (with all-or-none categories) is
highly reliable (close to 100%) and MEMBERSHIP is 100%. Only
speed/ease of categorization and typicality ratings are a matter of
degree. The underlying representation must hence account for
all-or-none categorization capacity itself first, then worry about its
fine-tuning.
This is not to deny that even all-or-none categorization may encounter
regions of uncertainty. Since ALL category representations in my model are
provisional and approximate (relative to the context of confusable
alternatives that have been sampled to date), it is always possible that
the categorizer will encounter an anomalous instance that he cannot classify
according to his current representation. The representation must
hence be revised and updated under these conditions, if ~100% accuracy
is to be re-attained. This still does not imply that membership is
fuzzy or a matter of degree, however, only that the (provisional
"defining") features that will successfully sort the members must be revised
or extended. The approximation must be tightened.
You are entitled to such an opinion, of course, but I do not accept the
position as proven. We do, of course, sort and categorize objects when
forced to do so. At the point of observable behavior, then, some kind
of noninvertible or symbolic categorization has taken place. Such
behavior, however, is distinct from any of the internal representations
that produce it. I can carry fuzzy and even conflicting representations
until -- and often long after -- the behavior is initiated. Even at
the instant of commitment, my representations need be unambiguous only
in the implicit sense that one interpretation is momentarily stronger
than the other -- if, indeed, the choice is not made at random.
It may also be true that I do reduce some representations to a single
neural firing or to some other unambiguous event -- e.g., when storing
a memory. I find this unlikely as a general model. Coarse coding,
graded or frequency encodings, and widespread activation seem better
models of what's going on. Symbolic reasoning exists in pure form
only on the printed page; our mental manipulation even of abstract
symbols is carried out with fuzzy reasoning apparatus.
-- Ken Laws
------------------------------
End of AIList Digest
********************
-------
∂29-Jun-87 0725 LAWS@Stripe.SRI.Com AIList Digest V5 #159
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Jun 87 07:21:50 PDT
Date: Sun 28 Jun 1987 23:05-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #159
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 29 Jun 1987 Volume 5 : Issue 159
Today's Topics:
Future Directions - Drexler and Nanotechnology,
History - AI in the 13th Century & Otto Selz,
Binding - Computer Composition of Music
----------------------------------------------------------------------
Date: Mon, 22 Jun 87 11:03:03 EDT
From: Bruce Nevin <bnevin@cch.bbn.com>
Subject: nano-engineering
There is a good summary article in _Whole Earth Review_ (Spring 1987),
pp. 8-14: A Technology of Tiny Things, Nanotechnics and Civilization,
by K. Eric Drexler. The bio in the footnote at the beginning says
Drexler got his SB from MIT in interdisciplinary science, followed by a
Master's in Aeronautics and Astronautics also at MIT. Recently he
founded the MIT Nanotechnology Study Group to develop the science
described in the article and book. Some excerpts from the former:
Whatever is, is obviously possible. Life is. Therefore that
demonstrates the possibility of molecular machines able to build
other molecular machines--the essence of both life and a new
method called nanotechnology. . . .
Whatever obeys natural law is also possible. Science now
understands the laws of ordinary matter and energy well enough
for most engineering purposes. Nanotechnology will enable us to
build new kinds of things. Physical laws let us calculate what
some of these things will be able to do.
The basic idea of nanotechnology is straightforward. . . .
Molecular machines are simply machines made of molecular-scale
parts having carefully arranged atoms.
. . . Nanotechnology assemblers will be molecular machines that
grab reactive molecules and bring them together in a controlled
way, building up a complex structure a few atoms at a time.
. . .
There is no new science in nanotechnology, only new engineering.
The possibility of nanotechnology was implicit in the science
known over 30 years ago, though no one saw it then. During the
1940s and 1950s, biochemistry revealed more and more of the
molecular machinery of the cell. In 1959, physicist Richard
Feynman touched on a similar idea in a talk: he spoke of using
small machines to build smaller machines ( . . . and so on). He
suggested that the smallest machines would be able to "put atoms
down where a chemist says" to make a "chemical substance." But
Feynman didn't explain how these machines were to work, and said
they "will really be useless," because chemists will be able to
make whatever they want without them. Decades passed with
little followup.
[Molecular biology advanced, Drexler's work at MIT indicated in
winter of 1976 the possibility of "what we now call assemblers";
he describes several paths for evolution of nanotechnics from
present science and technology. --BN]
As you can see, the starting point will make little difference.
All roads lead to assemblers, and assemblers will let us make
almost anything we are clever enough to design.
. . .
In a world full of competing companies and governments, only
global disaster or global domination could block the advance of
technology. This seems to be a fundamental principle; if so, it
must guide our plans.
. . .
What can nanotechnology do for us? Almost anything we want, in
physical terms. Once we have the software to direct them,
replicating assemblers can build almost anything, including
more of themselves, without human labor. Because they will
handle matter atom by atom, as trees do, they can be as clean
as trees, or cleaner. They need not produce smoke or sludge or
toxic chemical byproducts.
. . .
One important application will be the further miniaturization of
computers. Detailed study shows that assemblers could build the
equivalent of a large, modern computer in about 1/1000 of the
volume of a typical human cell. This could be a mechanical
computer (they're easier to analyze than electronic computers),
but moving parts on this scale can be small and fast enough to
make the computer faster than today's electronic machines.
. . .
Drexler also writes at some length about the enormous potential for
danger and disruption of society and biosphere.
Our survival may depend on our ability to tell sense from
nonsense regarding a complex technology that doesn't exist yet.
The nonsense will be abundant, no matter what we do: any field
on the borders of science fiction, quantum mechanics, and
biology is well positioned to import a lot of prefabricated
crap; any field where experiments and experience aren't yet
possible is going to have great trouble getting rid of that
crap. When someone says "nanotechnology" and begins to expound,
beware!
. . . a political movement to deal with nanotechnology must be a
movement to guide advance, not to stop it. I've already argued
that attempts to stop it would be futile; here are some reasons
for thinking such efforts would be socially irresponsible.
I leave this and much more for the interested reader to follow up in the
Spring issue of WER.
(This same issue by the way has Shank's `Reality Club' contribution
on why math should not be taught in public schools. As you know from
his AI work, it cannot be because he dislikes math or is bad at it.)
Bruce Nevin
bn@cch.bbn.com
(This is my own personal communication, and in no way expresses or
implies anything about the opinions of my employer, its clients, etc.)
------------------------------
Date: 24 Jun 87 15:39 PDT
From: JJD.MDC@OFFICE-1.ARPA
Subject: Drexler and Nanotechnology
Sorry I missed the NPR report on K. Eric Drexler and _Engines of Creation_.
Here's some background:
The book _Engines of Creation_ was publixhed by Anchor Press / Doubleday in
1986. The excited foreword is by Marvin Minsky. I know from the copy that I
just checked out that Drexler discusses AI in the book, but I am not sure what
his vantage point is. At minimum, of course, is the potential of
nanotechnology as a way to build much denser hardware. I suspect that Drexler
also at least touches on the idea of this enabling a critical mass and
consciousness. This will come later. It's a good read.
The book was excerpted in the Spring 1987 issue of _Whole Earth Review_. This
article is provocative and has some good conceptual illustrations.
The cover bio of Drexler identifies him as a "Research Affiliate at the MIT
Space Systems Laboratory." He is pictured with his back to the camera, staring
at an imposing and eclectic pile of books and a terminal.
I first encountered Drexler in the pages of the Summer 1976 issue of
_CoEvolution Quarterly_ (ancestor of _Whole Earth Review_). The theme of that
issue (later extended as a book) was Gerard O'Neill's concept of space
colonization and industrialization. Drexler was a very articulate advocate who
was actually doing something about it. He was a graduate student at the time,
and had built a six-foot-long track that could electromagnetically launch a
bucket of water into a wall at 80 miles per hour. It was a demonstration of
the feasibility of a mass driver to be built on the moon and to launch 10
kilogram sacks of material to colony construction sites. He contributed to the
book that came from the initial article, demolishing his opponents with gleeful
arrogance (apparently since moderated, perhaps by exposure to audiences in the
last few years).
I suspect that Drexler has a general interest in big fixes in answer to
contemporary dilemmas, motivating his fascination with both space
industrialization and with nanotechnology. More specifically, his earlier
interest in space has probably driven his interest in nanotechnology.
Nanotechnology promises to revolutionize both the ways things are made, and
their resulting performance characteristics. It makes vast systems of
capital-intensive, high-performance technology seems more approachable.
I leave further analysis to the next century's graduate theses re: contemporary
intellectual history.
------------------------------
Date: 26 Jun 87 18:28:37 GMT
From: jbn@glacier.stanford.edu (John B. Nagle)
Subject: Re: AI in the 13th Century
A thorough discussion of the Ars Magna ("Great Art") of Ramon Lull
can be found in Martin Gardner's "Science - Good, Bad and Bogus" (ISBN
0-87975-144-4). The Great Art is basically a system for exhaustively
combining terms, using a stack of disks, each containing a set of related
terms. For example, one set of Lull's disks contained the following words:
1. God, creature, operation
2. difference, similarity, contrariety
3. beginning, middle, end
4. majority, equality, minority
5. affirmation, negation, doubt
In operation, one chooses one term from each set, more or less at random.
One can thus explore, Gardner writes, "such topics as the beginning and
end of God, differences and similarities of animals, and so on."
The Great Art provides no assistance in selecting useful combinations from
the many produced, or for doing anything with them once selected. It
provides only a means for enumerating the possibilities inherent in some
taxonomic scheme. So, while the Great Art may be useful as a prod
for creative thinking by humans, it does not provide anything more profound.
It does, though, generate the illusion of profundity, which provides much of
its appeal.
John Nagle
------------------------------
Date: 24 Jun 87 13:23:51 GMT
From: edwards@unix.macc.wisc.edu (mark edwards)
Subject: AI in the 13th Century
A number of people have asked about the reference to AI in the
13th Century. Well I finally dug up the ole notebook and picked
it out. Unfortunately all I have is a name. The name is
Ramon Lull
Since the book was in latin, very old and so forth I guess I thought
I'd never check it out. Apparently Ramon was a popular person in the
sciences, black magic and those sort of things. His name appears
with other terms like shamans in my notebook.
I hope that helps.
mark
--
edwards@unix.macc.wisc.edu
{allegra, ihnp4, seismo}!uwvax!uwmacc!edwards
UW-Madison, 1210 West Dayton St., Madison WI 53706
------------------------------
Date: 24 Jun 87 17:03:34 GMT
From: duke!mps@mcnc.org (Michael P. Smith)
Subject: Re: AI in the 13th Century
In article <1654@uwmacc.UUCP> edwards@uwmacc.UUCP (mark edwards) writes:
>
> A number of people have asked about the reference to AI in the
> 13th Century. Well I finally dug up the ole notebook and picked
> it out. Unfortunately all I have is a name. The name is
>
> Ramon Lull
>
>
> Since the book was in latin, very old and so forth I guess I thought
> I'd never check it out. Apparently Ramon was a popular person in the
> sciences, black magic and those sort of things. His name appears
> with other terms like shamans in my notebook.
>
I'm no Lull expert, but here's part of an entry from W.L. Reese's
DICTIONARY OF PHILOSOPHY AND RELIGION (Humanities, 1980), p. 319:
\begin{quotation}
Lull, Raymond. 1236-1315.
Philosopher and missionary. Born in Palma, Majorca. Taught
several years at Paris. His goal was to state the truths Christianity
so succinctly that the infidels could not possibly deny them. To this
end he wrote the *Ars Magna*, a mechanical method of exhaustively
stating the possible relations of a topic. The method requires three
concentric circles divided into compartments. One circle is divided
into nine relevant subjects; a second circle is divided into nine
relevant predicates; the third circle is divided into nine questions:
whether? what? whence? why? how large? of what kind? when? where? how?
One circle is fixed; the others rotate, providing a complete series of
questions, and of statements in relation to them.
\end{quotation}
Lull is usually dismissed as a crackpot by historians, but had
influence on the likes of Descartes and Leibniz centuries later.
I believe that much of Lull's work is available in English translation.
No doubt some interesting comparisons can be drawn between Lull's
program and, say, conceptual dependency theory. But as to Mark's
claim that Lull used the term 'artificial intelligence', I suspect
that such usage occurs only in the mind of the translator.
----------------------------------------------------------------------------
Michael P. Smith "The world of the happy man is a different
ARPA: mps@duke.cs.duke.edu one from that of the unhappy man."
Wittgenstein
------------------------------
Date: 24 Jun 87 19:05:25 GMT
From: duke!jds@mcnc.org (Joseph D. Sloan)
Subject: Re: AI in the 13th Century
Martin Gardner devotes a chapter to Ramon Lull in
LOGIC, MACHINES AND DIAGRAMS, 2e, 1982, University
of Chicago Press.
Joe Sloan
jds@duke
------------------------------
Date: 25 Jun 87 14:03:37 GMT
From: nosc!humu!uhccux!stampe@sdcsvax.ucsd.edu (David Stampe)
Subject: Re: AI in the 13th Century
The nine questions of Ramon Lull's Ars Magna (whether? what? whence?
why? how large? of what kind? when? where? how?) seem to be what were
called the "modes of being" in the grammatical theories of the
"Modistae" during the middle ages. They were based ultimately on
Aristotle's Categories, which have been claimed during this century
(by Ryle?) to have been based on the Greek interrogative pronouns.
Regarding the similarities to conceptual dependency theory, it's
interesting that in *syntactic* dependency theory, in a phrase, it is
only the dependent member (adjunct, modifier, operator) that can be
interrogated vis a vis the independent (head, operand) member, not
vice versa.
Examples, with (Head (Adjunct)), and * for the bad cases:
(Verb (Object)) Q: Who does he like? A: Mary.
*Q: What he Mary? A: Likes her.
((Adj) Noun) Q: Which hat did she wear? A: The straw hat.
*Q: What straw did she wear? A: The hat.
((Adv) Adj) Q: How hot was it? A: Too hot.
*Q: Too what was it? A: Hot.
Etc. Typically the head is implied by the adjunct (e.g. to like Mary
is to like [someone], a straw hat is a hat, too hot is hot). That is,
adjuncts are rather like predicates. That is, they correspond to the
modes of being, the ways things can be.
There's not much new under the sun.
David Stampe, Linguistics, Univ. of Hawaii
uhccux!stampe@nosc.mil
------------------------------
Date: Sun, 21 Jun 87 19:24:42 +0300
From: NYSTERN%WEIZMANN.BITNET@wiscvm.wisc.edu
Subject: Re: Re: Taking AI models and applying them to biology...
I have two comments to say;
a) As far as I understand from the article, Otto Selz has DIED
in 1943 at Auschwits (If one takes into account what Auschwits was
that period it seems quite logical) thus he couldn't publish his work in
1943 ... If one remembers what were the types of people who died in
Auschwits (I.E Jews) and if one takes into account that they expelled from
The Universities and Research Institutions from about 1933 (Hitlers
election as Germany's prime minister) then the only logical concultion
is that He didn't publish his theory after 1933 (since he was banned)
1943-1933=10 years (woow , I made it ...) which means he published his
theory before Turing or Shannon published theirs ...
WWII was probably the main reason for the lack of knowledge about his work.
(Remember that the war was ended 2 years later and the world had enough on
his mind than to remember Selz's theory ...)
BTW The commentation above isn't based on facts since I know very little
about his life and death (I may be wrong and will found out that he died
As a top Nazy SS officer due to cancer ... but that possiblity seems
redundant to me)
b) As far as I know AI is based on Mathematics ans Biology.
Both of those Sciences and many of the disciplines adopted by AI
scientists were formed a long time ago even without being influenced by
AI/computers (in matter of fact up until now the fields of Biology
and Computers wasn't combined together when matters of theory comes
only as a tool (calculation programs and DNA decoding algorythms)
Well to sum up my point I feel that the computer-science field will
benefit more from the work of hopfield then any theoretical axiome ...
The scince world has become too specific while I believe that combining all
forces together instead of working in paralel on the same topic would be more
fruitful for the science world and for the world (With one objection that
one field should not impose his theory on the other let, 1000 flowers grow
together, but TOGETHER). There is a Master grad. in weizmann who has done
his thesis in the vision field in the Department of Applied Math, His
'problem' is that his thesis relates to many fields (physics,neuro biology)
and not only to Applied Math moreover He has proved emphirically and cited
Famous researchers in this field that Math is redundant in this specific field.
Ofcourse no one like his thesis in the Math Department ... As far as I know
He will have his Master (got above 80 in the oral test) BUT how much will he
get about hsi work ? no one knows. His work is great but it doesn't fit into
the cateogries of our formal science. There's no (yet) a field named
Applied neuro-math or Applied psycho-physics or even Applied neuro-physics.
I've brought this story up to show 1) The situation in the science world
nowadays 2) to emphesize the trends of science as I see them 3) to back
up the notion that Applied Math and AI would benifit alot by examening works
of other science fields.
I believe that that's all.
------------------------------
Date: 21 Jun 87 19:42:03 GMT
From: sunybcs!rapaport@ames.arpa (William J. Rapaport)
Subject: Re: Computer composition of music
In article <2198@mmintl.UUCP> johnt@mmintl.UUCP (John Tangney) writes:
>Some of the researchers I read about (like Max
>Mathews, Lejaren Hiller, Iannis Xenakis, Stephen Smoliar to name
>a few off the top of my head) must still be out there.
Lejaren Hiller is Prof. of Music at SUNY Buffalo and an adjunct prof. in
our CS dept. His email address is muslah@buffalo.csnet
------------------------------
End of AIList Digest
********************
∂30-Jun-87 0132 LAWS@Stripe.SRI.Com AIList Digest V5 #160
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 Jun 87 01:31:53 PDT
Date: Mon 29 Jun 1987 22:17-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #160
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 30 Jun 1987 Volume 5 : Issue 160
Today's Topics:
Queries - Plausible Reasoning &
Natural Language - Predicate Calculus - Theorem Proving &
Automatic Programming Bibliographies &
Frame Matching and Chaining,
Psychology - Why Did The $6,000,000 Man Run So Slowly?
----------------------------------------------------------------------
Date: Tue, 23 Jun 87 20:57:05 SST
From: Jenny <ISCLIMEL%NUSVM.BITNET@wiscvm.wisc.edu>
Subject: so what about plausible reasoning ?
As I read articles on plausible reasoning in expert systems, I come to the
conclusion that experts themselves do not exactly work with numbers as they
solve problems. And many of them are not willing to commit themselves into
specifying a figure to signify their belief in a rule. The deductive process
that occurs in their brain can never be replicated by any known plausible
reasoning models. The expert system technology is already a weak one per se,
why introduce further complexity and more bottleneck in the acquisition of
knowledge, knowing fully well that the numbers are probably inconsistent ?
If one obtains two conclusions with numbers indicating some significance,
say 75 % and 80 %, can one say that the conclusion with 80% significance is
the correct conclusion and ignore the other one ? These numbers do not seem
to mean much since they are just beliefs or probabilties.
Lim Eng-Lian
National University of Singapore
-- this opinion is my own and is not influenced by the color of my office
------------------------------
Date: Wed, 24 Jun 87 16:37:04 SET
From: "Adlassnig, Peter" <ADLASSNI%AWIIMC11.BITNET@wiscvm.wisc.edu>
Subject: natural language - predicate calculus - theorem proving
concerning my ph.d. thesis i would like to know who has dealt
already with the following themes:
1) translation of indefinite pronomina into predicat calculus.
parsing only simple english sentences (subj pred obj), with
reference to the distribution and interpretation of wh-words
and quantifiers. ( a lexicon should be minimized to the syntax
and not include semantik ambiguities-rules.)
2) representation of quantifiers in frames.
3) automated theorem prover algorith, which is easy to implement
for first-order predicat-logic.
are logic grammars the right field for 1)?
the aim of the whole system is to implement an expertsystem in logo,
to demonstrate in schools, that computers can "think".
i would be thankful for any help|
which literature would you advice to read?
ruth gruenberger
Please send response to adlassni%awiimc11.bitnet
Thank you Peter Adlassnig
------------------------------
Date: 29 Jun 87 19:36:07 GMT
From: pratt@vanhalen.rutgers.edu (Lorien Y. Pratt)
Subject: Request for automatic programming bibliographies
Has anyone recently put together a bibliography of work in automatic
program generation? I'd appreciate any pointers that you can give me.
--Lorien Pratt
------------------------------
Date: 23 Jun 87 21:13:20 GMT
From: ihnp4!drutx!mcp@ucbvax.Berkeley.EDU (Mike Paugh)
Subject: Need info on frame matching and chaining
I am looking for good reference material on building expert
systems using frames in Lisp. The environment will be GCLISP.
What I need is a good basic understanding of how to chain
through the frames and do the pattern matching.
I am new to this, so any good pointers will be appreciated.
Mike Paugh
AT&T IS Labs Denver
ihnp4!drutx!mcp
------------------------------
Date: 29 Jun 87 12:34:12 GMT
From: ihnp4!homxb!mtuxo!mtune!akgua!cpsc53!dwb@ucbvax.Berkeley.EDU
(Summer Hire)
Subject: Re: Need info on frame matching and chaining
>
> I am looking for good reference material on building expert
> systems using frames in Lisp. The environment will be GCLISP.
> What I need is a good basic understanding of how to chain
> through the frames and do the pattern matching.
>
> I am new to this, so any good pointers will be appreciated.
>
>
> Mike Paugh
> AT&T IS Labs Denver
> ihnp4!drutx!mcp
Hi, I am a summer hire from AT&T, and just finished a two term course on
conceptual dependencies (Frame-style inference netting) and pattern matching.
We conducted six member projects on the building of MARGIE. This Margie took
an english story and converted it into "Frames" where then it was pattern
matched against set scripts (senerios or events). From this matching the
system could then construct an infered sequence of actions form the given.
It took about six months to develop. The book we used as an outline, which
gave us a firm grasp on the basics of the entire system, was Roger Shanks
book named "INSIDE COMPUTER UNDERSTANDING." It gave us a great lead. We
did vary to a certain extent in actual development, but the basics are still
there.
I would be glad to aid you in any way for those further developments,
because they provided a more natural way of demonstrating working cognitive
structures. (In theory of course.) I must say that the book is a must
to get you going. Another great lead in this search would be to
contact George Stockman, Prof. at Michigan State University. He was the
developer of our course project and is a biggie on frame representation of
knowledge and expert systems. (He taught me every thing I know). Please
contact me if you need any assistance at all.
Dave Bigelow (summer hire and damn well worth it!)
------------------------------
Date: 20 Jun 87 15:44:33 GMT
From: mit-amt!mob@mit-amt.media.mit.edu (Mario O. Bourgoin)
Reply-to: mit-amt!mob@media-lab.media.mit.edu (Mario O. Bourgoin)
Subject: Re: Why Did The $6,000,000 Man Run So Slowly?
Because it made the special effects scenes last longer.
------------------------------
Date: Mon 22 Jun 87 10:12:25-CDT
From: Art Flatau <CMP.FLATAU@R20.UTEXAS.EDU>
Subject: Re: why did the $6,000,000 man run so slowly?
I think people have missed the obvious reason that the $6 Meg man ran so
slowly. To stretch the plots out to fill an hour time slot.
Art
------------------------------
Date: Mon, 22 Jun 87 09:47:32 PDT
From: lambert%cod@nosc.mil
Subject: Why did $6M man run so slowly?
Re: Why did $6M man run so slowly?
Why would a producer use slow motion to depict very fast movement? I suggest
the following reasons be added to the list:
1. ACHIEVE THE TECHNICAL EFFECT. The slow motion points out to the viewer the
fact that the flow of time is different. The context around the slow-motion
scene makes the magnitude and direction of this change obvious. This is all
the viewer really needs to sense the effect that the $6M man is moving much
faster than normal.
2. TAKE ADVANTAGE OF THE VIEWER'S IMAGINATION. The slow motion gives the
viewer's mind time to realize that fast motion is being represented, and to
appreciate the non-triviality of it (unlike a realtime presentation which
would tend to make it seem easy). It allows the viewer's imagination to be
creative, to draw on previous experience, and to construct the concepts and
images necessary to represent something so complex and
magnificently-engineered happening so fast. This increases the impact on the
viewer by enhancing appreciation of the $6M man's feats. Indeed, it can give
the viewer an experience far beyond what the producer can actually achieve on
the screen.
3. TAKE ADVANTAGE OF THE VIEWER'S INTEREST IN LEARNING ABOUT HIMSELF. The
viewer is treated to a slow-motion presentation of human qualities difficult
or impossible to observe at normal or faster speeds. This allows him to learn
new things about the actor, himself, and other humans.
4. ACHIEVE ARTISTIC EFFECT. The producer also achieves beautiful artistic
effect by allowing viewing of the visible signs of forces and motion,
observation of facial expressions, and contemplation of the beauty of the $6M
man's athletic qualities such as speed, power, grace, and coordination.
lambert@cod.nosc.mil (David R. Lambert)
------------------------------
Date: Mon, 22 Jun 87 16:38:32 PDT
From: "William J. Fulco" <lcc.bill@CS.UCLA.EDU>
Subject: Slow-motion / $6E6 man
amsler@flash.bellcore.com:
> ....
> I suspect what is happening is that this is analogous to the focusing
> of attention on the events which happened in a real moving image
> memory. That is, if one attempts to reconstruct an event that
> happened very quickly in real time after the fact, one will
> artificially create something like slow motion.
This "slo-motion" effect of perception also appears to work in real-time.
A good everyday example of this is (for people that play sports)
a pass or "drive" in basketball, a volly in tennis or hitting a baseball.
Professional baseball players talk about learning to see the ball they are
trying to hit. They say that they actuall see the ball - an object the size
of an orange, traveling at 90+ mph from 66 feet away.
I used to think that this wasn't really what was happening, but I have
been involved in basketball games where, for less than 1 second,
(real-time) I have had an open lane to the basket, or an oportunity to
make a pass. The perceived time was far slower, on the order of several
seconds.
During these perceived seconds, I had time to "think" about my options -
actually make verbal & image (mind's eye) judgments about what to do or
not to do, commit and make or skip the play.
One case of this that really stands out: playing basketball several weeks
ago I was left wide open for drive to the basket. I remember that
I couldn't beleive I was left this wide open and I started to think
"what's the catch". I then remember thinking that "I don't have time to
be thinking about thinking about what I should be doing - I should just go",
and with this I drove down the key (-: missed the shot :-).
The point is, I had time to "argue" with myself, "verbally", in my mind
before I took action, but in real-time no more that a second passed.
The first time you notice this effect it is truly erie.
(bill)
[Yup. It happened to me once, in 1962, as I was jumping out of a
swing into a sandlot. I had done this (at full speed from maximum
height) hundreds of times, and did so again afterwards, but only
this once did time slow to about 1/4 speed. I wonder if a similar
effect might be a part of the "born again" religious conversion
that is sometimes hits people during routine activities. -- KIL]
------------------------------
Date: 27 Jun 87 13:41:23 GMT
From: winfree!uucp@seismo.CSS.GOV (Unix Chit-Chat at
winfree.n3eua.cos.ampr.n3eua.cos.ampr)
Subject: Submission for comp-ai-digest
Path: winfree!hp-lsd!hpldola!ben
From: ben@hpldola.HP.COM (Benjamin Ellsworth)
Newsgroups: comp.ai.digest
Subject: Re: Why Did The $6,000,000 Man Run So Slowly?
Message-ID: <13330001@hpldola.HP.COM>
Date: 26 Jun 87 20:42:14 GMT
References: <870615144826.2.NICHAEL@BUBBAROMDOS.PALLADIAN.COM>
Organization: HP Logic Design Oper. -ColoSpgs
Lines: 15
From my film classes at school, I had gathered that the reason that the
action sequences in Kung Fu were slowed down for emphasis. When you
slow a scene down, whatever the content, you emphasize the action of
that scene. This is especially effective for violent action. Any good
anti-hunting film will slow down any shots of an actual Bambi kill.
The effect of slowing is to force the viewer to perceive the action in
more detail (and hence with greater emphasis) than he/she could view it
at normal speed. Speeding up a scene has the opposite effect.
Benjamin Ellsworth
hplabs!hpldola!ben
*** This posting is about the use of temporal distortion in film
making, not a statement regarding the morality of hunting.
------------------------------
Date: 24 Jun 87 21:34:36 GMT
From: ihnp4!chinet!nucsrl!coray@ucbvax.Berkeley.EDU (Elizabeth)
Subject: Re: Why did the six-million dollar man run so slowly?
/ nucsrl:comp.ai / tim@linc.cis.upenn.edu (Tim Finin) / 11:47 pm Jun 11, 1987 /
Why did the six million dollar man run so slowly?
The guy moves slowly in the same way that a car accident happens "slowly".
Slow motion simulates the increase in attention to detail and reaction
times which go with an increase in adrenaline. This makes slow motion,
oddly enough, exciting.
The thing with the cougar is right on because the pedator in the hunt
is just the sort of thing for which adrenaline evolved.
M. E. Corey
------------------------------
End of AIList Digest
********************
∂30-Jun-87 0345 LAWS@Stripe.SRI.Com AIList Digest V5 #161
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 Jun 87 03:44:45 PDT
Date: Mon 29 Jun 1987 22:26-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #161
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 30 Jun 1987 Volume 5 : Issue 161
Today's Topics:
Query - Mega-Monitor,
Robotics - Vectrobot Recommendation,
AI Tools - Object-Oriented Languages & CLP(R) Announcement
----------------------------------------------------------------------
Date: 26 Jun 87 15:50:15 GMT
From: stride!tahoe!unsvax!jimi!asci!brian@gr.utah.edu (Brian Douglass)
Subject: Mega-Monitor
I've been asked by a friend to research information about a super-size
monitor. Essentially, what I am looking for is a color monitor that is 10
feet by 10 feet with a resolution of say 13,000 by 13,000--don't ask me what
for because I don't know what for, I'm just the gumshoe--and any necessary
equipment to drive it. (can you imagine what kind of equipment is necessary
to drive 169 million pixels!) Basically, my friend needs to generate some very
large images with extremely fine details. Color is preferable, but not
absolute. Money is not really a concern at this moment, so lets hear anything
you got. Also, if it means building it custom, that is what my friend wants
to know. So IBM, RCA, Tektronik, HP, etc, if you're listening and have any
experience in a monitor this large I would like to hear from you, as well as
if you have any "off-the-top-of-you-head" price estimates send those along. I
fully expect to hear in the millions, but that's okay. Right now, my friend
needs to know if anybody has done this, or if anybody can do this.
I know that there are also some analog systems out and about of this type of
magnitude. Although not preferable, I would like to hear about them as well.
Please E-mail only your responses to me as I am gone periodically on business
and we keep only a days worth of news on our system for a myriad of reasons.
However, I will summarize periodically to comp.graphics the responses I do
receive, as I am sure there are others who are as fascinated as I with the
leviathan proportions of this Mega-Monitor.
Brian Douglass
Applied Systems Consultants, Inc. (ASCI)
P.O. Box 13301
Las Vegas, NV 89103
Office: (702) 733-6761
Home: (702) 871-8182
brian@asci.uucp
UUCP: {akgua,ihnp4,mirror,psivax,sdcrdcf}!otto!jimi!asci!brian
------------------------------
Date: 22 Jun 87 19:49:48 GMT
From: linus!alliant!sullivan@husc6.harvard.edu (Mike Sullivan)
Subject: Re: Search and Employ (Mobile robot)
If your work involves mobile robot navigation, or other research
in robotics requiring sturdy, reliable hardware, I recommend a small three
wheel drive, three wheel steer (synchronous drive) chassis called a
"Vectrobot". It is manufactured by a company in New Hampshire called
Real World Interface.
For info, or references call Grinnell or Curt at (603) 654-6334
#include <std/disclaimer.h>
______
/ \ \
Michael J Sullivan / \____\ Alliant
decvax!linus!alliant!sullivan / / \ ComputerSystemsCorporation
/____/_______\
------------------------------
Date: 21 Jun 87 11:42:01 GMT
From: munnari!koel.rmit.oz!rcopm@seismo.CSS.GOV (Paul Menon)
Subject: Re: Smalltalk-80 for Sun 3 ... (LONG)
In article <8706180728.AA10707@ucbvax.Berkeley.EDU>,
lcc.bill@CS.UCLA.EDU ("William J. Fulco") writes:
> I saw a really nice system, (I mean REALLY nice - with good color support)
> from Xerox PARC marketing spinoff at the 1986 AAAI show. It was running
> on a Sun 3/260 and it really sizzles.....
I can believe that, I was introduced to the 3/260 just recently. It would make
anything sprout wings.
The reason for my addition has a little to do with suns, Smalltalk, and
technology in general, so please bear with me. This is long.
I have just completed some sizable programs (well, to me they were), and
am in the "recovery stage", ie sizing up what I have done... was it all worth
while etc, etc. I have reached a few (frustrating) conclusions/opinions...
* If I leave these programs for a while, and then come back to change
them in the name of maintenance or further enhancement, I am not too
much better off than someone who has never seen the package before.
I don't mean that in the positive sense, nor would I have forgotten
the techniques I used; it is the dependence of data being spread
all over the program. It was written in Pascal. How many of you
decide to change a data structure halfway through a program, not
because of bad planning in the first place, but because a "new"
and more efficient technique requires extra "bits" embedded into
a data structure. Does "grep 'structtype' *.h *.p" ring a bell?
Not even then am I too sure if everything is covered, especially
if it belongs to an overall complex data structure with crosslinks.
No amount of documentation or cross-references will relieve the
manual task ahead. Good programming style can minimize this only to
a certain extent. C, Algol, Modula 2, perhaps even Ada suffers
from this.
* If I want to re-use techniques in another program, major surgery is
required. Some call this hacking. It's only ok if the same types are
being used by the new program. There is static binding available from
Ada, if you wish to learn such a complex language. But none of the
"standard languages" allow complete type independence. Lisp and
Prolog programs will suffer the same scalpel treatment as the others.
If you haven't already guessed where I am heading, object-oriented
programming languages will (in my opinion) relieve me of these woes. Ok says
I, which one do I use? There is the Grand-Daddy, Smalltalk-80; the pure one.
Then there are the nouveau hybrids C++, Objective-C and MacApp. Others come
in different Flavors, Loops or feathered Flamingos and Owls. Lisp and Prolog
do not satisfy my requirements because I cannot easily "build" on previous
applications experience.
I don't hold the generally dismal performance of Smalltalk aginst it.
Hardware is zooming ahead as witnessed on suns, and soon on the Mac II
(I hope). My questions to all who have not gone to sleep are...
Will Smalltalk mature from being the toy that it was? ie a full 32
bit machine with > 32000 objects etc.. Methinks this is the ideal language
to be using no matter how big or small the program. The objection to being
such an "open" system can be countered by their "change management tools", if
I may be permitted to steal the phrase.
Of the hybrids, Objective-C appears my favourite. Although I have never
used it, I delight in the similar Smalltalk syntax. It will be a good
stand-in until Smalltalk meets its hardware match. Could any user out there
please comment on Objective-C, including it's ease of use, availability,
portability (ie, which o/s's can it run on), and price?
My preference to Objective-C rather than C++ is that I "feel uncomfortable"
in the way the latter has been implemented. The extended syntax does not
"stand out", it either melds into the other hieroglphs, so I cannot pick the
wood from the trees or it further confuses my understanding of C. I wish I
had a video of me reading a C program.. I must have this perpetual frown.
Is it common? I would love to hear from C++ users, especially those who
have used C++ and Objective-C. Note that my primary preference to Objective-C
is its syntactical similarity to Smalltalk.
Why not MacApp as an interim? Why not indeed! It is another example of
brilliance on the part of Apple, and once I get over the confusion of records
and messages/methods, all should be swell. One hitch though. Apple had
deemed it necessary to inflict a licencing fee on anyone producing/marketing
software that uses MacApp, as well as restricting all such programs to
the Macintosh. I don't know whether this still holds. I have noted MacApp
being used on a 4.2 bsd system (refer to OOPSLA '86 procs pp 186 - 201). pity.
My main hope is Smalltalk. It is a pity that the ones that can really
benefit from such a system are usually the last to see it. Kids. It is
the big kids; ie those who have been ingrained or fed up with procedural
languages that get to use it. Does this make us shortsighted?
Or perhaps fatally dependent on the past?
This isn't a plug for trendy software. This is frustration with writing
applications from scratch that use (nearly) the same techniques time and
time again. I use the hardware of tomorrow, but give it the brains of
yesterday. I am supposed to build on experience; all I do is
re-invent the wheel.
If you have read the book ..
"Object Oriented Programming: An Evolutionary Approach"
Brad J. Cox.
Then a major part of my article echoes its theme. I could not have read
it at a more pertinent time.
Thankyou,
Paul Menon.
Dept of Communication & Electronic Engineering,
Royal Melbourne Institute of Technology,
124 Latrobe St, Melbourne, 3000, Australia
ACSnet: rcopm@koel UUCP: ...!seismo!munnari!koel.rmit.oz!rcopm
CSNET: rcopm@koel.rmit.oz ARPA: rcopm%koel.rmit.oz@seismo
BITNET: rcopm%koel.rmit.oz@CSNET-RELAY
PHONE: +61 3 660 2619.
------------------------------
Date: Fri, 26 Jun 87 15:18:25 est
From: munnari!moncsbruce.oz!clp@seismo.CSS.GOV (The CLP(R) Personae)
Subject: CLP(R) Distribution Announcement
(Can you please add the following announcement to the digest)
DISTRIBUTION NOTICE
___________________
We are pleased to announce the availability of our
interpreter for CLP(R), the new Constraint Logic Programming
language. This is being distributed in source code written
in C and it is compatible with most machines running UNIX,
eg. Vaxen, Pyramids and Suns. This is not intended to be a
commercial announcement and is targeted at educational or
research usage.
The distribution includes:
1. CLP(R) interpreter (source code);
2. Example CLP(R) programs;
3. Installation Manual and Programmer's Manual (hard
copies).
Further information can be found in the following papers:
1. J. Jaffar and J-L. Lassez, "Constraint Logic
Programming", Proc. 14th ACM-POPL, Munich, January
1987.
2. J. Jaffar and S. Michaylov, "Methodology and
Implementation of a CLP System", Proc. 4th ICLP,
Melbourne, May 1987.
3. N.C. Heintze, S. Michaylov and P.J. Stuckey, "CLP(R)
and Some Electrical Engineering Problems", Proc. 4th
ICLP, Melbourne, May 1987.
4. C. Lassez, K. McAloon and R. Yap, "Constraint Logic
Programming and Option Trading", IEEE Expert, Fall
Issue 1987, to appear.
If you would like a Site licence for educational or research
purposes, please send a request for more information to
either,
(a) Electronic Mail address:
ACSNET: clp@moncsbruce.oz
ARPANET,CSNET: clp@moncsbruce.oz.au
UUCP: seismo!munnari!moncsbruce.oz!clp
(b) Paper Mail address:
CLP(R) Distribution
Department of Computer Science
Monash University
Clayton
Victoria 3168
Australia
In order to cover distribution and media costs, a license
fee of $150 will apply.
------------------------------
End of AIList Digest
********************
∂30-Jun-87 0728 LAWS@Stripe.SRI.Com AIList Digest V5 #162
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 Jun 87 07:28:32 PDT
Date: Mon 29 Jun 1987 22:32-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #162
To: AIList@STRIPE.SRI.COM
AIList Digest Tuesday, 30 Jun 1987 Volume 5 : Issue 162
Today's Topics:
AI Tools - Kyoto Common Lisp
----------------------------------------------------------------------
Date: Mon 22 Jun 87 20:24:22-CDT
From: CL.BOYER@R20.UTEXAS.EDU
Subject: Kyoto Common Lisp
Kyoto Common Lisp (KCL) is a complete implementation of Common Lisp written
by T. Yuasa and M. Hagiya working under Professor R. Nakajima at the
Research Institute for Mathematical Sciences, Kyoto University. It runs on
many different machines and is highly portable. It executes very
efficiently and it is superbly documented. KCL is being made available at
no fee through the implementors' generosity. The complete sources are
included. One channel of distribution is via ftp on the Arpanet/Internet.
LICENSE REQUIRED!
IMPORTANT: Although there is no fee, KCL is not in the public domain. You
are authorized to obtain it only after signing and mailing in a license
agreement. Before you ftp KCL files you MUST fill out and send in the
license agreement included in this message. Otherwise, you are not
permitted to make copies of KCL.
COPYING KCL VIA INTERNET
KCL may be obtained from Internet source rascal.ics.utexas.edu [128.83.144.1],
a Sun-3 at the University of Texas at Austin. To obtain KCL, login as "ftp"
with password "guest". There are three tar files:
/pub/kcl.tar, 4.0 megabytes
/pub/kcl.tar.C, produced by compact from kcl.tar, 2.8 megabytes
/pub/kcl.tar.Z, produced by compress from kcl.tar, 1.2 megabytes
Any of the three files is sufficient to generate KCL. Please ftp the
compressed file if possible. Please use ftp at an odd hour if possible to
reduce traffic on a sometimes heavily loaded network. Be sure to use binary
mode with ftp. A current version of this message may be found as the file
/pub/kcl.broadcast.
MACHINES ON WHICH KCL RUNS
KCL runs on many machines. With the sources provided in the ftp file, KCL
may be executed on the following machines (and operating systems).
VAX/UNIX (4.2BSD)
SUN2 (OS2, 3) SUN3 (OS3)
SONY'S NEWS (4.2BSD)
ATT3B2 (System V)
Fujitu S3000 (System V)
Sumitomo's E15 (Uniplus System V)
Data General MV (DGUX)
Instructions for making the system are in the file doc/porting in the ftp
tar file.
KCL LICENSE FORM
To obtain the right to copy KCL, sign this license form and send it and a copy
to the Kyoto address at the end of the form. ONCE YOU HAVE MAILED THE SIGNED
LICENSE FORM, YOU MAY COPY KCL. YOU DO NOT HAVE TO WAIT FOR RECEIPT OF THE
SIGNED FORM.
--------------------------- cut here ----------------------------
!
LICENSE AGREEMENT
FOR
KYOTO COMMON LISP
The Special Interest Group in LISP (Taiichi Yuasa and Masami Hagiya) at the
Research Institute for Mathematical Sciences, Kyoto University (hereinafter
referred to as SIGLISP) grants to
USER NAME: _________________________________________
USER ADDRESS: ______________________________________
______________________________________
(hereinafter referred to as USER), a non-transferable and non-exclusive license
to copy and use Kyoto Common LISP (hereinafter referred to as KCL) under the
following terms and conditions and for the period of time identified in
Paragraph 6.
1. This license agreement grants to the USER the right to use KCL within their
own home or organization. The USER may make copies of KCL for use within their
own home or organization, but may not further distribute KCL except as provided
in paragraph 2.
2. SIGLISP intends that KCL be widely distributed and used, but in a
manner which preserves the quality and integrity of KCL. The USER may send
a copy of KCL to another home or organization only after either receiving
permission from SIGLISP or after seeing written evidence that the other
home or organization has signed this agreement and sent a hard copy of it
to SIGLISP. If the USER has made modifications to KCL and wants to
distribute that modified copy, the USER will first obtain permission from
SIGLISP by written or electronic communication. Any USER which has
received such a modified copy can pass it on as received, but must receive
further permission for further modifications. All modifications to copies
of KCL passed on to other homes or organizations shall be clearly and
conspicuously indicated in all such copies. Under no other circumstances
than provided in this paragraph shall a modified copy of KCL be represented
as KCL.
3. The USER will ensure that all their copies of KCL, whether modified or not,
carry as the first information item the following copyright notice:
(c) Copyright Taiichi Yuasa and Masami Hagiya, 1984. All rights reserved.
Copying of this file is authorized to users who have executed the true and
proper "License Agreement for Kyoto Common LISP" with SIGLISP.
4. Title to and ownership of KCL and its copies shall at all times remain
with SIGLISP and those admitted by SIGLISP as contributors to the
development of KCL. The USER will return to SIGLISP for further
distribution modifications to KCL, modifications being understood to mean
changes which increase the speed, reliability and existing functionality of
the software delivered to the USER. The USER may make for their own
ownership and use enhancements to KCL which add new functionality and
applications which employ KCL. Such modules may be returned to SIGLISP at
the option of the USER.
5. KCL IS LICENSED WITH NO WARRANTY OF ANY KIND. SIGLISP WILL NOT BE
RESPONSIBLE FOR THE CORRECTION OF ANY BUGS OR OTHER DEFICIENCIES. IN NO
EVENT SHALL SIGLISP BE LIABLE FOR ANY DAMAGES OF ANY KIND, INCLUDING
SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES, ARISING OUT OF OR IN CONNECTION
WITH THE USE OR PERFORMANCE OF KCL.
6. This license for KCL shall be effective from the date hereof and shall
remain in force until the USER discontinues use of KCL. In the event the USER
neglects or fails to perform or observe any obligations under this Agreement,
this Agreement and the License granted hereunder shall be immediately
terminated and the USER shall certify to SIGLISP in writing that all copies of
KCL in whatever form in its possession or under its control have been
destroyed.
7. Requests. KCL is provided by SIGLISP in a spirit of friendship and
cooperation. SIGLISP asks that people enjoying the use of KCL cooperate in
return to help further develop and distribute KCL. Specifically, SIGLISP
would like to know which machines KCL gets used on. A brief notice form is
appended to this agreement which the user is requested to send by email or
otherwise. Please send in further notifications at reasonable intervals if
you increase the number and type of machines on which KCL is loaded. You
may send these notices to another USER which is cooperating with SIGLISP
for this purpose.
USER
DATE: _________________________________________
BY: ___________________________________________
TITLE: ________________________________________
ADDRESS: ______________________________________
______________________________________
SIGLISP
DATE: _________________________________________
BY: ___________________________________________
Taiichi Yuasa Masami Hagiya
Special Interest Group in LISP
Research Institute for Mathematical Sciences
Kyoto University
Kyoto, 606, JAPAN
Telex: 05422020 RIMS J
JUNET: siglisp@kurims.kurims.kyoto-u.junet
CSNET: siglisp%kurims.kurims.kyoto-u.junet@utokyo-relay.csnet
USER has loaded KCL on the following machines since (date):
Model Number Production Name Number of Machines
!
END OF LICENSE FORM
--------------------------- cut here ------------------------
DOCUMENTATION
The principal documentation for KCL is, of course, the book "Common Lisp
The Language" by Guy L. Steele, Jr. with contributions by Scott E. Fahlman,
Richard P. Gabriel, David A. Moon, and Daniel L. Weinreb, Digital Press,
1984. Implementation-specific details of KCL (debugging, garbage
collection, data structure format, declarations, operating system
interface, installation) may be found in the 131 page "Kyoto Common Lisp
Report" by Taiichi Yuasa and Masami Hagiya, the authors of KCL. This
report is available from:
Teikoku Insatsu Inc.
Shochiku-cho,
Ryogae-cho-dori Takeya-machi Sagaru,
Naka-gyo-ku,
Kyoto, 604, Japan
tel: 075-231-4757
for 5,000 yen plus postage.
The KCL Report is produced by the text-formatter KROFF (Kyoto ROFF), which
is used locally within Kyoto University. Currently KROFF works only on
printers available in Japan. It is possible that an American
distributorship of this report will be arranged. The source of the report,
with KROFF commands, is found in the file doc/report on the ftp tar file.
It is possible to read this source, though it is as hard on the eyes as TeX
or Scribe source. A translation of this source into TeX is underway and
will be available as part of the distribution tape. Future information
about the availability of the KCL Report will be available in updated
versions of this message, in the file /pub/kcl.broadcast.
A document describing how to port KCL to other systems is available at no
charge from the authors of KCL.
Each of the KCL primitives is thoroughly described by the "describe"
function, which is based on 340K bytes of documentation.
SUPPORT
KCL is one of the most bug-free large software systems that we have ever used.
However, when bugs are found, they may be reported to the implementors:
hagiya%kurims.kurims.kyoto-u.junet%utokyo-relay.csnet@RELAY.CS.NET
yuasa%kurims.kurims.kyoto-u.junet%utokyo-relay.csnet@RELAY.CS.NET
We have found them extremely responsive to bug reports and suggestions.
SAMPLE TRANSCRIPT
Below is a complete transcript for obtaining and installing KCL on a Sun-3.
Make a directory for locating KCL
tutorial% mkdir /usr/joe/kcl
Get the compressed tar file
tutorial% cd /usr/joe/kcl
tutorial% ftp 128.83.144.1
220 rascal FTP server (Version 4.7 Sun Sep 14 12:44:57 PDT 1986) ready.
Name: ftp
Password: guest
ftp>binary
ftp>get /pub/kcl.tar.Z kcl.tar.Z
ftp>quit
Build the KCL directory structure
tutorial% uncompress kcl.tar.Z
tutorial% tar -xvf kcl.tar .
tutorial% rm kcl.tar
Make KCL
tutorial% cd /usr/joe/kcl/
tutorial% su
password: super-user-password
tutorial# cp h/cmpinclude.h /usr/include
tutorial# exit
tutorial% make
Edit and Install Two Files
We wish to replace "~" by "/usr/joe" in lc and kcl, and put
them in a directory on the search path e.g. "/usr/joe/bin"
tutorial% cd /usr/joe/kcl/unixport
tutorial% mkdir /usr/joe/bin
tutorial% sed -e "s.~./usr/joe/kcl.g" lc > /usr/joe/bin/lc
tutorial% sed -e "s.~./usr/joe/kcl.g" kcl > /usr/joe/bin/kcl
tutorial% chmod a+x /usr/joe/bin/lc /usr/joe/bin/kcl
It is now possible to run kcl:
tutorial% /usr/joe/bin/kcl
KCL (Kyoto Common Lisp)
>(+ 2 3)
5
>(bye)
It is best to become super user and execute the following commands, so that all
users may execute kcl.
tutorial% su
Password: superuser-password
tutorial# cp /usr/joe/bin/kcl /usr/local/bin
tutorial# cp /usr/joe/bin/lc /usr/local/bin
tutorial# exit
This transcript puts the entire kcl system, including sources and
documentation, in the directory /usr/joe/kcl. Any other directory name
would do as well, e.g., /usr/local instead of /usr/joe. Although this
transcript has worked perfectly for us on a Sun-3, it might not work for
you if you are running under NFS but not logged into the right machine:
you may need to login as root on the system where /usr/include and
/usr/local/bin are really located to do the super-user things. Immediately
after the make is finished about 8.4 megatyes of disk space are in use.
SINCERELY YOURS
Robert S. Boyer William F. Schelter
cl.boyer@r20.utexas.edu atp.schelter@r20.utexas.edu
This message was written by Robert S. Boyer and William F. Schelter. The
opinions expressed are theirs and are not necessarily those of the authors of
KCL, the University of Texas, or MCC. The authors of KCL have, however,
indicated that they have no objection to our distributing this message.
P.S. Thanks to Dave Capshaw, George Fann, Warren Hunt, Ken Rimey, and Carl
Quillen for helping debug this message. Ken Rimey,
rimey@ernie.Berkeley.EDU, makes the following remarks about bringing up
this release of KCL under BSD 4.3 on a Vax.
1. Bringing up KCL under BSD4.3. The machine on which I installed kcl was
a Vax 88xx running Ultrix V2.0. Kcl crashed when executing the final
save-system command in init_kcl.lsp. It also did so on a Vax running
BSD4.3. (I don't know of any Vaxen still running 4.2.) The problem is
caused by some highly non-portable code introduced into Lsave() in
c/unixsave.c since the version of March 28, 1986. I deleted the new code
and reintroduced the old which had been commented out. Here is the
resulting working Lsave():
Lsave()
{
char filename[256];
check_arg(1);
check_type_or_pathname_string_symbol_stream(&vs_base[0]);
coerce_to_filename(vs_base[0], filename);
_cleanup();
memory_save(kcl_self, filename);
exit(0);
/* no return */
}
KCL ran successfully after only fixing the Lsave problem.
2. The files o/makefile and unixport/makefile define variables that need to be
changed when compiling for any machine other than a Sun-3. These definitions
are found at the heads of these files. Here is the head of my copy of
o/makefile:
MACHINE = VAX
# Select 'VAX', 'SUN', 'SUN2R3', 'SUN3', 'ISI', 'SEQ', 'IBMRT',
# or 'NEWS'.
CHTAB = char_table.s
# Select 'char_table.s' or 'sun_chtab.s'.
# 1) char_table.s : for VAX, SEQ and NEWS
# 2) sun_chtab.s : for SUN, SUN2R3 and SUN3
# 3) isi_chtab.s : for ISI
# 4) ibmrt_chtab.s: for IBMRT
For machines other than Sun-3, one might change the MAKE KCL
section of this message to:
tutorial% cd /usr/joe/kcl/
tutorial% vi o/makefile (If not Sun-3, change definitions MACHINE and CHTAB.)
tutorial% vi o/unixport (If not Sun-3, change definition of MACHINE.)
tutorial% su
password: super-user-password
tutorial# cp h/cmpinclude.h /usr/include
tutorial# exit
tutorial% make
------------------------------
End of AIList Digest
********************
∂01-Jul-87 0429 LAWS@Stripe.SRI.Com AIList Digest V5 #164
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 1 Jul 87 04:29:26 PDT
Date: Tue 30 Jun 1987 23:07-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #164
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 1 Jul 1987 Volume 5 : Issue 164
Today's Topics:
Theory - The Symbol Grounding Problem
----------------------------------------------------------------------
Date: 30 Jun 87 00:19:12 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
marty1@houdi.UUCP (M.BRILLIANT) of AT&T Bell Laboratories, Holmdel asks:
> how about walking through what a machine might do in perceiving a chair?
> ...let a machine train its camera on that object. Now either it
> has a mechanical array of receptors and processors, like the layers
> of cells in a retina, or it does a functionally equivalent thing with
> sequential processing. What it has to do is compare the brightness of
> neighboring points to find places where there is contrast, find
> contrast in contiguous places so as to form an outline, and find
> closed outlines to form objects... Now the machine has the outline
> of an object in 2 dimensions, and maybe some clues to the 3rd
> dimension... inductively find a 3D form that would give rise to the
> 2D view the machine just saw... Then, if the object is really
> unfamiliar, let the machine walk around the chair, or pick it
> up and turn it around, to refine its hypothesis.
So far, apart from its understandable toward current engineering hardware
concepts, there is no particular objection to this description of a
stereoptic sensory receptor.
> Now the machine has a form. If the form is still unfamiliar,
> let it ask, "What's that, Daddy?" Daddy says, "That's a chair."
> The machine files that information away. Next time it sees a
> similar form it says "Chair, Daddy, chair!" It still has to
> learn about upholstered chairs, but give it time.
Now you've lost me completely. Having acknowledged the intricacies of
sensory transduction, you seem to think that the problem of categorization
is just a matter of filing information away and finding "similar forms."
> do you really want this machine to be so Totally Turing that it
> grows like a human, learns like a human, and not only learns new
> objects, but, like a human born at age zero, learns how to perceive
> objects? How much of its abilities do you want to have wired in,
> and how much learned?
That's an empirical question. All it needs to do is pass the Total
turing Test -- i.e., exhibit performance capacities that are
indistinguishable from ours. If you can do it by building everything
in a priori, go ahead. I'm betting it'll need to learn -- or be able to
learn -- a lot.
> But back to the main question. I have skipped over a lot of
> detail, but I think the outline can in principle be filled in
> with technologies we can imagine even if we do not have them.
> How much agreement do we have with this scenario? What are
> the points of disagreement?
I think the main details are missing, such as how the successful
categorization is accomplished. Your account also sounds as if it
expects innate feature detectors to pick out objects for free, more or
less nonproblematically, and then serve as a front end for another
device (possibly a conventional symbol-cruncher a la standard AI?)
that will then do the cognitive heavy work. I think that the cognitive
heavy work begins with picking out objects, i.e., with categorization.
I think this is done nonsymbolically, on the sensory traces, and that it
involves learning and pattern recognition -- both sophisticated
cognitive activities. I also do not think this work ends, to be taken
over by another kind of work: symbolic processing. I think that ALL of
cognition can be seen as categorization. It begins nonsymbolically,
with sensory features used to sort objects according to their names on
the basis of category learning; then further sorting proceeds by symbolic
descriptions, based on combinations of those atomic names. This hybrid
nonsymbolic/symbolic categorizer is what we are; not a pair of modules,
one that picks out objects and the other that thinks and talks about them.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 30 Jun 87 20:52:21 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem
In reply to my statement that
>> the *semantic* meaning of a symbol is still left largely unconstrained
>> even after you take account of it's "grounding" in perceptual
>> categorization. This is because what matters for intentional content
>> is not the objective property in the world that's being detected, but
>> rather how the subject *conceives* of that external property, a far
>> more slippery notion...
Stevan Harnad (harnad@mind.UUCP) writes:
>
> As to what people "conceive" themselves to be categorizing: My model
> is proposed in a framework of methodological epiphenomenalism. I'm
> interested in what's going on in people's heads only inasmuch as it is
> REALLY generating their performance, not just because they think or
> feel it is.
I regret the subjectivistic tone of my loose characterization; what people
can introspect is indeed not at issue. I was merely pointing out that the
*meaning* of a symbol is crucially dependent on the rest of the cognitive
system, as shown in the Churchland's example:
>> ... primitive people may be able to reliably
>> categorize certain large-scale atmospheric electrical discharges;
>> nevertheless, the semantic content of their corresponding states might
>> be "Angry gods nearby" or some such.
>>
> ... "Angry gods nearby" is not just an atomic label for
> "thunder" (otherwise it WOULD be equivalent to it in my model -- both
> labels would pick out approximately the same thing); in fact, it is
> decomposable, and hence has a different meaning in virtue of the
> meanings of "angry" and "gods." There should be corresponding internal
> representational differences (iconic, categorical and symbolic) that
> capture that difference.
"Angry gods nearby" is composite in *English*, but it need not be composite
in native, or, more to the point, in the supposed inner language of the
native's categorical mechanisms. They may have a single word, say "gog",
which we would want to translate as "god-noise" or some such. Perhaps they
train their children to detect gog in precisely the same way we train
children to detect thunder -- our internal thunder-detectors are identical.
Nevertheless, the output of their thunder-detector does not *mean* "thunder".
Let me try to clarify the point of these considerations. I am all for an
inquiry into the mechanisms underlying our categorization ablities. Anything
you can discover out about these mechanisms would certainly be a major
contribution to psychology. My only concern is with semantics: I was piqued
by what seemed to be an ambitious claim about the significance of the
psychology of categorization for the problem of "intentionality" or intrinsic
meaningfulness. I merely want to emphasize that the former, interesting
though it is, hardly makes a dent in the latter.
As I said, there are two reasons why meaning resists explication by this kind
of psychology: (1) holism: the meaning of even a "grounded" symbol will
still depend on the rest of the cognitive system; and (2) normativity:
meaning is dependent upon a determination of what is a *correct* response,
and you can't simply read such a norm off from a description of how the
mechanism in fact performs.
I think these points, particularly (1), should be quite clear. The fact that
a subject's brain reliably asserts the symbol "foo" when and only when
thunder is presented in no way "fixes" the meaning of "foo". Of course it is
obviously a *constraint* on what "foo" may mean: it is in fact part of what
Quine called the "stimulus meaning" of "foo", his first constraint on
acceptable translation. Nevertheless, by itself it is still way too weak to
do the whole job, for in different contexts the postive output of a reliable
thunder-detector could mean "thunder", something co-extensive but
non-synonymous with "thunder", "god-noise", or just about anything else.
Indeed, it might not *mean* anything at all, if it were only part of a
mechanical thunder-detector which couldn't do anything else.
I wonder if you disagree with this?
As to normativity, the force of problem (2) is particularly acute when
talking about the supposed intentionality of animals, since there aren't any
obvious linguistic or intellectual norms that they are trying to adhere to.
Although the mechanics of a frog's prey-detector may be crystal clear, I am
convinced that we could easily get into an endless debate about what, if
anything, the output of this detector really *means*.
The normativity problem is germane in an interesting way to the problem of
human meanings as well. Note, for example, that in doing this sort of
psychology, we probably won't care about the difference between correctly
identifying a duck and mis-identifying a good decoy -- we're interested in
the perceptual mechanisms that are the same in both cases. In effect, we are
limiting our notion of "categorization" to something like "quick and largely
automatic classification by observation alone".
We pretty much *have* to restrict ourselves in this way, because, in the
general case, there's just no limit to the amount of cognitive activity that
might be required in order to positively classify something. Consider what
might go into deciding whether a dolphin ought to be classified as a fish,
whether a fetus ought to be classified as a person, etc. These decisions
potentially call for the full range of science and philosophy, and a
psychology which tries to encompass such decisions has just bitten off more
than it can chew: it would have to provide a comprehensive theory of
rationality, and such an ambitious theory has eluded philosophers for some
time now.
In short, we have to ignore some normative distinctions if we are to
circumscribe the area of inquiry to a theoretically tractable domain of
cognitive activity. (Indeed, in spite of some of your claims, we seem
committed to the notion that we are limiting ourselves to particular
*modules* as explained in Fodor's modularity book.) Unfortunately -- and
here's the rub -- these normative distinctions *are* significant for the
*meaning* of symbols. ("Duck" doesn't *mean* the same thing as "decoy").
It seems that, ultimately, the notion of *meaning* is intimately tied to
standards of rationality that cannot easily be reduced to simple features of
a cognitive mechanism. And this seems to be a deep reason why a descriptive
psychology of categorization barely touches the problem of intentionality.
Anders Weinstein
BBN Labs
------------------------------
Date: 30 Jun 87 19:02:28 GMT
From: teknowledge-vaxc!dgordon@beaver.cs.washington.edu (Dan Gordon)
Subject: Re: The symbol grounding problem: Against Rosch &
Wittgenstein
In article <931@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>(And I must repeat: Whether or not we can introspectvely report the features
>we are actually using is irrelevant. As long as reliable, consensual,
>all-or-none categorization performance is going on, there must be a set of
>underlying features governing it -- both with sensory and more
Is this so? There is no reliable, consensual all-or-none categorization
performance without a set of underlying features? That sounds like a
restatement of the categorization theorist's credo rather than a thing
that is so.
Dan Gordon
------------------------------
Date: 30 Jun 87 20:49:32 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <937@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> ...
> marty1@houdi.UUCP (M.BRILLIANT) of AT&T Bell Laboratories, Holmdel asks:
> > how about walking through what a machine might do in perceiving a chair?
> > ... (a few steps skipped here)
> > Now the machine has a form. If the form is still unfamiliar,
> > let it ask, "What's that, Daddy?" Daddy says, "That's a chair."
> > The machine files that information away. Next time it sees a
> > similar form it says "Chair, Daddy, chair!" ...
>
> Now you've lost me completely. Having acknowledged the intricacies of
> sensory transduction, you seem to think that the problem of categorization
> is just a matter of filing information away and finding "similar forms."
I think it is. We've found a set of lines, described in 3 dimensions,
that can be rotated to match the outline we derived from the view of a
real chair. We file it in association with the name "chair." A
"similar form" is some other outline that can be matched (to within
some fraction of its size) by rotating the same 3D description.
> I think the main details are missing, such as how the successful
> categorization is accomplished......
Are we having a problem with the word "categorization"? Is it the
process of picking discrete objects out of a pattern of light and
shade ("that's a thing"), or the process of naming the object ("that
thing is a chair")?
> ..... Your account also sounds as if it
> expects innate feature detectors to pick out objects for free, more or
> less nonproblematically.....
You left out the part where I referred to computer-aided-design
modules. I think we can find outlines by looking for contiguous
contrasts. If the outlines are straight we (the machine, maybe also
humans) can define the ends of the straight lines in the visual plane,
and hypothesize corresponding lines in space. If hard-coding this
capability gives an "innate feature detector" then that's what I want.
> ...... and then serve as a front end for another
> device (possibly a conventional symbol-cruncher a la standard AI?)
> that will then do the cognitive heavy work. I think that the cognitive
> heavy work begins with picking out objects, i.e., with categorization.
I think I find objects with no conscious knowledge of how I do it (is
that what you call "categorization")? Saying what kind of object it is
more often involves conscious symbol-processing (sometimes one forgets
the word and calls a perfectly familiar object "that thing").
> I think this is done nonsymbolically, on the sensory traces, and that it
> involves learning and pattern recognition -- both sophisticated
> cognitive activities.
If you're talking about finding objects in a field of light and shade, I
agree that it is done nonsymbolically, and everything else you just said.
> ..... I also do not think this work ends, to be taken
> over by another kind of work: symbolic processing.....
That's where I have trouble. Calling a penguin a bird seems to me
purely symbolic, just as calling a tomato a vegetable in one context,
and a fruit in another, is a symbolic process.
> ..... I think that ALL of
> cognition can be seen as categorization. It begins nonsymbolically,
> with sensory features used to sort objects according to their names on
> the basis of category learning; then further sorting proceeds by symbolic
> descriptions, based on combinations of those atomic names. This hybrid
> nonsymbolic/symbolic categorizer is what we are; not a pair of modules,
> one that picks out objects and the other that thinks and talks about them.
Now I don't understand what you said. If it begins nonsymbolically,
and proceeds symbolically, why can't it be done by linking a
nonsymbolic module to a symbolic module?
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 30 Jun 87 19:47:08 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <937@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> marty1@houdi.UUCP (M.BRILLIANT) of AT&T Bell Laboratories, Holmdel asks:
> ....
> > do you really want this machine to be so Totally Turing that it
> > grows like a human, learns like a human, and not only learns new
> > objects, but, like a human born at age zero, learns how to perceive
> > objects? How much of its abilities do you want to have wired in,
> > and how much learned?
>
> That's an empirical question. All it needs to do is pass the Total
> turing Test -- i.e., exhibit performance capacities that are
> indistinguishable from ours. If you can do it by building everything
> in a priori, go ahead. I'm betting it'll need to learn -- or be able to
> learn -- a lot.
To refine the question: how long do you imagine the Total Turing Test
will last? Science fiction stories have robots or aliens living in
human society as humans for periods of years, as long as they live with
strangers, but failing after a few hours trying to supplant a human and
fool his or her spouse.
By "performance capabilities," do you mean the capability to adapt as a
human does to the experiences of a lifetime? Or only enough learning
capability to pass a job interview?
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
End of AIList Digest
********************
∂01-Jul-87 1027 LAWS@Stripe.SRI.Com AIList Digest V5 #163
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 1 Jul 87 10:27:35 PDT
Date: Tue 30 Jun 1987 23:02-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #163
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 1 Jul 1987 Volume 5 : Issue 163
Today's Topics:
Theory - The Symbol Grounding Problem & Graded Categories
----------------------------------------------------------------------
Date: 28 Jun 87 23:56:43 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: The symbol grounding problem....
In article <919@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> marty1@houdi.UUCP (M.BRILLIANT) of AT&T Bell Laboratories, Holmdel writes:
> ......
> > .... The feature extractor obviates the symbol-grounding
> > problem.
>
> ..... You are vastly underestimating the problem of
> sensory categorization, sensory learning, and the relation between
> lower and higher-order categories. Nor is it obvious that symbol manipulation
> can still be regarded as just symbol manipulation when the atomic symbols
> are constrained to be the labels of sensory categories....
I still think we're having more trouble with terminology than we
would have with the concepts if we understood each other. To
get a little more concrete, how walking through what a machine
might do in perceiving a chair?
I was just looking at a kitchen chair, a brown wooden kitchen
chair against a yellow wall, in side light from a window. Let's
let a machine train its camera on that object. Now either it
has a mechanical array of receptors and processors, like the
layers of cells in a retina, or it does a functionally
equivalent thing with sequential processing. What it has to do
is compare the brightness of neighboring points to find places
where there is contrast, find contrast in contiguous places so
as to form an outline, and find closed outlines to form objects.
There are some subtleties needed to find partly hidden objects,
but I'll just assume they're solved. There may also be an
interpretation of shadow gradations to perceive roundness.
Now the machine has the outline of an object in 2 dimensions,
and maybe some clues to the 3rd dimension. There are CAD
programs that, given a complete description of an object in
3D, can draw any 2D view of it. How about reversing this
essentially deductive process to inductively find a 3D form that
would give rise to the 2D view the machine just saw. Let the
machine guess that most of the odd angles in the 2D view are
really right angles in 3D. Then, if the object is really
unfamiliar, let the machine walk around the chair, or pick it
up and turn it around, to refine its hypothesis.
Now the machine has a form. If the form is still unfamiliar,
let it ask, "What's that, Daddy?" Daddy says, "That's a chair."
The machine files that information away. Next time it sees a
similar form it says "Chair, Daddy, chair!" It still has to
learn about upholstered chairs, but give it time.
That brings me to a question: do you really want this machine
to be so Totally Turing that it grows like a human, learns like
a human, and not only learns new objects, but, like a human born
at age zero, learns how to perceive objects? How much of its
abilities do you want to have wired in, and how much learned?
But back to the main question. I have skipped over a lot of
detail, but I think the outline can in principle be filled in
with technologies we can imagine even if we do not have them.
How much agreement do we have with this scenario? What are
the points of disagreement?
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 29 Jun 87 08:49:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: invertibility as a graded category ?
Harnad writes:
> In responding to Cugini and Brilliant I misinterpreted a point that
> the former had made and the latter reiterated. It's a point that's
> come up before: What if the iconic representation -- the one that's
> supposed to be invertible -- fails to preserve some objective property
> of the sensory projection? ... The reply is that an analog
> representation is only analog in what it preserves, not in what it fails
> to preserve. Icons are hence approximate too. ...
> There is no requirement that all the features of the sensory
> projection be preserved in icons; just that some of them should be --
> enough to subserve our discrimination capacities.
> ... But none of this
> information loss in either sensory projections or icons (or, for that
> matter, categorical representations) compromises groundedness. It just
> means that our representations are doomed to be approximations.
But then why say that icons, but not categorical representations or symbols
are/must be invertible? (This was *your* original claim, after all)?
Isn't it just a vacuous tautology to claim that icons are invertible
wrt to the information they preserve, but not wrt the information they
lose? How could it be otherwise? Aren't even symbols likewise
invertible in that weak sense?
(BTW, I quite agree that the information loss does not compromise
grounding - indeed my very point was that there is nothing especially
scandalous about non-invertible icons.)
Look, there's information loss (many to one mapping) at each stage of the game:
1. distal object
2. sensory projection
3. icons
4. categorical representation
5. symbols
It was you who seemed to claim that there was some special invertibility
between stages 2 and 3 - but now you claim for it invertibility in
only such a vitiated sense as to apply to all the stages.
So a) do you still claim that the transition between 2 and 3 is invertible
in some strong sense which would not be true of, say, [1 to 2] or [3 to 4], and
b) if so, what is that sense?
Perhaps you just want to say that the transition between 2 and 3 is usually
more invertible than the other transitions ?
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: 29 Jun 87 10:35:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: epistemological exception-taking
> > From me:
> >
> > What if there were a few-to-one transformation between the skin-level
> > sensors ...
> > My example was to suppose that #1:
> > a combination of both red and green retinal receptors and #2 a yellow
> > receptor BOTH generated the same iconic yellow.
> From: Neil Hunt <spar!hunt@decwrl.dec.com>
>
> We humans see the world (to a first order at least) through red, green and
> blue receptors. We are thus unable to distinguish between light of a yellow
> frequency, and a mixture of light of red and green frequencies, and we assign
> to them a single token - yellow. However, if our visual apparatus was
> equipped with yellow receptors as well, then these two input stimuli
> would *appear* quite different, as indeed they are. ...
Oh, really? How do you claim to know what the mental effect would be
of a hypothetical visual nerve apparatus? Do you know what it feels
like to be a bat?
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: 29 Jun 87 20:53:28 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: The symbol grounding problem: Against Rosch &
Wittgenstein
In article <931@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> marty1@houdi.UUCP (M.BRILLIANT) of AT&T Bell Laboratories, Holmdel asks:
> > Why require 100% accuracy in all-or-none categorizing?... I learned
> > recently that I can't categorize chairs with 100% accuracy.
>
> This is a misunderstanding. The "100% accuracy" refers to the
> all-or-none-ness of the kinds of categories in question. The rival
> theories in the Roschian tradition have claimed that many categories
> (including "bird" and "chair") do not have "defining" features. Instead,
> membership is either fuzzy or a matter of degree (i.e., percent)....
OK: once I classify a thing as a chair, there are no two ways about it:
it's a chair. But there can be a stage when I can't decide. I
vacillate: "I think it's a chair." "Are you sure?" "No, I'm not sure,
maybe it's a bed." I would never say seriously that I'm 40 percent
sure it's a chair, 50 percent sure it's a bed, and 10% sure it's an
unfamiliar object I've never seen before.
I think this is in agreement with Harnad when he says:
> Categorization preformance (with all-or-none categories) is highly reliable
> (close to 100%) and MEMBERSHIP is 100%. Only speed/ease of categorization and
> typicality ratings are a matter of degree....
> This is not to deny that even all-or-none categorization may encounter
> regions of uncertainty. Since ALL category representations in my model are
> provisional and approximate ..... it is always possible that
> the categorizer will encounter an anomalous instance that he cannot classify
> according to his current representation.....
> ...... This still does not imply that membership is
> fuzzy or a matter of degree.....
So to pass the Total Turing Test, a machine should respond the way a
human does when faced with inadequate or paradoxical sensory data: it
should vacillate (or bluff, as some people do). In the presence of
uncertainty it will not make self-consistent statements about
uncertainty, but uncertain and possibly inconsistent statements about
absolute membership.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 29 Jun 87 23:34:58 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: The symbol grounding problem: "Fuzzy" categories?
In comp.ai.digest: Laws@STRIPE.SRI.COM (Ken Laws) asks re. "Fuzzy Symbolism":
> Is a mechanical rubber penguin a penguin?... dead...dismembered
> genetically damaged or altered...? When does a penguin embryo become
> a penguin?... I can't unambiguously define the class of penguins, so
> how can I be 100% certain that every penguin is a bird?... and even
> that could change if scientists someday discover incontrovertible
> evidence that penguins are really fish. In short, every category is a
> graded one except for those that we postulate to be exact as part of
> their defining characteristics.
I think you're raising the right questions, but favoring the wrong
answers. My response to this argument for graded or "fuzzy" category
was that our representations are provisional and approximate. They
converge on the features that will reliably sort members from
nonmembers on the basis of the sample of confusable alternatives
encountered to date. Being always provisional and approximate, they
are always susceptible to revision should the context of confusable
alternatives be widened.
But look at the (not so hidden) essentialism in Ken's query: "how can I
be 100% certain that every penguin is a bird?". I never promised that!
We're not talking about ontological essences here, about the way things
"really are," from the God's Eye" or omniscient point of view! We're
just talking about how organisms and other devices can sort and label
APPEARANCES as accurately as they do, given the feedback and
experiential sample they get. And this sorting and labeling is
provisional, based on approximate representations that pick out
features that reliably handle the confusable alternatives sampled to
date. All science can do is tighten the approximation by widening the
alternatives (experimentally) or strengthening the features
(theoretically).
But provisionally, we do alright, and it's NOT because we sort things
as being what they are as a matter of degree. A penguin is 100% a bird
(on current evidence) -- no more or less a bird than a sparrow. If
tomorrow we find instances that make it better to sort and label them
as fish, then tomorrow's approximation will be better than today's,
but they'll then be 100% fish, and so on.
Note that I'm not denying that there are graded categories; just that
these aren't them. Examples of graded categories are: big,
intelligent, beautiful, feminine, etc.
> You are entitled to such an opinion, of course, but I do not
> accept the position as proven...
(Why opinion, by the way, rather than hypothesis, on the evidence and
logical considerations available? Nor will this hypothesis be proven:
just supported by further evidence and analysis, or else supplanted by
a rival hypothesis that accounts for the evidence better; or the
hypothesis and its supporting arguments may be shown to be incoherent
or imparsimonious...)
> ...We do, of course, sort and categorize objects when forced to do so.
> At the point of observable behavior, then, some kind of noninvertible
> or symbolic categorization has taken place. Such behavior, however,
> is distinct from any of the internal representations that produce it.
> I can carry fuzzy and even conflicting representations until -- and
> often long after -- the behavior is initiated. Even at the instant of
> commitment, my representations need be unambiguous only in the
> implicit sense that one interpretation is momentarily stronger than
> the other -- if, indeed, the choice is not made at random.
I can't follow some of this. Categorization is the performance
capacity under discussion here. ("Force" has nothing to do with it!).
And however accurately and reliably people can actually categorize things,
THAT'S how accurately our models must be able to do it under the same
conditions. If there's successful all-or-none performance, the
representational model must be able to generate it. How can the
behavior be "distinct from" the representations that produce it?
This is not to say that representations will always be coherent, or
even that incoherent representations can't sometimes generate correct
categorization (up to a point). But I hardly think that the basis of
the bulk of our reliable all-or-none sorting and labeling will turn
out to be just a matter of momentary relative strengths -- or even
chance -- among graded representations. I think probabilistic mechanisms
are more likely to be involved in feature-finding in the training
phase (category learning) rather than in the steady state phase, when
a (provisional) performance asymptote has been reached.
> It may also be true that I do reduce some representations to a single
> neural firing or to some other unambiguous event -- e.g., when storing
> a memory. I find this unlikely as a general model. Coarse coding,
> graded or frequency encodings, and widespread activation seem better
> models of what's going on. Symbolic reasoning exists in pure form
> only on the printed page; our mental manipulation even of abstract
> symbols is carried out with fuzzy reasoning apparatus.
Some of this sounds like implementational considerations rather than
representational ones. The question was: Do all-or-none categories
(such as "bird") have "defining" features that can be used to sort
members from nonmembers at the level of accuracy (~100%) with which we
sort? However they are coded, I claim that those features MUST exist
in the inputs and must be detected and used by the categorizer. A
penguin is not a bird as a matter of degree, and the features that
reliably assign it to "bird" are not graded. Nor is "bird" a fuzzy
category such as "birdlike." And, yes, symbolic representations are
likely to be more apodictic (i.e., categorical) than nonsymbolic ones.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
End of AIList Digest
********************
∂02-Jul-87 0508 LAWS@Stripe.SRI.Com AIList Digest V5 #165
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 2 Jul 87 05:07:59 PDT
Date: Wed 1 Jul 1987 22:49-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #165
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 2 Jul 1987 Volume 5 : Issue 165
Today's Topics:
Queries - Expert Systems in Marketing & KCL on ISI's,
Psychology - $6M Man & Methodology
----------------------------------------------------------------------
Date: 1 Jul 87 19:28:15 GMT
From: shire.dec.com!morand@decwrl.dec.com
Subject: EXPERT SYSTEMS IN MARKETING
I'm working on the definition of an DSS for Product pricing positioning and
I'm considering the EXPERT SYSTEMS as a potential answer to my problem.
Does any body had an experience or know an application of the expert system
to marketing ?
I would like to take in consideration :
- Product life cycle
- Price elasticity parameters
- Internal competition
- External competition
Thanks in advance,
Jean-claude MORAND DTN 7 821 4782 or (41 22) 87 47 82
DEC Europe
decvax!decwrl!rhea!shire!morand
------------------------------
Date: Wed, 1 Jul 87 10:54:49 edt
From: Connie Ramsey <ramsey@nrl-aic.ARPA>
Subject: KCL on ISI's
Has anybody tried to install the latest (documentation dated July 1986)
version of KCL on an ISI? We tried, but found that some code was missing
when machine=ISI. If anybody knows anything about this problem, we would
appreciate a response.
Thank you,
Connie Ramsey
ramsey@nrl-aic.arpa
------------------------------
Date: Tue, 30 Jun 87 15:57:23 MDT
From: Raul Machuca STEWS-ID-T 678-4686 <rmachuca@wsmr06.ARPA>
Subject: 6Mil man
The six-million dollar man has an explanation which is
biological rather than psychological.
The center on/off receptors of the eye are arranged
in a discrete matrix. An edge gives the greatest signal when
the edge passes thru the center of a cell. When there
is not enough of a signal the edge cannot be seen. An object
moving at a fast rate of speed will be seen by the mind as
a sequence of snapshots. These snapshots take place when the
edge is lined up with the centers of a group of receptors. I an object
is moving at a fast rate of speed the neurons will not recover
to take another snapshot until the object has moved a considerable
distance.
The slow motion still frame technique is simulating on
film exactly this process. The brain reacts in the same way
as if wewere seeing a quickly moving object and thus the neurons
generate the same signals as caused by actually looking at something
moving at a fast rate of speed.
------------------------------
Date: 1 Jul 87 06:36:44 GMT
From: umix!itivax!chinet!lee@RUTGERS.EDU (Lee Morehead)
Reply-to: umix!itivax!chinet!lee@RUTGERS.EDU (Lee Morehead)
Subject: Re: Why did $6M man run so slowly?
It is interesting to note that in the recent sequel movie to the $6M man,
his son could run with speeds measured in the hundreds of mph. While Steve
and Jamie retained the slow motion special effect, his son was given the
video blur special effect to indicate the several times greater speed of
his father. Interesting.
--
Lee Morehead
...!ihnp4!chinet!lee
"One size fits all."
Just who is this "all" person anyway,
and why is he wearing my clothes?
------------------------------
Date: Tue, 30 Jun 87 07:18:40 pdt
From: norman%ics@sdcsvax.ucsd.edu (Donald A. Norman)
Subject: On how AI answers psychological issues
A comment on sin in AI, or "Why did the $6M man run so slowly
AI researchers seem to like the sin of armchair reasoning. It's a
pleasant sin: comfortable, fun, stimulating. And nobody can ever be
proven right or wrong. Most scientists, on the other hand, believe
that real answers are generated through the collection of data,
interpreted by validated theories.
The question "why did the $6M man run so slowly" is a case in point,
but my answer is also stimulated by the conference on "Foundation of
AI" that I just attended (held at MIT, arguing about the several
theoretical approaches to the representationa and simulation of
intelligence). In AIlist, many folks have let forth their theories.
Some are clever, some are interesting. Some are probably right, some
are probably wrong. How would one ever know which? Letting forth
with opinions is no way to answer a scientific question.
At the conference, many of AI's most famed luminaries let forth with
their opinions. Psychological phenomena made up and explained faster
than the speed of thought. Same observation applies. The only thing
worse is when a researcher (in any discipline) becomes a parent. then
the theories spin wildly and take the form: my child did the following
thing; therefore, all children do it; and therefore here is how the
mind works.
Same for why the $6M man ran so slowly. If you really want to know
why slow motion was used, ASK THE FILM MAKER ! (producer, camerman,
editor, director). The film maker selected this method for one of
several possible reasons, and armchair reasoning about it will get you
nowhere. It might have been to stretch out the film, for budgetary
reasons, because they didn't know anything else to do, because they
accidentally hit the slow-motion switch once and, once they got
started on this direction, all future films had to be consistent, etc.
One suspects that filmmakers did not go through the long elaborated
reasoning that some of the respondents assumed. Whatever the reason,
the best (and perhaps only) way to find out is to ask the people who
made the decision. Of course, they themselves may not know, given
that much of our actions are not consciously known to us and do not
necessarly follow from neat declarative rurles stored in some nice
simple memory format (which is why expert systems methodology is
fundamentally flawed, but that is another story), but at least the
verbally described reasons can give you a starting point.
Note that the discussion has confounded several different questions.
One question is "why did the film makers chose to use slow motion?" A
second question is, given that they made that choice, "Why does the
slow motion presentation of speeded motion produce a reasonable
efffect on the viewer?" Here the answer can only come about through
experimentation. However, for this question, the armchair
explanations make more sense and can start out as a plausible set of
hypotheses to be examined.
A third question has gotten raised in the discusion, which is "during
times of stress, or incipient danger, or doing a rapid task when very
well skilled, does subjective time pass more slowly?" This is an
oft-reported finding. Damn-near impossible to test. (Possible,
though: subjective time, for example, changes with body temperature,
going faster when body temperature is raised, slower when lowered, and
since it is possible to determine that fact experimentally, you should
be able to determine the other). The nature of subjective time is
most complex, but evidence would have it that filled time passes quite
differently than unfilled time, and the expert or person intensly
focusssed upon events is apt to attend to details not normally
visible, hence filling the time interval with numerous more activity
and events, hence changing th perception of time.
But before you all bombard the net with lots of anectodes about what
it felt like when in you auto accient, or skiing incident or ..., let
me remind you that the experience you have DURING the event itself, is
quite different from your memory of that experience. The
esdperimental research on time perception shows that subjective
durations can reverse. ( Events that may be boring to experence --
time passes every so slowly -- may be judged to have taken almost no
time at all in future retrospections -- no remembered events. Events
with numerous things happening -- so quickly that you didn't have time
to respond to most of them -- in retropsect may seem to have taken
forever.)
The moral is that understanding the human (or animal) mind is most
difficult, it is apt to come about only through a combination of
experimental study, theoretical modeling, and simulation, and armchair
thinking, while fun, is pretty irrelevant to the endeavor.
Psychology, the field, can be frustrating to the non-participant.
Many tedious experiments. Dumb experiments. An insistence on
methodology that borders on the insane. And an apparent inability to
answer even the simplest questions. Guilty. But for reason. Thinking
about "how the mind works" is fun, but not science, not the way to get
to the correct answer.
don norman
Donald A. Norman
Institute for Cognitive Science C-015
University of California, San Diego
La Jolla, California 92093
norman@nprdc.arpa {decvax,ucbvax,ihnp4}!sdcsvax!ics!norman
norman@sdics.ucsd.edu norman%sdics.ucsd.edu@RELAY.CS.NET
------------------------------
End of AIList Digest
********************
∂02-Jul-87 1112 LAWS@Stripe.SRI.Com AIList Digest V5 #166
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 2 Jul 87 11:12:27 PDT
Date: Wed 1 Jul 1987 22:54-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #166
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 2 Jul 1987 Volume 5 : Issue 166
Today's Topics:
Theory - Perception,
Policy - Quoting
----------------------------------------------------------------------
Date: 29 Jun 87 22:46:31 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: The symbol grounding problem....
In article <1194@houdi.UUCP> marty1@houdi.UUCP (M.BRILLIANT) writes:
>
>I was just looking at a kitchen chair, a brown wooden kitchen
>chair against a yellow wall, in side light from a window. Let's
>let a machine train its camera on that object. Now either it
>has a mechanical array of receptors and processors, like the
>layers of cells in a retina, or it does a functionally
>equivalent thing with sequential processing. What it has to do
>is compare the brightness of neighboring points to find places
>where there is contrast, find contrast in contiguous places so
>as to form an outline, and find closed outlines to form objects.
>There are some subtleties needed to find partly hidden objects,
>but I'll just assume they're solved. There may also be an
>interpretation of shadow gradations to perceive roundness.
>
I have been trying to keep my distance from this debate, but I would like
to insert a few observations regarding this scenario. In many ways, this
paragraph represents the "obvious" approach to perception, assuming that
one is dealing with a symbol manipulation system. However, other approaches
have been hypothesized. While their viability remains to be demonstrated,
it would be fair to say that, in the broad scope of perception in the real
world, the same may be said of symbol manipulation systems.
Consider the holographic model posed by Karl Pribram in LANGUAGES OF THE
BRAIN. As I understand it, this model postulates that memory is a collection
of holographic transforms of experienced images. As new images are
experienced, the brain is capable of retrieving "best fits" from this
memory to form associations. Thus, the chair you see in the above
paragraph is recognized as a chair by virtue of the fact that it "fits"
other images of chairs you have seen in the past.
I'm not sure I buy this, but I'm at least willing to acknowledge it as
an alternative to your symbol manipulation scenario. The biggest problem
I have has to do with retrieval. As far as I understand, present holographic
retrieval works fine as long as you don't have to worry about little things
like change of scale, translation, or rotation. If this model is going to
work, then the retrieval process is going to have to be more powerful than
the current technology allows.
The other problem relates to concept acquisition, as was postulated in
Brilliant's continuation of the scenario:
>
>Now the machine has a form. If the form is still unfamiliar,
>let it ask, "What's that, Daddy?" Daddy says, "That's a chair."
>The machine files that information away. Next time it sees a
>similar form it says "Chair, Daddy, chair!" It still has to
>learn about upholstered chairs, but give it time.
>
The difficulty seems to be in what it means to file something away if
one's memory is simply one of experiences. Does the memory trace of the
chair experience include Daddy's voice saying "chair?" While I'm willing
to acknowledge a multi-media memory trace, this seems a bit pat. It
reminds me of Skinner's VERBAL BEHAVIOR, in which he claimed that one
learned the concept "beautiful" from stimuli of observing people saying
"beautiful" in front of beautiful objects. This conjures up a vision
of people wandering around the Metropolitan Museum of Art mutttering
"beautiful" as they wander from gallery to gallery.
Perhaps the difficulty is that the mind really doesn't want to assign a
symbol to every experience immediately. Rather, following the model of
Holland et. al., it is first necessary to build up some degree of
reinforcement which assures that a particular memory trace is actually
going to be retrieved relatively frequently (whatever that means).
In such a case, then, a symbol becomes a fast-access mechanism for
retrieval of that trace (or a collection of common traces). However,
this gives rise to at least two questions for which I have no answer:
1. What are the criteria by which it is decided that such a
symbol is required for fast-access?
2. Where does the symbol's name come from?
3. How is the symbol actually "bound" to what it retrieves?
These would seem to be the sort of questions which might help to tie
this debate down to more concrete matters.
Brilliant continues:
>That brings me to a question: do you really want this machine
>to be so Totally Turing that it grows like a human, learns like
>a human, and not only learns new objects, but, like a human born
>at age zero, learns how to perceive objects? How much of its
>abilities do you want to have wired in, and how much learned?
>
This would appear to be one of the directions in which connectionism is
leading. In a recent talk, Sejnowski talked about "training" networks
for text-to-speech and backgammon . . . not programming them. On the
other hand, at the current level of his experiments, designing the network
is as important as training it; training can't begin until one has a
suitable architecture of nodes and connections. The big unanswered
questions would appear to be: will all of this scale upward? That
is, is there ultimately some all-embracing architecture which includes
all the mini-architectures examined by connectionist experiments and
enough more to accommodate the methodological epiphenomenalism of real
life?
------------------------------
Date: 1 Jul 87 16:14:41 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem: Against Rosch &
Wittgenstein
In article <949@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
>> There is no reliable, consensual all-or-none categorization performance
>> without a set of underlying features? That sounds like a restatement of
>> the categorization theorist's credo rather than a thing that is so.
>
>If not, what is the objective basis for the performance? And how would
>you get a device to do it given the same inputs?
I think there's some confusion as to whether Harnad's claim is just an empty
tautology or a significant empirical claim. To wit: it's clear that we can
reliably recognize chairs from sensory input, and we don't do this by magic.
Hence, we can perhaps take it as trivially true that there are some
"features" of the input that are being detected. If we are taking this line
however, we have remember that it doesn't really say *anything* about the
operation of the mechanism -- it's just a fancy way of saying we can
recognize chairs.
On the other hand, it might be taken as a significant claim about the nature
of the chair-recognition device, viz., that we can understand its workings as
a process of actually parsing the input into a set of features and actually
comparing these against what is essentially some logical formula in
featurese. This *is* an empirical claim, and it is certainly dubitable:
there could be pattern recognition devices (holograms are one speculative
suggestion) which cannot be interestingly broken down into feature-detecting
parts.
Anders Weinstein
BBN Labs
------------------------------
Date: 1 Jul 87 22:33:50 GMT
From: teknowledge-vaxc!dgordon@unix.sri.com (Dan Gordon)
Subject: Re: The symbol grounding problem: Against Rosch &
Wittgenstein
In article <949@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
>
>dgordon@teknowledge-vaxc.ARPA (Dan Gordon)
>of Teknowledge, Inc., Palo Alto CA writes:
>
>> There is no reliable, consensual all-or-none categorization performance
>> without a set of underlying features? That sounds like a restatement of
>> the categorization theorist's credo rather than a thing that is so.
>
>If not, what is the objective basis for the performance? And how would
>you get a device to do it given the same inputs?
Not a riposte, but some observations:
1) finding an objective basis for a performance and getting a device to
do it given the same inputs are two different things. We may be able
to find an objective basis for a performance but be unable (for merely
contingent reasons, like engineering problems, etc., or for more funda-
mental reasons) to get a device to exhibit the same performance. And,
I suppose, the converse is true: we may be able to get a device to mimic
a performance without understanding the objective basis for the model
(chess programs seem to me to fall into this class).
2) There may in fact be categorization performances that a) do not use
a set of underlying features; b) have an objective basis which is not
feature-driven; and c) can only be simulated (in the strong sense) by
a device which likewise does not use features. This is one of the
central prongs of Wittgenstein's attack on the positivist approach to
language, and although I am not completely convinced by his criticisms,
I haven't run across any very convincing rejoinder.
Maybe more later, Dan Gordon
------------------------------
Date: 1 Jul 87 14:02:28 GMT
From: harwood@cvl.umd.edu (David Harwood)
Subject: Re: The symbol grounding problem - please start your own
newsgroup
In article <950@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
[...replying to M.B. about something...]
>................................................ I do not see this
>intimate interrelationship -- between names and, on the one hand, the
>nonsymbolic representations that pick out the objects they refer to
>and, on the other hand, the higher-level symbolic descriptions into
>which they enter -- as being perspicuously described as a link between
>a pair of autonomous nonsymbolic and symbolic modules. The relationship is
>bottom-up and hybrid through and through, with the symbolic component
>derivative from, inextricably interdigitated with, and parasitic on the
>nonsymbolic.
Uh - let me get this straight. This is the conclusion for your
most recent posting on "the symbol grounding problem." In the first
poorly written sentence you criticize to your bogeyman, saying he ain't
"perspicuous." Small wonder - you invent him for purposes of obsurantist
controversy; no one else even believes in him so far as I can tell.
But wait - there is more. You say your bogeyman - he ain't
"perspicuous." (as if you aren't responsible for this) Then you go on
with what you consider, apparently, to be a "perspicuous" account of
the meaning of "names." So far as I can tell, this sentence is the most
full and "perspicuous" accounting yet, confirmed by everything you've
written on this subject (which I shall not need quote, since it is fresh
on everyone's mind). You say, with inestimatable "perspicuity," concerning
your own superior speculations about the meaning of names (which I quote
since we have all day, day after day, for this): "The relationship is
bottom-up and hybrid through and through, with the symbolic component
derivative from, inextricably interdigitated with, and parasitic on the
symbolic." A mouthful all right. Interdigitated with something all right.
Could you please consider creating your own newsgroup, Mr. Harnad?
I don't know what your purpose is, except for self-aggrandizement, but
I'm fairly sure your purpose has nothing to do with computer science. There's
no discussion of algorithms, computing systems, not even any logical
formality in all this bullshit. And if we have to hear about the meaning of
names - why couldn't we hear from Saul Kripke, instead of you? Then we
might learn something.
Why not create your own soapbox? I will never listen or bother.
I wouldn't even bother to read BBS, which you apparently edit - with
considerable help no doubt, except that you don't write all the articles
(as you do here).
-David Harwood
------------------------------
Date: Wed, 1 Jul 1987 13:28 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #163
Too much, already. This "symbol grounding" has gotten out of hand.
This is a network, not a private journal.
------------------------------
Date: Wed 1 Jul 87 22:02:55-PDT
From: Ken Laws <Laws@Stripe.SRI.Com>
Reply-to: AIList-Request@STRIPE.SRI.COM
Subject: Policy on Quoting
Perhaps the discussion of philosophy/theory/perception would be
more palatable -- or even concise and understandable -- if we
refrained from quoting each other in the style of the old
Phil-Sci list. Quotations are often necessary, of course, but
the average reader can follow a discussion without each participant
echoing his predecessors. Those few who are really interested
in exact wordings can save the relevant back issues; I'll even
send copies on request.
On the whole, I think that this interchange has been conducted
admirably. My hope in making this suggestion is that participants
will spend less bandwidth attacking each other's semantics and more of
it constructing and presenting their own coherent positions. (It's OK
if we don't completely agree on terms such as "analog", as long as
each contributor builds a consistent world view that includes his own
Humpty-Dumpty variants.)
-- Ken
------------------------------
End of AIList Digest
********************
∂03-Jul-87 0010 LAWS@Stripe.SRI.Com AIList Digest V5 #166
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 Jul 87 00:10:20 PDT
Date: Wed 1 Jul 1987 22:54-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #166
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 2 Jul 1987 Volume 5 : Issue 166
Today's Topics:
Theory - Perception,
Policy - Quoting
----------------------------------------------------------------------
Date: 29 Jun 87 22:46:31 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: The symbol grounding problem....
In article <1194@houdi.UUCP> marty1@houdi.UUCP (M.BRILLIANT) writes:
>
>I was just looking at a kitchen chair, a brown wooden kitchen
>chair against a yellow wall, in side light from a window. Let's
>let a machine train its camera on that object. Now either it
>has a mechanical array of receptors and processors, like the
>layers of cells in a retina, or it does a functionally
>equivalent thing with sequential processing. What it has to do
>is compare the brightness of neighboring points to find places
>where there is contrast, find contrast in contiguous places so
>as to form an outline, and find closed outlines to form objects.
>There are some subtleties needed to find partly hidden objects,
>but I'll just assume they're solved. There may also be an
>interpretation of shadow gradations to perceive roundness.
>
I have been trying to keep my distance from this debate, but I would like
to insert a few observations regarding this scenario. In many ways, this
paragraph represents the "obvious" approach to perception, assuming that
one is dealing with a symbol manipulation system. However, other approaches
have been hypothesized. While their viability remains to be demonstrated,
it would be fair to say that, in the broad scope of perception in the real
world, the same may be said of symbol manipulation systems.
Consider the holographic model posed by Karl Pribram in LANGUAGES OF THE
BRAIN. As I understand it, this model postulates that memory is a collection
of holographic transforms of experienced images. As new images are
experienced, the brain is capable of retrieving "best fits" from this
memory to form associations. Thus, the chair you see in the above
paragraph is recognized as a chair by virtue of the fact that it "fits"
other images of chairs you have seen in the past.
I'm not sure I buy this, but I'm at least willing to acknowledge it as
an alternative to your symbol manipulation scenario. The biggest problem
I have has to do with retrieval. As far as I understand, present holographic
retrieval works fine as long as you don't have to worry about little things
like change of scale, translation, or rotation. If this model is going to
work, then the retrieval process is going to have to be more powerful than
the current technology allows.
The other problem relates to concept acquisition, as was postulated in
Brilliant's continuation of the scenario:
>
>Now the machine has a form. If the form is still unfamiliar,
>let it ask, "What's that, Daddy?" Daddy says, "That's a chair."
>The machine files that information away. Next time it sees a
>similar form it says "Chair, Daddy, chair!" It still has to
>learn about upholstered chairs, but give it time.
>
The difficulty seems to be in what it means to file something away if
one's memory is simply one of experiences. Does the memory trace of the
chair experience include Daddy's voice saying "chair?" While I'm willing
to acknowledge a multi-media memory trace, this seems a bit pat. It
reminds me of Skinner's VERBAL BEHAVIOR, in which he claimed that one
learned the concept "beautiful" from stimuli of observing people saying
"beautiful" in front of beautiful objects. This conjures up a vision
of people wandering around the Metropolitan Museum of Art mutttering
"beautiful" as they wander from gallery to gallery.
Perhaps the difficulty is that the mind really doesn't want to assign a
symbol to every experience immediately. Rather, following the model of
Holland et. al., it is first necessary to build up some degree of
reinforcement which assures that a particular memory trace is actually
going to be retrieved relatively frequently (whatever that means).
In such a case, then, a symbol becomes a fast-access mechanism for
retrieval of that trace (or a collection of common traces). However,
this gives rise to at least two questions for which I have no answer:
1. What are the criteria by which it is decided that such a
symbol is required for fast-access?
2. Where does the symbol's name come from?
3. How is the symbol actually "bound" to what it retrieves?
These would seem to be the sort of questions which might help to tie
this debate down to more concrete matters.
Brilliant continues:
>That brings me to a question: do you really want this machine
>to be so Totally Turing that it grows like a human, learns like
>a human, and not only learns new objects, but, like a human born
>at age zero, learns how to perceive objects? How much of its
>abilities do you want to have wired in, and how much learned?
>
This would appear to be one of the directions in which connectionism is
leading. In a recent talk, Sejnowski talked about "training" networks
for text-to-speech and backgammon . . . not programming them. On the
other hand, at the current level of his experiments, designing the network
is as important as training it; training can't begin until one has a
suitable architecture of nodes and connections. The big unanswered
questions would appear to be: will all of this scale upward? That
is, is there ultimately some all-embracing architecture which includes
all the mini-architectures examined by connectionist experiments and
enough more to accommodate the methodological epiphenomenalism of real
life?
------------------------------
Date: 1 Jul 87 16:14:41 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem: Against Rosch &
Wittgenstein
In article <949@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
>> There is no reliable, consensual all-or-none categorization performance
>> without a set of underlying features? That sounds like a restatement of
>> the categorization theorist's credo rather than a thing that is so.
>
>If not, what is the objective basis for the performance? And how would
>you get a device to do it given the same inputs?
I think there's some confusion as to whether Harnad's claim is just an empty
tautology or a significant empirical claim. To wit: it's clear that we can
reliably recognize chairs from sensory input, and we don't do this by magic.
Hence, we can perhaps take it as trivially true that there are some
"features" of the input that are being detected. If we are taking this line
however, we have remember that it doesn't really say *anything* about the
operation of the mechanism -- it's just a fancy way of saying we can
recognize chairs.
On the other hand, it might be taken as a significant claim about the nature
of the chair-recognition device, viz., that we can understand its workings as
a process of actually parsing the input into a set of features and actually
comparing these against what is essentially some logical formula in
featurese. This *is* an empirical claim, and it is certainly dubitable:
there could be pattern recognition devices (holograms are one speculative
suggestion) which cannot be interestingly broken down into feature-detecting
parts.
Anders Weinstein
BBN Labs
------------------------------
Date: 1 Jul 87 22:33:50 GMT
From: teknowledge-vaxc!dgordon@unix.sri.com (Dan Gordon)
Subject: Re: The symbol grounding problem: Against Rosch &
Wittgenstein
In article <949@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
>
>dgordon@teknowledge-vaxc.ARPA (Dan Gordon)
>of Teknowledge, Inc., Palo Alto CA writes:
>
>> There is no reliable, consensual all-or-none categorization performance
>> without a set of underlying features? That sounds like a restatement of
>> the categorization theorist's credo rather than a thing that is so.
>
>If not, what is the objective basis for the performance? And how would
>you get a device to do it given the same inputs?
Not a riposte, but some observations:
1) finding an objective basis for a performance and getting a device to
do it given the same inputs are two different things. We may be able
to find an objective basis for a performance but be unable (for merely
contingent reasons, like engineering problems, etc., or for more funda-
mental reasons) to get a device to exhibit the same performance. And,
I suppose, the converse is true: we may be able to get a device to mimic
a performance without understanding the objective basis for the model
(chess programs seem to me to fall into this class).
2) There may in fact be categorization performances that a) do not use
a set of underlying features; b) have an objective basis which is not
feature-driven; and c) can only be simulated (in the strong sense) by
a device which likewise does not use features. This is one of the
central prongs of Wittgenstein's attack on the positivist approach to
language, and although I am not completely convinced by his criticisms,
I haven't run across any very convincing rejoinder.
Maybe more later, Dan Gordon
------------------------------
Date: 1 Jul 87 14:02:28 GMT
From: harwood@cvl.umd.edu (David Harwood)
Subject: Re: The symbol grounding problem - please start your own
newsgroup
In article <950@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
[...replying to M.B. about something...]
>................................................ I do not see this
>intimate interrelationship -- between names and, on the one hand, the
>nonsymbolic representations that pick out the objects they refer to
>and, on the other hand, the higher-level symbolic descriptions into
>which they enter -- as being perspicuously described as a link between
>a pair of autonomous nonsymbolic and symbolic modules. The relationship is
>bottom-up and hybrid through and through, with the symbolic component
>derivative from, inextricably interdigitated with, and parasitic on the
>nonsymbolic.
Uh - let me get this straight. This is the conclusion for your
most recent posting on "the symbol grounding problem." In the first
poorly written sentence you criticize to your bogeyman, saying he ain't
"perspicuous." Small wonder - you invent him for purposes of obsurantist
controversy; no one else even believes in him so far as I can tell.
But wait - there is more. You say your bogeyman - he ain't
"perspicuous." (as if you aren't responsible for this) Then you go on
with what you consider, apparently, to be a "perspicuous" account of
the meaning of "names." So far as I can tell, this sentence is the most
full and "perspicuous" accounting yet, confirmed by everything you've
written on this subject (which I shall not need quote, since it is fresh
on everyone's mind). You say, with inestimatable "perspicuity," concerning
your own superior speculations about the meaning of names (which I quote
since we have all day, day after day, for this): "The relationship is
bottom-up and hybrid through and through, with the symbolic component
derivative from, inextricably interdigitated with, and parasitic on the
symbolic." A mouthful all right. Interdigitated with something all right.
Could you please consider creating your own newsgroup, Mr. Harnad?
I don't know what your purpose is, except for self-aggrandizement, but
I'm fairly sure your purpose has nothing to do with computer science. There's
no discussion of algorithms, computing systems, not even any logical
formality in all this bullshit. And if we have to hear about the meaning of
names - why couldn't we hear from Saul Kripke, instead of you? Then we
might learn something.
Why not create your own soapbox? I will never listen or bother.
I wouldn't even bother to read BBS, which you apparently edit - with
considerable help no doubt, except that you don't write all the articles
(as you do here).
-David Harwood
------------------------------
Date: Wed, 1 Jul 1987 13:28 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #163
Too much, already. This "symbol grounding" has gotten out of hand.
This is a network, not a private journal.
------------------------------
Date: Wed 1 Jul 87 22:02:55-PDT
From: Ken Laws <Laws@Stripe.SRI.Com>
Reply-to: AIList-Request@STRIPE.SRI.COM
Subject: Policy on Quoting
Perhaps the discussion of philosophy/theory/perception would be
more palatable -- or even concise and understandable -- if we
refrained from quoting each other in the style of the old
Phil-Sci list. Quotations are often necessary, of course, but
the average reader can follow a discussion without each participant
echoing his predecessors. Those few who are really interested
in exact wordings can save the relevant back issues; I'll even
send copies on request.
On the whole, I think that this interchange has been conducted
admirably. My hope in making this suggestion is that participants
will spend less bandwidth attacking each other's semantics and more of
it constructing and presenting their own coherent positions. (It's OK
if we don't completely agree on terms such as "analog", as long as
each contributor builds a consistent world view that includes his own
Humpty-Dumpty variants.)
-- Ken
------------------------------
End of AIList Digest
********************
∂06-Jul-87 0246 LAWS@Stripe.SRI.Com AIList Digest V5 #167
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 6 Jul 87 02:46:36 PDT
Date: Mon 6 Jul 1987 00:46-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #167
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 6 Jul 1987 Volume 5 : Issue 167
Today's Topics:
Seminars - Planning Actions with Context-Dependent Effects (SRI) &
Automated Process Planning using Abstraction (CMU),
Conference - SLUG '87 Reminder &
Simulation and AI &
Expert Systems in the ADP Environment
----------------------------------------------------------------------
Date: Tue, 30 Jun 87 11:52:11 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Planning Actions with Context-Dependent Effects (SRI)
SYNTHESIZING PLANS THAT CONTAIN ACTIONS
WITH CONTEXT-DEPENDENT EFFECTS
Edwin P.D. Pednault (VAX135!EPDP@UCBVAX.BERKELEY.EDU)
Knowledge Systems Research Department
AT&T Bell Laboratories
Crawfords Corner Road
Holmdel, NJ 07733
11:00 AM, MONDAY, July 6
SRI International, Building E, Room EJ228
In this talk, I will present an approach to solving planning problems
that involve actions whose effects depend on the state of the world at
the time the actions are performed. To solve such problems, the idea
of a secondary precondition is introduced. A secondary precondition
for an action is a condition that must be true at the time the action
is performed for the action to have its desired effect. By imposing
the appropriate secondary precondition as an additional precondition
to an action, we can coerce that action to preserve a desired
condition or to cause a desired condition to become true. I will
demonstrate the use of secondary preconditions and show how they can
be derived from the specification of a planning problem in a
completely general and domain-independent fashion.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: 30 Jun 87 12:21:51 EDT
From: Marcella.Zaragoza@isl1.ri.cmu.edu
Subject: Seminar - Automated Process Planning using Abstraction (CMU)
SPECIAL SEMINAR
TOPIC: AUTOMATED PROCESS PLANNING USING HIERARCHICAL ABSTRACTION *
WHO: Dana S. Nau
Computer Science Department and Institute for
Advanced Computer Studies, University of Maryland, and
Factory Automation Systems Division, National Bureau of Standards
WHEN: Monday, July 6, 10:00-11:30 a.m.
WHERE: WeH 4623
ABSTRACT
SIPS is a system which uses AI techniques to decide what machining
operations to use in the creation of metal parts. SIPS generates its
plans completely from scratch, using the specification of the part to be
produced and knowledge about the intrinsic capabilities of each
manufacturing operation.
Rather than using a rule-based approach to knowledge representation,
SIPS uses a hierarchical abstraction technique called hierarchical knowledge
clustering. Problem-solving knowledge is organized in a taxonomic hierarchy
using frames, and problem solving is done using an adaptation of Branch and
Bound.
The development of SIPS was done with two long-term goals in mind:
the use of AI techniques to develop a practical generative process planning
system, and the investigation of fundamental AI issues in representing and
reasoning about three-dimensional objects. SIPS represents an important
step toward these goals, and a number of extensions and enhancements to SIPS
are either underway or planned. SIPS is currently being integrated into the
Automated Manufacturing Research Facility (AMRF) project at the National
Bureau of Standards.
* This work has been supported in part by the following sources: an NSF
Presidential Young Investigator Award to Dana Nau, NSF Grant NSFD
CDR-85-00108 to the University of Maryland Systems Research Center, IBM
Research, General Motors Research Laboratories, and Martin Marietta
Laboratories.
------------------------------
Date: Sat, 27 Jun 1987 14:13 CDT
From: CS.PURVIS@R20.UTEXAS.EDU
Subject: Conference - SLUG '87 Reminder
This is a reminder that the national meeting of the
Symbolics Lisp Users Group
will be held in Seattle, July 6-10th. You may register in advance by
calling the University of Washington at (206) 543-2300.
The conference schedule is listed below. Note particularly the panel
discussions on Thursday and Friday that will examine available
alternatives to the Symbolics Lisp development environment
architecture and consider what trade-offs are involved.
This is THE Lisp machine conference. Don't miss it!
SLUG '87 Schedule
July 6-10, 1987 - Seattle, Washington
MONDAY -- (tutorials)
8:00
Registration desk opens
9:00 to 12:30
* AI Program Design
* Overview of Site Administration
* Color Graphics I
2:00 to 5:30
* AI Program Design (cont'd)
* Overview of Site Administration (cont'd)
* Color Graphics II
* Color Graphics III
TUESDAY -- (tutorials)
8:00
Registration desk opens
9:00 to 12:30
* Programming Productivity I
* Introduction to ART
* Building Knowledge System Interfaces
2:00 to 5:30
* Programming Productivity II
* Introduction to ART (cont'd)
7:00 - 9:00
Reception
WEDNESDAY -- (conference sessions)
8:00
Registration desk opens
9:00 to 12:30
* Welcome & Opening remarks
* State of SLUG
* Symbolics Corporate Status Report
* Software & Hardware Support
* Technical Status Report
* New Product Announcements
* General and Reverse Q & A
2:00 to 6:00
* Software Engineering on LISP Machines
* Symbolic Computing for New Users
* General Technical Q & A
Evening -- BOAF (Birds Of A Feather)
* Critique of the Symbolics User Interface -- GNU EMACS and HP's
NMODE both present a novel way of interacting with LISP.
Is the LISP machine paradigm better? This meeting will drive
tomorrow afternoon's
session.
* New user training: Sharing insights, techniques, and introductory
materials for new users.
* Symbolics maintenance issues.
THURSDAY -- (conference sessions)
9:00 to 12:30
* Common LISP -- What is the status of Common LISP the Language?
Classes? Common Windows? Error handling?
* SLUG Library -- What's new and available?
* Networks -- VMS, UNIX, DECNET, IP-TCP, Namespaces,
Domain Resolution, etc.
* Non-LISP Language Support -- PROLOG, ADA, FORTRAN, PASCAL, C, etc.
2:00 to 5:30
* LISPM pearls -- An informal presentation of useful but little
known LISP machine features and capabilities.
* Critique of the Symbolics User Interface -- See yesterday's BOAF.
* Technical Q & A
FRIDAY -- (conference sessions)
9:00 to 12:30
* Trade-offs in LISP (development) environments -- This is a panel
discussion of the differences between developing LISP software
on different workstation architectures.
* Conference Summary & Feedback
* SLUG Business Meeting
2:00 to 3:30
* Expert Systems Session
------------------------------
Date: Thu, 25 Jun 87 10:50:35 edt
From: Paul Fishwick <fishwick%bikini.cis.ufl.edu@RELAY.CS.NET>
Subject: Conference - SIMULATION AND AI
ANNOUNCEMENT AND CALL FOR PAPERS
SIMULATION AND ARTIFICIAL INTELLIGENCE CONFERENCE
Part of the 1988 SCS MultiConference
San Diego, CA Feb 3-5, 1988
Paper and Special Session Proposals should be sent to SCS (Society for
Computer Simulation) by July 15, 1987 [note: the deadline has been extended].
Some suggested topics are listed below:
Relation between AI and Simulation
Intelligent Simulation Environments
Knowledge-Based Simulation
Decision Support Systems
Qualitative Simulation (there will be a panel discussion on this topic)
Simulation in AI
Ada and AI and Simulation
Aerospace Applications
Biomedical Applications
Expert Systems in Emergency Planning
Automatic Model Generation
Expert Systems
Learning Systems
Natural Language Processing
Robotics
Speech Recognition
Vision
AI Hardware/Workstations
AI Programming Languages
AI/ES Software Tools
A paper proposal should be submitted (approx. 300 words) to:
SCS
P.O. Box 17900
San Diego, CA 92117-7900
------------------------------------------------------------------------------
People attending the AI and Simulation workshop at AAAI and others interested
in AI and Simulation are strongly encouraged to attend!
Paul Fishwick
University of Florida
CSNET: fishwick@ufl.edu
------------------------------
Date: 24 Jun 87 15:35:00 EST
From: "LFA" <lfa@ornl-stc10.arpa>
Reply-to: "LFA" <lfa@ornl-stc10.arpa>
Subject: Conference - Expert Systems in the ADP Environment
CALL FOR PAPERS
==== === ======
NARDAC Washington/ORNL/DSRD Conference
on
Expert Systems Technology in the ADP Environment
to be held in
Washington, D.C.
November 2-3, 1987
THE CONFERENCE
=== ==========
The Naval Regional Data Automation Center in Washington, D.C., the Oak
Ridge National Laboratory, and the Data Systems Research and Development
Program, Martin Marietta Energy Systems, Inc., are sponsoring a conference whose
primary focus is on the use of Artificial Intelligence in traditional computing
domains and its potential for further exploitation. Both invited talks and
contributed papers will be given at the conference.
INVITED SPEAKERS
======= ========
Several individuals have tentatively accepted invitations to speak at
this conference on the various aspects of Artificial Intelligence as it
pertains to traditional computing problems. Scheduled speakers and their
topic areas include:
Prof. James Slagle (Minnesota) - Keynote speaker
Prof. Brian Gaines (Calgary) - Intelligent Interfaces for
Knowledge-Based Systems
Prof. Larry Henschen (Northwestern) - Logic and Databases
Dr. Sukhumay Kundu (Louisiana State) - AI in Software Engineering
CONTRIBUTED PAPERS
=========== ======
In addition to the invited talks, papers are being solicited from
researchers in academia, government and industry in the following areas:
ADP Project and Systems Management,
Knowledge-Based Simulation and Modeling,
Intelligent Man-Machine Interfaces,
Intelligent Databases,
AI in Software Engineering,
AI as a Tool for Decision-Making, and
Innovative Applications in MIS or Scientific Computing.
SUBMISSION DETAILS
========== =======
Authors are asked to submit five (5) copies of their paper, which is to
be single-spaced and between five to seven pages in length. Both finished and
ongoing research will be considered by the program committee and referees.
Authors should adhere to the following submission schedule:
August 1, 1987 - Submission Deadline
August 15, 1987 - Notification of acceptance
September 15, 1987 - Camera-ready copies due
Send papers, requests for additional information, and all other correspondence
to
Lloyd F. Arrowood
Program Chairman
Oak Ridge National Laboratory
Building 4500-North, Mail Stop 207
Oak Ridge, TN 37831
or
BITNET: LFA@ORNLSTC
------------------------------
End of AIList Digest
********************
∂06-Jul-87 0459 LAWS@Stripe.SRI.Com AIList Digest V5 #168
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 6 Jul 87 04:58:54 PDT
Date: Mon 6 Jul 1987 00:50-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #168
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 6 Jul 1987 Volume 5 : Issue 168
Today's Topics:
Policy - Hard Limit on Quotations,
Theory - The Symbol Grounding Problem & Against Rosch and Wittgenstein
----------------------------------------------------------------------
Date: Thu 2 Jul 87 09:41:54-PDT
From: Ken Laws <Laws@Stripe.SRI.Com>
Subject: Hard Limit on Quotations
The "quotation problem" has become so prevalent across all of the
Usenet newsgroups that the gateway now rejects any message with more
quoted text than new text. If a message is rejected for this reason,
I am unlikely to clean it up and resend.
As I indicated last week, I think we could get along just fine
with more "I say ..." and less "You said ...". Paraphrases are
fine and even beneficial, but trying to reestablish the exact
context of each comment is not worth the hassle to the general
readership. Perhaps some of the hair splitting could be carried
on through private mail, with occasional reports to the list on
points of agreement and disagreement. Discussions of perception
and categorization are appropriate for AIList, but we cannot give
unlimited time and attention to any one topic.
I've engaged in "interpolated debate" myself, and have enjoyed
this characteristic mode of net discussions. I won't object to
occasional use, but I do get very tired of seeing the same text
quoted in message after message. I used to edit such repetitions
out of the digest, but I can't manage it with this traffic volume.
Please keep in mind that this is a broadcast channel and that many
readers have slow terminals or have to pay intercontinental
transmission fees. Words are money.
It seems that a consistent philosophy cannot be put forth in less
than a full book, or at least a BBS article, and that meaningful
rebuttals require similar length. We have been trying to cram this
through a linear channel, with swirls of debate spinning off from each
paragraph [yes, I know that's a contradiction], and there is no
evidence of convergence. Let's try to slow down for a while.
I would also recommend that messages be kept to a single topic,
even if that means (initially) that a full response to a previous
message must be split into parts. Separate discussion of grounding,
categorization, perception, etc., would be more palatable than the
current indivisible stream. I would like to sort the discussions,
if only for ease of meaningful retrieval, but can't do so if they
all carry the same subject line and mix of topics.
-- Ken
------------------------------
Date: Thu, 2 Jul 87 09:37:21 EDT
From: Alex Kass <kass-alex@YALE.ARPA>
Subject: AIList Digest V5 #163
Can't we bag this damn symbol grounding discussion already?
If it *must* continue, how about instituting a symbol grounding news
group, and freeing the majority of us poor AILIST readers from the
burden of flipping past the symbol grounding stuff every morning.
-Alex
ARPA: Kass@yale
UUCP: {decvax,linus,seismo}!yale!kass
BITNET: kass@yalecs
US: Alex Kass
Yale University Computer Science Department
New Haven, CT 06520
------------------------------
Date: 2 Jul 87 05:19:05 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
smoliar@vaxa.isi.edu (Stephen Smoliar)
Information Sciences Institute writes:
> Consider the holographic model proposed by Karl Pribram in LANGUAGES
> OF THE BRAIN... as an alternative to [M.B. Brilliant's] symbol
> manipulation scenario.
Besides being unimplemented and hence untested in what they can and can't
do, holographic representations seem to inherit the same handicap as
all iconic representations: Being unique to each input and blending
continuously into one another, how can holograms generate
categorization rather than merely similarity gradients (in the hard
cases, where obvious natural gaps in the input variation don't solve
the problem for you a priori)? What seems necessary is active
feature-selection, based on feedback from success and failure in attempts
to learn to sort and label correctly, not merely passive filtering
based on natural similarities in the input.
> [A] difficulty seems to be in what it means to file something away if
> one's memory is simply one of experiences.
Episodic memory -- rote memory for input experiences -- has the same
liability as any purely iconic approach: It can't generate category
boundaries where there is significant interconfusability among
categories of episodes.
> Perhaps the difficulty is that the mind really doesn't want to
> assign a symbol to every experience immediately.
That's right. Maybe it's *categories* of experience that must first be
selectively assigned names, not each raw episode.
> Where does the symbol's name come from? How is the symbol actually
> "bound" to what it retrieves?
That's the categorization problem.
> The big unanswered question...[with respect to connectionism]
> would appear to be: will [it] all... scale upward?
Connectionism is one of the candidates for the feature-learning
mechanism. That it's (i) nonsymbolic, that it (ii) learns, and that it
(iii) uses the same general statistical algorithm across problem-types
(i.e., that it has generality rather than being ad hoc, like pure
symbolic AI) are connectionism's plus's. (That it's brainlike is not,
nor is it true, on current evidence, nor even relevant at this stage.)
But the real question is indeed: How much can it really do (i.e., will it
scale up)?
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 2 Jul 87 04:36:37 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem: Against Rosch &
Wittgenstein
dgordon@teknowledge-vaxc.ARPA (Dan Gordon)
of Teknowledge, Inc., Palo Alto CA writes:
> finding an objective basis for a performance and getting a device to
> do it given the same inputs are two different things. We may be able
> to find an objective basis for a performance but be unable...to get a
> device to exhibit the same performance. And, I suppose, the converse
> is true: we may be able to get a device to mimic a performance without
> understanding the objective basis for the model
I agree with part of this. J.J. Gibson argued that the objective basis of much
of our sensorimotor performance is in stimulus invariants, but this
does not explain how we get a device (like ourselves) to find and use
those invariants and thereby generate the performance. I also agree that a
device (e.g., a connectionist network) may generate a performance
without our understanding quite how it does it (apart from the general
statistical algorithm it's using, in the case of nets). But the
point I am making is neither of these. It concerns whether performance
(correct all-or-none categorization) can be generated without an
objective basis (in the form of "defining" features) (a) existing and
(b) being used by any device that successfully generates the
performance. Whether or not we know know what the objective basis is
and how it's used is another matter.
> There may in fact be categorization performances that a) do not use
> a set of underlying features; b) have an objective basis which is not
> feature-driven; and c) can only be simulated (in the strong sense) by
> a device which likewise does not use features. This is one of the
> central prongs of Wittgenstein's attack on the positivist approach to
> language, and although I am not completely convinced by his criticisms,
> I haven't run across any very convincing rejoinder.
Let's say I'm trying to provide the requisite rejoinder (in the special case of
all-or-none categorization, which is not unrelated to the problems of
language: naming and description). Wittgenstein's arguments were not governed
by a thoroughly modern constraint that has arisen from the possibility of
computer simulation and cognitive modeling. He was introspecting on
what the features defining, say, "games" might be, and he failed to
find a necessary and sufficient set, so he said there wasn't one. If
he had instead asked: "How, in principle, could a device categorize
"games" and "nongames" successfully in every instance?" he would have had
to conclude that the inputs must provide an objective basis
which the device must find and use. Whether or not the device can
introspect and report what the objective basis is is another matter.
Another red herring in Wittegenstein's "family resemblance" metaphor was
the issue of negative and disjunctive features. Not-F is a perfectly good
feature. So is Not-F & Not-G. Which quite naturally yields the
disjunctive feature F-or-G. None of this is tautologous. It just shows
up a certain arbitrary myopia there has been about what a "feature" is.
There's absolutely no reason to restrict "features" to monadic,
conjunctive features that subjects can report by introspection. The
problem in principle is whether there are any logical (and nonmagical)
alternatives to a feature-set sufficient to sort the confusable
alternatives correctly. I would argue that -- apart from contrived,
gerrymandered cases that no one would want to argue formed the real
basis of our ability to categorize -- there are none.
Finally, in the special case of categorization, the criterion of "defining"
features also turns out to be a red herring. According to my own model,
categorization is always provisional and context-dependent (it depends on
what's needed to successfully sort the confusable alternatives sampled to date).
Hence an exhaustive "definition," good till doomsday and formulated from the
God's-eye viewpoint is not at issue, only an approximation that works now, and
can be revised and tightened if the context is ever widened by further
confusable alternatives that the current feature set would not be able to
sort correctly. The conflation of (1) features sufficient to generate the
current provisional (but successful) approximation and (2) some nebulous
"eternal," ontologically exact "defining" set (which I agree does not exist,
and may not even make sense, since categorization is always a relative,
"compared-to-what?" matter) has led to a multitude of spurious
misunderstandings -- foremost among them being the misconception that
our categories are all graded or fuzzy.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 2 Jul 87 15:51:40 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
On ailist cugini@icst-ecf.arpa writes:
> why say that icons, but not categorical representations or symbols
> are/must be invertible? Isn't it just a vacuous tautology to claim
> that icons are invertible wrt to the information they preserve, but
> not wrt the information they lose?... there's information loss (many
> to one mapping) at each stage of the game: 1. distal object...
> 2. sensory projection... 3. icons... 4. categorical representation...
> 5. symbols... do you still claim that the transition between 2
> and 3 is invertible in some strong sense which would not be true of,
> say, [1 to 2] or [3 to 4], and if so, what is that sense?... Perhaps
> you just want to say that the transition between 2 and 3 is usually
> more invertible than the other transitions [i.e., invertibility as a
> graded category]?
[In keeping with Ken Laws' recommendation about minimizing quotation, I have
compressed this query as much as I could to make my reply intelligible.]
Iconic representations (IRs) must perform a very different function from
categorical representations (IRs) or symbolic representations (SRs).
In my model, IRs only subserve relative discrimination, similarity
judgment and sensory-sensory and sensory-motor matching. For all of
these kinds of task, traces of the sensory projection are needed for
purposes of relative comparison and matching. An analog of the sensory
projection *in the properties that are discriminable to the organism*
is my candidate for the kind of representation that will do the job
(i.e., generate the performance). There is no question of preserving
in the IR properties that are *not* discriminable to the organism.
As has been discussed before, there are two ways that IRs could in
principle be invertible (with the discriminable properties of the
sensory projection): by remaining structurally 1:1 with it or by going
into symbols via A/D and an encryption and decryption transformation in a
dedicated (hard-wired) system. I hypothesize that structural copies are
much more economical than dedicated symbols for generating discrimination
performance (and there is evidence that they are what the nervous system
actually uses). But in principle, you can get invertibility and generate
successful discrimination performance either way.
CRs need not -- indeed cannot -- be invertible with the sensory
projection because they must selectively discard all features except
those that are sufficient to guide successful categorization
performance (i.e., sorting and labeling, identification). Categorical
feature-detectors must discard most of the discriminable properties preserved
in IRs and selectively preserve only the invariant properties shared
by all members of a category that reliably distinguish them from
nonmembers. I have indicated, though, that this representation is
still nonsymbolic; the IR to CR transformation is many-to-few, but it
continues to be invertible in the invariant properties, hence it is
really "micro-iconic." It does not invert from the representation to
the sensory projection, but from the representation to invariant features of
the category. (You can call this invertibility a matter of degree if
you like, but I don't think it's very informative. The important
difference is functional: What it takes to generate discrimination
performance and what it takes to generate categorization
performance.)
Finally, whatever invertibility SRs have is entirely parasitic on the
IRs and CRs in which they are grounded, because the elementary SRs out
of which the composite ones are put together are simply the names of
the categories that the CRs pick out. That's the whole point of this
grounding proposal.
I hope this explains what is invertible and why. (I do not understand your
question about the "invertibility" of the sensory projection to the distal
object, since the locus of that transformation is outside the head and hence
cannot be part of the internal representation that cognitive modeling is
concerned with.)
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 2 Jul 87 01:19:35 GMT
From: ctnews!pyramid!prls!philabs!pwa-b!mmintl!franka@unix.sri.com
(Frank Adams)
Subject: Re: The symbol grounding problem: Correction re.
Approximationism
In article <923@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
|In responding to Cugini and Brilliant I misinterpreted a point that
|the former had made and the latter reiterated. It's a point that's
|come up before: What if the iconic representation -- the one that's
|supposed to be invertible -- fails to preserve some objective property
|of the sensory projection? For example, what if yellow and blue at the
|receptor go into green at the icon? The reply is that an analog
|representation is only analog in what it preserves, not in what it fails
|to preserve.
I'm afraid when I parse this, using the definitions Harnad uses, it comes
out as tautologically true of *all* representations.
"Analog" means "invertible". The invertible properties of a representation
are those properties which it preserves. Is there some strange meaning of
"preserve" being used here? Otherwise, I don't see how this statement has
any meaning.
--
Frank Adams ihnp4!philabs!pwa-b!mmintl!franka
Ashton-Tate 52 Oakland Ave North E. Hartford, CT 06108
------------------------------
Date: 2 Jul 87 01:07:00 GMT
From: ctnews!pyramid!prls!philabs!pwa-b!mmintl!franka@unix.sri.com
(Frank Adams)
Subject: Re: The symbol grounding problem
In article <917@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
|Finally, and perhaps most important: In bypassing the problem of
|categorization capacity itself -- i.e., the problem of how devices
|manage to categorize as correctly and successfully as they do, given
|the inputs they have encountered -- in favor of its fine tuning, this
|line of research has unhelpfully blurred the distinction between the
|following: (a) the many all-or-none categories that are the real burden
|for an explanatory theory of categorization (a penguin, after all, be it
|ever so atypical a bird, and be it ever so time-consuming for us to judge
|that it is indeed a bird, is, after all, indeed a bird, and we know
|it, and can say so, with 100% accuracy every time, irrespective of
|whether we can successfully introspect what features we are using to
|say so) and (b) true "graded" categories such as "big," "intelligent,"
|etc. Let's face the all-or-none problem before we get fancy...
I don't believe there are any truely "all-or-none" categories. There are
always, at least potentially, ambiguous cases. There is no "100% accuracy
every time", and trying to theorize as though there were is likely to lead
to problems.
Second, and perhaps more to the point, how do you know that "graded"
categories are less fundamental than the other kind? Maybe it's the other
way around. Maybe we should try to understand to understand graded
categories first, before we get fancy with the other kind. I'm not saying
this is the case; but until we actually have an accepted theory of
categorization, we won't know what the simplest route is to get there.
--
Frank Adams ihnp4!philabs!pwa-b!mmintl!franka
Ashton-Tate 52 Oakland Ave North E. Hartford, CT 06108
------------------------------
End of AIList Digest
********************
∂06-Jul-87 0823 LAWS@Stripe.SRI.Com AIList Digest V5 #169
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 6 Jul 87 08:23:31 PDT
Date: Mon 6 Jul 1987 00:59-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #169
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 6 Jul 1987 Volume 5 : Issue 169
Today's Topics:
Theory - "Fuzzy" Categories?
----------------------------------------------------------------------
Date: 2 Jul 87 01:44:00 GMT
From: ctnews!pyramid!prls!philabs!pwa-b!mmintl!franka@unix.sri.com
(Frank Adams)
Subject: Re: The symbol grounding problem: "Fuzzy" categories?
In article <936@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
|The question was: Do all-or-none categories (such as "bird") have "defining"
|features that can be used to sort members from nonmembers at the level of
|accuracy (~100%) with which we sort? However they are coded, I claim that
|those features MUST exist in the inputs and must be detected and used by the
|categorizer. A penguin is not a bird as a matter of degree, and the features
|that reliably assign it to "bird" are not graded.
I don't see how this follows. It is quite possible to make all-or-none
judgements based on graded features. Thermostats, for example, do it all
the time. People do, too. The examples which come to mind as being
obviously in this category are all judgements of actions to take based on
such features, not of categorization. But then, we don't understand how we
categorize.
But to take an example of categorizing based on a graded feature. Consider
a typical, unadorned, wooden kitchen chair. We have no problem categorizing
this as a "chair". Consider the same object, with no back. This is
clearly categorized as a "stool", and not a "chair". Now vary the size of
the back. With a one inch back, the object is clearly still a "stool"; with
a ten inch back, it is clearly a "chair"; somewhere in between is an
ambiguous point.
I would assert that we *do*, in fact, make "all-or-none" type distinctions
based precisely on graded distinctions. We have arbitrary (though vague)
cut off points where we make the distinction; and those cut off points are
chosen in such a way that ambiguous cases are rare to non-existent in our
experience[1].
In short, I see nothing about "all-or-none" categories which is not
explainable by arbitrary cutoffs of graded sensory data.
---------------
[1] There are some categories where this strategy does not work. Colors are
a good example of this -- they vary over all of their range, with no very
rare points in it. In this case, we use instead the strategy of large
overlapping ranges -- two people may disagree on whether a color should be
described as "blue" or "green", but both will accept "blue-green" as a
description. The same underlying strategy applies: avoid borderline
situations.
--
Frank Adams ihnp4!philabs!pwa-b!mmintl!franka
Ashton-Tate 52 Oakland Ave North E. Hartford, CT 06108
------------------------------
Date: 3 Jul 87 12:43:39 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <958@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes:
> On ailist cugini@icst-ecf.arpa writes:
> > why say that icons, but not categorical representations or symbols
> > are/must be invertible? Isn't it just a vacuous tautology to claim
> > that icons are invertible wrt to the information they preserve, but
> > not wrt the information they lose?... there's information loss (many
> > to one mapping) at each stage of the game ...
In Harnad's response he does not answer the question "why?" He
only repeats the statement with reference to his own model.
Harnad probably has either a real problem or a contribution to
the solution of one. But when he writes about it, the verbal
problems conceal it, because he insists on using symbols that
are neither grounded nor consensual. We make no progress unless
we learn what his terms mean, and either use them or avoid them.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 3 Jul 87 19:26:40 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem: "Fuzzy" categories?
In Article 176-8 of comp.cog-eng: franka@mmintl.UUCP (Frank Adams)
of Multimate International, E. Hartford, CT.writes:
> I don't believe there are any truly "all-or-none" categories. There are
> always, at least potentially, ambiguous cases... no "100% accuracy
> every time"... how do you know that "graded" categories are less
> fundamental than the other kind?
On the face of it, this sounds self-contradictory, since you state
that you don't believe "the other kind" exists. But let's talk common sense.
Most of our object categories are indeed all-or-none, not graded. A
penguin is not a bird as a matter of degree. It's a bird, period. And
if we're capable of making that judgment reliably and categorically,
then there must be something about our transactions with penguins that
allows us to do so. In the case of sensory categories, I'm claiming
that a sufficient set of sensory features is what allows as to make
reliable all-or-none judgments; and in the case of higher-order
categories, I claim they are grounded in the sensory ones (and their
features).
I don't deny that graded categories exist too (e.g., "big," "smart"), but
those are not the ones under consideration here. And, yes, I
hypothesize that all-or-none categories are more fundamental in the
problem of categorization and its underlying mechanisms than graded
categories. I also do not deny that regions of uncertainty (and even
arbitrariness) -- natural and contrived -- exist, but I do not think that
those regions are representative of the mechanisms underlying successful
categorization.
The book under discussion ("Categorical Perception: The Groundwork of
Cognition") is concerned with the problem of how graded sensory continua
become segmented into bounded all-or-none categories (e.g., colors,
semitones). This is accomplished by establishing upper and lower
thresholds for regions of the continuum. These thresholds, I must
point out, are FEATURES, and they are detected by feature-detectors.
The rest is a matter of grain: If you are speaking at the level of
resolution of our sensory acuity (the "jnd" or just-noticeable-difference),
then there is always a region of uncertainty at the border of a category,
dependent on the accuracy and sensitivity of the threshold-detector.
But discrimination grain is not the right level of analysis for
questions about higher-order sensory categories, and all-or-none
categorization in general. The case for the putative "gradedness" of
"penguin"'s membership in the category "bird" is surely not being
based on the limits of sensory acuity. If it is, I'll concede at once,
and add that that sort of gradedness is trivial; the categorization
problem is concerned with identification grain, not discrimination grain.
All categories will of course be fuzzy at the limits of our sensory
resolution capacity. My own grounding hypothesis BEGINS with
bounded sensory categories (modulo threshold uncertainty) and attempts
to ground the rest of our category hierarchy bottom-up on those.
Finally, as I've stressed in responses to others, there's one other
form of category uncertainty I'm quite prepared to concede, but that
likewise fails to imply that category membership is a matter of
degree: All categories -- true graded ones as well as all-or-none ones
-- are provisional and approximate, relative to the context of
interconfusable members and nonmembers that have been sampled to date. If
the sample ever turns out to have been nonrepresentative, the feature-set that
was sufficient to generate successful sorting in the old context must
be revised and updated to handle the new, wider context. Anomalies and
ambiguities that had never occurred before must now be handled. But what
happens next (if all-or-none sorting performance can be successfully
re-attained at all) is just the same as with the initial category learning
in the old context: A set of features must be found that is sufficient to
subserve correct performance in the extended context. The approximation
must be tightened. This open-endedness of all of our categories, however, is
really just a symptom of inductive risk rather than of graded representations.
> "Analog" means "invertible". The invertible properties of a
> representation are those properties which it preserves...[This
> sounds] tautologically true of *all* representations.
For the reply to this, see my response to Cugini, whose criticism you
cite. Sensory icons need only be invertible with the discriminable properties
of the sensory projection. There is no circularity in this. And in a dedicated
system invertibility at various stages may well be a matter of degree, but
this has nothing to do with the issue of graded/nongraded category membership,
which is much more concerned with selective NONinvertibility.
> It is quite possible to make all-or-none judgements based on graded
> features [e.g., thermostats]
Apart from (1) thresholds (which are features, and which I discussed
earlier), (2) probabilistic features so robust as to be effectively
all-or-none, and (3) gerrymandered examples (usually playing on the
finiteness of the cases sampled, and the underdetermination of the
winning feature set), can you give examples?
> "chair"... with no back... [is a] "stool"... Now vary the size
> of the back
The linguist Labov, with examples such as cup/bowl, specialized in
finding graded regions for seemingly all-or-none categories.
Categorization is always a context-dependent, "compared-to-what"
task . Features must reliably sort the members from the nonmembers
they can be confused with. Sometimes nature cooperates and gives us
natural discontinuities (horses could have graded continuously into
zebras). Where she does not, we have only one recourse left: an
all-or-none sensory threshold at some point in the continuum. One can
always generate a real or hypothetical continuum that would foil our
current feature-detectors and necessitate a threshold-detector. Such
cases are only interesting if they are representative of the actual
context of confusable alternatives that our category representation
must resolve. Otherwise they are not informative about our actual
current (provisional) feature-set.
> I see nothing about "all-or-none" categories which is not explainable
> by arbitrary cutoffs of graded sensory data... [and] avoid[ing]
> borderline situations.
Neither do I. (Most feature-detection problems, by the way, do not
arise from the need to place thresholds along true continua, but from
the problem of underdetermination: there are so many features that it
is hard to find a set that will reliably sort the confusable
alternatives into their proper all-or-none categories.)
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 5 Jul 87 00:51:01 GMT
From: sher@cs.rochester.edu (David Sher)
Subject: Re: The symbol grounding problem: "Fuzzy" categories?
In article <967@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
>Most of our object categories are indeed all-or-none, not graded. A
>penguin is not a bird as a matter of degree. It's a bird, period.
Just for the record is this an off hand statement or are you speaking
as an expert when you say most of our categories are all or none. Do
you have some psychology experiments that measure the size of human
category spaces and using a metric on them shows that most categories
are of this form? Can I quote you on this? Personally I have trouble
imagining how to test such a claim but psychologists are clever
fellows.
--
-David Sher
sher@rochester
{ seismo , allegra }!rochester!sher
------------------------------
Date: 5 Jul 87 04:52:30 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem: "Fuzzy" categories?
In Article 185 of comp.cog-eng sher@rochester.arpa (David Sher) of U of
Rochester, CS Dept, Rochester, NY responded as follows to my claim that
"Most of our object categories are indeed all-or-none, not graded. A penguin
is not a bird as a matter of degree. It's a bird, period." --
> Personally I have trouble imagining how to test such a claim...
Try sampling concrete nouns in a dictionary.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 5 Jul 87 05:29:02 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem
In Article 184 of comp.cog-eng: adam@gec-mi-at.co.uk (Adam Quantrill)
of Marconi Instruments Ltd., St. Albans, UK writes:
> It seems to me that the Symbol Grounding problem is a red herring.
> If I took a partially self-learning program and data (P & D) that had
> learnt from a computer with 'sense organs', and ran it on a computer
> without, would the program's output become symbolically ungrounded?...
> [or] if I myself wrote P & D without running it on a computer at all?
This begs two of the central questions that have been raised in
this discussion: (1) Can one speak of grounding in a toy device (i.e.,
a device with performance capacities less than those needed to pass
the Total Turing Test)? (2) Could the TTT be passed by just a symbol
manipulating module connected to transducers and effectors? If a
device that could pass the TTT were cut off from its transducers, it
would be like the philosophers' "brain in a vat" -- which is not
obviously a digital computer running programs.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 5 Jul 87 02:47:25 GMT
From: ihnp4!twitch!homxb!houdi!marty1@ucbvax.Berkeley.EDU
(M.BRILLIANT)
Subject: Re: The symbol grounding problem
In article <605@gec-mi-at.co.uk>, adam@gec-mi-at.co.uk (Adam Quantrill) writes:
> It seems to me that the Symbol Grounding problem is a red herring.
As one who was drawn into a problem that is not my own, let me
try answering that disinterestedly. To begin with, a "red
herring" is something drawn across the trail that distracts the
pursuer from the real goal. Would Adam tell us what his real
goal is?
Actually, my own real goal, from which I was distracted by the
symbol grounding problem, was an expert system that would (like
Adam's last example) ground its symbols only in terminal I/O.
But that's a red herring in the symbol grounding problem.
..... If I took a partially self-learning program and data (P & D)
that had learnt from a computer with 'sense organs', and ran it on a
computer without, would the program's output become symbolically
ungrounded?
No, because the symbolic data was (were?) learned from sensory
data to begin with - like a sighted person who became blind.
Similarily, if I myself wrote P & D without running it on a computer
at all, [and came] up with identical P & D by analysis. Does that
make the original P & D running on the computer with
'sense organs' symbolically ungrounded?
No, as long as the original program learned its symbolic data
from its own sensory data, not by having them defined by a
person in terms of his or her sensory data.
A computer can always interact via the keyboard & terminal
screen, (if those are the only 'sense organs'), grounding its
internal symbols via people who react to the output, and provide
further stimulus.
That's less challenging and less useful than true symbol
grounding. One problem that requires symbol grounding (more
useful and less ambitious than the Total Turing Test) is a
seeing-eye robot: a machine with artificial vision that could
guide a blind person by giving and taking verbal instructions.
It might use a Braille keyboard instead of speech, but the
"terminal I/O" must be "grounded" in visual data from, and
constructive interaction with, the tangible world. The robot
could learn words for its visual data by talking to people who
could see, but it would still have to relate the verbal symbols
to visual data, and give meaning to the symbols in terms of its
ultimate goal (keeping the blind person out of trouble).
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
End of AIList Digest
********************
∂06-Jul-87 1229 LAWS@Stripe.SRI.Com AIList Digest V5 #170
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 6 Jul 87 12:29:25 PDT
Date: Mon 6 Jul 1987 01:02-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #170
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 6 Jul 1987 Volume 5 : Issue 170
Today's Topics:
Theory - Symbol Grounding Metadiscussion
----------------------------------------------------------------------
Date: 3 Jul 87 01:02:48 GMT
From: mnetor!utzoo!utgpu!water!watmath!watcgl!ksbooth@seismo.css.gov
Subject: Re: The symbol grounding problem - please start your own
newsgroup
Hooray for David Harwood.
------------------------------
Date: 5 Jul 87 05:39:38 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem - please start your own
newsgroup
In Article 186 of comp.cog-eng, ksbooth@watcgl.waterloo.edu (Kelly Booth)
of U. of Waterloo, Ontario writes:
> Hooray for David Harwood.
David Harwood has made two very rude requests that I stop the symbol grounding
discussion, which I ignored. But perhaps it's time to take a poll. Please send
me e-mail indicating whether or not you find the discussion useful and worth
continuing. I promise to post and abide by the results.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 5 Jul 87 05:05:53 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: The symbol grounding problem: 3 routes to grounding
needed?
In Article 181 of comp.cog-eng berleant@ut-sally.UUCP (Dan Berleant)
of U. Texas CS Dept., Austin, Texas writes:
> may not be much difference between a classical view augmented to...
> *arbitrary* boolean expressions of features...and a probabilistic view
I agree that such a probabilistic representation is possible. Now the question
is, will it work, is it economical (and is it right)? Note, though, that even
graded (probabilistic) individual features must yield an all-or-none feature
SET. So even this would not be evidence of graded membership. (I don't think
you'd disagree.)
> need to...explain...typicality and reaction time results...interpreted
> as supporting probabilistic and exemplar-based category representations
Yes, but it seems only appropriate that we should account for the
categorization performance capacity itself before we worry about its
fine tuning. (Experimental psychology has a long history of bypassing
the difficult but real problems underlying our behavioral capacities
and fixating instead on fine-tuning.)
> may [be] 2 representations for categories: a 'core' of defining features
> and a heuristic categorizer... 2 pathways [grounding] categories
You may be right. It's an empirical question whether the heuristic component
will be necessary to generate successful performance. If it is, it is still not
obvious that the need for it would be directly related to the grounding problem.
> [Re:] Anders Weinstein [on] the semantic meaning of...thunder/...`angry
> gods nearby'...: The terms in the definition presumably are grounded
> via the 2 routes discussed above... [now] Consider a sentence with 2
> variables, e.g. FISH SWIM... Obviously, many bindings would satisfy
> the sentence. [But]...by adding many more true sentences, the possible
> bindings of the variables become much more constrained.
I accepted this argument the first time you made it. I think it's
right; I've made similar degrees-of-freedom arguments against Quine myself,
and I've cross-referenced your point in my response to Weinstein. I
don't believe, though, that this reduction of the degrees of freedom
of the interpretation (even to zero) is sufficient to ground a symbol
system. Even if there's only one way to interpret an entire language,
the decryption must be performed; and it's not enough that the mapping
should be into a natural language (that's still a symbol/symbol
relation, leaving the entire edifice hanging by a skyhook of derived
rather than intrinsic meaning). The mapping must be into the world.
But, in any case, you seem to rescind your degrees-of-freedom
argument immediately after you make it:
> On the other hand... Maybe a Martian [or] your neighbor... could
> figure out [an alternative] way to do it consistently... but as long
> as you both agree on the truthfulness of all the sentences you are
> mutually aware of, there is no way to tell! Shades of the Turing test...
This is standard Quinean indeterminacy again! So you don't believe
your degrees-of-freedom argument! Well I do. And it's partly because
of degrees-of-freedom and convergence considerations that I am so
sanguine about the TTT. (I called this the "convergence" argument in
"Minds, Machines and Searle": There may be many arbitrary ways to
successfully model a toy performance, but as you move toward the TTT,
the degrees of freedom shrink.)
> would this method of 'grounding' the semantics of categories be
> sufficient to do the job? Only in theory? Potentially in practice? ...
I think it would not (although it may simplify the task of grounding
somewhat). Even if only one interpretation is possible, it must be
intrinsic, not derivative.
> Are you assuming a representation of episodes (more generally,
> exemplars) that is iconic rather than symbolic?
Yes, I am assuming that episodic representations would be iconic. This is
related to the distinction in the human memory literature concering
"episodic" vs. "semantic" memory. The former involves qualitative
recall for when something happened (e.g., Kennedy's assassination) and
the particulars of the experience; the latter involves only the
*product* of past learning (e.g., knowing how to ride a bicycle, do
calculus or speak English). It's much harder to imagine how the former
could be symbolic (although, of course, there are "constructive" memory
theories such as Bartlett's that suggest that what we remember as an
episode may be based on reconstruction and logical inference...).
> *no* category representation method can generate category boundaries
> when there is significant interconfusability among categories!
I would be very interested to know your basis for this assertion
(particularly as "significant interconfusability" is not exactly a
quantitative predicate). If I had said "complete indeterminacy," or even
"radical underdetermination" (say, features that would require
exponential search to find), I could understand why you would say this
-- but significant interconfusability... Can you remember first
looking at cellular structures under a microscope? Have you seen Inuit snow
taxonomies? Have you ever tried serious mushroom-picking? Or chicken
sexing? Or tumor identification? Art classification? Or, to pick some
more abstract examples: paleolinguistic taxonomy? ideological
typologizing? or problems at the creative frontiers of pure mathematics?
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 5 Jul 87 18:34:37 GMT
From: bloom-beacon!bolasov@husc6.harvard.edu (Benjamin I Olasov)
Subject: Re: The symbol grounding problem - please start your own
newsgroup
I personally don't feel that it's Harwood's place to make a
recommendation such as the one he made (rude or otherwise). If the
discussion is germaine to the stated purpose(s) of the newsgroup
(which it is), and is carried on in an intellectually responsible
manner (which it certainly has been), why should it not be allowed to
continue?
Isn't the solution for those who don't find the topic interesting to
simply not read the messages bearing that topic on the subject line?
After all, any number of discussions can be carried on concurrently.
------------------------------
Date: 5 Jul 87 17:31:15 GMT
From: harwood@cvl.umd.edu (David Harwood)
Subject: Re: The symbol grounding problem - please start your own
newsgroup
In article <977@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
>David Harwood has made two very rude requests that I stop the symbol grounding
>discussion, which I ignored. But perhaps it's time to take a poll. Please send
>me e-mail indicating whether or not you find the discussion useful and worth
>continuing. I promise to post and abide by the results.
As I have told others, I don't really want you to quit posting
altogether to this or other newsgroups. And I would be glad for you to
form your own group for your "dialogues," such as they are. But I have
to complain about your insufferable postings on two grounds: (i) they
have nearly nothing to do with computer science, nevertheless preoccupy
comp.ai with your various and sundry self-referential, just vaguely
intelligible musings; (ii) your postings, in my opinion, are the heighth,
width, and breadth of unresponsive, presumptuous, and condescending
twaddle. Worse than anything which I've read which was contributed as
an original article to BBS, for example. Of course, as my colleagues
advise, BBS does not publish my research - and is unlikely to in the
near distant future. Such are the wages of public sin.)
Yes, my two replies to you were sarcastic (more than "very rude,"
I think; I never recieved any serious complaint about either, perhaps
because others knew what I meant, even if they did not quite agree with
me.)
Let me give you back an illustration of how you talk. You just
a moment ago replied to D.S. who question what psychological evidence you
have that perceptual categorization is usually "all-or-none." He seemed to
question your expertese as a perceptual psychologist. (I might add that
you have tried to impress us with generally slighting remarks about
psychologists as well as computer scientists, but this may be a "policy
of controversy" (perhaps used to secure competitive funding - who knows;-).
Anyway, your one line reply did not answer the question, but was
more of a silly riposte, something like, "Check the concrete nouns in
your dictionary." He asks you something, and you ignore this. Or, taking
you seriously, you tell him to go supply his own evidence for your claims.
(I suppose that if he were your research assistant, that you would sagely
explain that a "concrete" noun is one admitting "all-or-none" categorization.)
I have no prejudice concerning your views - to be sure, I rarely
can make sense of them. But I wish you would simply take your own advise,
"Check the concrete nouns of your dictionary," and use them sometimes to
good effect in your postings. Define your abstractions. Cite evidence for
your speculations. Do not cite your own damn article like a parrot. If you
prefer, post the damn thing, which has got to be more intelligible than
your recent stuff, and we will be done with this particular "symbol grounding
problem."
Then I will look forward to your new occasional postings, even
in this newsgroup.
David Harwood
------------------------------
Date: 5 Jul 87 21:48:28 GMT
From: harwood@cvl.umd.edu (David Harwood)
Subject: Re: The symbol grounding problem - please start your own
newsgroup
Letter sent by email to Stevan Harnad (with postscript added)
re his postings to comp.ai about "the symbol grounding problem."
I don't want you to quit posting altogether - I would just like
you to realize that you are hogging comp.ai with what seems, to me at least,
to be mostly pompous and unintelligible postings, that have very little to
do with computer science. I heard from a student colleague, who is not opposed
to a "cognitive science" viewpoint (if this means anything to you), that the
first thing you did to explain your views at a recent colloquim was make
reference to your net discussions.
My oh my, either you are an modest comedian, or these dialogues of
yours - why - if even they be blarney and posing of feathers - why they be
verily verily immortal.
You have made your views, whatever these are, resoundingly reknown
- by, I suppose, half or more of the recent volume of comp.ai. I simply wish
you'd pipe down for awhile, especially about your "symbol grounding problem."
I will be especially verily verily glad to see you post the source
code which implements your theoretical improvements; this should keep us off
the streets for awhile; and I will try to be first to applaud your success.
David Harwood
Computer Vision Laboratory
Center for Automation Research
University of Maryland
My views are simply my own. Please note all typos and mistakes, as I prepare
to publish an edition (with permission which is surely forthcoming) of
_Recent Contributions to the Dialogue de Problem Profundo Symbo-Grundo:
New Foundations and New Vocations in Computer Science_.
[This postscript added to my letter emailed S.H.]
------------------------------
Date: 6 Jul 87 02:19:01 GMT
From: bloom-beacon!bolasov@husc6.harvard.edu (Benjamin I Olasov)
Subject: Re: The symbol grounding problem - please start your own
newsgroup
In article <2328@cvl.umd.edu> harwood@cvl.UUCP (David Harwood) writes:
> I don't want you to quit posting altogether - I would just like
>you to realize that you are hogging comp.ai with what seems, to me at least,
>to be mostly pompous and unintelligible postings, that have very little to
>do with computer science.
↑↑↑↑↑↑↑↑ ↑↑↑↑↑↑↑
This point should not need to be made, but this newsgroup doesn't deal
exclusively with computer science issues per se. Many important
contributions to AI, after all, have come from outside the field of CS,
as conventionally understood- much of Marvin Minsky's research for example,
is not restricted to CS, and yet has significant implications for AI.
Some of the most challenging and interesting problems of AI are philosophical
in nature. I frankly don't see why this fact should disturb anyone.
Perhaps if more of us pursued our theoretical models with comparable rigor
to that with which Mr. Harnad pursues his, the balance of topics represented
on comp.ai might shift .....
------------------------------
End of AIList Digest
********************
∂06-Jul-87 1551 LAWS@Stripe.SRI.Com AIList Digest V5 #171
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 6 Jul 87 15:51:22 PDT
Date: Mon 6 Jul 1987 01:07-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #171
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 6 Jul 1987 Volume 5 : Issue 171
Today's Topics:
Queries - AI Expert Source for Hopfield Nets &
Liability of Expert System Developers,
Programming - Software Reuse,
Scientific Method - Psychology vs. AI & Why AI is not a Science
----------------------------------------------------------------------
Date: 2 Jul 87 20:45:24 GMT
From: ucsdhub!dcdwest!benson@sdcsvax.ucsd.edu (Peter Benson)
Subject: AI Expert source for Hopfield Nets
I am looking for the source mentioned in Bill Thompson's
article on Hopfield Nets in the July, 1987 issue of
AI Expert magazine. At one time, someone was posting all the
sources, but has, apparently, stopped. Could that person,
or some like-minded citizen post the source for this
Travelling Salesman solution.
Thanks in advance !!
--
Peter Benson | ITT Defense Communications Division
(619)578-3080 | 10060 Carroll Canyon Road
ucbvax!sdcsvax!dcdwest!benson | San Diego, CA 92131
dcdwest!benson@SDCSVAX.EDU |
------------------------------
Date: 5 Jul 87 22:00:58 GMT
From: bloom-beacon!bolasov@husc6.harvard.edu (Benjamin I Olasov)
Subject: Liability of Expert System Developers
I'm told that a hearing is now underway which would set a legal precedent
for determining the extent of liability to be borne by software developers
for the performance of expert systems authored by them. Does anyone have
details on this?
------------------------------
Date: 4 Jul 87 21:19:48 GMT
From: jbn@glacier.stanford.edu (John B. Nagle)
Subject: Re: Software Reuse -- do we really know what it is ? (long)
The trouble with this idea is that we have no good way to express
algorithms "abstractly". Much effort was put into attempting to do so
in the late 1970s, when it looked as if program verification was going to
work. We know now that algebraic specifications (of the Parnas/SRI type)
are only marginally shorter than the programs they specify, and much
less readable. Mechanical verification that programs match formal
specifications turned out not to be particularly useful for this reason.
(It is, however, quite possible; a few working systems have been
constructed, including one by myself and several others described in
ACM POPL 83).
We will have an acceptable notation for algorithms when each algorithm
in Knuth's "Art of Computer Programming" is available in machineable form
and can be used without manual modification for most applications for which
the algorithm is applicable. As an exercise for the reader, try writing
a few of Knuth's algorithms as Ada generics and make them available to
others, and find out if they can use them without modifying the source
text of the generics.
In practice, there now is a modest industry in reusable software
components; see the ads in any issue of Computer Language. Worth noting
is that most of these components are in C.
John Nagle
------------------------------
Date: 02 Jul 87 09:55:35 EDT (Thu)
From: sas@bfly-vax.bbn.com
Subject: Don Norman's comments on time perception and AI
philosophizing
Actually, many studies have been done on time perception. One rather
interesting one reported some years back in Science showed that time
and size scale together. Smaller models (mannikins in a model office
setting) move faster. It was kind of neat paper to read.
I agree that AI suffers from a decidedly non-scientific approach.
Even when theoretical physicists flame about liberated quarks and the
anthropic principle, they usually have some experiments in mind. In
the AI world we get thousands of bytes on the "symbol grounding
problem" and very little evidence that symbols have anything to do
with intelligence and thought. (How's that for Drano[tm] on troubled
waters?)
There have been a lot of neat papers on animal (and human) learning
coming out lately. Maybe the biological brain hackers will get us
somewhere - at least they look for evidence.
Probably overstating my case,
Seth
------------------------------
Date: Thu 2 Jul 87 12:10:08-PDT
From: PAT <HAYES@SPAR-20.ARPA>
Subject: Re: AIList Digest V5 #165
HEY, DON!!! RIGHT ON!
Pat Hayes
[Donald Norman, I presume. -- KIL]
------------------------------
Date: 3 Jul 87 18:01:33 GMT
From: nosc!humu!uhccux!stampe@sdcsvax.ucsd.edu (David Stampe)
Subject: Submission for comp-ai-digest
Path: uhccux!stampe
From: stampe@uhccux.UUCP (David Stampe)
Newsgroups: comp.ai.digest
Subject: Re: On how AI answers psychological issues
Message-ID: <651@uhccux.UUCP>
Date: 3 Jul 87 18:01:33 GMT
References: <8706301418.AA08078@sunl.ICS>
Distribution: world
Organization: U. of Hawaii, Manoa (Honolulu)
Lines: 44
In-reply-to: norman%ics@SDCSVAX.UCSD.EDU's message of 30 Jun 87 14:18:40 GMT
norman%ics@SDCSVAX.UCSD.EDU (Donald A. Norman) writes:
> Thinking about "how the mind works" is fun, but not science, not
> the way to get to the correct answer.
In fact it's the ONLY way to get the correct answer. Experiments
don't design themselves, and they don't interpret their own results.
We don't see with outward eyes or hear with outward ears alone. The
outward perception or behavior does not exist without the inward one.
If you practice your remembered violin in your imagination, while your
actual violin is being repaired, you, as well as the violin, may sound
much better when the repairs are finished.
I am a linguist. I write a tongue twister on the board that they
haven't hear before: 'Unique New York Unique New York Unique New
York....' My students watch silently, but when I ask them what errors
this tongue twister induces, they immediately name the very errors I
discovered before class, when I tried to pronounce it aloud. You
didn't have to say it aloud, either, did you?
It is not introspection that is AI's trouble. It is that an expert
system, for example, isn't likely to model expertise correctly until
it is designed by someone who is himself the expert, or who knows how
to discover the nature of the expert's typically unconscious wisdom.
Linguistics has struggled for over a century to develop tools for
learning how human beings acquire and use language. It seems likely
that a comparable struggle will be required learn how the expert
diagnostician, welder, draftsman, or reference librarian does what he
or she does.
I often feel that when a good student of language takes a job building
a natural language interface for some AI project, in her work --
though it may be viewed by others in the project as marginal, if not
menial -- she is more likely to turn up something of scientific import
than are those working on the core of the project. This is just
because she has spent years learning to learn how experts -- in this
case language users -- do what they do. On the other hand, she is not
likely to believe that programs can realistically model much of the
human linguistic faculty, at least in the imaginable future. For
example, computer parsers presuppose grammars. But it is not clear
whether children, the only devices so far known to have mastered any
natural language, come equipped with any analogous utilities.
David Stampe, Linguistics, Univ. of Hawaii
------------------------------
Date: Thu, 2 Jul 87 22:36:05 edt
From: amsler@flash.bellcore.com (Robert Amsler)
Subject: Re: thinking about thinking not being science
I think Don Norman's argument is true for cognitive psychologists,
but may not be true for AI researchers. The reason is that the two
groups seek different answers. If AI were only the task of finding
out how people work, then it would be valid to regard armschair
reasoning as an invalid form of speculation. One can study
people directly (this is the old ``stop arguing over the number of
teeth in a horse's mouth and go outside and count them'' argument).
However, some AI researchers are really engineers at heart. The
question then is not how do people work, but how could processes
providing comparable performance quality to those of humans be made
to work in technological implementations. `Could' is important.
Airplanes are clearly not very good imitations of birds. They are
too big, for one thing. They have wheels instead of feet, and the
list goes on and on (no feathers!). Speculating about flight might
lead to building other types of aircraft (as certainly those now
humorous old films of early aviation experiments show), but it would
certainly be a bad procedure to follow to understand birds and how
they fly. Speculating about why the $6M man appears as he does
while running is a tad off the beaten path for AILIST, but that
process of speculation is hardly worthless for arriving at novel
means of representing memory or perception FOR COMPUTER SYSTEMS.
Lets not squabble over the wrong issue. The problem is that the
imagery of the $6M man's running is just too weak as a springboard for
much directed thought and the messages (including my own earlier
reply) are just rambling off in directions more appropriate to
SF-Lovers than AILIST. I do agree that the CURRENT discussion isn't
likely to lead anywhere--but not that the method of armchair
speculation is invalid in AI.
------------------------------
Date: Fri, 3 Jul 87 07:29:41 pdt
From: norman%ics@sdcsvax.ucsd.edu (Donald A. Norman)
Subject: Why AI is not a science
A private message to me in response to my recent AI List posting,
coupled with general observations lead me to realize why so many of us
otherwise friendly folks in the sciences that neighbor AI can be so
frustrated with AI's casual attitude toward theory: AI is not a science
and its practitioners are woefuly untutored in scientific method.
At the recent MIT conference on Foundations of AI, Nils Nilsson stated
that AI was not a science, that it had no empirical content, nor
claims to emperical content, that it said nothing of any emperical
value. AI, stated Nilsson, was engineering. No more, no less. (And
with that statement he left to catch an airplane, stopping further
discussion.) I objected to the statement, but now that I consider it
more deeply, I believe it to be correct and to reflect the
dissatisfaction people like me (i.e., "real scientists") feel with AI.
The problem is that most folks in AI think they are scientists and
think they have the competence to pronounce scientific theories about
almost any topic, but especially about psychology, neuroscience, or
language. Note that perfectly sensible dsciplines such as
mathematics and philosophy are also not sciences, at least not in the
normal intrerpretation of that word. It is no crime not to be a
science. The crime is to think you are one when you aren't.
AI worries a lot about methods and techniques, with many books and
articles devoted to these issues. But by methods and techniques I
mean such topics as the representation of knowledge, logic,
programming, control structures, etc. None of this method includes
anything about content. And there is the flaw: nobody in the field of
Artificial Intelligence speaks of what it means to study intelligence,
of what scientific methods are appropriate, what emprical methods are
relevant, what theories mean, and how they are to be tested. All the
other sciences worry a lot about these issues, about methodology,
about the meaning of theory and what the appropriate data collection
methods might be. AI is not a science in this sense of the word.
Read any standard text on AI: Nilsson or Winston or Rich or
even the multi-volumned handbook. Nothing on what it means to
test a theory, to compare it with others, nothing on what
constitutes evidence, or with how to conduct experiments.
Look at any science and you will find lots of books on
experimental method, on the evaluation of theory. That is why
statistics are so important in psychology or biology or
physics, or why counterexamples are so important in
linguistics. Not a word on these issues in AI.
The result is that practitioners of AI have no experience in the
complexity of experimental data, no understanding of scientific
method. They feel content to argue their points through rhetoric,
example, and the demonstration of programs that mimic behavior thought
to be relevant. Formal proof methods are used to describe the formal
power of systems, but this rigor in the mathematical analysis is not
matched by any similar rigor of theoretical analysis and evaluation
for the content.
This is why other sciences think that folks in AI are off-the-wall,
uneducated in scientific methodology (the truth is that they are), and
completely incompetent at the doing of science, no matter how
brilliant at the development of mathematics of representation or
formal programming methods. AI will contribute to the A, but will
not contribute to the I unless and until it becomes a science and
develops an appreciation for the experimental methods of science. AI
might very well develop its own methods -- I am not trying to argue
that existing methods of existing sciences are necessarily appropriate
-- but at the moment, there is only clever argumentation and proof
through made-up example (the technical expression for this is "thought
experiment" or "gadanken experiment"). Gedanken experiments are not
accepted methods in science: they are simply suggestive for a source
of ideas, not evidence at the end.
don norman
Donald A. Norman
Institute for Cognitive Science C-015
University of California, San Diego
La Jolla, California 92093
norman@nprdc.arpa {decvax,ucbvax,ihnp4}!sdcsvax!ics!norman
norman@sdics.ucsd.edu norman%sdics.ucsd.edu@RELAY.CS.NET
------------------------------
End of AIList Digest
********************
∂09-Jul-87 2331 LAWS@Stripe.SRI.Com AIList Digest V5 #172
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 9 Jul 87 23:30:57 PDT
Date: Wed 8 Jul 1987 17:22-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #172
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 9 Jul 1987 Volume 5 : Issue 172
Today's Topics:
Query - Xlisp,
Programming - Software Reuse & Abstract Specifications,
Scientific Method - Is AI a Science?
----------------------------------------------------------------------
Date: Tue 7 Jul 87 09:18:25-PDT
From: BEASLEY@EDWARDS-2060.ARPA
Subject: xlisp
If anyone has any information or has heard any information about using
XLISP (eXperimental LISP) on the PC, please send me that information at
beasley@edwards-2060.ARPA. Thank you.
------------------------------
Date: 6 Jul 87 05:28:23 GMT
From: vrdxhq!verdix!ogcvax!dinucci@seismo.css.gov (David C. DiNucci)
Subject: Re: Software Reuse -- do we really know what it is ? (long)
In article <titan.668> ijd@camcon.co.uk (Ian Dickinson) writes:
>> Xref: camcon comp.lang.ada:166 comp.lang.misc:164
>Hence a solution: we somehow encode _abstractions_ of the ideas and place
>these in the library - in a form which also supplies some knowledge about the
>way that they should be used. The corollary of this is that we need more
>sophisticated methods for using the specifications in the library.
>(Semi)-automated transformations seem to be the answer to me.
>
>Thus we start out with a correct (or so assumed) specification, apply
>correctness-preserving transormation operators, and so end up with a correct
>implementation in our native tongue (Ada, Prolog etc, as you will). The
>transformations can be interactively guided to fit the precise circumstance.
>[Credit] I originally got this idea from my supervisor: Dr Colin Runciman
>@ University of York.
In his Phd thesis defense here at Oregon Graduate Center, Dennis
Volpano presented his package that did basically this. Though certainly
not of production quality, the system was able to take an abstraction
of a stack and, as a separate module, a description of a language and
data types within the language (in this case integer array and file,
if I remember correctly), and produce code which was an instantiation
of the abstraction - a stack implemented as an array or as a file.
I haven't actually read Dennis' thesis, so I don't know what the
limitations of constraints on his approach are. I believe he is
currently employed in Texas at MCC.
---
Dave DiNucci dinucci@Oregon-Grad
------------------------------
Date: 7 Jul 87 02:21:06 GMT
From: vrdxhq!verdix!ogcvax!pase@seismo.css.gov (Douglas M. Pase)
Subject: Re: Software Reuse (short title)
In article <glacier.17113> jbn@glacier.UUCP (John B. Nagle) writes:
>
> The trouble with this idea is that we have no good way to express
>algorithms "abstractly". [...]
Well, I'm not sure just where the limits are, but polymorphic types can go
a long way towards what you have been describing. It seems that a uniform
notation for operators + the ability to define additional operators +
polymorphically typed structures are about all you need. Several functional
languages already provide an adequate basis for these features. One such
language is called LML, or Lazy ML. Current language definitions tend to
concentrate on the novel features rather than attempt to make LML a full-blown
"production" language, and therefore may be missing some of your favorite
features. However, my point is that we may well be closer to your objective
than some of us realize.
I apologize for the brevity of this article -- if I have been too vague,
send me e-mail and I will be more specific.
--
Doug Pase -- ...ucbvax!tektronix!ogcvax!pase or pase@Oregon-Grad.csnet
------------------------------
Date: 7 Jul 87 15:18:32 GMT
From: debray@arizona.edu (Saumya Debray)
Subject: Automatic implementation of abstract specifications
In article <1337@ogcvax.UUCP>, dinucci@ogcvax.UUCP (David C. DiNucci) writes:
> In his Phd thesis defense here at Oregon Graduate Center, Dennis
> Volpano presented his package that did basically this. Though certainly
> not of production quality, the system was able to take an abstraction
> of a stack and, as a separate module, a description of a language and
> data types within the language (in this case integer array and file,
> if I remember correctly), and produce code which was an instantiation
> of the abstraction - a stack implemented as an array or as a file.
I believe there was quite a bit of work on this sort of stuff at MIT
earlier in the decade. E.g. there was a PhD thesis [ca. 1983] by
M. K. Srivas titled "Automatic Implementation of Abstract Data Types"
(or something close to it). The idea, if I remember correctly, was to
take sets of equations specifying the "source" ADT (e.g. stack) and the
"target" ADT (e.g. array), and map the source into the target.
--
Saumya Debray CS Department, University of Arizona, Tucson
internet: debray@arizona.edu
uucp: {allegra, cmcl2, ihnp4} !arizona!debray
------------------------------
Date: Mon, 6 Jul 87 10:06:05 MDT
From: shebs%orion@cs.utah.edu (Stanley T. Shebs)
Subject: AI vs Scientific Method
I can understand Don Norman's unhappiness about the lack of scientific method
in AI - from a practical point of view, the lack of well-understood criteria
for validity means that refereeing of publications is unlikely to be very
objective... :-(
The scientific method is a two-edged sword, however. Not only does it define
what is interesting, but what is uninteresting - if you can't devise a con-
trolled experiment varying just a single parameter, you can't say anything
about a phenomenon. A good scientist will perhaps be able to come up with
a different experiment, but if stymied enough times, he/she is likely to move
on to something else (at about the same time the grant money runs out :-) ).
Established sciences like chemistry have an advantage in that the parameters
most likely to be of interest are already known; for instance temperature,
percentages of compounds, types of catalysts, and so forth. What do we have
for studying intelligence? Hardly anything! Yes, I know psychologists have
plenty of experimental techniques, but the quality is pretty low compared to
the "hard sciences". A truly accurate psychology experiment would involve
raising cloned children in a computer-controlled environment for 18 years.
Even then, you're getting minute amounts of data about incredibly complex
systems, with no way to know if the parameters you're varying are even
relevant.
There's some consolation to be gained from the history of science/technology.
The established fields did not spring full-blown from some genius' head;
each started out as a confused mix of engineering, science, and speculation.
Most stayed that way until the late 19th or early 20th century. If you don't
believe me, look at an 18th or early 19th century scientific journal (most
libraries have a few). Quite amusing, in fact very similar to contemporary
AI work. For instance, an article on electric eels from about 1780 featured
the observations that a slave grabbing the eel got a stronger shock on the
second grab, and that the shock could be felt through a wooden container.
No tables or charts or voltmeter readings :-).
My suggestion is to not get too worked up about scientific methods in AI.
It's worth thinking about, but people in other fields have spent centuries
establishing their methods, and there's no reason to suppose it will take any
less for AI.
stan shebs
shebs@cs.utah.edu
------------------------------
Date: Mon, 6 Jul 1987 16:29 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #170
I would like to see that discussion of "symbol grounding" reduced to
much smaller proportions because I think it is not very relevant to
AI, CS, or psychology. To understand my reason, you'd have to read
"Society of Mind", which argues that this approach is obsolete because
it recapitulates the "single agent" concept of mind that dominates
traditional philosophy. For example, the idea of "categorizing"
perceptions is, I think, mainly an artifact of language; different
parts of the brain deal with inputs in different ways, in parallel.
In SOM I suggest many alternative ways to think about thinking and, in
several sections, I also suggest reasons why the single agent idea has
such a powerful grip on us. I realize that it might seem self-serving
for me to advocate discussing Society of Mind instead. I would have
presented my arguments in reply to Harnad, but they would have been
too long-winded and the book is readily available.
------------------------------
Date: Mon, 6 Jul 87 18:25:51 EDT
From: Jim Hendler <hendler@brillig.umd.edu>
Subject: Re: AIList Digest V5 #171
While I have some quibbles with Don N.'s long statement on AI viz (or
vs.) science, I think he gets close to what I have felt a key point
for a long time -- that the move towards formalism in AI, while important
in the change of AI from a pre-science (alchemy was Drew McDermott's
term) to a science, is not enough. For a field to make the transition
an experimental methodology is needed. In AI we have the potential
to decide what counts as experimentation (with implementation being
an important consideration) but have not really made any serious
strides in that direction. When I publish work on planning and
claim ``my system makes better choices than <name of favorite
planning program's>'' I cannot verify this other than by showing
some examples that my system handles that <other>'s can't. But of
course, there is no way of establishing that <other> couldn't do
examples mine can't and etc. Instead we can end up forming camps of
beliefs (the standard proof methodology in AI) and arguing -- sometimes
for the better, sometimes for the worse.
While I have no solution for this, I think it is an important issue
for consideration, and I thank Don for provoking this discussion.
-Jim Hendler
------------------------------
Date: Tue, 7 Jul 1987 01:11 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #171
At the end of that long and angry flame, I think D.Norman unwittingly
hit upon what made him so mad:
> Gedanken experiments are not accepted methods in science: they are
> simply suggestive for a source of ideas, not evidence at the end.
And that's just what AI has provided these last thirty years - a
source of ideas that were missing from psychology in the century
before. Representation theories, planning procedures, heuristic
methods, hundreds of such. The history of previous psychology is ripe
with "proved" hypotheses, few of which were worth a damn, and many of
which were refuted by Norman himself. Now "cognitive psychology" -
which I claim and Norman will predictably deny (see there: a testable
hypothesis!) is largely based on AI theories and experiments - is
taking over at last - as a result of those suggestions for ideas.
------------------------------
Date: Tue, 7 Jul 87 01:28 MST
From: "Paul B. Rauschelbach" <Rauschelbach@HIS-PHOENIX-MULTICS.ARPA>
Subject: What is science
I normally only observe this discussion, but Don Norman's pomposity
struck a nerve. The first objection I have is to his statement that
mathematics and philosophy are not sciences "in the normal
interpretation of the word." The Webster's definition (a fairly normal
interpretation) is: "accumulated knowledge systematized and formulated
with reference to the discovery of general truths or the operation of
general laws." This certainly applies to both.
The next problem is his statement that AI people think they're
scientists. He seemed to believe that it was a science until Nils Nilsson
told him the obvious. AI, like it's name implies, is a product, not a
phenomenon, not an occurence of nature to be described. The problem is the
creation of a product, an engineering problem. The preservation of theory is
far from an engineer's mind. The engineer uses theory to describe possible
solutions. If an engineer comes across a possible solution that has not been
addressed by theory, s/he may get his hands a little dirty before the
"scientists" take control of it. It seems to me that much of the talk in this
discussion is of a hypothetical nature, one of the elements of THE SCIENTIFIC
METHOD he was defending. This is a good place for that portion of the
method, as well as statement of the problem. The experimentation is left to
the psychologists, neurologists, etc. I see no one but scientists claiming
to be scientists, and I hear AI people shouting, "Yeah, but how do you code
it?" or "What doohickey will do that?" Implementation of theory. I have also
read discussion of the testing of implementation. Come to think of it,
engineering also fits the definition of science.
Both things, implementation and theory have been and should be discussed here.
If they intermingle, this can only be healthy, even if somewhat confusing. I
hope we can both get down off our respective high horses now.
Paul Rauschelbach
Honeywell Bull
P.O. Box 8000, M/S K55, Phoenix, AZ 85006
(602) 862-3650
pbr%pco@BCO-MULTICS.ARPA
Disclaimer: The opinions expressed above are mine, and not endorsed by
Honeywell Bull.
------------------------------
Date: 7 Jul 87 08:41:33 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Why AI is not a science
Date: Fri, 3 Jul 87 07:29:41 pdt
From: norman%ics@sdcsvax.ucsd.edu (Donald A. Norman)
I started out writing a message that said this message was
97% true, but that there was an arguable 3%, namely:
The problem is that most folks in AI think they are scientists * * *
I was going to pick a nit with the word "most".
Then, I remembered that the AAAI-86 Proceedings were
split into a "Science" track and an "Engineering" track,
the former being about half again as thick as the latter...
------------------------------
Date: 8 Jul 87 01:37:17 GMT
From: munnari!goanna.oz!jlc@uunet.UU.NET (J.L Cybulski)
Subject: Re: Why AI is not a science
Don Norman says that AI is not a Science!
Is Mathematics a science or is it not?
No experiments, no comparisons, thus they are not Sciences!
Perhaps both AI and Maths are Arts, ie. creative disciplines.
Both adhere to their own rigour and methods.
Both talk about hypothetical worlds.
Both are used by researchers from other disciplines as tools,
Maths is used to formally describe natural phenomena,
AI is used to construct computable models of these phenomena.
So, where is the problem?
Hmmm, I think some of the AI researchers wander into the
areas of their incompetence and they impose their quasi-theories
on the specialists from other scientific domains. Some of those
quasi-theories are later reworked and adopted by the same specialists.
Is it, then, good or bad? It seems that lack of scientific constraints
may be helpful in advancing knowledge about the principles of science,
it seems that the greatest breakthroughs in Science come from those
who were regarded as unorthodox in their methods.
May be AI is such unorthodox Science, or perhaps an Art.
Let us keep AI this way!
Jacob L. Cybulski
------------------------------
Date: 07-Jul-1987 0829
From: billmers%aiag.DEC@decwrl.dec.com (Meyer Billmers, AI
Applications Group)
Subject: Re: AIList Digest V5 #171
Don Norman writes that "AI will contribute to the A, but will not
contribute to the I unless and until it becomes a science...".
Alas, since physics is a science and mathematics is not one, I guess the
latter cannot help contribute to the former unless and until mathematicians
develop an appreciation for the experimental methods of science. Ironic
that throughout history mathematics has been called the queen of sciences
(except, of course, by Prof. Norman).
Indeed, physics is a case in point. There are experimental physicists, but
there are also theoretical ones who formulate, posulate and hypothesize
about things they cannot measure or observe. Are these men not scientists?
And there are those who observe and measure that which has no theoretical
foundation (astrologists hypothesize about people's fortunes; would any
amount of experimentation turn astrology into a science?). I believe the
mix between theoretical underpinnings and scientific method makes for
science. The line is not hard and fast.
By my definition, AI has the right attributes to make it a science. There
are theoretically underpinnings in several domains (cognitive science,
theory of computation, information theory, neurobiology...) and yes, even an
experimental nature. Researchers postulate theories (of representation, of
implementation) but virtually every Ph.D. thesis also builds a working
program to test the theory.
If AI researchers seem to be weak in the disciplines of the scientific
method I submit it is because the phenomena they are trying to understand
are far more complex and elusive of definition that that of most science.
This is not a reason to deny AI the title of science, but rather a reason
to increase our efforts to understand the field. With this understanding
will come an increasingly visible scientific discipline.
------------------------------
End of AIList Digest
********************
∂10-Jul-87 0310 LAWS@Stripe.SRI.Com AIList Digest V5 #172
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Jul 87 03:09:55 PDT
Date: Wed 8 Jul 1987 17:22-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #172
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 9 Jul 1987 Volume 5 : Issue 172
Today's Topics:
Query - Xlisp,
Programming - Software Reuse & Abstract Specifications,
Scientific Method - Is AI a Science?
----------------------------------------------------------------------
Date: Tue 7 Jul 87 09:18:25-PDT
From: BEASLEY@EDWARDS-2060.ARPA
Subject: xlisp
If anyone has any information or has heard any information about using
XLISP (eXperimental LISP) on the PC, please send me that information at
beasley@edwards-2060.ARPA. Thank you.
------------------------------
Date: 6 Jul 87 05:28:23 GMT
From: vrdxhq!verdix!ogcvax!dinucci@seismo.css.gov (David C. DiNucci)
Subject: Re: Software Reuse -- do we really know what it is ? (long)
In article <titan.668> ijd@camcon.co.uk (Ian Dickinson) writes:
>> Xref: camcon comp.lang.ada:166 comp.lang.misc:164
>Hence a solution: we somehow encode _abstractions_ of the ideas and place
>these in the library - in a form which also supplies some knowledge about the
>way that they should be used. The corollary of this is that we need more
>sophisticated methods for using the specifications in the library.
>(Semi)-automated transformations seem to be the answer to me.
>
>Thus we start out with a correct (or so assumed) specification, apply
>correctness-preserving transormation operators, and so end up with a correct
>implementation in our native tongue (Ada, Prolog etc, as you will). The
>transformations can be interactively guided to fit the precise circumstance.
>[Credit] I originally got this idea from my supervisor: Dr Colin Runciman
>@ University of York.
In his Phd thesis defense here at Oregon Graduate Center, Dennis
Volpano presented his package that did basically this. Though certainly
not of production quality, the system was able to take an abstraction
of a stack and, as a separate module, a description of a language and
data types within the language (in this case integer array and file,
if I remember correctly), and produce code which was an instantiation
of the abstraction - a stack implemented as an array or as a file.
I haven't actually read Dennis' thesis, so I don't know what the
limitations of constraints on his approach are. I believe he is
currently employed in Texas at MCC.
---
Dave DiNucci dinucci@Oregon-Grad
------------------------------
Date: 7 Jul 87 02:21:06 GMT
From: vrdxhq!verdix!ogcvax!pase@seismo.css.gov (Douglas M. Pase)
Subject: Re: Software Reuse (short title)
In article <glacier.17113> jbn@glacier.UUCP (John B. Nagle) writes:
>
> The trouble with this idea is that we have no good way to express
>algorithms "abstractly". [...]
Well, I'm not sure just where the limits are, but polymorphic types can go
a long way towards what you have been describing. It seems that a uniform
notation for operators + the ability to define additional operators +
polymorphically typed structures are about all you need. Several functional
languages already provide an adequate basis for these features. One such
language is called LML, or Lazy ML. Current language definitions tend to
concentrate on the novel features rather than attempt to make LML a full-blown
"production" language, and therefore may be missing some of your favorite
features. However, my point is that we may well be closer to your objective
than some of us realize.
I apologize for the brevity of this article -- if I have been too vague,
send me e-mail and I will be more specific.
--
Doug Pase -- ...ucbvax!tektronix!ogcvax!pase or pase@Oregon-Grad.csnet
------------------------------
Date: 7 Jul 87 15:18:32 GMT
From: debray@arizona.edu (Saumya Debray)
Subject: Automatic implementation of abstract specifications
In article <1337@ogcvax.UUCP>, dinucci@ogcvax.UUCP (David C. DiNucci) writes:
> In his Phd thesis defense here at Oregon Graduate Center, Dennis
> Volpano presented his package that did basically this. Though certainly
> not of production quality, the system was able to take an abstraction
> of a stack and, as a separate module, a description of a language and
> data types within the language (in this case integer array and file,
> if I remember correctly), and produce code which was an instantiation
> of the abstraction - a stack implemented as an array or as a file.
I believe there was quite a bit of work on this sort of stuff at MIT
earlier in the decade. E.g. there was a PhD thesis [ca. 1983] by
M. K. Srivas titled "Automatic Implementation of Abstract Data Types"
(or something close to it). The idea, if I remember correctly, was to
take sets of equations specifying the "source" ADT (e.g. stack) and the
"target" ADT (e.g. array), and map the source into the target.
--
Saumya Debray CS Department, University of Arizona, Tucson
internet: debray@arizona.edu
uucp: {allegra, cmcl2, ihnp4} !arizona!debray
------------------------------
Date: Mon, 6 Jul 87 10:06:05 MDT
From: shebs%orion@cs.utah.edu (Stanley T. Shebs)
Subject: AI vs Scientific Method
I can understand Don Norman's unhappiness about the lack of scientific method
in AI - from a practical point of view, the lack of well-understood criteria
for validity means that refereeing of publications is unlikely to be very
objective... :-(
The scientific method is a two-edged sword, however. Not only does it define
what is interesting, but what is uninteresting - if you can't devise a con-
trolled experiment varying just a single parameter, you can't say anything
about a phenomenon. A good scientist will perhaps be able to come up with
a different experiment, but if stymied enough times, he/she is likely to move
on to something else (at about the same time the grant money runs out :-) ).
Established sciences like chemistry have an advantage in that the parameters
most likely to be of interest are already known; for instance temperature,
percentages of compounds, types of catalysts, and so forth. What do we have
for studying intelligence? Hardly anything! Yes, I know psychologists have
plenty of experimental techniques, but the quality is pretty low compared to
the "hard sciences". A truly accurate psychology experiment would involve
raising cloned children in a computer-controlled environment for 18 years.
Even then, you're getting minute amounts of data about incredibly complex
systems, with no way to know if the parameters you're varying are even
relevant.
There's some consolation to be gained from the history of science/technology.
The established fields did not spring full-blown from some genius' head;
each started out as a confused mix of engineering, science, and speculation.
Most stayed that way until the late 19th or early 20th century. If you don't
believe me, look at an 18th or early 19th century scientific journal (most
libraries have a few). Quite amusing, in fact very similar to contemporary
AI work. For instance, an article on electric eels from about 1780 featured
the observations that a slave grabbing the eel got a stronger shock on the
second grab, and that the shock could be felt through a wooden container.
No tables or charts or voltmeter readings :-).
My suggestion is to not get too worked up about scientific methods in AI.
It's worth thinking about, but people in other fields have spent centuries
establishing their methods, and there's no reason to suppose it will take any
less for AI.
stan shebs
shebs@cs.utah.edu
------------------------------
Date: Mon, 6 Jul 1987 16:29 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #170
I would like to see that discussion of "symbol grounding" reduced to
much smaller proportions because I think it is not very relevant to
AI, CS, or psychology. To understand my reason, you'd have to read
"Society of Mind", which argues that this approach is obsolete because
it recapitulates the "single agent" concept of mind that dominates
traditional philosophy. For example, the idea of "categorizing"
perceptions is, I think, mainly an artifact of language; different
parts of the brain deal with inputs in different ways, in parallel.
In SOM I suggest many alternative ways to think about thinking and, in
several sections, I also suggest reasons why the single agent idea has
such a powerful grip on us. I realize that it might seem self-serving
for me to advocate discussing Society of Mind instead. I would have
presented my arguments in reply to Harnad, but they would have been
too long-winded and the book is readily available.
------------------------------
Date: Mon, 6 Jul 87 18:25:51 EDT
From: Jim Hendler <hendler@brillig.umd.edu>
Subject: Re: AIList Digest V5 #171
While I have some quibbles with Don N.'s long statement on AI viz (or
vs.) science, I think he gets close to what I have felt a key point
for a long time -- that the move towards formalism in AI, while important
in the change of AI from a pre-science (alchemy was Drew McDermott's
term) to a science, is not enough. For a field to make the transition
an experimental methodology is needed. In AI we have the potential
to decide what counts as experimentation (with implementation being
an important consideration) but have not really made any serious
strides in that direction. When I publish work on planning and
claim ``my system makes better choices than <name of favorite
planning program's>'' I cannot verify this other than by showing
some examples that my system handles that <other>'s can't. But of
course, there is no way of establishing that <other> couldn't do
examples mine can't and etc. Instead we can end up forming camps of
beliefs (the standard proof methodology in AI) and arguing -- sometimes
for the better, sometimes for the worse.
While I have no solution for this, I think it is an important issue
for consideration, and I thank Don for provoking this discussion.
-Jim Hendler
------------------------------
Date: Tue, 7 Jul 1987 01:11 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #171
At the end of that long and angry flame, I think D.Norman unwittingly
hit upon what made him so mad:
> Gedanken experiments are not accepted methods in science: they are
> simply suggestive for a source of ideas, not evidence at the end.
And that's just what AI has provided these last thirty years - a
source of ideas that were missing from psychology in the century
before. Representation theories, planning procedures, heuristic
methods, hundreds of such. The history of previous psychology is ripe
with "proved" hypotheses, few of which were worth a damn, and many of
which were refuted by Norman himself. Now "cognitive psychology" -
which I claim and Norman will predictably deny (see there: a testable
hypothesis!) is largely based on AI theories and experiments - is
taking over at last - as a result of those suggestions for ideas.
------------------------------
Date: Tue, 7 Jul 87 01:28 MST
From: "Paul B. Rauschelbach" <Rauschelbach@HIS-PHOENIX-MULTICS.ARPA>
Subject: What is science
I normally only observe this discussion, but Don Norman's pomposity
struck a nerve. The first objection I have is to his statement that
mathematics and philosophy are not sciences "in the normal
interpretation of the word." The Webster's definition (a fairly normal
interpretation) is: "accumulated knowledge systematized and formulated
with reference to the discovery of general truths or the operation of
general laws." This certainly applies to both.
The next problem is his statement that AI people think they're
scientists. He seemed to believe that it was a science until Nils Nilsson
told him the obvious. AI, like it's name implies, is a product, not a
phenomenon, not an occurence of nature to be described. The problem is the
creation of a product, an engineering problem. The preservation of theory is
far from an engineer's mind. The engineer uses theory to describe possible
solutions. If an engineer comes across a possible solution that has not been
addressed by theory, s/he may get his hands a little dirty before the
"scientists" take control of it. It seems to me that much of the talk in this
discussion is of a hypothetical nature, one of the elements of THE SCIENTIFIC
METHOD he was defending. This is a good place for that portion of the
method, as well as statement of the problem. The experimentation is left to
the psychologists, neurologists, etc. I see no one but scientists claiming
to be scientists, and I hear AI people shouting, "Yeah, but how do you code
it?" or "What doohickey will do that?" Implementation of theory. I have also
read discussion of the testing of implementation. Come to think of it,
engineering also fits the definition of science.
Both things, implementation and theory have been and should be discussed here.
If they intermingle, this can only be healthy, even if somewhat confusing. I
hope we can both get down off our respective high horses now.
Paul Rauschelbach
Honeywell Bull
P.O. Box 8000, M/S K55, Phoenix, AZ 85006
(602) 862-3650
pbr%pco@BCO-MULTICS.ARPA
Disclaimer: The opinions expressed above are mine, and not endorsed by
Honeywell Bull.
------------------------------
Date: 7 Jul 87 08:41:33 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Why AI is not a science
Date: Fri, 3 Jul 87 07:29:41 pdt
From: norman%ics@sdcsvax.ucsd.edu (Donald A. Norman)
I started out writing a message that said this message was
97% true, but that there was an arguable 3%, namely:
The problem is that most folks in AI think they are scientists * * *
I was going to pick a nit with the word "most".
Then, I remembered that the AAAI-86 Proceedings were
split into a "Science" track and an "Engineering" track,
the former being about half again as thick as the latter...
------------------------------
Date: 8 Jul 87 01:37:17 GMT
From: munnari!goanna.oz!jlc@uunet.UU.NET (J.L Cybulski)
Subject: Re: Why AI is not a science
Don Norman says that AI is not a Science!
Is Mathematics a science or is it not?
No experiments, no comparisons, thus they are not Sciences!
Perhaps both AI and Maths are Arts, ie. creative disciplines.
Both adhere to their own rigour and methods.
Both talk about hypothetical worlds.
Both are used by researchers from other disciplines as tools,
Maths is used to formally describe natural phenomena,
AI is used to construct computable models of these phenomena.
So, where is the problem?
Hmmm, I think some of the AI researchers wander into the
areas of their incompetence and they impose their quasi-theories
on the specialists from other scientific domains. Some of those
quasi-theories are later reworked and adopted by the same specialists.
Is it, then, good or bad? It seems that lack of scientific constraints
may be helpful in advancing knowledge about the principles of science,
it seems that the greatest breakthroughs in Science come from those
who were regarded as unorthodox in their methods.
May be AI is such unorthodox Science, or perhaps an Art.
Let us keep AI this way!
Jacob L. Cybulski
------------------------------
Date: 07-Jul-1987 0829
From: billmers%aiag.DEC@decwrl.dec.com (Meyer Billmers, AI
Applications Group)
Subject: Re: AIList Digest V5 #171
Don Norman writes that "AI will contribute to the A, but will not
contribute to the I unless and until it becomes a science...".
Alas, since physics is a science and mathematics is not one, I guess the
latter cannot help contribute to the former unless and until mathematicians
develop an appreciation for the experimental methods of science. Ironic
that throughout history mathematics has been called the queen of sciences
(except, of course, by Prof. Norman).
Indeed, physics is a case in point. There are experimental physicists, but
there are also theoretical ones who formulate, posulate and hypothesize
about things they cannot measure or observe. Are these men not scientists?
And there are those who observe and measure that which has no theoretical
foundation (astrologists hypothesize about people's fortunes; would any
amount of experimentation turn astrology into a science?). I believe the
mix between theoretical underpinnings and scientific method makes for
science. The line is not hard and fast.
By my definition, AI has the right attributes to make it a science. There
are theoretically underpinnings in several domains (cognitive science,
theory of computation, information theory, neurobiology...) and yes, even an
experimental nature. Researchers postulate theories (of representation, of
implementation) but virtually every Ph.D. thesis also builds a working
program to test the theory.
If AI researchers seem to be weak in the disciplines of the scientific
method I submit it is because the phenomena they are trying to understand
are far more complex and elusive of definition that that of most science.
This is not a reason to deny AI the title of science, but rather a reason
to increase our efforts to understand the field. With this understanding
will come an increasingly visible scientific discipline.
------------------------------
Date: Mon, 6 Jul 87 17:19:38 PDT
From: cottrell%ics@sdcsvax.ucsd.edu (Gary Cottrell)
Subject: Re: thinking about thinking not being science
In article <8707030236.AA29872@flash.bellcore.com>
amsler@FLASH.BELLCORE.COM (Robert Amsler) writes:
>I think Don Norman's argument is true for cognitive psychologists,
>but may not be true for AI researchers. The reason is that the two
>groups seek different answers. [....] Speculating about flight might
>lead to building other types of aircraft (as certainly those now
>humorous old films of early aviation experiments show), but it would
>certainly be a bad procedure to follow to understand birds and how
>they fly.
In fact, the Wright Brothers spent quite a bit of time studying how
birds fly, and as a recent Scientific American notes, we may still have
a lot to learn from natural systems. A piece of Dennis Conner's boat was
based on a whale's tailfin.
I think Don's point was that many times AI researchers spend a lot of time
theorizing about how humans work, and then use that as justification for
their designs for AI systems, without ever consulting the facts.
It is certainly true that Cognitive Scientists and AI researchers are at
different ends of a spectrum (from NI (Natural Intelligence) to AI), but it
would be foolish for AI researchers not to take hints from the best example
of an intelligient being we have. On the other hand, it is not appropriate
for a medical expert system to make the same mistakes doctors do - sometimes
a criterion for a "good" cognitive model.
gary cottrell
Institute for Cognitive Science C-015
UCSD,
La Jolla, Ca. 92093
cottrell@nprdc.arpa (ARPA) (or perhaps cottrell%ics@cs.ucsd.edu)
{ucbvax,decvax,akgua,dcdwest}!sdcsvax!sdics!cottrell (USENET)
**********************************************************************
THE FUTURE'S SO BRIGHT I GOTTA WEAR SHADES - Timbuk 3
**********************************************************************
------------------------------
End of AIList Digest
********************
∂10-Jul-87 0632 LAWS@Stripe.SRI.Com AIList Digest V5 #173
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Jul 87 06:32:02 PDT
Date: Wed 8 Jul 1987 17:35-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #173
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 9 Jul 1987 Volume 5 : Issue 173
Today's Topics:
Humor - Symbol Grounding References,
Theory - Fuzzy Categories,
Policy - Symbol-Grounding Metadiscussion
----------------------------------------------------------------------
Date: 7-JUL-1987 15:50:42
From: UBACW59%cu.bbk.ac.uk@Cs.Ucl.AC.UK
Subject: References Required.
Does anyone have any pointers to the "symbol grounding problem" or some
such area? Searches in the literature have proved fruitless.
The Joka.
------------------------------
Date: 7 Jul 1987 11:00-EDT
From: Spencer.Star@h.cs.cmu.edu
Subject: Re: AIList Digest V5 #169
> ...a penguin is not a bird of degree...
The point of view that a bird IS a bird, and a rose IS a rose, has
limited usefulness. If the question that we are trying to answer is
seen as how a person will classify a penguin after having seen one for
the first time, I think the answer is clear. A large number of people
would not classify a penguin as a bird. A program would likely be more
successful at imitating a human response if it based its response on
the features of the human answering the query as well as the features
of the concept it was trying to recognize. Whether a penguin is a bird
then becomes quite dependent on context as well as a simple relation
between features and classes.
------------------------------
Date: 8 Jul 87 16:08:27 GMT
From: sunybcs!dmark@ames.arpa (David M. Mark)
Subject: Re: The symbol grounding problem: "Fuzzy" categories?
In article <974@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>
>
>In Article 185 of comp.cog-eng sher@rochester.arpa (David Sher) of U of
>Rochester, CS Dept, Rochester, NY responded as follows to my claim that
>"Most of our object categories are indeed all-or-none, not graded. A penguin
>is not a bird as a matter of degree. It's a bird, period." --
>
>> Personally I have trouble imagining how to test such a claim...
>
>Try sampling concrete nouns in a dictionary.
Well, a dictionary may not always be a good authority fro this sort of
thing. Last semester I led a graduate Geography seminar on the topic:
"What is a map?" If you check out dictionaries, the definitions seem
unambiguous, non-fuzzy, concrete. Even the question may seem foolish, since
"map" probably is a "basic-level" object/concept. However, we conducted
a number of experiments and found many ambiguous stimuli near the boundary
of the concept "map". Air photos and satellite images are an excellent
example: they fit the dictionary definition, and some people feel very
strongly that they *are* maps, others sharply reject that claim, etc.
Museum floor plans, topographic cross-profiles, digital cartographic
data files on tape, verbal driving directions for navigation, etc., are
just some examples of the ambiguous ("fuzzy"?) boundary of the concept
to which the English word "map" correctly applies. I strongly suspect
that "map" is not unique in this regard!
------------------------------
Date: Mon 6 Jul 87 16:18:12-PDT
From: PAT <HAYES@SPAR-20.ARPA>
Subject: Re: AIList Digest V5 #170
Talk about walking into a minefield, but here goes. Concerning the Harnad
grounding problem. This is lovely stuff, and I save every word for later
reading, but it does seem recently to have gone from interesting discussions
and arguments to a rather repetitive grinding over the main points again and
again. THe result is that Stevan is reduced to repeating himself and
reiterating his points in the face of what must seem to him to be increasing
stubbornness. I seem to be seeing more and more phrases like '..as I have
emphasised earlier..'. All of us who teach are familiar with the syndrome
where the 35th occurrence of the same error makes us more exasperated than the
first one did.
Let me suggest that perhaps nothing much new is being said
in these discussions any more, and certainly no-one is saying anything which
is going to cause Stevan to change any of his positions. Perhaps the right
thing to do is for people to send their comments directly to Harnad, and for
him to send us the selections which HE considers worth public airing, together
with his responses. That way we will be spared reading all this stuff which
is, apparently, of such low intellectual caliber, and Laws will have an easier
time, and public feelings will not get to the point which produces letters
like David Harwood's.
Just an idea.
Pat Hayes
------------------------------
Date: Mon, 6 Jul 87 16:56:06 PDT
From: cottrell%ics@sdcsvax.ucsd.edu (Gary Cottrell)
Subject: Automatic newsgroup creation to reduce aggravation
How about some software to automatically create newsgroups after a certain
amount of traffic with the same subject line? And an appropriate expiration
of the newsgroup after traffic dies down? Then people could decide to add
the newsgroup or not. E.g., comp.ai.symbol.grounding.. It doesn't even sound
hard enough to be called AI! I am a net.news.software.innocent, however.
gary cottrell
------------------------------
Date: Mon, 06 Jul 87 22:03:51 EST
From: Tim Daciuk <ACAD8023%RYERSON.BITNET@wiscvm.wisc.edu>
Subject: Symbol Grounding Problem
Having read the recent "discussion" regarding the Symbol Grounding Problem,
I would have to suggest that I tend to agree with Mr. Harwood. Though the
discussion which has taken place on this subject was interesting, it has
become, at least to me, tedious and boring. In addition, I think that any-
one joining AI-List at this point would find this topic almost impossible
to follow, due to the number of references to previous editions of the
journal, and due to the highly interactive mode which this discussion has
assumed. I do not think that a separate discussion should be started,
however, I would suggest that future Symbol Grounding Problem entries be
sorted to the bottom of the list. This would allow the list to continue
in publishing this important part of AI, and would allow those of us who
no longer have the stamina to ponder the implications of blue, green, blue-
green, etc., to quit at an appropriate time.
Would sorting the list with Symbol Grounding coming at the bottom be very
difficult Ken?
Tim Daciuk
Ryerson Polytechnical Institute
Toronto Ontario
Canada
[That's essentially what I've been doing, although lengthy conference
announcements sometimes get sorted even lower. I was holding all of
the symbol grounding discussion for the weekend, although that did
create some synchronization problems between messages sent to my
Arpanet mailbox and replies that went directly to Usenet. I have
usually published symbol grounding issues in separate digest issues,
making them easier to skip (or save). Usenet readers don't get the
benefit of that sorting, of course (but make up for it by eliminating
the digesting delay). Sorting to the true "bottom" of an infinite
discussion stream would seem a little extreme. -- KIL]
------------------------------
Date: 6 Jul 87 21:38:29 GMT
From: harwood@cvl.umd.edu (David Harwood)
Subject: An apology for being overly sarcastic
I want to apologize for being overly sarcastic with Mr. Harnad.
Although I consider my complaint about his postings to be justified, I am
sorry about my overly-sarcastic manner. For the record, this apology was
my own idea, not involving discussion with others. I simply felt fairly
guilty about my irritable responses. (Actually, it is only recently that
I've had a chance to read this newsgroup; it has been suggested that I
read the moderated newsgroup instead - without posting of course!)
\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\
Briefly responding to a posted reply by B.I. Olasov, also to
correspondence by email from D. Stampe (for different reasons):
In article <1071@bloom-beacon.MIT.EDU> bolasov@aphrodite.UUCP
(Benjamin I Olasov) writes:
[...]
>Some of the most challenging and interesting problems of AI are philosophical
>in nature. I frankly don't see why this fact should disturb anyone.
>
>Perhaps if more of us pursued our theoretical models with comparable rigor
>to that with which Mr. Harnad pursues his, the balance of topics represented
>on comp.ai might shift .....
As I tried to make clear - supplying fairly clear examples of his
posting style - it is definitely not Mr. Harnad's particular philosophy or
theoretical proclivity which irritated me - it was his manner of discussion
I was complaining about. (Just as others complained about my sarcasm, more
than the content of my complaint.) Among other things, for example, I
scarcely consider his arguments to be what you say "rigorous." Some of the
discussants themselves have complained, albeit politely, about his somewhat
idiosyncratic usage of terminology (among other things).
So you are mistaken in your suggestion about my complaint. Rigorous
use of very complex and abstract concepts is commonplace in many branches
of computer science, eg. semantic specification of languages executed by
parallel systems. The level of abstraction and rigor is not at all less
than in any area of inquiry, including philosophy or cognitive psychology.
On the other hand, I fully agree that both philosophy and psychology have
very important and relevant contributions to what is called "artificial
intelligence," although it seems to me that too much of the purported
interdisciplinary discussion is polemical and political rather than really
constructive. And I would add that much, even most, of AI's recent "advance"
has been nonsensical propaganda for funding, and devoid of theoretical
foundation.
Also, I would add that Mr. Harnad - what is clear by his
postings - is perhaps only superficially familiar with what are real
advances in symbolical "AI", eg development of very powerful systems for
automatic deduction, which have practical importance for all of "AI"
as well as have rigorous foundations. These surely are not entirely
founded on theories of human psychology or on speculative philosophy,
and probably should not be, since we would like to consider computing
machines which do some things according to specification, and better
than we do.
I realize very well that some areas of AI are very much
harder than others - computer vision comes to mind ;-) and it is
obvious to everyone concerned that we need both numerical and symbolical
algorithms and representations. (I will not get involved in discussing
what S.H. might mean by "symbolical", "analog", "invertible", and so
forth - I don't really know.)
I think it is also apparent that we might have yet
to consider some "connectionist" architectures and algorithms, which
perhaps do not admit any simple formal specification of input/output
relations. This would invite some philosophical speculation about
the adequacy of purely logical specification for development of
artificial intelligence. Conversely, we may already have sufficient
theoretical basis for 'creating' human-like artificial intelligence,
by functional simulation of neurons, although we do have the technology
(and moral sense I hope) to de-engineer a human brain. This will surely
happen in the distant future only depending on our technology and not
on major improvements in our theoretical understanding of neurons. The
situation might well be that we can recreate human intelligence which
we still largely cannot comprehend by formal specification. In part,
these means that psychology, theoretical "AI", even S.H.'s "Total
Turing Test" are loose ends as much as interdependent.
(As a religious person, I wonder about what this might mean -
I recall that an ancient interpretation of the Genesis story said that
when mankind ate of the fruit of the knowledge of good and evil - just
as the serpent claimed - mankind became endowed with a power like that
of God - that is, having the power to create and to destroy worlds. In
our times, our technology has surpassed our moral sensibilty - which
many computer sceientists say does not exist anyway. Of course, other
Jewish tradition has it that many worlds have already been destroyed
before this one. I'm not even sure that pursuit of "AI" technology
is such a good thing, if it contributes to our destruction or loss of
dignity. But who knows, except for God?)
Response to a reply by email:
\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\
Message-Id: <8707061548.AA11938@uhmanoa.ICS.HAWAII.EDU>
Date: Mon, 6 Jul 87 05:36:04-1000
From: seismo!scubed!sdcsvax!uhccux.UHCC.HAWAII.EDU!nosc!humu!stampe
(David Stampe)
To: harwood@cvl.umd.edu (David Harwood)
In-Reply-To: harwood@cvl.umd.edu's message of 5 Jul 87 21:48:28 GMT
Subject: Re: The symbol grounding problem - please start your own newsgroup
Status: R
You have now posted four messages to comp.ai containing nothing
but rude complaints about another's postings on symbol grounding.
They are not required reading, and they don't prevent you from
reading or posting on other topics. What you MAY NOT do is
disturb the newsgroup with irrelevant and loutish postings like
your last four. There are people who care about how University of
Maryland employees behave in public.
If I were you, I'd consider a public apology.
David Stampe, Univ. of Hawaii.
\\\\\\\\\\\\
I don't have any desire to prevent S.H. from posting,
as I have made clear. You are right that I should apologize for
being overly sarcastic. He deserved some of it, but I overdid
it.
I don't like your mention of my employment here - which
might be considered to be a threat, either to my employment or
to post things which you dislike, even sarcastic complaints. If
you did threaten me like this, you would have misjudged me, also
misjudged what would be my reaction.
In any case, you are right about the apology being due.
-David Harwood
------------------------------
Date: Tue, 7 Jul 87 07:33:49 edt
From: dg1v+@andrew.cmu.edu (David Greene)
Subject: handling the S.G.P issue
While some of the discussion has proven interesting, it is become burdensome
to sort through and rather recursive as arguments start focusing on what
prior arguments meant...
Perhaps a seperate bboard would be more appropriate. At the very least, Ken
Laws' suggestion that the arguments (and subject lines) be broken into
discrete categories seems to go a long way toward making this disscussion
palatable if not worthwhile.
Mr. Harnad might want to consider proposing a subject taxonomy prefaced with
"SGP".
David Greene
Carnegie Mellon
------------------------------
Date: Wed, 8 Jul 87 11:02:53 GMT
From: Caroline Knight <cdfk%hplb.csnet@RELAY.CS.NET>
Subject: Debating
As a so-far passive reader of the grounding problem debate via
AIList Digest I have at last been spurred to action:
For the proponents of a theory to be able to understand and discuss
the positive, the negative and the intersting aspects of it is a sign
of strength. For them to resort to personal name calling is not.
However I do have sympathy with those who have now started to put the
boot in. Especially with those who are tired of the language which
is frequently unclear and suspiciously polysyllabic.
A thought for those who honestly believe that an idea is wrong and the
holder of it would be better off without it:-
1. It is much easier to change one's mind and throw away useless ideas
if one has NOT been pushed to defend them tooth and nail.
2. Few ideas (or accepted theories) are completely correct. One can
gain more by simply acknowledging that an idea has flaws than by
trying to stretch it until it rips. Of course these anomolies might
trigger new ideas.
Caroline Knight
------------------------------
End of AIList Digest
********************
∂12-Jul-87 0159 LAWS@Stripe.SRI.Com AIList Digest V5 #174
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 Jul 87 01:58:59 PDT
Date: Sat 11 Jul 1987 22:31-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #174
To: AIList@STRIPE.SRI.COM
AIList Digest Sunday, 12 Jul 1987 Volume 5 : Issue 174
Today's Topics:
Seminars - Object-Oriented Databases (IBM) &
A Model for Distributed Planning (SU) &
Pengi: A Theory of Activity (UCB) &
Learning Conjunctive Concepts (SU),
Conferences - Concurrent Logic Programming, Open Systems Programming &
NEXUS meeting at AAAI &
Fifth International Machine Learning Conference &
Second International Conference on AI in Engineering
----------------------------------------------------------------------
Date: Wed, 01 Jul 87 13:54:22 PDT
From: IBM Almaden Research Center Calendar <CALENDAR@ibm.com>
Subject: Seminars - Object-Oriented Databases (IBM)
IBM Almaden Research Center
650 Harry Road
San Jose, CA 95120-6099
Excerpts from
RESEARCH CALENDAR
July 6 - 10, 1987
EFFICIENT SUPPORT FOR DERIVED OBJECTS IN RELATIONAL DATABASE SYSTEMS
E. Hanson, University of California at Berkeley
Comp. Sci. Sem. Tues., July 7 10:00 A.M. Room: B3-247
Recently, an incremental algorithm known as Algebraic View Maintenance
(AVM) was proposed for maintaining materialized copies of views.
Another incremental view maintenance algorithm called Rete View
Maintenance (RVM) is presented in this talk. RVM is based on the Rete
network, a type of discrimination network used to support efficient
forward chaining rule interpreters in expert systems shells. RVM is
known as a statically optimized view maintenance algorithm because the
execution plan for maintaining views is compiled in advance into the
Rete network. In contrast, AVM is dynamically optimized since an
execution plan for maintaining a view is found after each base
relation update that affects the view. A statically optimized
variation of AVM is also presented. Using algorithms for view
maintenance as a starting point, a collection of methods is proposed
to allow other kinds of derived objects to be maintained. These
include aggregates, database procedures, and views and procedures
containing aggregates.
Host: S. Finkelstein
EPIDEMIC ALGORITHMS FOR REPLICATED DATABASE MAINTENANCE
A. Demers, Xerox Palo Alto Research Center
Bay Area Syst. Symp. Fri., July 10 11:15 A.M. Room: Front Aud.
When a database is replicated at many sites, maintaining mutual
consistency among the sites in the face of updates is a significant
problem. This paper describes several randomized algorithms for
distributing updates and driving the replicas toward consistency. The
algorithms are very simple and require few guarantees from the
underlying communication system, yet they ensure that the effect of
every update is eventually reflected in all replicas. The cost and
performance of the algorithms are tuned by choosing appropriate
distributions in the randomization step. The algorithms are closely
analogous to epidemics, and the epidemiology literature aids in
understanding their behavior. One of the algorithms has been
implemented in the Clearinghouse servers of the Xerox Corporate
Internet, solving long-standing problems of high traffic and database
inconsistency.
Host: L.-F. Cabrera
OBJECT-ORIENTED INTERFACES TO RELATIONAL DATABASES
R. Cattell, SUN Microsystems
Bay Area Syst. Symp. Fri., July 10 1:30 P.M. Room: Front Aud.
Users of engineering workstations have requirements that traditional
database systems often do not address. A number of research projects
have recently examined addressing engineering requirements with
additional semantics that an "object-oriented" database system can
provide over a relational database system. My talk will focus on two
topics that have received relatively little attention: (1)
object-oriented end-user interfaces to databases exploiting the
capabilities of an engineering workstation, and (2) the *performance*
that these tools and engineering applications require from a database
system, without which additional semantics are useless. Examples will
be provided from some of our own database and user interface work
combining features of object-oriented and relational database models.
Users may graphically view and edit a database schema, view database
objects that span multiple relations, browse through databases by
pointing with a mouse, and display specialized objects such as
documents and images stored in a database. To quantify performance,
we have proposed a set of benchmarks that measure the simple
object-oriented operations that we believe engineering applications
most typically execute. I will discuss the results of performing
these benchmarks on several relational database systems, and the
implications for database system architecture for engineering
applications.
Host: L.-F. Cabrera
For further information on individual talks, please contact the host
listed above.
------------------------------
Date: Fri 3 Jul 87 14:17:35-PDT
From: Charlie Koo <KOO@Sushi.Stanford.EDU>
Subject: Seminar - A Model for Distributed Planning (SU)
A Model for Distributed Performance --
Synchronizing Plans among Intelligent Agents
via Communication
Charles C. Koo
July 8, Wednesday
9:00am - 10:00am
Room 352
Margaret Jacks Hall
In a society where a group of agents cooperate to achieve certain goals,
agents perform their tasks based on certain plans. Some tasks may interact
with tasks done by other agents. One way to coordinate those tasks is to let
a master planner generate a plan to begin with, and distribute tasks to
individual agents accordingly. However, there are two difficulties
with this approach, given that agents are resource-limited. First, the
master planner needs to know all the expertise that each agent has. The
amount of knowledge sharply increases with the number of specialties.
Second, the centralized planning process takes longer turn-around time than
if each agent plans for itself. This causes a lot of computing resources
not being utilized. Thus, distributed planning is desirable.
In this presentation, I will describe a model for synchronizing and
monitoring plans autonomously made by intelligent agents via communication.
The model suggests an planning algorithm that allows agents to plan in
parallel and then synchronize their plans via a commitment-based
communication vehicle. Represenation as well as reasoning issues in the
distributed environment will be addressed.
Communication plays an integral role in planning for synchronization
purposes. The communication vehicle includes a minimal set of protocols
that enables the synchronization, a set of communication operators and a
set of commitment tracking operators. The tracking operators provide means
to monitor the progress of plan execution, to prevent delays, and to modify
plans with less effort when delays happen. A deadlock detection scheme will
also be described.
------------------------------
Date: Mon, 6 Jul 87 08:48:17 PDT
From: teresa@ernie.berkeley.edu (teresa diaz)
Subject: Seminar - Pengi: A Theory of Activity (UCB)
Special Seminar
Phil Agre
Artificial Intelligence Laboratory
Massachusettes Institute of Technology
Pengi: An Implementation
of a
Theory of Activity
2:00 - 4:00 p.m.
Friday, July 10, 1987
1011 Evans Hall
AI has typically sought to understand the organized
nature of human activity in terms of the making and execu-
tion of plans. There can be no doubt that people use plans.
But before and beneath any plan-use is a continual process
of moment-to-moment improvisation. An improvising agent
might use a plan as one of its resources, just as it might
use a map, the materials on a kitchen counter, or a string
tied round its finger. David Chapman and I have been study-
ing the organization of the most common sort of activity,
the everyday, ordinary, routine, familiar, practiced,
unproblematic activity typified by activities like making
breakfast, driving to work, and stuffing envelopes. Our
theory describes the central role of improvisation and the
inherent orderliness, coherence, and laws of change of
improvised activity. The organization of everyday routine
activity makes strong suggestions about the organization of
the human cognitive architecture. In particular, one can
get along remarkably well with a peripheral system much as
described by Marr and Ullman and a central system made of
combinational logic. Chapman has built a system with such
an architecture. Called Pengi, it plays a commercial video
game called Pengo, in which a player controls a penguin to
defend itself against ornery and unpredictable bees. The
game requires both moderately complex tactics and constant
attention to opportunities and contingencies. I will out-
line our theory of activity, describe the Pengi program, and
indicate the directions of ongoing further research.
______________________________________________________________________
This information is also kept in usr/public/seminars.
------------------------------
From: Peter Karp <KARP@SUMEX-AIM.STANFORD.EDU>
Subject: Seminar - Learning Conjunctive Concepts (SU)
[Forwarded from the AFLB list.]
David Haussler from UC Santa Cruz will be giving a talk at the GRAIL
learning seminar this Thursday 7/9 at the Welch Road Conference room at
1:15. This is Room A1110 in Building A at 701 Welch Road, across from
the Stanford Barn.
Learning Conjunctive Concepts in Structural Domains
David Haussler
Department of Computer Science,
University of California, Santa Cruz, CA 95064
We study the problem of inductively learning conjunctive concepts from
examples on structural domains like the blocks world. This class of
concepts is formally defined and it is shown that even when each example
(positive or negative) is a two-object scene it is NP-complete to
determine if there is any consistent concept in this class. We
demonstrate how this result affects the feasibility of Mitchell's
version space approach and how it shows that it is unlikely that this
class of concepts is polynomially learnable from random examples in the
sense of Valiant. On the other hand, we show that for any fixed number
of objects per scene this class is polynomially learnable from random
examples if
(1) we allow a larger hypothesis space, or
(2) we answer cetrain types of queries in addition to providing
random examples.
------------------------------
Date: Mon, 6 Jul 87 14:43:14 PDT
From: Ken Kahn <Kahn.pa@Xerox.COM>
Reply-to: Kahn.pa@Xerox.COM
Subject: Conference - Concurrent Logic Programming, Open Systems
Programming
We are pleased to announce that Xerox PARC with support from AAAI will
host a workshop on concurrent logic programming, meta-programming, and
open systems programming on September 8 and 9 (the first business days
after the Fourth IEEE Symposium on Logic Programming in San Francisco).
Participation is by invitation only. The purpose of the workshop is to
promote informal scientific interchanges between members of various
laboratories doing research centered around concurrent logic programming
languages such Guarded Horn Clauses and KL1 at ICOT, Parlog at Imperial
College, FCP at Weizmann Institute of Science, and Vulcan at Xerox PARC.
Other topics of interest include meta-programming to support programming
abstractions and issues related to programming large open distributed
systems. The format of the workshop will consist of informal
presentations and discussions of work in progress. Presentations given
at the Fourth SLP are not to be repeated. There will be several panel
discussions on topics such as the different proposals for dataflow
synchronization in these languages, the role of meta-programming in
supporting abstractions, and why it is that there are several indepenent
implementation efforts for different dialects of concurrent logic
programming languages (or are they committed choice programming
langauges or open systems programming languages?).
Live demonstrations of software is encouraged. Available computers
include Xerox computers running Xerox Common Lisp, Vaxes under Unix
4.2BSD, Sun 3's, IBM PC's, and Macintoshes (SE and II).
We will not be covering participants' transportation or living expenses.
Lunches will be provided. We are expecting between 20 and 40
participants. If you are interested in coming, or know someone who
might be, please send a letter or electronic message indicating what you
would like to talk about or demo to:
Kenneth Kahn
Xerox PARC
3333 Coyote Hill Road
Palo Alto, CA 94304
(415) 494-4390
or
ArpaNet: Kahn.pa@Xerox.Com
Here's the preliminary list of invitees:
Ehud Shapiro, Weizmann Institute
Shmuel Klinger, Weizmann Institute
Vijay Saraswat, CMU
Leon Sterling, Case Western Reserve
Keith Clark, Imperial College
Steve Gregory, Imperial College
Andrew Davison, Imperial College
M. Huntbach, Imperial College
Mitsuhiro Kishimoto, Fujitsu
Y. Takayama, ICOT
A. Okumura, ICOT
Y. Kimura, ICOT
H. Seki, ICOT
T. Chikayama, ICOT
Kazonuri Ueda, ICOT
K. Furukawa, ICOT
Fernando Pereira, SRI
Tony Kusalik, Univ. of Saskatchewan
Leon Alkalaj, UCLA
Richard O'Keefe, Quintus Compter Systems
Bill Kornfeld
Lee Naish, Melbourne University
G. Levi, University of Pisa
Walter Wilson, IBM
M. Maher, IBM
Carl Hewitt, MIT
Will Clinger, Tektronics
Mark Miller, Xerox PARC
Danny Bobrow, Xerox PARC
Curtis Abbott, Xerox PARC
Ken Kahn, Xerox PARC
Eric Tribble, Xerox PARC
------------------------------
Date: Wed, 8 Jul 87 21:34:05 CDT
From: Dan Cerys <cerys@XX.LCS.MIT.EDU>
Subject: Conference - NEXUS meeting at AAAI
I don't recall seeing the following on these lists, but this meeting is
probably interesting to those interested in the TI Explorer. Please
post if it will appear before July 15.
The National Explorer Users' Society will meet during AAAI-87 in
Conference Room A of the Conference Center House at Seattle Center in
Seattle, Washington on Wednesday, the fifteenth of July from three
o'clock until six o'clock.
3:00 Welcome, Introductions, and Organization
Rich Acuff, Stanford University
3:20 Explorer II
Chuck Corley, Strategic Systems Engineering, TI
3:30 New Customer Support Offerings
Phil Campbell, Technical Support Center, TI
3:35 Release 3.0 Summary
Joyce Statz, User Interface Branch, TI
3:45 TGC, System Training
Jim Mynatt, AI Technical Consultant, TI
3:55 Networking, Namespace, and Generic Network Interface
Roger Frech, Networking Branch, TI
4:05 New Compiler Features
Merrill Cornish, member, Group Technical Staff, TI
4:15 Future Directions
Henry Carr, Explorer Software Development, TI
4:25 Educational Marketing Survey
John Alden, Educational Marketing, TI
4:30 Bi-Directional Question and Answer
5:10 Break into groups to talk about
Explorer II with Chuck Corley
LX/Multiprocessing with Kari Karhi
Networking with Roger Frech
TI Prolog with Dan Cerys
NEXUS, the National Explorer Users' Society, met last year as
the Explorer Users' Group at AAAI-86. The purpose of the group is to
share technical information about the Explorer. There are no dues or
membership fees. Membership is open to all Explorer users. To join,
send your name, address, phone number, and net address to either of the
following addresses:
Rich Acuff
Stanford University
251 Medical School Office Building
Stanford CA 94305
acuff@sumex-aim.stanford.edu
Glenda S. McKinney M/S 2201
Texas Instruments
P. O. Box 2909
Austin TX 78769
mckinney%dsg%ti-csl@csnet-relay
Conference Room A is on the second floor of the Conference
Center House, in the northeast corner. The Conference Center House is
across the plaza from the Coliseum.
------------------------------
Date: Fri, 10 Jul 87 11:01:21 EDT
From: laird@caen.engin.umich.edu (John Laird)
Subject: Conference - Fifth International Machine Learning Conference
CALL FOR PAPERS
FIFTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING
Ann Arbor, Michigan
June 12-15, 1988
The Fifth International Conference on Machine Learning will be held at the
University of Michigan, Ann Arbor, during June 12-15, 1988. The goal of the
conference is to bring together researchers from all areas of machine learning.
The conference will have open attendance and registration fees.
REVIEW CRITERIA
In order to ensure high quality papers, each submission will be reviewed
by two members of the program committee and judged on clarity, significance,
and originality. The best papers will be published in the proceedings, and
their authors will be invited to give a talk on their work or describe it at
a poster session. All submissions should contain new work, new results, or
major extensions to prior work. Summaries and overviews are discouraged.
The ideal paper will present a clear description of the learning task being
addressed and the proposed solution to that problem. If the paper describes
a running system, it should explain that system's representation of inputs
and outputs, its performance component, and its learning methods. It should
include a detailed example, as well as relate the work to earlier research.
Most important, all papers should include some evaluation of the work in the
form of substantive results. Papers are not required to take this form, but
authors are strongly encouraged to follow this format.
SUBMISSION OF PAPERS
Each paper must have a cover sheet with the title, authors' names, primary
author's address and telephone number, and an abstract of about 200 words. The
cover page should also give three keywords that specify the problem area,
general approach, and evaluation criteria. Some examples of each are:
PROBLEM AREA GENERAL APPROACH EVALUATION CRITERIA
Concept learning Genetic algorithms Empirical evaluation
Learning and planning Empirical methods Theoretical analysis
Language learning Explanation-based Psychological validity
Learning and design Connectionist
Machine discovery Analogical reasoning
The body of the paper must not exceed 13 double-spaced pages in twelve point
font, including figures but excluding references. Authors should send four
copies of their papers to:
Machine Learning Conference
Cognitive Science and Machine Intelligence Laboratory
The University of Michigan
904 Monroe Street
Ann Arbor, MI 48109-1234
Internet: ml88@csmil.umich.edu
The deadline for submission of papers is January 15, 1988. Authors will be
notified of acceptance by March 1, 1988. Final camera-ready copies of the
papers will be due April 1, 1988.
Organizing Committee
J. E. Laird (chairman) University of Michigan
J. H. Holland, S. L. Lytinen, G. M. Olson University of Michigan
J. G. Carbonell, T. M. Mitchell Carnegie-Mellon University
P. Langley University of California, Irvine
R. S. Michalski University of Illinois
------------------------------
Date: Fri, 10 Jul 87 23:40:17 EDT
From: sriram@ATHENA.MIT.EDU
Subject: Conference - Second International Conference on AI in
Engineering
SECOND INTERNATIONAL CONFERENCE ON
AI IN ENGINEERING
The program agenda for the above conference, which is to be held in
Boston from August 3-8, 1987, can be obtained from Ms Sandra Elliott,
Computational Mechanics Inst., 25 Bridge Street, Billerica, MA 01821,
USA (Tel. No: (617)667 5841). I have a copy of the agenda online. If
you are interested in getting a copy, send me mail.
Some program highlights:
Keynote speaker: Dr. Randy Davis, MIT, USA
Banquet speaker: Dr. Mark Stefik, Xerox,USA
Invited speakers:
Dr. John Gero, Univ. of Sydney, Australia
Dr. Jean-Claude Latombe, ITMI, France
(Currently atStanford Univ.)
Dr. B. Chandrasekaran, OSU, USA
Panels on:
AI in Mechancial Engineering: The Commerical Reality
AI in Electrical Engineering: The Commerical Reality
AI in Engineering Design: The Research Issues
AI in Engineering: The Engineer's Perspective
Over 80 papers dealing with various applications of knowledge-based
systems, robotics, and natural language processing will be presented.
Sriram@athena.mit.edu
------------------------------
End of AIList Digest
********************
∂12-Jul-87 0524 LAWS@Stripe.SRI.Com AIList Digest V5 #175
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 Jul 87 05:24:25 PDT
Date: Sat 11 Jul 1987 22:43-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #175
To: AIList@STRIPE.SRI.COM
AIList Digest Sunday, 12 Jul 1987 Volume 5 : Issue 175
Today's Topics:
Queries - ANIMAL in BASIC & XLisp & Monkey and Bananas Benchmark &
Conference on Production Planning and Control & Neural Networks &
GLISP,
Tools - Real Time Expert Systems,
Programming - Software Reuse,
Law - Liability in Expert Systems,
Expert Systems - Plausible Reasoning
----------------------------------------------------------------------
Date: 9 Jul 87 03:04:14 GMT
From: David L. Brauer <nosc!humu!dbrauer@sdcsvax.ucsd.edu>
Subject: ANIMAL in BASIC ???
Somewhere in the darkest reaches of my memory I recall seeing a listing
of the game ANIMAL in BASIC. It's that old standby introduction to rule-based
reasoning that tries to deduce what animal you have in mind by asking
questions like "Does it have feathers?", "Does it have hooves?" etc.
The problem is that I described this program to my wife and she now wants
to program it on an Apple IIc for her elementary school students. I believe
I saw the listing in an "Intro to AI" article in some magazine but I'm not
sure. I would prefer not to have to help her program the thing from
scratch so any pointers would be greatly appreciated.
Thanks,
David C. Brauer
MilNet: dbrauer@NOSC.Mil
------------------------------
Date: Thu 9 Jul 87 08:51:29-PDT
From: BEASLEY@EDWARDS-2060.ARPA
Subject: clarification
I would like to clarify my request for information about XLISP. The particular
version i have is XLISP Experimental Object-oriented Language Version 1.6
by David M. Betz for use on the IBM PC and others. Any information would be
greatly appreciated. By the way, i have the article from BYTE magazine.
The examples didn't work!!!!
Please send the info to beasley@edwards-2060.arpa.
joe
------------------------------
Date: Fri, 10 Jul 87 10:20:10 SET
From: "Adlassnig, Peter" <ADLASSNI%AWIIMC11.BITNET@wiscvm.wisc.edu>
Subject: Monkey and Bananas Benchmark
RE: Inquiry for Production Systems
Since we finished our PAMELA (PAttern Matching Expertsystem Language)
we are interesting in the Monkeys and Bananas benchmark (NASA MEMO
FM7(86-51). I wonder how to obtain the source code.
In addition to that we would be interested in YAPS (Yet Another Production
System) running under VAX/UNIX. Is there any information available.
I have no direct access to the ARPANET. Please return mails to my
friend's email address:
adlassni at awiimc11.bitnet
my postal address is: Franz Barachini
ALCATEL-ELIN Research Center
Floridusgasse 50
A-1210 Vienna
Austria
------------------------------
Date: 10 Jul 87 13:46:58 GMT
From: dhj@aegir.dmt.oz (Dennis Jarvis)
Subject: conference on production planning and control
In a (not so) recent posting to comp.ai.digest, it was announced that a
conference entitled "Expert Systems and the Leading Edge in Production
Planning and Control" would be held from May 10-13 in Charleston, South
Carolina. I would like to obtain a copy of the proceedings of that
conference - any assistance in this regard would be greatly appreciated.
________________________________________________________________________
Dennis Jarvis, CSIRO, PO Box 4, Woodville, S.A. 5011, Australia.
UUCP: {decvax,pesnta,vax135}!mulga!aegir.dmt.oz!dhj
PHONE: +61 8 268 0156 ARPA: dhj%aegir.dmt.oz!dhj@seismo.arpa
CSNET: dhj@aegir.dmt.oz
------------------------------
Date: Fri, 10 Jul 87 11:04:59 +0200
From: mcvax!idefix.laas.fr!helder@seismo.CSS.GOV (Helder Araujo)
Subject: Neural Networks
I am just starting working on a vision system, for which I am
considering several different architectures. I am interested in studying the
utilization of a neural network in such a system. My problem is that I am
lacking information on neural networks. I would be grateful if anyone could
suggest me a bibliography and references on neural networks. As I am not
a regular reader of AIlist I would prefer to receive this information
directly. My address:
mcvax!inria!lasso!magnon!helder
I will select the information and put it on AIlist.
Helder Araujo
LAAS
mcvax!inria!lasso!magnon!helder
7, ave. du Colonel-Roche
31077 Toulouse
FRANCE
[I have forwarded this to the neuron%ti-csl.csnet@relay.cs.net
neural-network list. -- KIL]
------------------------------
Date: 10 Jul 87 14:45:41 GMT
From: uwmcsd1!leah!itsgw!nysernic!b.nyser.net!weltyc@unix.macc.wisc.ed
u (Christopher A. Welty)
Subject: Looking for GLISP
I am looking for some references to G-LISP, something written
by a guy named Novac (sp?) at Stanford. I don't actually need G-LISP,
but I would like to see the papers or any other references. Any help
would be much appreciated. With enough interest I'll post to the
list..
Christopher Welty - Asst. Director, RPI CS Labs
weltyc@cs.rpi.edu ...!seismo!rpics!weltyc
------------------------------
Date: Fri, 10 Jul 87 01:22:56 gmt
From: Aaron Sloman <aarons%cvaxa.sussex.ac.uk@Cs.Ucl.AC.UK>
Subject: Real Time expert systems
Hi,
I saw your enquiry about real time expert systems. A UK firm called
Systems Designers have used our Poplog system to implement a prototype
system called RESCU which can control production of detergent at ICI.
This was one of the UK Alvey Programme's "community club" projects,
i.e. a number of industrial firms potentially able to benefit from
the development helped to fund the prototype demonstration system.
They were so pleased with the result that the development work
is continuing.
They used Poplog on a VAX-730 connected to a variety of monitoring
devices displays, etc.
The system was written in POP-11 extended by a task specific rule
language for which they implemented an incremental compiler using
the POP-11 compiler-building tools.
There have been various relatively short reports on RESCU in newspapers, etc.,
as well as conference presentations, but I have not seen a full write-up.
If you want to know more about RESCU write to:
Mike Dulieu,
Systems Designers Plc,
Pembroke House,
Pembroke Broadway
Camberley, Surrey, GU15 3XD
England
Phone +44 276 686200
I hope this information is of some use.
Best wishes
Aaron Sloman,
U of Sussex, School of Cognitive Sciences, Brighton, BN1 9QN, England
UUCP: ...mcvax!ukc!cvaxa!aarons
ARPANET : aarons%uk.ac.sussex.cvaxa@cs.ucl.ac.uk
JANET aarons@cvaxa.sussex.ac.uk
PS
Robin Popplestone at University of Amherst Mass (pop@edu.umass.cs) is
taking over academic distribution of Poplog in USA. He may have some
information about RESCU. He'll be at Amherst and SUN stands at AAAI
conference.
------------------------------
Date: 9 Jul 87 03:10:00 GMT
From: johnson@p.cs.uiuc.edu
Subject: Re: Software Reuse (short title)
Object-oriented programming languages like Smalltalk provide a great
deal of software reuse. There seems to be several reasons for this.
One is that the late bound procedure calls (i.e. message sending)
provide polymorphism, so it is easier to write generic algorithms.
Late binding encourages the use of abstract interfaces, since the
interface to an object is the set of messages it accepts. Another
reason is that class inheritance lets the programmer take some code
that is almost right and convert it without destroying the original,
i.e. it permits "programming by difference". These two features
combine to encourage the creation of "application frameworks" or
"application toolkits", which are sets of objects and, more importantly,
interfaces that let the application developer quickly build an application
by mixing and matching objects from existing classes.
There are a number of ways that an abstract algorithm can be expressed
in these languages. An abstract sort or summation algorithm can be
built just using a polymorphic procedure. Abstract "process all" and
reduction algorithms are provided by inheritance in the Collection
class hierarchy of Smalltalk, and a toolkit can be used to describe
the abstract design of a browser or editor from a set of abstract
data types, a display manager, and a dialog control component
(i.e. the Model/View/Controller system).
The Smalltalk programming environment also provides tools to help
the user find code and to figure out what it does. While these tools
(and the language) could stand some improvement, they already provide
a lot of what is needed for code reuse. And they don't use A.I!
------------------------------
Date: Fri, 10 Jul 87 07:53:43 PDT
From: George Cross <cross%cs1.wsu.edu@RELAY.CS.NET>
Subject: Re: Liability in Expert Systems
Hi,
I don't know about any pending cases, but readers interested in this subject
should check the article by Christopher J. Gill, High Technology Law Journal,
Vol 1, #2, P483-520, Fall 1986 entitled "Medical Expert Systems: Grappling
with Issues of Liability." An important legal issue is
whether the use of a medical expert system constitutes a product or a service.
If an expert system is a product, strict liability applies whereas if it a
service then a negligence standard applies. Perhaps some lawyer reading
Risks or AILIST could read this article and summarize it for us.
It is not easy going.
---- George
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
George R. Cross cross@cs1.wsu.edu
Computer Science Department ...!ucbvax!ucdavis!egg-id!ui3!wsucshp!cs1!cross
Washington State University faccross@wsuvm1.BITNET
Pullman, WA 99164-1210 Phone: 509-335-6319 or 509-335-6636
------------------------------
Date: Wed, 8 Jul 87 09:56 EDT
From: DON%atc.bendix.com@RELAY.CS.NET
Subject: Plausibility reasoning
>From: Jenny <ISCLIMEL%NUSVM.BITNET@wiscvm.wisc.edu>
>Subject: so what about plausible reasoning ?
>As I read articles on plausible reasoning in expert systems, I come to the
>conclusion that experts themselves do not exactly work with numbers as they
>solve problems.
You are correct in several senses. One, the psychology literature has
shown time and time again that human belief revision does not conform to
Bayesian evidence accumulation (e.g., Edwards, 1968; Fischhoff &
Beyth-Marom, 1983; Robinson & Hastie, 1985; Schum, Du Charme, & DePitts,
1973; Slovic & Lichtenstein, 1971). Two, it does not appear that
humans literally use any of the methods.
However, the humans do appear to be weighing alternatives. Although,
for a period, it may seem that the humans are performing sequential
hypothesis testing, for stochastic domains with non-trivial uncertainty,
humans gather support for a large set of hypotheses at the same time.
They may appear to only gather support for their "favorite"; however, if
asked for an ordering over the alternatives or if asked how much they
believe the alternatives, it is obvious that they have allowed the
evidence to change their beliefs about the non-favorite hypotheses
(e.g., Robinson & Hastie, 1985).
The question becomes, "what are they doing?" For the sake of argument,
let's take your assertion and say they are not explicitly manipulating
numbers -- it does seem absurd that the automobile mechanic who can't
add simple integers without a calculator could possibly perform the
complex aggregations necessary to use numbers.
Another possibility is that they are performing a type of non-monotonic
logic with the choice of assumptions and generation and testing of
possible worlds. This possibility suggests that, if the human is not
using numbers at any level, the human's choice of one assumption over
another uses a simple set of context sensitive rules. The only time the
human should change assumptions (generate an alternative path or
possible world) is if the current assumptions are defeated or if some
magical attentional process causes the human to arbitrarily try another
path. When choosing another path, there should be a fixed set of
rules guiding the choice of alternative -- there can be no idea of
"this looks a little stronger than that" because such comparisons
require a comparison metric which is not built into non-monotonic
logics.
The psychological research on human search strategies (especially for
games such as chess) suggests that humans often abandon one search path
to test another which looks like it might be as strong or stronger and
then return to the original path. This return to the original path
leads to a rejection of the hypothesis that humans maintain a set of
assumptions until evidence refutes those assumptions. By my previous
argument, then, if non-monotonic logics model human decision making, the
humans must be choosing to change path generation based on an
attentional mechanism. If numbers are not involved, then the
attentional mechanism is probably rule-driven.
Of course, I've laid out a straw man. I've said it's either numbers
or rules; however, there are probably many other possibilities.
The most likely possibility is an analog process something akin to
comparisons of weights. If we were to model this process in a computer,
we would use numbers; so, we're back to numbers. The trouble with
just using numbers, of course, is determining how to combine them
under different circumstances and how to interpret them. Plausibility
reasoning has been used because it, at least, suggests methods for
both of these processes. Something, even an approximation, which
has validity at some level, is better than nothing.
Rather than turn this into a thesis, let's go on to your next point.
>And many of them are not willing to commit themselves into
>specifying a figure to signify their belief in a rule.
Hum, this sounds like something from Buchanan and Shortliffe. Let's
think about the implications of this argument. You're saying, if
humans find it difficult to generate numbers to represent their degrees
of belief, then numbers must be ineffective. Perhaps even at a
higher-level, if humans find some piece of knowledge or knowledge
artifact difficult to specify, then it probably is ineffective.
What evidence do we have for these claims? What are the implications
of these claims? From a personal standpoint, I find any knowledge,
beyond the trivial, is difficult to specify in some external formalism
(including writing, rules, and probabilities). It seems unlikely
that we will ever generate external formalisms which allow painless
knowledge transfer. Does that imply that knowledge transfer is
hopeless? Let's hope not because that is the modus operandi of the
human species. Granted, it will not be perfect, it will be painfull,
it will take time, but does that imply that it is worthless?
We "know" that human experts have knowledge which is effective.
There is growing evidence that purely logical formalisms for
representing this knowledge will not work for all problem domains
due to the stochastic nature of the domains or the incomplete
understanding of the domain. Does this mean that automated problem
solving must be limited to non-stochastic domains in which there
is a full and complete understanding of the causal relations and
elements?
I fear that I have left the primary argument which I wanted to use in
response to your statement. I looked at statements such as these and
asked myself whether "comfort" was a legitimate metric for determining
the effectiveness of knowledge. This question suggested an experiment
in which different sets of experts were asked to generate the
comfortable MYCIN confidence factors, the uncomfortable but definable
conditional and a priori probabilities needed for Bayes' theorem, and
the interesting, but perhaps not well-defined, probability bounds for
the typical Dempster-Shafer formulation.
I ran this experiment in which the experts were matched for knowledge in
the domain. Each expert was asked to provide the parameters needed for
only one of the plausibility reasoning formulisms. The results were
that, at a superficial level, humans can provide better MYCIN and
Dempster-Shafer parameters than Bayesian numbers. However, when
considering how these numbers are used and how errors in the numbers
propagate through repeated applications of the aggregation formulae, the
Bayesian parameters led to more effective automated decision making than
the MYCIN parameters. The performance of the Demspter-Shafer parameters
was not significantly better or worse than either system in this test.
(This research is documented in two papers -- ask me for references.)
The conclusion: the domain expert's comfort is not a legitimate
determinant of knowledge effectiveness.
>If one obtains two conclusions with numbers indicating some significance,
>say 75 % and 80 %, can one say that the conclusion with 80% significance is
>the correct conclusion and ignore the other one ?
There is a fundamental problem here. If you are refering to
percentages, then the numbers cannot add to more than 100. You are
correct in that a decision theory for plausibility reasoning must
take into account the accuracy of the parameters, and I believe that
some researchers have not considered this problem; however, most
plausibility reasoning researchers consider the decision theory to
be an important component which must be given strict attention.
>These numbers do not seem to mean much since they are just beliefs or
>probabilties.
I alluded to this problem earlier. Actually, if they are probabilities,
they mean a lot. Probabilities have clear operational and theoretical
definitions. Some, for example Shafer (1981), have suggested that
the definition of probabilities can be extended to better account
for the subjective nature of the probabilities used in most decision
support systems. The real problem is with the MYCIN style confidence
factors. Although Heckman (1986) has developed a formal interpretation
of confidence factors, the interpretation is ad hoc and it seems
difficult to imagine that domain experts use this interpretation.
The meaningfulness of the numbers is an important criterion for
determining the successful application of the numbers and is one
of the strongest arguments for using probabilities and perhaps for
using Bayes' theorem.
Donald H. Mitchell Don@atc.bendix.com
Bendix Aero. Tech. Ctr. Don%atc.bendix.com@relay.cs.net
9140 Old Annapolis Rd. (301)964-4156
Columbia, MD 21045
------------------------------
End of AIList Digest
********************
∂12-Jul-87 0816 LAWS@Stripe.SRI.Com AIList Digest V5 #176
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 Jul 87 08:16:33 PDT
Date: Sat 11 Jul 1987 22:53-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #176
To: AIList@STRIPE.SRI.COM
AIList Digest Sunday, 12 Jul 1987 Volume 5 : Issue 176
Today's Topics:
Binding - Interactive Fiction List,
Philosophy of Science - Is AI a Science
----------------------------------------------------------------------
Date: 8 Jul 87 20:16:34 GMT
From: engst@tcgould.tn.cornell.edu (Adam C. Engst)
Subject: Re: Interactive fiction
For those of you who cannot (or don't want to) read the Usenet or Bitnet
discussion groups on interactive fiction we are back in mailing list form.
If you want to send mail to the list, the address is . . . . . . . . . .
>>>> gamemasters@parcvax.xerox.com <<<<
Just include "Interactive fiction" on the Subject line so the moderator can
separate it out from the adventure game discussion messages. If you want to
add yourself to the mailing list (so you get digests every day or so) send a
request to . . . . . . . .
>>>> gamemasters-request@parcvax.xerox.com <<<<
and ask to be added. You can also ask to be deleted from the list, ask for
archived mail, or report a mailer failure at the request address. I will be
sending the messages that come from Bitnet and Usenet as well, so everyone
will have access to all the messages. If anyone has any questions, just
email me at either of the below addresses and I'll try to help. Thanks a
lot for the discussion up to now and I hope that it will improve even more
with the increased audience.
Adam C. Engst
engst@tcgould.tn.cornell.edu
pv9y@cornella.bitnet
------------------------------
Date: 9 Jul 87 14:37 PDT
From: Tony Wilkie /DAC/ <TLW.MDC@OFFICE-1.ARPA>
Subject: Is AI a Science? A Pragmatic Test Offered!
I'm inclined to belive that Don Norman is right, and that AI is not a science;
which is okay, there being a number of perfectly good, self-respecting fields
of study out there that are not sciences.
Still, its likely that there have been sensitivities offended and a defense is
to be anticipated. In lieu of a more respectable and formal argument in defense
of AI being a science, I am prepared to steal from William James and proffer a
pragmatic test. The rationale is as follows:
1. Grant moneys are issued by various public and private agencies for the
support of research in both sciences and non-sciences
2. Issuing agencies are generally authorized to finance projects falling
within their scope of study only.
3. These agencies have some criteria for determining what appropriate
projects are.
THEREFORE:
4. Any projects funded by an agency as a science (e.g. NSF) are science
projects reflecting scientific work (except for method or instrumentation
projects).
The challenge, then, is to find any researcher working on an AI project funded
by a science-supportive agency.
If only it were all this easy...
Tony Wilkie <TLW.MDC@Office-1.ARPA>
------------------------------
Date: Fri, 10 Jul 87 10:34:39 n
From: Paul Davis <DAVIS%EMBL.BITNET@wiscvm.wisc.edu>
Subject: AI, science & Don Norman
Briefly - seems to me that most everyone (including DN himself) has
missed out on two key points. First, after Searle, there isn't only
*one* AI but two (Searle's strong and weak AI): the first is a suitable
target of DN's critique since its whole raison d'etre can be summed up
in its idea of AI as `cognitive science', ie; that computer science is
a way to approach an understanding of what *existing* intelligent systems
do and how they do it. However, let us not forget `weak' AI, which makes
no such claims - there is no assumption that the products of weak AI
function analagously to "real" intelligent systems, only that they
are capable of doing X by some means or another.
Second, given that `strong' AI *does* claim to have some intimate relation-
ship with cognitive science, its worth asking "is there any other way to
study the brain/mind ?". Don Norman castigates (probably correctly) AI
for not being a science, but he also fails to point out the likely
impossibility of any non-AI-stimulated approaches ever coming to terms
with the complexity of the brain. AI models are *NOT* testable!!
Just imagine that a keen AI worker comes up with an implementation
of his/her model of human brain activity, and that this implementation
is so good, and so powerful that it saunters through Mr. Harnad's TTT
like a knife through butter.... it is vital to see that there is very
little information in this result bearing on the question "is this
the correct model of the brain ?". The ONLY way to confirm (test)
a `strong' AI model is to demonstrate functionally equivalent hardware
behaviour, and psychology is a century or more from being able to do this.
Norman seems right to castigate AI workers for excessive speculation
unsupported by `real experiments', and undoubtedly, if the aim of
`strong' AI is ever to succeed, then we *must* know what it is that
we are trying to model, but he should also recognize that AI
cannot be tested or developed as other sciences simply because it is
unique in studying one domain (computers) with the idea of understanding
another (the brain). When AI *is* a science, it will be called psychology..
too long..,
paul davis
EMBL, Heidelberg, FRG
bitnet: davis@embl arpa: davis%embl.bitnet@wiscvm.wisc.edu
uucp: ...!psuvax1!embl.bitnet!davis
------------------------------
Date: Fri 10 Jul 87 09:43:03-PDT
From: Douglas Edwards <EDWARDS@Stripe.SRI.Com>
Subject: Don Norman on AI as nonscience
Don Norman assumes that he knows enough about scientific methods to
assert that AI doesn't use them.
I don't believe that he, or anyone else, has a good general
characterization of how science discovers what it discovers.
Especially, I don't believe that he has used scientific methods in
determining what scientific methods are. Attempts at characterizing
the methods of science typically come from intuitive reflection, or
from philosophy, not from science. There are some questions we have
to make educated guesses at, because scientific answers are not yet
available.
Norman's attack on AI is vitiated by the same weakness that vitiated
Dresher and Hornstein's earlier attack on AI. The critics'
characterizations of scientific methods are far *less* firmly grounded
than most assertions being made from within the discipline being
attacked.
Among intuitive and philosophical theories of scientific method--the
only kind yet available--a priori reasoning of the type used in AI
plays a prominent role. Exactly what relation such a priori reasoning
must have to experimental data is very much an open question.
My own background is in philosophy. I have gotten involved in AI
partly because I believe, on intuitive grounds, that it *is* a
science, and that it has a better shot at giving rise to a truly
scientific characterization of scientific methods than philosophy,
psychology, linguistics, or neuroscience. (I am not saying anything
against interdisciplinary cross-fertilization.) I am now trying to
work out a logical characterization of hypothesis formation.
Douglas D. Edwards
EK225
SRI International
333 Ravenswood Ave.
Menlo Park CA 94025
(edwards@warbucks.sri.com)
(edwards@stripe.sri.com)
------------------------------
Date: 10 Jul 87 18:37:00 GMT
From: jbn@glacier.STANFORD.EDU (John B. Nagle)
Reply-to: jbn@glacier.UUCP (John B. Nagle)
Subject: Re: AIList Digest V5 #171
In article <8707062225.AA18518@brillig.umd.edu> hendler@BRILLIG.UMD.EDU
(Jim Hendler) writes:
>When I publish work on planning and
>claim ``my system makes better choices than <name of favorite
>planning program's>'' I cannot verify this other than by showing
>some examples that my system handles that <other>'s can't. But of
>course, there is no way of establishing that <other> couldn't do
>examples mine can't and etc. Instead we can end up forming camps of
>beliefs (the standard proof methodology in AI) and arguing -- sometimes
>for the better, sometimes for the worse.
Of course there's a way of "establishing that <other> couldn't do
examples mine can't and etc." You have somebody try the same problems on
both systems. That's why you need to bring the work up to the point that others
can try your software and evaluate your work. Others must repeat your
experiments and confirm your results. That's how science is done.
I work on planning myself. But I'm not publishing yet. My planning
system is connected to a robot and the plans generated are carried out in the
physical world. This keeps me honest. I have simple demos running now;
the first videotaping session was last month, and I expect to have more
interesting demos later this year. Then I'll publish. I'll also distribute
the code and the video.
So shut up until you can demo.
John Nagle
------------------------------
Date: Fri, 10 Jul 87 20:32:07 GMT
From: Caroline Knight <cdfk%hplb.csnet@RELAY.CS.NET>
Subject: AI applications
This is sort of growing out from the discussion on whether AI is a
science or not, although I'm more concerned with the status of AI
applications.
Ever since AI applications started to catch on there has been a
growing divide between those who build software as some form of
experiment (no comment on the degree of scientific method applied) and
those who are building software *FOR ACTUAL USE* using techniques
associated with AI.
Many people try to go about the second as though it were the first.
This is not so: an experimental piece of software has every right to
be "toy" in all those dimensions which can be shown to be unnecessary
for testing the hypotheses. A fancy interface with graphics does not
necessarily make this into a usable system. However most pieces of
software built to do a job have potential users some of whom can be
consulted right from the start.
I am not the first person to notice this, I know. See, for instance,
Woods' work on human strengths and weakness or Alty and Coombes
alternative paradigm for expert systems or Kidd's work on expert
systems answering the wrong questions (sorry I haven't the refs to
hand - if you want them let me know and I'll dig them out).
I think I have a good name for it: complementary intelligence. By this
I mean complementary to human intelligence. I am not assuming that the
programmed part of the system need been seen as intelligent at all.
However this does not mean that it has nothing to do with AI or
cognitive psychology:
AI can help build up the computer's strengths and define what
will be weaknesses for sometime yet.
Cog psy can help define what human's strengths and weaknesses
are.
Somehow we then have to work out how to put this information together
to support people doing various tasks. It is currently much easier to
produce a usable system if the whole task can be given to a machine
the real challenge for complementary intelligence is in how to share
tasks between people and computers.
All application work benefits from some form of systems analysis or
problem definition. This is quite different from describing a system
to show off a new theory. It also allows the builder to consider the
people issues:
Job satisfaction - if the tool doesn't enrich the job how are you
going to persuade the users to adopt it?.
Efficient sharing of tasks - just because you can automate some
part does not mean you should!
Redesign of process?
I could go on for ages about this. But back to the main point about
whether AI is a science or not.
AI is a rather fuzzy area to consider as a science. Various sub-parts
might well have gained the status. For instance, vision has good
criteria to measure the success of a hypothesis against.
I suggest that the area that I am calling complementary intelligence
consists of both a science and an engineering discipline. It is a
science in which experiments such as those of cog psy can be applied.
They are hard to make clear cut but so are many others (didn't you
ever have a standard classroom physics experiment fail at school?).
It is engineering because it must build a product.
And if we want to start a new debate off how about whether it is more
profitable to apply engineering methods to software production or to
consider it an art - I recently saw a film of Picasso painting in
front of a camera and I could see more parallels with some of the
excellent hackers I've observed than with what I've seen of engineers
at work. (This is valid AI stuff rather than just a software
engineering issue because it is about how people work and anyone
interested in creating the next generation of programmer's assistants
must have some views on this subject!).
Caroline Knight This is my personal view.
Hewlett-Packard Ltd
Bristol, UK
------------------------------
Date: 11 Jul 87 04:48:04 GMT
From: isis!csm9a!japplega@seismo.CSS.GOV (Joe Applegate)
Subject: Re: Why AI is not a science
> From jlc@goanna.OZ.AU.UUCP Sat Feb 5 23:28:16 206
>
> May be AI is such unorthodox Science, or perhaps an Art.
> Let us keep AI this way!
I'm not sure there is any maybe about it! AI development, is in my humble
opinion, the most creative expression of the programmers art. Any semi-
educated fool can code a program... but the creation of a useful, productivity
enhancing application or system is far more art than science! The same is
more so in AI development, a query and answer style expert system can be
coded in basic by a high school hacker... but the true application for AI
is in sophisticated applications that employ high quality presentation
techniques that eliminate the ambiguities so often present in a text only
presentation.
One benefit of the advent of the personal computer is the redirection of
software product developent away from data driven environment of DP and
accounting and towards the presentation style environment of the non-DP
professional. Fortunately, most AI development systems are acknowledging
this trend by providing graphical interfaces.
Art mimics science and the application of science is an art!
Joe Applegate - Colorado School of Mines Computing Center
{seismo, hplabs}!hao!isis!csm9a!japplega
or
SYSOP @ M.O.M. AI BBS - (303) 273-3989 - 300/1200/2400 8-N-1 24 hrs.
*** UNIX is a philosophy, not an operating system ***
*** BUT it is a registered trademark of AT&T, so get off my back ***
------------------------------
End of AIList Digest
********************
∂13-Jul-87 0022 LAWS@Stripe.SRI.Com AIList Digest V5 #177
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 Jul 87 00:22:32 PDT
Date: Sun 12 Jul 1987 21:30-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #177
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 13 Jul 1987 Volume 5 : Issue 177
Today's Topics:
Theory - Symbol Grounding Poll: Yea's
----------------------------------------------------------------------
Date: 9 Jul 87 03:32:45 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Results of Symbol Grounding Poll (1st of 3 parts)
In the poll on whether the symbol grounding discussion was useful and
worth continuing there were 24 yea's and 37 nays (with some ambiguous
ones I have tried to classify non-self-servingly), so the nays have it.
As promised, I am posting the results (yea's in part 2 and nays in
part 3) and I will abide by the decision. Perhaps I may be allowed a few
parting reflections:
(1) It is not entirely clear what the motivation of the nays was:
ecological/economic considerations about overuse of the airways or
reluctance to perform the dozen or so keystrokes per week (or to
put in the software filter) that would flush unwanted topic headers.
(2) There were distinct signs of the default option "I can't follow it,
therefore it makes no sense" running through some of the nays (and indeed
some of the discussion itself). This may be a liability of polling as a
method of advancing human inquiry.
(3) Along with several thoughtful replies, there was unfortunately also some
ad hominem abusiveness, both in the poll and in the discussion. This is the
ugly side of electronic networks: unmoderated noise from the tail end of the
gaussian distribution. It will certainly be a serious obstacle to making the
Net the reliable and respectable medium of scholarly communication that I
and (I trust) others are hoping it will evolve into. It may turn out that
moderated groups, despite the bottle-necking they add -- a slight step
backward from the unique potential of electronic nets -- will have
to be the direction this evolution takes.
(4) I continue to be extremely enthusiastic about and committed to
developing the remarkable potential of electronic networks for scholarly
communication and the evolution of ideas. I take the present votes to
indicate that the current Usenet Newsgroups may not be the place to attempt
to start this.
(5) Starting a special-interest Newsgroup every time a topic catches
on does not seem like the optimal solution. It is also unclear whether
even majority lack of interest should prevail over minority interest
when all that seems to be at issue is a keystroke. (Not only is there
software to screen out unwanted topics, but to filter multiple postings
as well. I have been posting to both comp.ai and comp.cog-eng because they
each have a relevant nonoverlapping sub-readership. I subscribe to both; my own
version of "rn" only displays multiple postings once. Secondary
digests like the ailist are another matter, but everyone knows that
half or more of it duplicates comp.ai anyway. The general ecology and economy
of the airwaves, on the other hand, should perhaps be deliberated at a higher
level, by whoever actually pays the piper.)
(6) The current majority status of engineers, computer scientists and
programmers on the Net also seems to be a constraint on the development of
its broader scholarly potential. Although these two disciplines developed the
technology and were the first to use it widely, it's now rather as if
Guttenberg and a legion of linotype operators were largely determining not
just the form but the content of the printed page. The other academic
disciplines need *much* greater representation in the intellectual Newsgroups
(such as those devoted to biology, language, philosophy, music, etc.)
if the Net's scholarly contribution is ever to become serious and lasting; right
now these Newsgroups seem only to be outlets for the intellectual hobbies of the
two predominant disciplines. This may just be a quirk of initial conditions
and a matter of time. I wlll certainly do my best to get the other disciplines
involved in this unique and powerful new medium.
[N.B.: I am of course in no way deprecating the great value or contribution
to knowledge of the two disciplines I mentioned; I just believe that their
incidental monopoly over the electronic networks should be benignly dissolved
as soon as possible by the entry of the other disciplines that have a hand in
the written word, scholarly communication and the advancement of knowledge.
The interdisciplinary field of cognitive science happens to be a microcosm of
this larger problem of temporary disciplinary imbalance on the Net,
and the subfield of artificial intelligence -- though of course legitimately
skewed toward computer science -- seems to be showing some of its effects too,
especially on foundational topics like the symbol grounding problem.]
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: 10 Jul 87 11:32:00 EST
From: "Robert Breaux" <breaux@ntsc-74.arpa>
Reply-to: "Robert Breaux" <breaux@ntsc-74.arpa>
Subject: SYMBOL GROUNDING DIES DOWN
It occurs to me that the flare up then dying of symbol grounding in
the ai list is an evolution not possible until recently. I believe
it is good. In the "old days" prior to electronic bulletin boards,
this argument would have raged for years, camps divided, universities
would have created "schools of thought", and perhaps books written
which would not have stood the "test of time" as a classic issue.
Now, we can have "face to face", so to speak, discussions early on,
resolve the issues which are not "classic" or seminal, and get on
with it.
It's GREAT, wouldn't you say?
------------------------------
Date: 9 Jul 87 03:41:27 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Results of Symbol Grounding Poll: Yea's (2nd of 3 parts)
[These are the 24 yea's in response to the poll on whether or not to
continue the symbol grounding discussion on comp.ai/comp.cog-eng. I have
removed names and addresses because I had not asked for permission to repost
them. If you wish to communicate with anyone, specify by number (*and* whether
"yea" or "nay") and I will forward it to the author.]
-------------------------
1. I am finding the symbol grounding discussion very interesting and would
like it to continue. More generally, the community is better served by having
too much information flow than too little. I hope the discussion will continue
even if most respondents to your poll disagree.
----------------------
2. I personally don't feel that it's Harwood's place to make a
recommendation such as the one he made (rude or otherwise). If the
discussion is germane to the stated purpose(s) of the newsgroup
(which it is), and is carried on in an intellectually responsible
manner (which it certainly has been), why should it not be allowed to
continue?
Isn't the solution for those who don't find the topic interesting to
simply not read the messages bearing that topic on the subject line?
After all, any number of discussions can be carried on concurrently.
---------------------
3. I vote to continue on symbol grounding. And by all means, keep going
with your good and interesting work.
-------------------
4. I don't read this discussion anymore. I couldn't find the beginning,
and never felt that I really understood what the problem was.
However, I have absolutely no objection to the discussion continuing.
I presume that the discussants get value out of it.
----------------------
5. Although I only peruse most of the symbol grounding discussion I think
it is well placed in comp.ai and I vote to see it continue. Personally, I do
not see why intelligent use of the NET needs to be defended but apparently
there is always an 'offended' party.
---------------------
6. [re. ailist] I initially found some of the symbol grounding discussion
interesting, but at the moment it is getting in my way, interfering with my
work of reviewing what is already too much material in AIList. Perhaps a
general solution to "what belongs on AIList" is to put lengthy, continuing
discussions which are of a temporary nature in separate issues, each clearly
titled so it can be deleted by the recepient at the title level without danger
of deleting other AIList topics.
[Ken Laws, Ailist's moderator, then replied that he was sorting already]
Thanks for the reply. Indeed, you are sorting the material already.
Thanks for the reference to the mail scanning program. It, or an enhancement of
the one I am using, could fill the bill nicely. Perhaps a one-character
appendage to the digest name to indicate the issue pertains exclusively to a
continuing lengthy discussion? Then, if desired, a smart mailer could
automatically omit or delete them. Just a thought.
------------------------
7. I would, with the following reservation, vote against splitting
off this discussion. It is tangential to some important aspects
of AI and discussions of this sort tend to emphasize areas which
need further scientific exploration.
My reservation, which I have until now contained, is that your
contributions do tend to be lengthy, wordy, vague, and full of
(sigh) ungrounded symbols. At times they also appear to lack
respect for the views of other contributors. If you're looking
for a soapbox, please find one that doesn't appear in my
mailbox. If you have a point to make, and can do so precisely,
concisely, and with an open mind towards the responses you receive
and respect for their contributors, please contribute to the AIList.
This is offered in the spirit of constructive criticism, and I hope
you can accept it as such.
----------------
8. I think symbol grounding discussion are *very* critical to
the AIList and count me as pro-discussion on the AIList.
--------------------
9. Ha! I subscribe to quite a few bulletin boards. The symbol grounding
problem is the only discussion topic for which I religiously archive all notes.
It's far, FAR more important than 99.9% of the drivel you see on the net.
What are your critics suggesting? Free up more slots for dumb jokes and
sophomoric opinions about the nature of intelligence? I say, "Right on! Keep
the symbol grounding discussion going."
If you want to be magnanimous, you might request that the discussion
be confined to one bulletin board. It seems to inhabit ai, cog-eng, and language
boards, at least, now. If you decide to start your own board, however, please
let me know.
---------------------
10. Please continue! Critics who care would notice that (in the ailist
version at least) these discussions are usually in a posting on their own, and
are thus easily discarded by those uninterested.
---------------------
11. Mark one with thumbs up.
-------------------
12. As per our phone conversation this morning... continue the dialogue.
-------------------------
13. Please continue the very enlightening discussion on symbol grounding in
its present arena. And thanks very much for the effort you put into explaining
quite carefully what you propose.
----------------------------
14. I consider the recent discussion on the symbol grounding problem to be
very interesting and relevant. Please continue.
--------------------------
15. What I am doing is responding to your poll request. Please continue
the discussion of the symbol grounding problem. I have not had time to
contribute, but I find the contributions, especially yours, quite valuable.
(Your contributions are good, but I also value "bad" contributions, since they
are often clear examples of the bad philosophy and epistemology which people
inflict on themselves and others.) My vote: continue posting.
-------------------
16. Despite the complaints from McCarthy and Minsky, there does seem to be
some benefit of the Symbol Grounding discussion for we lurkers. Sometimes I
almost think I understand what the issue is.
However, I do find it distracting that essentially the same material is
arriving by both comp.ai and comp.cog-eng newsgroups. I don't want to
unsubscribe to either, but I'd like to have to see the material only once.
Is it possible to move this discussion to just comp.cog-eng, since it
seems to be the (weak?) AI community that finds much of this correspondence
tiresome?
I think if you simply announce your intention to operate on one group,
and then make all your submissions there (while monitoring both, of course),
the news stream will become a bit easier to cope with for many of us.
[See earlier material on filtering multiple postings.]
---------------------------
17. I followed your early discussion in symbol grounding but now skip
over it. Maybe its gone on too long? But * as long as Ken Laws [ailist]
separates it into its own volumes * (as he has been doing) I can skip it and
others can follow it as they wish. If he decides this is too much work for him,
I would suggest moving it to a different forum.
--------------------------
18. I find the discussion of symbol grounding useful and worth
contuinuing. I vote to continue.
-----------------------------------
19. You get my vote for continuing the discussion.
---------------------------
20. Simple response. I don't participate, but I enjoy the discussion.
I'm a novice in this area, and seeing exchanges like this help educate.
-----------------------
21. Yes I find it useful and worth continuing.
[Mild ad hominem remarks about a prior rude poster deleted]
-----------------------------
22. My response to your request for a vote: I am emphatically *FOR*
keeping discussions such as the symbol grounding discussion *ON* Ailist Digest.
Though I don't always read all of them (I'm amazed at your energy and
ability to sustain these discussions on "paper") as a philosopher I find
discussions such as yours the the most important part of the digest. If
people think that AI is just computer science, let them start another list.
Laws obviously thinks that these discussions are part of AI and he's right.
I think that your policy of initially ignoring the rude remarks made
against you was a good one. It is unfortunate that some people lose their
manners when they go electronic.
----------------------
23. I vote that you continue the symbol grounding discussion and related
topics in the present forum. I've found these articles to be far more
enlightening, useful, and relevant than the typical requests and responses
for the latest references on KB techniques or expert systems marketing. Not
to say that such articles are inappropriate, but that this forum is for all
AI-related discussion. Please continue to ignore Booth and Harwood.
-------------------------
24. A difficult question. The discussion HAS been going on at considerable
length, but it evolves, and maintains a certain interest. Many people
(including me) seem not to work from the same foundation as you, and
therefore you need many words to get across what often sounds like
reiterations. But if you used fewer words, perhaps we might misunderstand
worse than we do.
Personally, I think you skirt some important points about
categorization, which may be in your book: that it is probably required
only for communication (perhaps for a conversation within a single brain,
as Gordon Pask would insist); that it usually depends on the existence
of a catastrophe function (anywhere near the border of a category,
the data may lead unequivocally to more than one result depending
on historic and local context); that symbols need not be grounded
in real-world phenomena, but in agreed categories constrained by context
(people DO communicate about religion and politics, in which fields
there is unlikley to be any real-world grounding of the symbols).
There are probably other issues. As for continuing the discussion,
I would say yes if the contributions could be kept under 75 lines,
no otherwise. Or else act as a moderator and submit weekly digests
of the arguments people send you privately.
------------------------
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
End of AIList Digest
********************
∂13-Jul-87 0332 LAWS@Stripe.SRI.Com AIList Digest V5 #178
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 Jul 87 03:32:38 PDT
Date: Sun 12 Jul 1987 22:05-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #178
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 13 Jul 1987 Volume 5 : Issue 178
Today's Topics:
Theory - Symbol Grounding Poll: Nays,
Comment - Characteristics of Discussion Lists
----------------------------------------------------------------------
Date: 9 Jul 87 03:44:34 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: Re: Results of Symbol Grounding Poll: Nays (3rd of 3 parts)
[These are the 37 nays in response to the poll on whether to continue
the symbol grounding discussion in comp.ai/comp.cog-eng. I have removed
names and addresses because I had not asked for permission to repost them.
If you wish to communicate with anyone, specify by number (*and* whether
"yea" or "nay") and I will forward it to the author.]
-------
[The first three nays (from Harwood, Minsky and Booth) preceded this
poll; enumeration accordingly begins with 4.]
-------
4. Please do not take this personally. I have almost stopped reading
comp.ai because of the ridiculous quantity of material being posted by you
and Brilliant, and others. This discussion has been completely unuseful
to me and I would really like to see it stopped. It is much more like
philosophy than AI to me and I am sure there are others who feel the same way
but wont tell you. Please stop dominating this newsgroup.
-------
5. Either you start another newsgroup or I unsubscribe to this one.
I cannot take any more.
-------
6. Please start your own newsgroup!
-------
7. My vote: *do* start your own news group or private mailing list.
This discussion, however interesting it may be to the participants,
has gone on too long to continue in "comp.ai".
-------
8. I enjoy skiming your symbol grounding writing though for my research it
is totally irrelevant. However since there are relatively few people
who do AI who need to consider the TTT (most people in AI are just
trying to make machines more intelligent right now) I suspect that the
symbol grounding problem better belongs in sci.philosophy.tech. The
issues wont come up in the real world for at least 5 years because we
are not even close to human emulation at the moment. On the other
hand you may be working on psychological modelling. If so then there
must be a news group or mailing list more close to that topic than
comp.ai. All together I suspect that sci.philosophy.tech is the best
place along with periodic notes to comp.ai notifying people that there
is a discussion of importance to those who model human beings there.
This would get your messages to the relevant people. Also if
sci.philosophy.tech doesn't exist for some reason then talk.philosophy
would be the next best thing. If the problem is that you can not
reach the arpa world that way, I think there is a psychology mailing list.
BTW about graded vs ungraded concepts, point taken.
On the other hand most of the verbs in any language are regular but
most of the verbs used by the speakers of a language are irregular.
The dictionary is not meant to be and is not a fair sample of usage.
Nor does the set of nouns in the language necessarily correspond to
the set of concepts employed by its speakers, (it corresponds to the
set of concepts that the speakers find convinient to convey rapidly).
However you have presented inconclusive evidence that most concepts
are not graded. If you had a dictionary that was sorted by usage and
gave the usage of words rather than their definitions you would
have better evidence that most concepts are not graded.
-------
9. As to your polling request regarding the symbol grounding issue:
I am quite tired of all the traffic it has generated. Considering that no
real information has been revealed, I feel it is time to drop it. In the
recent time that these postings have filled the newsgroup, most all other
worthy postings have vanished.
The newsgroup should address a range of pertinent issues that will
enlighten subscribers. I feel that the symbol grounding issue has only
enlightened me in the use of the 'n' key!
While I am on the subject, the cross-posting to 'comp.cog-eng' are
atrocious. Either post to one or the other. Most every symbol grounding
article has appeared in both. This generated to much traffic on the net
and defeats the purpose of making special purpose groups.
I thank you for your ability to notice fellow subscribers views.
-------
10. Can't we bag this damn symbol grounding discussion already?
If it *must* continue, how about instituting a symbol grounding news
group, and freeing the majority of us poor AILIST readers from the
burden of flipping past the symbol grounding stuff every morning.
-------
11. I generally do not read the SGP articles simply because I do not
understand them (and they are so looong!). If there are a few people interested
in reading and discussing SGP, there is no reason to prevent such postings. But
if there are also many people who do not want to read that sort of things in
comp.ai, then it would be wise to consider the possibility of creating a
news-subgroup `comp.ai.sgp'.
-------
12. The ramblings on this topic passed my threshhold of boredom long ago.
I'm not proposing censorship, but if you choose to continue the discussion
with a smaller group of people who find this topic of interest, I will
applaud your good manners.
-------
13. I vote you start your own newsgroup--I was bored with "Symbol Grounding"
about 500 kilo-bytes ago. Ditto "The Total Touring Test" or whatever
your last filibuster was called. . . .
-------
14. My vote is for ending the discussion on the symbol grounding problem.
Thanks. p.s. If you are interested in finding out why I voted against
continuing the discussion, please let me know -- I will be glad to oblige.
-------
15. Thank you for taking a poll on whether the symbol grounding problem
discussion should or should not continue in comp.ai. My vote is to remove the
discussion from this newsgroup. Maybe it could be moved to a new newsgroup
talk.symbolgroundingproblem ???
-------
16. I think that the discussion has been out of hand for a long time now.
It doesn't seem to contain any useful insights, and is taking up inordinate
resources. Not the least of which is the time spent by the authors
expounding their viewpoints. I think that this sort of disagreement is
better done in position papers in and letters to journals.
The odd use of terms hasn't helped keep the discussion on a high level.
Not to point fingers, but your nonstandard use of "analog" made a large number
of your posts completely incomprehensible to me until you said that you meant
something other than the usual meaning of the term.
So, I vote to flush this discussion.
-------
17. Personally, I have been skiping most of the articles in this discussion.
I was referred to this newsgroup as a forum for other discussion but have
seen little other than what appears to be a war of words from two opposing
camps. By now the sides must be set--perhaps it is time to move the
discussion from "news" to an e-mail mailing-list.
-------
18. Definitely neither useful nor worth continuing.
-------
19. The manner in which the issue was raised *was* rather rude, but I regret
to say that I find much of what was stated about your extended discussions
very much to the point. I tried to keep up with discussion; I found it
rather interesting at first. But it rapidly became clear that you were
all talking at cross purposes, refusing to accept conventional usage or
even common-usage-for-the-purpose-of-debate of the key words in question.
The appalling level of quotation made things much, much worse and it became
well-nigh impossible to ferret out the pearls of insight in the flood of
verbiage. I do not wish your discussion to completely vanish from the
airwaves, as it were, but without a bit of self-restraint all round,
together with some sincere efforts to try to answer one another's
objections, I don't think the discussion is particularly useful. (e.g.
wrt all-or-none categories: pointing to concrete nouns in the dictionary
or to the very special categories that have "hardware support" is not,
in my opinion, a sincere effort to meet the objections to the contention
that categories are all (or mostly) all-or-none, a rather contrary-to-
common-observation position.)
Perhaps the new policy on quotation will help: there has been a modest
improvement in a couple of the recent postings. I remain hopeful. All
I can say is, until things improve quite a bit, I will probably be
flushing all the digests with "Symbol Grounding" in the topics list. Sorry.
-------
20. I do not find the symbol grounding problem discussion worthwhile.
Thank you for (politely) asking.
-------
21. I vote for discontinuing the discussion. It would be interesting except
that there is far too much confusion over who's using what terminology.
Probably dozens of articles have been wasted over "well, I don't know
what *you* mean by 'analog', but when *I* say 'analog' I mean etc etc etc".
-------
22. You have made an unseemly attempt to bias this vote. The question is
not whether your discussion is ``useful and worth continuing,'' but whether
we *ALL* need to read or even be sent the truly amazing volume that you
seem able to generate on this one topic !?!
** Please remove your discussion from the AI-list (to a new bboard?). **
{And if you find it absolutely necessary to be mad at how stupid and
unjust the rest of the world is, go ahead and tally this as a vote for
your discussion being useless and not worth continuing}
-------
23.
1. I find it neither interesting nor useful.
2. The arguments, until I stopped following it, somtimeseveral weeks ago,
are circular if not repetitive.
3. I've speculated privately that the argruments were cranked out by a
machine in someone basement as a Turing Test on the rest of the net.
Either that or ...
4. But none of this justifies setting up another news group. comp.ai
isn't being used for anything else. For a heavily used group, see
comp.sys.ibm.pc.
5. Personally, I'd suggest that you take all of the correspondence. Put
it in a folder, and open it again at New Years. Reread it, and write
a real paper.
-------
24. Please stop!
-------
25. NO! Please take this discussion to e-mail. It's gone far
beyond the point where it's interesting to anyone other than
you and the few people still arguing.
-------
26. Stop it!
-------
27. The symbol grounding problem - please start your own newsgroup.
DEFINITELY!
-------
28. Although I don't think that AI-list should be strictly limited to
discussions of algorithms and similarly down-to-earth items, I do think
that the symbol grounding discussion has gotten a bit out of hand and
should be conducted privately among the three or four major participants,
with perhaps a summary to appear at some future date.
-------
29. In article <977@mind.UUCP> you write:
>David Harwood has made two very rude requests
(Yes, he was way out of line.)
As a former philosophy undergrad and current A.I. grad student,
I've found the topic in general to be interesting.
BUT . . . I think it should in fact be moved to its own newgroup.
Comp.ai is now completely dominated by exchanges between you and
Marty Brilliant, Anders Weinstein, etc. After a while, "listening"
to a few other people argue gets tedious, no matter how interesting
the topic. Frankly, I think people have been frightened away from
the newsgroup in the past few months, with the result that there have
been no discussions other than this one, unless you count a few
requests for info on some language.
P.S. I enjoyed your "uncomplemented categories" talk at the Phil/Psych meetings.
-------
30. I vote to cease the endless symbol grounding discussion!
-------
31. I find the discussion neither useful or worth continuing.
------------
32. Please stop it. I agree with Law that most of the discussion can be
carried thru private mail. I can see that R is easier to type than
mail ...%....@...... etc but, then use the facilities provided by
Unix like aliases etc. I am looking forward to your results.
-------
33. You asked for votes. Mine is... no more on the symbol grounding
problem. Thanks for asking.
-------
34. I for one would greatly appreciate having the discussion removed from
subsequent AIlists. As in a conference presentation, if a heated topic goes
on for too long, the people involved should agree to meet later and discuss
the issue amongst themselves without burdening the whole group. You must know
by now who the interested parties are; can't you just send mail to each other?
-------
35. It not the discussion per se that I think people object to as
much as it is the size of the discussion. The replys are very
large, each addressing 15 points of reply to the previous reply.
It takes a while to read through the text, and extract
some salient points of interest. Having real work to do, I sometimes
just file the message, thinking I'll get to it later.
I save ALL my mod.ai mail for a time in the near future when I attempt
to complete my MS and want to scan back over the current "hot" topics.
Unfortunatly I've had to start a special archive just for this discussion,
and it's chewing my disk drive all to bits with saved mail.
I find the disscussion interesting, and informative but...
(Now for the poll): If discussion continues to involve ginormous reply's: END IT
If discussion stops taking over whole digests: KEEP IT.
-------
36. I'm sorry but for me the discussion is no longer interesting.
-------
37. I think that this discussion belongs to philosophy, not to AI. I hope
that it will relocate itself accordingly.
--
Stevan Harnad (609) - 921 7771
{bellcore, psuvax1, seismo, rutgers, packard} !princeton!mind!harnad
harnad%mind@princeton.csnet harnad@mind.Princeton.EDU
------------------------------
Date: Thu 9 Jul 87 10:41:46-PDT
From: Ken Laws <LAWS@IU.AI.SRI.COM>
Subject: Characteristics of Discussion Lists
[Excerpt from a message to Steven Harnad.]
A problem with large, permanent lists is that they are primarily for
those on the fringes of a field who want to monitor or join what is
happening further in -- but not so far in that it becomes a full-time
occupation or involves incomprehensible jargon. The professionals
already have channels of communication among themselves (including
personal visits, seminars, conferences, publications, and even e-mail
or phone calls) and have little time for list discussions that are
outside their own exceedingly narrow specialties.
As to the suggestion of continuing via e-mail, it's not really so bad.
Two options exist. One is to cc everyone on each message, letting the
mailer propagate the cc list from one message to another. It is usually
easy to add new members to such a discussion, but impossible to drop old
ones without retyping the whole list. There is also a problem that BITNET
gateways don't add necessary routing information to message that are
handed over to the Arpanet. The other option is for one person to
maintain a file with all the addresses, headed by a "label:" to suppress
the information in the cc field of each message. All traffic is sent
to this one individual, who then remails it to the distribution. That's
a moderated list. (Anyone can get in this business!)
One of the charges in your Nay summary was that discussion of other
topics has been down since the fundamentals discussion took over.
I believe that's true, although there seems no rational reason for
it. Even queries and replies have been reduced, although that could
be a coincidence due to the end of the school year and of the proposal
year. A few people have dropped off the list because of the volume,
many more have added themselves because AIList was beginning to
border on their interests. The effects are complex, and certainly
not just a linear addition of your text to whatever would have been
present anyway.
I believe that the proper model of a discussion list is the town
meeting. AIList began with my own announcement of myself as
moderator, or chairman/speaker of the house. A group of interested
individuals formed, and through custom and convention we have worked
out an informal social contract that governs the proceedings. Part
of the contract is that participants pay reasonable attention to
the proceedings, if only to avoid redundant or naive remarks. This,
together with the serial nature of current message streams, implies
that only one person (more or less ...) has the floor. Part of
my job as moderator is to insure a balanced discussion, soliciting
(or forwarding) new topics and viewpoints. Not every list is run
as a town meeting, but that's my view of AIList.
The symbol grounding discussion was carried out with great respect
for the participants and with incredible attention to detail. AI
needs to grapple with the problems you raised. (Whether AIList
needs to is debated in your vote summaries.) The difficulty is simply
that people can't pay attention to everything, and your discussion
was demanding more attention than they could spare. The other rings
of the circus require equal time.
Incidentally, much of the personal criticism has been sparked by the
one-against-all nature of your discussion.
If the level of discussion had been more approachable, we might have
had more people joining your cause and providing examples for your
position. That would have been more interesting, and might have
reached an obvious conclusion or stalemate sooner. It is a common
characteristic of net debates, however, that nothing is ever settled.
Points that are agreed to are simply dropped, with little or no mention
that agreement has been reached, and may even be picked up by some
other participant. Net discussions generate a continuous stream of
ideas, but conclusions are lacking. I thank you for repeatedly
reminding us that conclusions have not been reached in this particular
topic area, and hope you will continue to contribute to AIList.
-- Ken
------------------------------
End of AIList Digest
********************
∂15-Jul-87 1048 LAWS@Stripe.SRI.Com AIList Digest V5 #182
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Jul 87 10:48:22 PDT
Date: Tue 14 Jul 1987 23:20-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #182
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 15 Jul 1987 Volume 5 : Issue 182
Today's Topics:
Logic Programming - ICOT Prolog Progress,
Humor - AI Justification of Star Wars,
Speculation - Moravec on Immortality,
Philosophy of Science - AI as a Science
----------------------------------------------------------------------
Date: Wed, 15 Jul 87 10:32:20 JST
From: Chikayama Takashi <chik%icot.jp@RELAY.CS.NET>
Reply-to: chik@icot.icot.JUNET (Chikayama Takashi)
Subject: Re: Say, what ever happened to ... ICOT Prolog?????
In article <8706111231.AA18169@mitre.arpa> elsaesser%mwcamis@MITRE.ARPA writes:
>It seems ages ago that the 5th generation project was going to
>reinvent AI in a Prolog "engine" that was to do 10 gazillion "
>LIPS". Anyone know what happened? I mean, if you can make so many
>"quality" cars (sans auto transmission, useful A/C, paint that can take
>rain and sun, etc.), why can't you make a computer that runs an NP-complete
>applications language in real time??? Semi-seriously, what is the status
>of the 5th generation project, anyone got an update?
Well, we are sorry not distributing enough information to the AI
society. Most papers related to ICOT's research are distributed to
the logic programming society but not to the AI world (I guess you
know how poor propagandist Japanese are:-). Many are reported in:
International Conference on Logic Programming
IEEE Symposium on Logic Programming
Please look into proceedings of these conferences.
For about 10 gazillion LIPS computers: What our research of these 5
years revealed is that highly parallel hardware can never be practical
without much software effort, including new concepts in programming
languages. More stress is put upon software than in the original
project plan. Indeed, VLSI technology is dropped off from the
project. Our experience shows that VLSI technology is NOT the most
difficult point in the way to realistic highly parallel computer
systems. An efficient system with 256 processors may be built without
changing the software at all. But for systems with 4096 processors,
we need a drastic change. And this is what we need to achieve 10
gazillion LIPS. NOT that VLSI technology has become easier, but that
we have found MORE difficult problems, unfortunately.
Where are we? Well, one of our recent hardware achievement is the
development of the PSI-II machine, which executes 400 KLIPS (much less
than 10 gazillion, I guess :-). It is a sequential machine and will
be used as element processors of our prototype parallel processor
Multi-PSI V2 (with 64 PE's), whose hardware is scheduled to come up at
the end of this year.
If you are interested in our research, a survey by myself titled:
"Parallel Inference System Researches in the FGCS Project"
will be presented in the IEEE Symposium on Logic Programming, held at
San Francisco during Aug 31-Sep 4, 1987. If you are more interested
in our project, please join the FGCS'88 conference. It will be held
in Tokyo during Nov 28-Dec 2, 1988.
Takashi Chikayama
------------------------------
Date: 14-Jul-1987 2028
From: minow%thundr.DEC@decwrl.dec.com (Martin Minow THUNDR::MINOW
ML3-5/U26 223-9922)
Subject: Book Report
From "Dirk Gently's Holistic Detective Agency," by Douglas Adams.
(New York: Simon and Schuster, 1987):
"Well," he said, "it's to do with the project which first made
the software incarnation of the company profitable. It was
called _Reason_, and in its own way it was sensational."
"What was it?"
"Well, it was a kind of back-to-front program. It's funny how
many of the best ideas are just an old idea back-to-front. You
see, there have already been several programs written that help
you make decisions by properly ordering and analysing all the
relevant facts.... The drawback with these is that the decision
which all the properly ordered and analyzed facts point to is not
necessarily the one you want.
"... Gordon's great insight was to design a program which allowed
you to specify in advance what decision you wished it to reach,
and only then to give it all the facts. The program's task, ...
was simply to construct a plausible series of logical-sounding
steps to connect the premises with the conclusion." ....
"Heavens. and did the program sell very well?"
"No, we never sold a single copy.... The entire project was bought
up, lock, stock, and barrel, by the Pentagon. The deal put WayForward
on a very sound financial foundation. Its moral foundation, on the
other hand, is not something I would want to trust my weight to.
I've recently been analyzing a lot of the arguments put forward in
favor of the Star Wars project, and if you know what you're looking
for, the pattern of the algorithms is very clear.
"So much so, in fact, that looking at Pentagon policies over the
last couple of years I think I can be fairly sure that the US
Navy is using version 2.00 of the program, while the Air Force for
some reason only has the beta-test version of 1.5. Odd, that."
------------------------------
Date: Wed 8 Jul 87 16:19:25-PDT
From: Ken Laws <LAWS@IU.AI.SRI.COM>
Subject: Moravec on Immortality
[Forwarded with permission of Hans.Moravec@ROVER.RI.CMU.EDU.]
From AP Newsfeatures, June 14, 1987
By MICHAEL HIRSH
Associated Press Writer
PITTSBURGH (AP) - If you can survive beyond the next 50 years or so,
you may not have to die at all - at least, not entirely. [...]
Hans Moravec, director of Mobile Robot Laboratory of the Robotics
Institute at Carnegie Mellon University, believes that computer
technology is advancing so swiftly there is little we can do to avoid
a future world run by superintelligent robots.
Unless, he says, we become them ourselves.
In an astonishingly short amount of time, scientists will be able to
transfer the contents of a person's mind into a powerful computer,
and in the process, make him - or at least his living essence -
virtually immortal, Moravec claims.
''The things we are building are our children, the next
generations,'' the burly, 39-year-old scientist says. ''They're
carrying on all our abilities, only they're doing it better. If you
look at it that way, it's not so devastating.'' [...]
''I have found in traveling throughout all of the major robotics and
artificial intelligence centers in the U.S. and Japan that the ideas
of Hans Moravec are taken seriously,'' says Grant Fjermedal, author
of ''The Tomorrow Makers,'' a recent book about the future of
computers and robotics. [He] Devotes the first five chapters of
his book to the work of Moravec and his proteges at CMU.
MIT's Gerald J. Sussman, who wrote the authoritative textbook on
artificial intelligence, agreed that computerized immortality for
people ''isn't very long from now.''
''A machine can last forever, and even if it doesn't you can always
make backups,'' Sussman told Fjermedal. ''I'm afraid, unfortunately,
that I'm the last generation to die. Some of my students may manage
to survive a little longer.'' [...]
CMU's Alan Newell, one of the so-called founding fathers of
artificial intelligence, cautions that while little stands in the way
of intelligent machines, the transfer of a human mind into one is
''going down a whole other path.''
''The ability to create intelligent systems is not at all the same
as saying I can take an existing mind and capture what's in that
mind. You might be able to create intelligence but not (capture) the
set of biological circumstances that went into making a particular
mind,'' he says.
In Moravec's forthcoming book, ''Mind Children,'' he argues that
economic competition for faster and better information-processing
systems is forcing the human race to engineer its own technological
Armageddon, one that a nuclear catastrophe can only delay.
Natural evolution is finished, he says. The human race is no longer
procreating, but designing, its successors.
''We owe our existence to organic evolution. But we owe it little
loyalty,'' Moravec writes. ''We are on a threshold of a change in the
universe comparable to the transition from non-life to life.''
Moravec's projections are based on his research showing that, on the
average, the cost of computation has halved every two years from the
time of the primitive adding machines of the late 19th century to the
supercomputers of the 1980s. [...]
Moreover, the rate is speeding up, and the technological pipeline is
full of new developments, like molecule-sized computer circuits and
recent advances in superconductors, that can ''sustain the pace for
the foreseeable future,'' he says.
The implications of a continued steady decrease in computing costs
are even more mind-boggling.
It is no surprise that studies in artificial intelligence have shown
sparse results in the last 20 years, Moravec says. Scientists are
severely limited by the calculating speed and capacity of laboratory
computers. Today's supercomputers, running at full tilt, can match in
power only the 1-gram brain of a mouse, he says.
But by the year 2010, assuming the growth rate of the last 80 years
continues, the best machines will be a thousand times faster than
they are today and equivalent in speed and capacity to the human
mind, Moravec argues. [...]
''All of our culture can be taken over by robots. It'll be boring to
be human. If you can get human equivalence by 2030, what will you
have by 2040?'' Moravec asks, laughing.
''Suppose you're sitting next to your best friend and you're 10
times smarter than he is. Are you going to ask his advice? In an
economic competition, if you make worse decisions, you don't do as
well,'' he says.
''We can't beat the computers. So that opens up another possibility.
We can survive by moving over into their form.''
There are a number of different scenarios of ''digitizing'' the
contents of the human mind into a computer, all of which will be made
plausible in the next 50 to 100 years by the pace of current
technology, Moravec says.
One is to hook up a superpowerful computer to the corpus callosum,
the bundle of nerve fibers that connects the two hemispheres of the
brain. The computer can be programmed to monitor the traffic between
the two and, eventually, to teach itself to think like the brain.
After a while, the machine begins to insert its own messages into
the thought stream. ''The computer's coming up with brilliant
solutions and they're just popping into your head,'' Moravec says [...]
As you lose your natural brain capacity through aging, the computer
takes over function by function. And with advances in brain scanning,
you might not need any ''messy surgery,'' Moravec says. ''Perhaps you
just wear some kind of helmet or headband.'' At the same time, the
person's aging, decrepit body is replaced with robot parts.
''In the long run, there won't be anything left of the original. The
person never noticed - his train of thought was never interrupted,''
he says.
This scenario is probably more than 50 years away, Moravec says, but
because breakthroughs in medicine and biotechnology are likely to
extend people's life spans, ''anybody now living has a ticket.''
Like many leading artificial intelligence researchers, Moravec
discounts the mind-body problem that has dogged philosophers for
centuries: whether a person's identity - in religious terms, his soul
- can exist independently of the physical brain.
''If you can make a machine that contains the contents of your mind,
then that machine is you,'' says MIT's Sussman.
Moravec believes a machine-run world is inevitable ''because we
exist in a competing economy, because each increment in technology
provides an advantage for the possessor . . . Even if you can keep
them (the machines) slaves for a long time, more and more
decision-making will be passed over to them because of the
competitiveness.
''We may be still be left around, like the birds. It may well be
that we can arrange things so the machines leave us alone. But sooner
or later they'll accidently step on us. They'll need the material of
the earth.''
Such talk is dismissed as sheer speculation by Moravec's detractors,
among them his former teacher, Stanford's John McCarthy, who is also
one of the founding fathers of artificial intelligence research.
McCarthy says that while he respects Moravec's pioneering work on
robots, his former Ph.D student is considered a ''radical.''
''I'm more uncertain as to how long it (human equivalence) will
take. Maybe it's five years. Maybe it's 500. He has a slight tendency
to believe it will happen as soon as computers are powerful enough.
They may be powerful enough already. Maybe we're not smart enough to
program them.''
Even with superintelligent machines, McCarthy says, it's hardly
inevitable that computers will take over the world.
''I think we ought to work it out to suit ourselves. In particular
it is not going to be to our advantage to give things with
human-level intelligence human-like emotions (like ambition). You
might want something to sit there and maybe read an encyclopedia
until you're ready to use it again,'' he says.
George Williams, an emeritus professor of divinity at Harvard
University, called Moravec's scenario ''entirely repugnant.'' [...]
McCarthy, however, insists there's no need to panic.
''Because the nature of the path that artificial intelligence will
take is so unknown, it's silly to attempt to plan any kind of social
policy at this early time,'' he says.
------------------------------
Date: Sun 12 Jul 87 19:45:34-PDT
From: Lee Altenberg <CCOCKERHAM.ALTENBERG@BIONET-20.ARPA>
Subject: AI is not a science
This discussion has brought to my mind the question of undecidability
in cellular automata, as discussed by S. Wolfram. For some rules and initial
sequences , the most efficient way of finding out how the automaton will behave
is simply to run it. Now, what is the status of knowledge about the
behavior of automata and the process of obtaining this knowledge? Is it a
science or not?
Invoking some of the previous arguments regarding AI, it could be
said that it is not a science because knowing something about an
automaton tells one nothing about the actual world. That is why mathematics
has been called not science.
Yet, to find out how undecidable automata behave one needs to
carry out experiments of running them. In this way they are just like a
worldly phenomenon where knowledge about them comes from observing them.
One must take an empirical approach to undecidable systems.
But there is another angle of evaluation. Naturalists have been
belittled as "not doing science" because their work is largely descriptive.
Does science consist then in making general statements? Or to be more precise,
does science consist of redescribing reality in terms of some general
statements plus smaller sets of statements about the world, which when combined
can generate the full (the naturalists's) description of reality? If this
is to be the case, then all examples of undecidable (and chaotic, I would
guess) processes fall outside the dominion of science, which seems to me
overly restrictive.
------------------------------
Date: Mon, 13 Jul 87 15:08:07 bst
From: Stefek Zaba <sjmz%hplb.csnet@RELAY.CS.NET>
Subject: AI as science: establishing generality of algorithms
In response to the points of Jim Hendler and John Nagle, about whether
you can verify that your favourite planning system can be shown to be
more general than the Standard Reference:
At the risk of drawing the slings and arrows of people who sincerely believe
Formalism to be the kiss of death to AI, I'd argue that there *are* better
characterisations of the power of algorithms than a battery of test cases -
or, in the case of the typical reported AI program, described in necessarily
space-limited journals, a tiny number thereof. Such characterisations are in
the form of more formal specs of the algorithm - descriptions of it which
strip away implementation efficiency tricks, and typically use quantification
and set operations to get at the gist of the algorithm. You can then *prove*
the correctness of your algorithm *under given assumptions*, or "equivalently"
derive conditions under which your algorithm produces correct results.
Such proofs are usually (and, I believe, more usefully) "rigorous - but -
informal"; that is a series of arguments with which your colleagues cannot
find fault, rather than an immensely long and tortuous series of syntactic
micro-steps which end up with a symbol string representing the desired
condition. Often it's easier to give sufficient (i.e. stronger than
necessary) conditions under which the algorithm works than a precise set of
necessary-and-sufficient ones. *Always* it's harder (for mere mortals like
me, anyway) than just producing code which works on some examples.
An example of just such a judicuious use of formalism which I personally found
inspiring is Tom Mitchell's PhD thesis covering the version space algorithm
(Stanford 1978, allegedly available as STAN-CS-78-711). After presenting a
discursive description of the technique in chapter 2, chapter 3 gives a formal
treatment which introduces a minimum of new terminology, and gives a simple
and *testable* condition under which the algorithm works: "A set of patterns P
with associated matching predicate M is said to be an admissible pattern
language if and only if every chain [totally ordered subset] of P has a
maximum and a minimum element".
Stefek Zaba, Hewlett-Packard Labs, Bristol, England.
[Standard disclaimer concerning personal nature of views applies]
------------------------------
Date: 13 Jul 87 05:23:56 GMT
From: ihnp4!lll-lcc!esl.ESL.COM!ssh@ucbvax.Berkeley.EDU (Sam)
Reply-to: ssh@esl.UUCP (Sam)
Subject: is AI a science?
[There are several components of AI, as there are of CS, but...]
Let's take a step back. Is "Computer Science" a science? -- Sam
------------------------------
End of AIList Digest
********************
∂15-Jul-87 1158 LAWS@Stripe.SRI.Com AIList Digest V5 #179
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Jul 87 11:58:19 PDT
Date: Tue 14 Jul 1987 22:35-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #179
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 15 Jul 1987 Volume 5 : Issue 179
Today's Topics:
Review - Spang Robinson 3#6, 6/87 &
Spang Robinson 3#7, 7/87 &
Canadian AI, 7/87,
Report - Strategy Learning with Connectionist Networks,
Bibliography - Definitions for Leff a58C &
Leff a58C (Part 1 of 2)
----------------------------------------------------------------------
Date: Sat, 11 Jul 1987 17:39 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: bm654 - Spang Robinson 3#6, 6/87
Summary of Spang Robinson Report on Artificial Intelligence
June 1987, Volume 3, No. 6
AI and The Military
In 1985, DOD AI activity was 91.1 million with funding of 500 million/year
estimated at 1992.
The rest discusses
summary of military activities, hopes and prospects in the AI field including
disillusionment on the part of some in industry. Gary Martins of Intelligent
Software is quoted as saying
"Early returns from the first two major AI projects under the strategic
computing program show few real accomplishments... The autonomous land vehicle
projected resulted in the construction of a handsome test track and a huge,
lumbering van stuffed with computers running expert systems software. If it
travels slowly enough (under three m.p.h), the van is sometimes able to
make it all the way around the brightly lit, carefully marked, optically
smooth course without serious mishap." "The pilot's associate project
aims to produce a refrigerator sized computing system, having functionality
comparable to a 3 inch by 5-inch check list car."
Charles Anderson of the SDI group said AI would use would be quite low
in the SDI project with no increase in the ADI budget for AI applications
in spite of the fact that the ADI budget itself is growing." However,
the SDI is still spending 200 million per year on AI.
Rome Air Force Development Center is building a system to help decide
if foreign rocket launches are threats. They also have systems to schedule
pilots and aircraft hours. They also have an expert system that links
together various office automation tools and can generate its own forms.
()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()
Shorts
AION corporation's ADS is being extended to CICS and IMS and other
IBM data base products.
Lockheed has set up a 4.5 million dollar AI center.
Symbolics has announced a single chip LISP processor which fits on one
card after adding interface and memory chips.
Coopers and Lybrand has developed an expert system to monitor brokerage
accounts for irregularities.
Allan Levine will be manager of Gold Hill's Los Angeles sales office.
James McGowan will be Palladian's vice president of sales and
marketing nad Thomas Murphy will be their director of sales.
40% of the Japanese Information Processing Association's presentations
were related to AI .
*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(*(
This issue also include a directory of people working at various companies,
agencies and the like in Military Artificial Intellgience and announcements
of various tools and expert systems at the above show.
------------------------------
Date: Sat, 11 Jul 1987 17:39 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: bm660 - Spang Robinson 3#7, 7/87
Summary of Spang Robinson Report on AI, Volume 3, No. 7, July 1987
The New AI Pioneers: The Knowledge Merchants
The market for pre-built expert systems was estimated at 10 to 15 million
for 1986 with expected growth to 40 million in 1987. Many developers
found extensive customization was needed for each customer while there
were many rules that were common to everybody in the application domain.
Some info on various expert systems being sold including data on how
many sold and time/cost to develop. UNDERWRITER saves three percent
in insurance losses while Syntelligence reports a five to ten percent
improvement in loss ratios.
The numbers on the left are the development cost or times while the
numbers on the right are the purchase price.
40 man years: APEX Plan Power (125 sold) ~$34,500
20 man years: APEX Client Profiling ~$100,000
50 man years: Palladian operations planning system ~$100,000
50 man years: Palladian project management system ~$100,000
Sterling Wentworth: PLANMAN, PC based planning system
(800 copies, 7500 rules)
8 million: Syntelligence Syntel (risk assesment) ~500,000
Expert Technlogies (yellow page layout)
Cogensys: judgement processing for financial service applications
(9 systems installed.) ~ $250,000
Composition Systems: publishing systems
Eloquent Systems: Hotel Inventory Processing
Applicon: circuit design
Direct Marketing: Persorft
TRansform Logic: Computer Aided Software Engineering
(Generates COBOL generation)
General Data System, RATER and UNDERWRITER for insurance ~$250,000
_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-
Real Time Expert Systems on PC's and micros.
Texas Instruments developed an expert system in FORTH to control water
treatment plan. McDonald Douglas is using a Fuzzy Logic based Forth running
on the NOVIX forth engine running 30,000 rules per second.
UME Corporation offers an Expert Controller
box which is a self-contained controller using expert system technology
supporting 5000 rules/second and 16,000 rules total.
It is being used in automotive hood stamping process control and for industrial
clothes driers.
ONSPEC sells a Stand Alone System for $895.00 and Superintendant intended
for running Programmable Logic Controllers. The systems support a user-friendly
operator interface for the final system, explicit handling of unknown
data and retraction of facts.
The system handles 1000 rules and 50 rules per second. (A review of
this software is in the issue.)
()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()
Shorts:
Natural Language Incorporated has a product licensing and equity financing
agreement with MicroSoft.
DATA General will be distributing Gold Hill's products.
Teknowledge has named a former Under Secretary of Defense to
it's board of directors.
Nestor, a maker of a neural-network based system,
reported a net loss of $539,252 on revenues of $8,016.
MicroProducts is marketing PowerLisp, a virtual memory based system,
for Intel 286 and 386 based PC's.
Programs in Motion is now offering
an expert system with code generators for Pascal, C, dbase III interfacing
and form design capabilities.
Automated Reasoning is developing expert systems for ATE programming
and generates source code in BASIC, C, ATLAS, ADA or Pascal.
------------------------------
Date: Sat, 11 Jul 1987 17:39 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: bm668 - Canadian AI, 7/87
Summary of Canadian Artificial Intellgience, July 1987, No. 12
Discussion of the Canadian Governments research initiative.
The Canadian AI Conference for 1988 will be June 6-10, 1988 in Edmonton.
It will be held simultaneously with the Canadian Image Processing and Pattern
Recognition Society and Canadian Man-Computer Communications Society
meetings.
Jose A. Ambros_Ingerson of University of California, Irvine is collecting
info re AI applications and efforts in Third World Countries.
Canada is setting up a research consortium for AI and robotics.
This is similar to MCC and other efforts in that companies produce
research that they all can use before competitive additions and
applications are made.
There was a report on the National Meeting of the Fifth Generation Society.
There are a variety of research infrastructures in Canada involving
joint industry-academic type efforts.
New bindings:
Nick Cercone will be Director of the Centre for Systems Science at
Simon Fraser University.
Randy Goebel is now at the University of Alberta.
Brian Schaefer, Beverly Smith, Ian Morrison and Julian Siegel are now
at Acquired Intelligence, 2304 Epworth Street, Victoria B. C. V8R 5L2.
Report on Research at University of Toronto:
Hector Levesque and Ray Reiter are working on formal foundations of
knowledge-based systems.
John Mylopoulos is working on AI applications to software engineering
and databases.
Russ Greiner on learning by analogy.
Effort to develop an autonomous vision-guided robot.
Interpretation of Remotely Sensed Images, e. g. from satellites.
Applications include river or lake ice measurements and interpreting
weather data for storm forecasting
Knowledge Based Debugging system based on MRS.
Reviews of "Robotics Research: The Third International Symposium"
New Horizons in Educational Computing by Masoud Yazdani
The Mathematics of Inheritance Systems by David S. Touretsky
Robotics and Ai: An Introduction to Applied Machine Intelligence
by Andrew C. Staugaard.
Abstracts of papers in Computational Intelligence and some
AI Technical Reports.
Report on the recent CHI+GI+87 conference on Computer Human Interactions
and Graphical Interfaces.
------------------------------
Date: Mon, 13 Jul 87 14:23:53 EDT
From: Chuck Anderson <cwa0%gte-labs.csnet@RELAY.CS.NET>
Subject: Technical Report: Strategy Learning with Connectionist
Networks
Strategy Learning with Multilayer Connectionist Representations
Chuck Anderson
(cwa@gte-labs.csnet)
GTE Laboratories Incorporated
40 Sylvan Road
Waltham, MA 02254
Abstract
Results are presented that demonstrate the learning and
fine-tuning of search strategies using connectionist mechanisms.
Previous studies of strategy learning within the symbolic,
production-rule formalism have not addressed fine-tuning behavior.
Here a two-layer connectionist system is presented that develops its
search from a weak to a task-specific strategy and fine-tunes its
performance. The system is applied to a simulated, real-time,
balance-control task. We compare the performance of one-layer and
two-layer networks, showing that the ability of the two-layer network
to discover new features and thus enhance the original representation
is critical to solving the balancing task.
(Also appears in the Proceedings of the Fourth International Workshop on
Machine Learning, Irvine, June, 1987)
------------------------------
Date: Sat, 11 Jul 1987 17:39 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: defs for a58C
D MAG115 Pattern Recognition\
%V 20\
%N 1\
%D 1987
D MAG116 1985 International Test Conference\
%D 1985
D MAG117 Proceedings IEEE International Symmposium on Circuits and Systems\
%C Kyoto, Japan\
%D JUN 5-7 1985
D MAG118 Proceedings of the Second Australian Conference on Applications of Expe
rt Systems\
%C Sydney\
%D 14-16 May 1986
D BOOK66 International Conference on Computers in Engineering Conference and Exh
ibit (Las Vegas)\
%D 1984\
%I American Society for Mechanical Engineers
D MAG119 Proceedings of the 1986 International Test Conference\
%D SEP 9-11, 1986
D MAG120 1986 IEEE International Conference on Computer Design (Port Chester, NY
)\
%D October 6-9, 1986
D BOOK67 1985 Engineering Software IV\
%I Springer Verlag\
%C Berlin-Heidelberg New York\
%D 1985\
%E R. A. Edey
D MAG121 American Control Conference (Seattle, WA)\
%D JUN 18-20 1986
D MAG122 1985 Proceedings Annual Reliability and Maintainability Symposium\
%D 1985
D MAG123 Proceedings of the 1986 International Computers and Engineering Confere
nce (Chicago, Ill.)\
%D JUL 1986
D MAG124 International Conference on Computer Aided Design (Santa Clara, CA)\
%D 1986
D MAG130 AT&T Technical Journal\
%V 65\
%N 5\
%D SEP-OCT 1986
D MAG131 Pattern Recognition Letters\
%V 5\
%N 3\
%D MAR 1987
D BOOK80 Mathematical Foundations of Computer Science\
%S Lecture Notes in Computer Science\
%V 233\
%I Springer-Verlag\
%C Berlin-New York\
%D 1986
D MAG132 J. Logic Programming\
%V 3\
%N 3\
%D 1986
D BOOK81 GWAI-85 Proceedings of the Ninth German Workshop on Artificial Intellig
ence\
%E Herbert Stoyan\
%S Technical Reports on Information Science\
%V 118\
%I Springer-Verlag\
%C Berlin-New York\
%D 1986
D BOOK82 Eighth International Conference on Automated Deduction (Oxford 1986)\
%P 470-488\
%S Lecture Notes in Computer Science\
%V 230\
%I Springer-Verlag\
%C Berlin-New York\
%D 1986
D BOOK83 Algebra, Combinatorics and Logic in Computer Science, Vol I. II, (Gyor,
1983)\
%S Colloq. Math. Soc. Janos Bolyai\
%V 42\
%I North-Holland\
%C Amsterdam-New York\
%D 1986
D BOOK84 Category Theory and Computer Programming (Guildford, 1985)\
%S Lecture Notes in Computer Science\
%V 240\
%I Springer-Verlag\
%C Berlin-New York\
%D 1986
D MAG135 Journal of Logic Programming\
%V 3\
%N 4\
%D 1986\
D MAG136 IEEE Transactions on Geoscience and Remote Sensing\
%V 25\
%N 3\
%D MAY 1987
D MAG137 Soviet Journal of Computer and Systems Sciences\
%V 24\
%N 6\
%D NOV-DEC 1986
------------------------------
Date: Sat, 11 Jul 1987 17:39 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: a58C (Part 1 of 2)
%A M. J. Amundsen
%T The Compact LISP Machine, a Lisp Machine in a Shoe Box
%J IEEE National Aerospace and Electronics Conference
%V 4
%D 1986
%P 1309-1314
%K H02
%A Robert Buday
%T LISP-Machine Maker Symbolics, Spawned at MIT, is Growing Up
%J Information Week
%N 5
%D MAR 3, 1986
%P 34-37
%K H02 AT16
%A M. Carlsson
%T A Microcoded Unifier for LISP Machine Prolog
%B Symposium on Logic Programming
%D 1985
%P 162-171
%K T02 H02
%A H. Maegawa
%T Fast LISP Machine and Lisp Evaluation Processor Eval II-processor Architectur
e
and Hardware Configuration
%J Journal of Information Processing (Japan)
%V 8
%N 2
%D 1985
%P 121-126
%K H02 GA01
%A S. Sakamooto
%T The Design of a Firmware LISP Machine
%R Technology Reports of the Seikei University
%I Faculty of Engineering, Fukuoka, Japan
%N 41
%D 1986
%P 2751-2752
%K H02
%A H. Schotel
%A J. Pijls
%T A Prototype From Grammatical Instruction on a LISP Machine
%J Informatie (Netherlands)
%V 28
%N 1
%D 1986
%P 48-50
%A J. Spoerl
%T The Architecture of the Symbolics LISP Machine
%J Informatique
%V 1
%D 1986
%P 140-144
%A J. M. Switlik
%A R. J. Short
%T The Database Environment and the LISP Machine
%B Artificial Intelligence and Advanced Computer Technology Conference and
Exhibition. Proceedings.
%D 1986
%A M. Yuhara
%T Evaluation of the FACOM Alpha LISP Machine
%B Thirteenth Annual International Symposium on Computer Architecture
%D 1986
%P 184-190
%K H02
%A V. W. Zue
%T The Development of the MIT LISP-Machine Based Research Workstation
%J International Conference on Acoustics, Speech and Signal Processing.
proceedings
%V 1
%D 1986
%P 329-332
%A Y. J. Chao
%T Image Processing Methods in Ductile Fracture of Solids
%J Mechanics
%V 14
%N 1
%D JAN-FEB 1987
%P 57-60
%K AA05 AI06
%A Yu. S. Afonin
%T Blocked Branch and Bound Method
%J Automation and Remote Control
%V 47
%N 8 Part II
%D AUG 1986
%P 1107
%K AI03
%A I. B. Muchnik
%A P. M. Snegirev
%T Algorithm to Estimate the Approximation Accuracy of an Empirical Dependence
%J Automation nad Remote Control
%V 47
%N 8 Part II
%D AUG 1986
%K O06 AI04 O04
%A J. L. Nevins
%T Information-Control Aspects of Sensor Systems for Intelligent Robotics
%J Journal of Robotic Systems
%V 4
%N 2
%D APR 1987
%P 215-228
%K AI07 AI06
%A Hooshang Hemami
%A Ralph E. Goddard
%T Recognition of Geometrical Shape by a Robotic Probe
%J Journal of Robotic Systems
%V 4
%N 2
%D APR 1987
%P 237-258
%K AI06 AI07
%A Ren C. Luo
%T MIcrocomputer-Based Robot Dynamic Sensing Using Linear Array Sensor for
Object Recognition and Manipulation
%J Journal of Robotic Systems
%V 4
%N 2
%D APR 197
%P 199-214
%K AI06 AI07 H01
%A C. Morandi
%A F. Piazza
%A R. Capancioni
%T Digital Image Registration by Phase Correlation Between Boundary Maps
%J IEE Proceedings-E
%V 134
%N 2 Part E
%P 101-104
%D MAR 1987
%K AI06
%A J. Mantas
%T Methodologies in Pattern Recognition and Image Analysis -- A Brief
Survey
%J MAG115
%P 1-6
%K AI06
%A R. W. Smith
%T Computer Processing of Line Images: A Survey
%J MAG115
%P 7-16
%K AI06
%A S. J. Roan
%A J. K. Aggarwal
%A W. N. Martin
%T Multiple Resolution Imagery and Texture Analysis
%J MAG115
%P 17-34
%K AI06
%A S. Basu
%A K. S. Fu
%T Image Segmentation by Syntactic Method
%J MAG115
%P 35-44
%K AI06
%A Zhen Zhang
%A M. Simaan
%T A Rule-Based Interpretation System for Segmentation of Seismic Images
%J MAG115
%P 45-54
%K AI06
%A Maylor K. Leung
%A Yee-Hong Yang
%T Human Body Motion Segmentation in a Complex Scene
%J MAG115
%P 55-64
%K AI065
%A D. J. Peuquet
%A Zhang Ci-Xiang
%T An Algoirthm to Determine the Directional Relationship Between Arbitrarily-
Shaped Polygons in the Plane
%J MAG115
%P 65-74
%K AI06
%A L. G. Shapiro
%A R. S. MacDonald
%A S. R. Sternberg
%T Ordered Structural Shape Matching with Primitive Extraction by Mathematical
Morphology
%J MAG115
%P 75-90
%K AI06
%A M. R. Korn
%A C. R. Dyer
%T 3-D Multiview Object Representations for Model-Based Object Recognition
%J MAG115
%P 91-104
%K AI06
%A Toshifumi Tsukiyama
%A T. S. Huang
%T Motion Stereo for Navigation of Autonomous Vehicles in Man-Made Environments
%J MAG115
%P 105-114
%K AI06 AA19
%A S. Y. Lee
%A S. Yalamanchili
%A J. K. Aggarwal
%T Parallel Image Normalization on a Mesh Connected Array Processor
%J MAG115
%P 115-124
%K AI06 H03
%A H. D. Cheng
%A K. S. Fu
%T VLSI Architectures for String Matching and Pattern Matching
%J MAG115
%P 125-142
%K AI06 O06 H03
%A H. Mellink
%A H. Buffart
%T Abstract Code Network as a Model of Perceptual Memory
%J MAG115
%P 143
%K AI08
%A K. N. Ngan
%A A. A. Kassim
%A H. S. Singh
%T Parallel Image-Processing System Based on the TMS 32010 Digital
Signal Processor
%J IEE Proceedings E
%V 134
%N 2 Part E
%D MAR 1987
%K AI06 H03
%A Soundar R. T. Kumara
%A R. L. Kashyap
%A C. L. Moodie
%T Expert System for Industrial Facilities Layout Planning and Analysis
%J Computers and Industrial Engineering
%V 12
%N 2
%D 1987
%K AA05 AI01
------------------------------
End of AIList Digest
********************
∂15-Jul-87 1236 LAWS@Stripe.SRI.Com AIList Digest V5 #180
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Jul 87 12:35:41 PDT
Date: Tue 14 Jul 1987 22:48-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #180
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 15 Jul 1987 Volume 5 : Issue 180
Today's Topics:
Bibliography - Leff a58C (Part 2 of 2)
----------------------------------------------------------------------
Date: Sat, 11 Jul 1987 17:39 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: a58C (Part 2 of 2)
%A D. Driankov
%T An Outline of a Fuzzy Sets Approach to Decison making with Interdependent
Goals
%J Fuzzy Sets and Systems
%V 21
%N 3
%D MAR 1987
%P 275-288
%K O04 AI13
%A J. J. Buckley
%T The Fuzzy Mathematics of Finance
%J Fuzzy Sets and Systems
%V 21
%N 3
%D MAR 1987
%P 257-274
%K AA06 O04
%A S. K. M. Wong
%A W. Ziarko
%T Comparison of the Probabilistic Approximate Classification and the Fuzzy
Set Model
%J Fuzzy Sets and Systems
%V 21
%N 3
%D MAR 1987
%P 357-362
%K O04
%A W. Karkowkski
%A N. O. Mulholland
%A T. L. Ward
%T A Fuzzy Knowledge Base of an Expert System for Analysis of Manual Lifting
Tasks (Case Studies and Applications Contribution)
%J Fuzzy Sets and Systems
%V 21
%N 3
%D MAR 1987
%P 363
%K AA05 O04
%A S. S. Rao
%T Description and Optimum Design of Fuzzy Mechanical Systems
%J Journal of Mechanisms, Transmissions and Automation in Design
%V 109
%N 1
%D MAR 1987
%K AA05 O04
%P 126-132
%A Heiko Krumm
%T Logical Verification of Concurrent Programs
%J Angewandte Informatik
%N 4
%D APR 1987
%P 131-140
%K AA08
%A Janice I. Glasgow
%A Glenn H. MacEwen
%T Developing and Proof of a Formal Specification for a Multilevel
Secure System
%J ACM Transactions on Computer Systems
%V 5
%N 2
%D May 1987
%P 151
%K AA08
%A A. Pashtan
%T A Prolog Implementation of an Instruction-level Simulator
%J Software Practice and Experience
%V 17
%N 5
%D MAY 1987
%P 309-318
%K AA08 AA04 T02
%A James L. Flanagan
%T Speech Processing an Evolving Technology
%J MAG130
%P 2-11
%K AI05
%A James G. Josenhans
%A John F. Lynch, Jr.
%A Marian R. Rogers
%A Richard R. Rosinski
%A Wendy P. VanDame
%T Speech Processing Application Standards
%J MAG130
%P 23-33
%K AI05
%A Robert J. Perdue
%A Eugene L. Rissanen
%T Conversant 1 Voice System: Architecture and Applications
%J MAG130
%P 34-47
%K AI05
%X Conversant is a Registered Trademark
%A John G. Ackenhusen
%A Syed S. Ali
%A James G. Josenhans
%A John W. Moffett
%A Reuel R. Robertson
%A Jaime R. Tormos
%T Speech Processing for AT&T Workstations
%J MAG130
%P 60-67
%K AI05
%A John G. Ackenhausen
%A Syed S. Ali
%A David Bishop
%A Louis F. Rosa
%A Reed Thorkildsen
%T Single-Board General-Prupose Speech Recognition System
%J MAG130
%P 48-59
%K AI05
%A Martha Birnbaum
%A Larry A. Cohen
%A Frank X. Welsh
%T A Voice Password System for Access Security
%J MAG130
%P 68-74
%K AI05
%A Bishnu S. Atal
%A Lawrence R. Rabiner
%T Speech Research Directions
%J MAG130
%P 75-88
%K AI05
%A Knut Conradsen
%A Gert Nilsson
%T Data Dependent Filters for Edge Enhancement of Landsat Images
%J Computer Vision, Graphics, and Image Processing
%V 38
%N 2
%D MAY 1987
%P 101-121
%K AI06
%A Ken-Ichi Kanatani
%T Structure and Motion from Optical Flow Under Perspective Projection
%J Computer Vision, Graphics, and Image Processing
%V 38
%N 2
%D MAY 1987
%P 122-146
%K AI06
%A Azriel Rosenfeld
%T Picture Processing: 1986
%J Computer Vision, Graphics, and Image Processing
%V 38
%N 2
%D MAY 1987
%P 147
%K AI06
%A W. Greblicki
%A M. Pawlak
%T Necessary and Sufficient Conditions for Bayes Risk Consistency of a Recursive
Kermnel Classification
%J IEEE Transactions on Information Theory
%D MAY 1987
%V 33
%N 3
%P 408-411
%K O04
%A V. Wispfenning
%T The Complexity of the Word Problem for Abelian I-Groups
%J Theoretical Computer Science
%V 48
%N 1
%D 1986
%P 127
%K AI14 AI10
%A A. V. Zhozhikashvili
%A V. L. Stefanyuk
%T The Category Theory in Problems of Knowledge Representation and Learning
%J Soviet Journal of Computer and Systems Sciences
%V 24
%N 5
%D SEP-OCT 1986
%P 11-23
%K AI16 AI04
%A Ye. K. Gordiyenko
%T Implementation of Search Functions of the FRL Language Using a Two-Tag
Associative Memory
%J Soviet Journal of Computer and Systems Sciences
%V 24
%N 5
%D SEP-OCT 1986
%P 43-58
%K AI03
%A L. I. Feygin
%T Estimation of the Value of the Planning Horizon in the Case of Fuzzy
Durations of the Operations
%J Soviet Journal of Computer and Systems Sciences
%V 24
%N 5
%D SEP-OCT 1986
%P 97-101
%K AI09 O04
%A Ronald R. Yager
%T On the Dempster-Shafer Framework and New Combination Rules
%J Information Sciences
%V 41
%N 2
%D MAR 1987
%P 93-138
%K O04
%A J. C. A. Van Der Lubbe
%A D. E. Boekee
%A Y. Boxma
%T Bivariate Certainty and Information Measures
%J Information Sciences
%V 41
%N 2
%D MAR 1987
%P 139-170
%K O04
%A M. A. Zuenkev
%A A. S. Kulguskin
%A A. G. Poletykin
%T Forming Similarity Relations in Analogy-Driven Systems
%J Automation and Remote Control
%V 47
%N 11 Part 2
%D NOV 1986
%P 1543-1551
%K AI16
%A S. Daley
%A f. F. Gill
%T Attitude Control of a Spacecraft Using an Extended Self-Organizing
Fuzzy Logic Control
%J Proceedings of the Institution of Mechanical Engineers Part C
%V 201
%N 2
%D 1987
%P 97-106
%K AA05 O04
%A G. Jumarie
%T A Concept of Observed Weighted Entropy and its Application to Pattern
Recognition
%J MAG131
%P 191-194
%K AI06
%A J. H. Kim
%T Distributed Inference for Plausible Classification
%J MAG131
%P 195-202
%K AI06
%A J. Ma
%A X. Lu
%A C. Wu
%T A Motion Constraint Equation Under Space-Varying or Time Varying
Illumination
%J MAG131
%P 203-206
%K AI06
%A M. Werman
%A A. Y. Wu
%A R. A. Melter
%T Recognition and Characterization of Digitized Curves
%J MAG131
%P 207-214
%K AI06
%A G. Cristobal
%A J. Bescos
%A J. Santamaria
%A J. Montes
%T Wigner Distribution Representation of Digital Images
%J MAG131
%P 215-222
%K AI06
%A S. Peleg
%A D. Keren
%A L. Schweitzer
%T Improving Image Resolution Using Subpixel Motion
%J MAG131
%P 223-226
%K AI06
%A M. C. Yuan
%A J. G. Li
%T A Production System for LSI Chip Anatomizing
%J MAG131
%P 227-232
%K AI06
%A R. D. Grisell
%T Noniterive Correction of Images and Motion Sequences
%J MAG131
%P 223-242
%K AI06
%A P. Fua
%A A. J. Hanson
%T Resegmentation Using Generic Shape: Locating General Cultural Objects
%J MAG131
%P 243
%K AI06
%A A. M. Rustamov
%A N. G. Dzhanibekova
%A V. G. Zakiev
%T Development of the Automated System on the Analysis of Reader Demand in
Regional Integral Automated Library-Bibliography Systems
%J Nauchno-Tekhnicheskaya Informatsiya, Seriya II - Informatsionnye
Protsessy I Sistemy
%N 3
%D 1987
%P 11-18
%K AA14
%A I. A. Bolshakov
%T Pure Automatic Seplling Correction Based on the Keyboard Model of
Common Errors
%J Nauchno-Tekhnicheskaya Informatsiya, Seriya II - Informatsionnye
Protsessy I Sistemy
%N 3
%D 1987
%P 11-18
%A K. V. K. K. Prasad
%A T. S. Lamba
%T Natural Language Interface Based on Keyword Extraction Using AWK
%J Microprocessors and Microsystems
%V 11
%N 3
%D APR 1987
%K AI02
%P 157-160
%A A. N. Averkin
%A V. B. Tarasov
%T The Fuzzy Modeling Relation and its Application to Artificial Intelligence
%J MAG122
%P 3-24
%K O04
%A A. V. Alexeyev
%A A. N. Borisov
%A V. I. Glushkov
%A O. A. Krumberg
%A G. V. Merkuryeva
%A V. A. Popov
%A N. N. Slyadz
%T A Linguistic Approach to Decision-Making Problems
%J MAG123
%P 25-42
%K AI02 AI13 O04
%A R. A. Aliev
%T Production Control on the Basis of Fuzzy Models
%J MAG123
%P 43-56
%K O04
%A A. F. Blishun
%T Fuzzy Learning Models in Expert Systems
%J MAG123
%P 57-70
%K AI01 AI04 O04
%A V. E. Zhukovin
%A F. V. Burshtein
%A E. S. Korelov
%T A Decisoin Making Model with Vector Fuzzy Preference Relation
%J MAG123
%P 71-80
%A S. G. Svarovski
%T Usage of Linguistic Variable Concept for Human Operator Modelling
%J MAG123
%P 107-114
%K O04 AI02
%A D. A. Pospelov
%T Fuzzy Reasoning in Pseudo-Physical Logics
%J MAG123
%P 115-120
%K O04
%A S. V. Chesnokov
%T The Effect of Semantic Freedom in the Logic of Natural Language
%J MAG123
%P 121-154
%K AI02 O04
%A D. I. Shapiro
%T Human Specifics, Fuzzy Categories and Counteraction in Decision
Making Problems
%J MAG123
%P 155-170
%K AI13 O04
%A I. A. Newman
%A R. P. Stallard
%A M. C. Woodward
%T A Hybrid Multiple Processor Garbage Collection Algorithm
%J The Computer Journal
%V 30
%N 2
%D APR 1987
%P 110-118
%K T01 H03
%A J. L. Dupouey
%T Using Artificial Intelligence Languages for the Calculation of
Inbreeding Coefficients - New Tools for an Old Problem
%J Computers in Biology and Medicine
%V 17
%N 2
%D 1987
%P 71-74
%K AA10
%A Rob Gerth
%A W. P. de Roever
%T Proving Monitors Revisited: a First Step Towards Verifying Object
Oriented Systems
%J Fund. Inform.
%V 9
%D 1986
%N 4
%P 371-399
%K AA08
%A P. T. Cox
%T On Determining the Causes of Nonunifiability
%J J. Logic Programming
%V 4
%D 1987
%N 1
%P 33-58
%K AI14 AI10
%A Peter van Emde Boss
%T A Semantical Model for Integration and Modularization of Rules
%B BOOK80
%P 78-92
%K AI01 AI16
%A Ken Hirose
%T An Approach to Proof Checker
%B BOOK80
%P 113-127
%K AA13 AI14 AI11
%A Guy Jumarie
%T New Decision Rules in Statistical Pattern Recognition
%J Kybernetes
%V 16
%D 1987
%N 1
%P 11-18
%K AI06
%A A. V. Kabulov
%A B. I. Zufarov
%T Logical Methods for the Design of Optimal Correctors of Heuristic
Algorithms
%B "Fan"
%C Tashkent
%D 1985
%P 11-17
%K AI16
%A I. V. Kotel'nikov
%T An Algorithm for Constructing a Set of Irredundant Fuzzy Sets
%J Avtomat. i. Telemekh.
%D 1986
%N 9
%P 139-144
%K O04
%A M. A. Nait Abdallah
%T Al-Khowarizmi: A Formal System for Higher Order Logic Programming
%B BOOK80
%P 545-553
%K AI10
%A Zbigniew W. Ras
%A Maria Zemankova
%T Learning in Knowledge Based Systems, a Possibilistic Approach
%B BOOK80
%P 630-638
%K AI04 O04
%A D. Snyers
%T Theorem Proving Techniques and P-Functions for Logic Design and
Logic Programming
%J Philips J. Res
%V 41
%D 1986
%N 5
%P 560-505
%K AA04 AI11 AI10
%A Zbigniew M. Wojcik
%T The Rough Sets Utilization for Linguistic Pattern Recognition
%J Bull. Polish Acad. Sci. Tech. Sci
%V 34
%D 1986
%N 5-6
%P 285-312
%K AI06 AI02
%A S. K. M. Wong
%T Algorithm for Inductive Learning
%J Bull. Polish Acad. Sci. Tech. Sci.
%V 34
%D 1986
%N 5-6
%P 271-276
%K AI04
%A S. K. M. Wong
%A Wojciech Ziarko
%T Remarks on Attribute Selection Criterion in Inductive Learning Based
on Rough Sets
%J Bull. Polish. Acad. Sci. Tech. Sci
%V 34
%D 1986
%N 5-6
%P 273-283
%K AI04
%A W. Bibel
%A Ph. Jorrand
%T Fundamentals of Artificial Intelligence. An Advanced Course.
%S Lecture Notes in Computer Science
%V 232
%I Springer-Verlag
%C Berlin-New York
%D 1986
%K AI16 AT15
%A V. Arvind
%A Somenath Biswas
%T An O($N sup 2$) algorithm for the Satisfiability Problem of a Subset
of Propositional Sentences in CNF that Includes all Horn Sentences
%J Inform. Process. Lett
%V 24
%D 1987
%P 67-69
%K O06 AI10
%A Luis Farinas del Cerro
%A Martti Pentonnen
%T A Note on the Complexity of the Satisfiability of Modal Horn Clauses
%J J. Logic Programming
%V 4
%D 1987
%N 1
%P 1-10
%K AI11 O06
%A Fracoise Fogelman-Soulie
%A Gerard Weisbuch
%T Random Iterations of Threshold Networks and Associative Memory
%J SIAM J. Comput
%V 16
%D 1987
%N 1
%P 203-220
%K AI16 AI08
%A Erik Tiden
%T First-order Unification in Combinations of Equational Theories (Ph. D.
Thesis)
%I Royal Institute of Technology
%C Stockholm
%D 1986
%K AI14 AI11
%A Moshe Y. Vardi
%T Querying Logical Databases
%J J. Comput. System Sci
%V 33
%D 1986
%N 2
%P 142-160
%K AA09 AI10
%A Zbigniew M. Wojcik
%T Contextual Information Research within Sentence with the Aid of the Rough
Sets
%J Bull. Polish Acad. Sci. Tech. Sci
%V 34
%D 1986
%N 5-6
%P 313-330
%K AI02 O04
%A Friedhelm Hinz
%T Regular Chain Code Picture Languages of Nonlinear Descriptional
Complexity
%B BOOK80
%P 414-421
%K AI06
%A Stephen D. Brookes
%T A Fully Abstract Semantics and a Proof System for an ALGOL-like language
with Sharing
%B Mathematical Foundations of Programming Semantics
%P 59-100
%S Lecture Notes in Computer Science
%I Springer-Verlag
%C Berlin-New York
%D 1986
%K AA08
%A Susanne Graf
%T A Complete Inference System for an Algebra of Regular Acceptance Models
%B BOOK80
%P 386-395
%K AI10
%A Laszlo Bela Kovacs
%T Automated Protocol Verification
%B Kozl.-MTA Szamitastech. Automat. Kutato Int. Budapest
%N 33
%D 1985
%P 37-45
%A M. J. Beeson
%T Proving Programs and Programming Proofs
%B Logic, Methodology and Philosophy of Science, VII
%S Stud. Log Foundations Math.
%V 114
%I North-Holland
%C Amsterdam-New York
%D 1986
%K AA08 AI16
%A Anne-Marie Deroualt
%A Bernard Merialdo
%T Language Modelling Using a Hidden Markov Chain with Application
to Automatic Transcription of French Stenotypy
%B Semi-Markov Models
%I Plenum
%C New York-London
%D 1986
%K AI02
%A A. J. Baddeley
%T Stochastic Geometry and Image Analysis
%B Mathematics and Computer Science (Amsterdam 1983)
%P 1-18
%S CWI Monographs
%V 1
%I North-Holland
%C Amsterdam-New York
%D 1986
%K AI06
%A A. G. Ivakhenko
%A S. A. Petukhova
%T Objective Computerized Clustering. I. Theoretical Questions
%J Soviet J. Automat. Inform. Sci
%V 19
%D 1986
%N 3
%P 1-9
%K O06
%A Hassan Ait-Kaci
%T LOGIN: A Logic Programming Language with Built-in Inheritance
%J MAG132
%P 185-215
%K AI10
%A Marco Bellia
%A Giorgia Levi
%T The Relation Between Logic and Functional Languages: A Survey
%J MAG132
%P 217-236
%K AT08
%A Karl-Hans Blasius
%T Equality Reasoning with Equality Paths
%B BOOK81
%P 57-76
%K AI14
%A Wolfram Buttner
%T Unification in the Data Structure Sets
%B BOOK82
%P 470-488
%K AI14 AA08
%A Ahlenλm Ben Cherifs
%A Pierre Lescane
%T An Actual Implementation of a Procedure that Mechanically Proves
Termination of Rewriting Systems Based on Inequalities Between
Polynomial Interpretations
%B BOOK82
%P 42-51
%K AI14 AI11
%A P. Ciancarini
%A P. Degano
%T An Approach to Proving Properties of Nonterminating Logic Programs
%B BOOK83
%P 223-243
%K AI14 AA08 O02
%A Hubert Comon
%T Sufficient Completeness, Term Rewriting Systems and "Anti-Unification"
%B BOOK82
%P 128-140
%K AI14 AI11
%A P. Tox Cox
%A T. Pietrzykowski
%T Causes for Events: Their Computation and Applications
%B BOOK82
%K AI11 temporal reasoning
%A A. J. J. Dick
%A R. J. Cunningham
%T Using Narrowing to Do Isolation in Symbolic Equation Solving
%B BOOK82
%P 272-280
%K AI14
%A Roland Dietrich
%T Relating Resolution and Algebraic Completion for Horn Logic
%B BOOK82
%P 62-78
%K AI14 AI10 AI11
%A B. Fronhofer
%T On Refinements of the Connection Method
%B BOOK83
%P 391-401
%A Isabelle Gnaedig
%A Pierre Lescanne
%T Proving Termination of Associative Commutative Rewriting Systems by
Rewriting
%B BOOK82
%P 52-61
%K AI14 AI11
%A Richard Gobel
%T Completion of Globally Finite Term Rewriting Systems for Inductive
Proofs
%B BOOK81
%P 101-110
%K AI11 AI14
%A I. R. Goodman
%T Some Asymptotic Results for the Combination of Evidence Problem
%J Math. Modelling
%V 8
%D 1987
%P 216-221
%K O04 O06
%A Alexander Herold
%T Combination of Unification Algorithms
%B BOOK82
%P 450-469
%K AI11 AI14
%A Douglas Howe
%T Implementing Number Theory: an Experiment with Nuprl.
%B BOOK82
%P 404-415
%K AA13 AI11 AI14
%A Tadashi Kanamori
%A Hiroshi Fujita
%T Formulation of Induction Formulas in Verification of Prolog Programs
%B BOOK82
%P 281-299
%K AI14 AI11 O02
%A Deepak Kapur
%A Paliath Narendran
%A Hantao Zhang
%T Proof by Induction Using Test Sets
%B BOOK82
%P 99-117
%K AI14 AI11
%A Deepak Kapur
%A Paliath Narendran
%T NP-Completeness of the Set Unification and Matching Problems
%B BOOK82
%P 489-495
%K O06 AI11
%A Thomas Kaufl
%T Program Verifier "Tatzelwurm": Reasoning About Systems of Linear
Inequalities
%B BOOK82
%P 300-305
%K AA13 AA08 AI11
%A Younghwan Lim
%T The Heuristics and Experimental Results of a New Hyperparamodulation: HL-
Resolution
%B BOOK82
%P 240-253
%K AI11
%A Rasiah Loganantharaj
%A Robert A. Mueller
%T Parallel Theorem Proving with Connection Graphs
%B BOOK82
%P 337-352
%K AI11 H03
%A Zohar Manar
%A Richard Waldinger
%T How to Clear a Block: Plan Formulation in Situational Logic
%B BOOK82
%P 622-640
%K AI07 AI09 AI11
%A Ursula Maritn
%A Tobias Nipkow
%T Unification in Boolean Rings
%B BOOK82
%P 506-513
%K AI14 AI11
%A Jalel Mzali
%T Matching with Distributivity
%B BOOK82
%P 496-502
%K O06 AI11
%A Sanjal Narain
%T A Technique for Doing Lazy Evaluation in Logic
%J MAG132
%P 259-276
%K AI10
%A Hung T. Nguyen
%T On Modeling of Expert Knowledge and Admissibility of Uncertainty Measures
%J Math. Modelling
%V 8
%D 1987
%P 222-226
%K O04 AI01
%A Hans-Jurgen Ohlbach
%T Theory Unification in Abstract Clause Graphs
%B BOOK81
%P 77-100
%K AI14 AI11
%A F. Oppacher
%A E. Suen
%T Controlling Deduction with Proof Condensation and Heuristics
%B BOOK82
%P 384-393
%K AI11 AI14
%A Lawrence C. Paulson
%T Natural Deduction as Higher-Order Resolution
%J MAG131
%P 237-258
%K AI10 AI11
%A David A. Plaisted
%T Abstraction Using Generalization Functions
%B BOOK82
%P 365-376
%K AI11
%A D. Rydeheard
%T A Categorical Unification Algorithm
%B BOOK84
%K AI14 AI11
%A Manfred Schmidt-Schauss
%T Unification in Many-Sorted Equational Theories
%B BOOK82
%P 538-552
%K AI14 AI11
%A Manfred Schmidt-Schauss
%T Unification in a Many Sorted Calculus with Declarations
%B BOOK81
%P 118-132
%K AI14 AI11
%A Hans-Albert Schneider
%T An Improvement of Deduction Plans: Refutation Plans
%B BOOK82
%P 377-383
%K AI11
%A O. Stepankova
%A P. Stepanek
%T And/or Schemes and Logic Programs
%B BOOK83
%P 765-776
%K AI10 AI03
%A Mandayam Thathachar
%A P. S. Sastry
%T Learning Optimal Discriminant Functions Through a Cooperative Game of
Automata
%J IEEE Trans. Systems Man Cybernet.
%V 17
%D 1987
%N 1
%P 73-85
%K AI12 AI04
%A Erik Tiden
%T Unification in Combinations of Collapse-Free Theories with Disjoint
Sets of Function Symbols
%B BOOK82
%P 431-449
%K AI11 AI14
%A F. Winkler
%A B. Buchberger
%T A Criterion for Eliminating Unnecessary Reductions in the Knuth-Bendix
Algorithm
%B BOOK83
%P 849-869
%K AI14 AI11
%A L. Wos
%A W. McCune
%T Negative Paramodulation
%B BOOK82
%P 229-239
%K AI14 AI11
%A Martin Abadi
%A Zohar Manna
%T Modal Theorem Proving
%B BOOK82
%P 172-189
%K AI11
%A Peter B. Andrews
%T Connections and Higher-Order Logic
%B BOOK82
%P 1-4
%K AI11 AI10
%A Leo Bachmair
%A Nachum Dershowitz
%T Commutation, Transformation, and Termination
%B BOOK82
%P 5-20
%K AI11 AI14
%A Julian Besag
%T On the Statistical Analysis of Dirty Pictures
%J J. Royal Statistical Society Series B
%V 48
%D 1986
%N 3
%P 259-302
%K AI06
%A R. Book
%T On the Unification Hierarchy
%B BOOK81
%P 111-117
%K AI14 AI11
%A Frank Malloy Brown
%T A Commonsense Theory of Nonmonotonic Reasoning
%B BOOK82
%P 209-228
%K AI15
%A Hans-Jurgen Burckert
%T Some Relationships Between Unification, Restricted Unification, and
Matching
%B BOOK82
%P 514-524
%K AI11 AI14 O06
%A Cynthia Dwork
%A Paris Kanellakis
%A Larry Stockmeyer
%T Parallel Algorithms for Term Matching
%B BOOK82
%P 416-430
%K AI11 O06 H03 AI14
%A Norbert Eisenger
%T What You Always Wanted to Know About Clause Graph Resolution
%B BOOK82
%P 316-336
%K AI11
%A M. Falaschi
%A Giorgia Levi
%A C. Palamidesi
%T The Formal Semantics of Processes and Streams in Logic Programming
%B BOOK83
%P 363-378
%K AI10 O02
%A Jieh Hsiang
%A Michael Fusinowitch
%T A New Method for Establishing Refutational Completeness in Theorem
Proving
%B BOOK82
%P 141-152
%K AI14 AI11
%A Gerhard Jaeger
%T Some Contributions to the Logical Analysis of Circumscription
%B BOOK82
%P 154-171
%K AI15 AI11
%A Kurt Konolige
%T Resolution and Quantified Epistemic Logics
%B BOOK82
%P 199-208
%K AI10 AI11 AI14
%A Xu Hua Liu
%T Generalized Resolution Using Paramodulation
%J Kexue Tongbao (English Edition)
%V 31
%D 1986
%N 21
%P 1441-1444
%K AI11 AI14
%A Neil V. Murray
%T Theory Links in Semantic Graphs
%B BOOK82
%P 353-364
%K AI16
%A David A. Plaisted
%T A Simple Nontermination Test for the Knuth-Bendix Algorithm
%B BOOK82
%P 69-88
%K AI11 AI14
%A Patrick Saint-Dizler
%T An Approach to Natural-Language Semantics in Logic Programming
%J MAG135
%P 329-356
%K AI02 AI10
%A P. H. Schmitt
%T Computational Aspects of Three-Valued Logic
%B BOOK82
%P 190-198
%K AI11 O04
%A Yoshohito Toyama
%T How to Prove Equivalence of Term Rewriting Systems without Induction
%B BOOK82
%P 118-127
%K AI11 AI14
%A Jonathan Traugott
%T Nested Resolution
%B BOOK82
%P 394-402
%K AI11
%A Kyastutis Urba
%T Redundancy of Features in a Classification Problem
%J Statist. Problemy Upravleniya No. 72
%D 1986
%P 56-63
%K O04
%X Russian with English and Lithuanian Summaries
%A Christoph Walther
%T A Classification of Many-Sorted Unification Problems
%B BOOK82
%P 525-537
%K AI11 AI14
%A Tie Cheng Wang
%T ECR: An Equality Conditional Resolution Proof Procedure
%B BOOK82
%P 254-271
%K AI11
%A Yuan Yuan Wang
%T A Generalized Paramodulation-Resolution Method
%J Nanjing Daxue Xuebao Ziran Kexue Ban
%V 22
%D 1986
%N 2
%P 205-210
%K AI11
%X Chinese with English Summary
%A Richard Cole
%A Chee K. Yap
%T Shape From Probing
%J J. Algorithms
%V 8
%D 1987
%N 1
%P 19-38
%K AI06 AI07
%A Peter Hall
%A D. M. Titterington
%T On Some Smoothing Techniques Used in Image Restoration
%J J. Roy. Satist. Soc. Ser. B.
%V 48
%D 1986
%N 3
%P 330-343
%K AI06
%A R. Schott
%T Nonlinear Filtering and Stochastic Textures
%J Math. Modelling
%V 8
%D 1987
%P 167-169
%K AI06
%A Miguel Filgueiras
%T Cooperating Rewrite Processes for Natural-Language Analysis
%J MAG135
%P 299-328
%K AI11 AI02
%A Horst Reichel
%T Behavioral Program Specification
%B BOOK83
%P 390-411
%K AA08
%A Eugenio Moggi
%T Categories of Partial Morphisms and the $lambda sub p$ - Calculus
(extended abstract)
%B BOOK84
%P 242-251
%K AA08
%A P. Hajek
%T Some Conservativeness Results for Nonstandard Dynamic Logic
%B BOOK83
%P 443-449
%K AI10
%A Thomas M. Fischer
%T On the Average Complexity of Searching for Partial Match Queries in
Multidimensional Search Trees
%B BOOK83
%P 379-390
%K O06
%A Werner Alexi
%T Extraction and Verification of Programs through the Analysis of
Formal Proofs
%B BOOK81
%P 135-152
%K AA08
%A P. Borowik
%A W. Korczynski
%A T. Kudla
%T An Axiomatic Characterisation of an Algebra of Processes
%B BOOK83
%P 141-150
%K AA08
------------------------------
End of AIList Digest
********************
∂15-Jul-87 1313 LAWS@Stripe.SRI.Com AIList Digest V5 #181
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Jul 87 13:13:28 PDT
Date: Tue 14 Jul 1987 22:58-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #181
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 15 Jul 1987 Volume 5 : Issue 181
Today's Topics:
Classification - Natural kinds & Fuzzy Categories,
Comment - Need for Harnad-Style Discussions
----------------------------------------------------------------------
Date: 10 Jul 87 1019 PDT
From: John McCarthy <JMC@SAIL.STANFORD.EDU>
Subject: Natural kinds
Recently philosophers, Hilary Putnam I think, introduced the concept
of natural kind which, in my opinion, is one of the few things they
have done that is useful for AI. Most nouns designate natural kinds,
uncontroversially "bird", and in my opinion, even "chair". (I don't
consider "natural kind" to be a linguistic term, because there may
be undiscovered natural kinds and never articulated natural kinds).
The clearest examples of natural kind are biological species -
say penguin. We don't have a definition of penguin; rather we
have learned to recognize penguins. Penguins have many properties
I don't know about; some unknown even to penguin specialists.
However, I can tell penguins from seagulls without a precise definition,
because there aren't any intermediates existing in nature.
Therefore, the criteria used by people or by the programs we build
can be quite rough, and we don't all need to use the same criteria,
because we will come out with the same answer in the cases that
actually arise.
In my view the same is true of chairs. With apologies to Don Norman,
I note that my 20 month old son Timothy recognizes chairs and tables.
So far as I know, he is always right about the whether the objects
in our house are chairs. He also recognizes toy chairs, but just
calls them "chair" and similarly treats pictures of chairs in books.
He doesn't yet say "real chair", "toy chair" and "picture of a chair",
but he doesn't try to sit on pictures of chairs. He is entirely
prepared to be corrected about what an object is. For example, he
called a tomato "apple" and accepted correction.
We should try to make AI systems as good as children in this respect.
When a an object is named, the system should generate a
gensym, e.g. G00137. To this symbol should be attached the name
and what the system is to remember about the instance. (Whether it
remembers a prototype or a criterion is independent of this discussion;
my prejudice is that it should do both if it can. The utility of
prototypes depends on how good we have made it in handling similarities.)
The system should presume (defeasibly) that there is more to the concept
than it has learned and that some of what it has learned may be wrong.
It should also presume (although will usually be built into the design
rather than be linguistically represented) that the new concept is
a useful way to distinguish features of the world, although some new
concepts will turn out to be mere social conventions.
Attaching if-and-only-if definitions to concepts will sometimes be
possible, and mathematical concepts often are introduced by definitions.
However, this is a rare case in common sense experience.
I'm not sure that philosophers will agree with treating chairs as
natural kinds, because it is easy to invent intermediates between
chairs and other furniture. However, I think it is psychologically
correct and advantageous for AI, because we and our robots exist
in a world in which doubtful cases are rare.
The mini-controversy about penguins can be treated from this point of
view. That penguins are birds and whales are mammals has been discovered
by science. Many of the properties that penguins have in common with
other birds have not even been discovered yet, but we are confident that
they exist. It is not a matter of definition. He who gets fanatical
about arbitrary definitions will make many mistakes - for example,
classifying penguins with seals will lead to not finding tasty penguin
eggs.
------------------------------
Date: Sat 11 Jul 87 21:45:36-PDT
From: Ken Laws <Laws@Stripe.SRI.Com>
Reply-to: AIList-Request@STRIPE.SRI.COM
Subject: Natural Kinds
I would not be so quick to thank recent philosophers for the concept
of natural kinds. While I am not familiar with their contributions,
the notion seems similar to "species" in biology and "cluster" in
engineering and statistics. Cluster and discriminant analysis go
back to at least the 1930s, and have always depended on the tendency
of objects under study to group into classes.
-- Ken
------------------------------
Date: 13 Jul 87 16:31:17 GMT
From: uwslh!lishka@rsch.wisc.edu (Christopher Lishka)
Subject: Re: The symbol grounding problem: "Fuzzy" categories?
In article <3930@sunybcs.UUCP> dmark@marvin.UUCP (David M. Mark) writes:
>In article <974@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>>
>>
>>In Article 185 of comp.cog-eng sher@rochester.arpa (David Sher) of U of
>>Rochester, CS Dept, Rochester, NY responded as follows to my claim that
>>"Most of our object categories are indeed all-or-none, not graded. A penguin
>>is not a bird as a matter of degree. It's a bird, period." --
>>
>>> Personally I have trouble imagining how to test such a claim...
>>
>>Try sampling concrete nouns in a dictionary.
>
>Well, a dictionary may not always be a good authority for this sort of
>thing.
I don't want to start a huge discussion on a related topic, but I guess I'll
throw in my two-cents worth.
Mr. Harnad states that one should try sampling concrete nouns in a
dictionary. It seems to me that a short while ago there was some
discussion around the country as to what a dictionary's purpose
actually is, to which a prominent authority on the subject replied
that a dictionary is *only* a description of what people are commonly
using certain words for. Now, one upshot of this seems to be that a
dictionary, in the end, is NOT a final authority on many words (if not
all of them included). It can only provide a current description of
what the public in general is using the word for.
In the case of some words, many people will use them for many
different things. This may be one reason for the problems with the
word 'map.' In the case of a penguin, scientifically it is considered
a bird. I consider it a bird, although a penguin certainly does not
fly in the air. However, if every English-speaking person except a
few, say myself and Mr. Harnad, suddenly decided to think of a penguin
as something other than a bird, than a dictionary's description would
need to be changed, for myself and Mr. Harnad would be far outweighed.
I suspect that the dictionary would have some entry as to the
historical meaning of 'penguin' (i.e. a penguin used to be considered
a bird, but now it is something else). However, since a dictionary is
supposed to be descriptive of a language in its current usage, the
entry for penguin would have to be modified.
Which brings me to my point. Given that a dictionary is a descriptive
tool that seeks to give a good view of a language as it is currently being
used, can it really be used as a final authority? My feeling is no;
just look at all the different uses of a certain word among your
friends, not to mention the entire state you live in, not to mention
your continent, not to mention the entire English-speaking population
of the world. Holy cow! You've suddenly got a lot of little
differences in meaning for a certain word. Not to mention slang and
local terms (e.g. has anyone ever heard of the word 'bubbler?' It
means a 'Water Fountain' here in Wisconsin, but you'd be surprised how
many people don't know this term). In this case you can only look at
words as a 'graded' term, not an all-or-none term if you are using a
dictionary as the basis for a definition. Sure, if you want to use a
scientific definition for penguin, go ahead...since science seems to
seek to be unambiguos (unlike general spoken language), then you will
have a better all-or-none description. But I don't think you can go
about using a dictionary, which is a descriptive tool, as an
all-or-none decisive authority on what a word means. If I remember
back to a Linguistics course I took, this is the same difference as
denotation vs. connotation.
A couple notes: if you notice above (and right here), I use the word
'you' (as a technical writer would use the word 'one') to refer to a
person in general (i.e. the reader). This is not generally accepted
as proper English by the people who seek to define proper English, but
it is the term that is used by most people that I have known (here in
Wisconsin). It seems to me that this is further evidence of my
argument above, because I do not think twice in using this term 'you;'
it is how I was raised.
Also, please don't start a discussion on language in this group unless
it pertains to A.I. (and in some case it does); I just felt that
someone ought to speak up on the ambiguity of words, and how to
different people there might be problems with using a dictionary as a
basis for judgement. If you want to continue this discussion, please
e-mail me, and I will respond in a decent amount of time (after I cool
off in the case of flames ;-)
--
Chris Lishka /lishka@uwslh.uucp
Wisconsin State Lab of Hygiene <-lishka%uwslh.uucp@rsch.wisc.edu
\{seismo, harvard,topaz,...}!uwvax!uwslh!lishka
------------------------------
Date: 10 Jul 87 16:47:54 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: The symbol grounding problem: "Fuzzy" categories?
In article <3930@sunybcs.UUCP> dmark@marvin.UUCP (David M. Mark) writes:
> we conducted
>a number of experiments and found many ambiguous stimuli near the boundary
>of the concept "map". Air photos and satellite images are an excellent
>example: they fit the dictionary definition, and some people feel very
>strongly that they *are* maps, others sharply reject that claim, etc.
>Museum floor plans, topographic cross-profiles, digital cartographic
>data files on tape, verbal driving directions for navigation, etc., are
>just some examples of the ambiguous ("fuzzy"?) boundary of the concept
>to which the English word "map" correctly applies. I strongly suspect
>that "map" is not unique in this regard!
Indeed, it almost seems as if "What is a map?" is not really the appropriate
question. The better question might be "What can be used as a map?" or
perhaps "How can I use a FOO as a map?" Furthermore, I agree that "map"
is probably not unique. There are probably any number of bindings for
BAR for which "What is a BAR?" runs into similar difficulty and for which
"How can I use a FOO as a BAR?" is the more useful question.
One candidate I might propose to discuss along these lines is the concept
of "algorithm." There are any number of entities which might be regarded
as being used as algorithms, ranging from Julia Child's recipies to
chromosomes. It would seem that any desire to classify such entities
as algorithms is only valuable to the extent that we are interested in
the algorithmic properties such entities possess. For example, we might
be interested in the nature of recipes which incorporate "while loops"
because we are concerned with how such loops terminate.
In an earlier posting, Harnad gave the example of how we classify works of
art according to particular styles. Such classifications may also be
susceptible to this intermediate level of interpretation. Thus, you
may or may not choose to view a particular tapestry as an allegory.
You may or may not choose to view it as a pastoral. Such decisions
influence the way you see it and "parse" it as part of your artistic
appreciation, regardless of whether or not your particular view coincides
with that of the creator!
I suspect there is a considerable amount of such relativity in the way we
detect categories. That relativity is guided not by what the categories
are or what their features are but by how we intend to put those
categories to use. (In other words, the issue isn't "What features
are present?" but "What features do we want to be present?")
------------------------------
Date: 14 Jul 87 15:37:00 GMT
From: apollo!laporta@beaver.cs.washington.edu (John X. Laporta)
Subject: Re: The symbol grounding problem: "Fuzzy" categories?
In article <245@uwslh.UUCP> lishka@uwslh.UUCP (Christopher Lishka) writes:
>Given that a dictionary is a descriptive
>tool that seeks to give a good view of a language as it is currently being
>used, can it really be used as a final authority? My feeling is no;
SUMMARY
(1) You are absolutely right. There is no 'final authority' because language
changes even as one tries to pin it down, with a dictionary, for example.
(2) AI programs designed to 'understand' natural language must include
an encyclopedic as well as a lexicological (dictionary) competence.
(3) The nonexistence to date of perfect artificial understanders of natural
language should not be surprising, given the enormity of the task of
constructing an artificial encyclopedic competence.
(4) The encyclopedia in this instance must grow with the language, preserving
past states, simulating present states, and predicting future states.
ELABORATION
Tackling (2) first:
While dictionary definitions are helpful guides in some respects, the nature of
linguistic competence is encyclopedic rather than lexicological. For instance,
you might hear someone say:
Because I was going to give a cocktail party, I went to the mall
to buy whiskey, peanuts, and motor oil.
A lexicological competence would deem this sentence grammatical and
unremarkably consistent, since 'mall' includes the availability of all the
items mentioned. An encyclopedic competence, on the other hand, would
mark this sentence as strange, since 'motor oil' is not a part of 'cocktail
party,' unless, I suppose, you were willing to assume that some of the guests
needed mechanical, not social, lubrication. Even this conjecture is unlikely,
however, because 'cocktail party' includes humans consuming alcoholic
beverages. A case of Billy Beer at the local Exxon is not a cocktail party.
Car mechanics do not come to work in little black dresses. An encyclopedic
competence is able (a) to isolate the assumptions an utterance requires for
coherence, (b) to rank their probability, and (c) thus to evaluate the
coherence of the utterance as a whole.
Further, 'encyclopedic' in this context includes more than is found in the
_Brittanica_. A humorist might write (in the character of a droll garage
mechanic) about a parley to negotiate sale of a gas station. He decides to
provide a little festive atmosphere by bringing along some beer. But even
this hypothesis doesn't eliminate all strangeness: why is the mechanic
buying motor oil at the supermarket? Certainly he could get a better price
from his distributor.
This sentence is a mine of linguistics lessons, but the above should be
enough to suggest my point. Encyclopedic competence, however provided,
(scripts or semantically marked graphs of words, to give two examples
which are not mutually exclusive) is crucial to understanding even the
topic of an utterance.
The wider question evolves from (1) ... :
Language is an elaboration of symbols which refer to other symbols. The
'last stop' (the boundary of semiotic analysis, not the the boundary of the
linguistic process itself in actual beings or machines) is the connection of
certain signs to 'cultural units.' These pieces of memory are what ground
symbol nets to whatever they are grounded upon. (I prefer Harnad's
formulation, but that is not crucial for this discussion.) When Og the Caveman
remembers one morning the shape of the stone that he used as a scraper
yesterday, a cultural unit exists, and stones of that shape are the first signs
dependent upon it. To oversimplify, the process continues infinitely as signs
are connected to other signs, new cultural units are formed, signs modify
other signs, etc.
... and concludes with (3) and (4):
Meaning is 'slippery' because language changes as it is used. A historically
amnesiac encyclopedic competence for 1980 would mark as improbable
sentences used daily at American slave auctions of the 1840's.
SOURCE NOTE: Nearly everything I have said here has been elaborated by
Umberto Eco in his book 'A Theory of Semiotics' and subsequent writings.
------------------------------
Date: 14 Jul 87 20:25:01 GMT
From: ritcv!cci632!dwp@cs.rochester.edu (Dana Paxson)
Subject: Re: Thanks. (was Re: Results of Symbol Grounding Poll)
In article <1010@mind.UUCP> ghn@mind.UUCP (Gregory Nelson) writes:
>In article <993@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>>[]
>>[make the] Net the reliable and respectable medium of scholarly communication
>>that I and (I trust) others are hoping it will evolve into.
>> ...
>>(4) I continue to be extremely enthusiastic about and committed to
>>developing the remarkable potential of electronic networks for scholarly
>>communication and the evolution of ideas. I take the present votes to
>>indicate that the current Usenet Newsgroups may not be the place to attempt
>>to start this.
>
> ... Perhaps you should take some time off to
>look at some of the other newsgroups. The comp.xxxx discussions are naturally
>oriented to computer people, but things like rec.xxx and sci.xxx are much
>more "broadminded" (if you will.) If you want a real surprise, try tuning
>in to the Deja Vu discussion on misc.psi or something like that.
>
I realize that this is belated input.
As one who followed along with an occasional understanding of
the discussion on symbol grounding, I have been attracted both
to the discussion and to the way in which Stevan Harnad
conducted it. I admire the discipline and rigor evident in his
postings, and see his work as an example of how a newsgroup
functioning often as a bulletin board with limited scope can
be enriched by some really difficult exploration. Some of the
other contributors to the discussion appeared to work well at a
level near Mr. Harnad's. It has been an exciting series of
exchanges.
I regret the loss of the discussion from the newsgroup. Any
reader of the most potent material on computer science will find
that the authors reach out to many fields to gain inspiration,
illustration, and, yes, even forms of grounding(!) for their
work. Especially grounding.
Like any other science area with meaning, computer science does
not begin in words (or bytes) and end in bytes (or words). It
ends in application, or at least applicability, to our lives.
In the AI realm, that applicability is becoming an intimate
metamorphism, a mapping/transformation, of how we work rather
than a translation of what we do. If I can characterize an
aspect of the symbol grounding discussion, it is a knife-sharp
exploration of the type of problem dismissed by so many as
having a self-evident solution. This class of problem is
precisely the type which is most difficult even to see, let
alone solve. Witness the depth and detail of the exchanges we
have seen. If others become impatient with the material, they
don't have to read it; but this topic area appears to be poorly
understood by anybody, and desperately needs close dialogue.
Personally, I feel strongly the need to extend my cognitive
framework with such powerful and challenging material.
Perhaps the outcomes from discussions like this one have too
much potential for making a lot of funded thesis work and
product development irrelevant... but then some outcomes can
unfold whole new realms of exploration and advancement. Unless
I am mistaken, these newsgroups can play an active role in this
unfoldment. I don't want to see anything this good be relegated
to an obscure electronic cranny, or lumped with a lot of diffuse
and irrelevant outpourings. Computer scientists have a lot to
learn from the symbol-grounding exchanges right here.
I sense that there are many quiet readers out there who have
powerful ideas relating to this subject, but who have kept
silent on seeing contemptuous and abusive complaints of
others about the length and content of the postings. For
complaints, it seems reasonable to address the complaints to
authors privately, or to the moderator if there is one; but
open criticism on the net discourages its use by those whose
insight and sensitivity exceed their boldness. Making one's
views public is an intimidating process in itself, so why should
we raise the level of intimidation?
For my part, I would like to ask for a citation for Mr. Harnad's
original article on the subject of symbol grounding; I want to
read it to find out what started the interchange I have seen. I
tuned in late in the process.
Thanks to all of the participants in this probing discussion.
The views expressed here are my own.
Dana Paxson
Systems Engineering
Computer Consoles, Incorporated
Rochester, New York
716 482-5000
CIS User ID: 76327,65
------------------------------
End of AIList Digest
********************
∂17-Jul-87 0110 LAWS@Stripe.SRI.Com AIList Digest V5 #183
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 17 Jul 87 01:10:01 PDT
Date: Thu 16 Jul 1987 23:05-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #183
To: AIList@STRIPE.SRI.COM
AIList Digest Friday, 17 Jul 1987 Volume 5 : Issue 183
Today's Topics:
Philosophy - Natural Kinds & Philosophy of Science &
Categorization & Symbol Grounding
----------------------------------------------------------------------
Date: 15 Jul 87 14:19 PDT
From: Tony Wilkie /DAC/ <TLW.MDC@OFFICE-1.ARPA>
Subject: Natural Kinds
I may get sizzled for this, but I will suggest that the term "natural kind",
while a fairly recent addition to the philosophical lexicon, is a conceptual
descendant of Plato`s Forms, and more closely approximated in meaning to
Aristotle's discussions of 'kinds' in his Metaphysics.
Chairs would certainly be a paradigm example of a Platonic Form, and Aristotle
in his Metaphysics used his horse, Bucephalus, as an example in his discussion
of kinds. Given his inclination as sort of a teleological guerilla, Aristotle
would have (and may have) had a tough time separating his 'kinds' concept from
'species' in the biological cases. Still, I think it safe to say that
philosophical discussion of ontology preceded the development of a formal
concept of species.
Tony L. Wilkie <TLW.MDC@Office-1.ARPA>
------------------------------
Date: Thu, 16 Jul 87 15:42:11 EDT
From: mclean@nrl-css.arpa (John McLean)
Subject: Natural Kinds
Even "recent" philosophical discussions of natural kinds go back 20 years
and much further if you count Nelson Goodman's stuff on projectibility of
predicates (why do we assume emeralds are green and not grue, i. e.,
green until the year 2000 and then blue?) or much of the stuff written
in response to Hempel's problem whether a nonblack nonraven could could
count as a confirming instance of the claim that all ravens are black (since
the claim that all P's are Q's is logically equivalent to the claim that
all nonQ's are nonP's). But I think you can also view much of what Plato
had to say about forms and what Aristotle had to say about substance as
being concerned with the problem of natural kinds as well.
However, I think the issue being raised about recognizing penguins,
chairs, etc. goes back to Wittgenstein's _Philosophical_Investigations_:
For if you look at them you will not see something that is common to
all, but similarities, relationships, and whole series of them at
that...I can think of no better expression to characterize these
similarities than "family resemblance"...
John McLean
------------------------------
Date: 16 Jul 87 2207 PDT
From: John McCarthy <JMC@SAIL.STANFORD.EDU>
Subject: re: AIList Digest V5 #181
[In reply to message sent Tue 14 Jul 1987 22:58-PDT.]
The distinction I had in mind between natural kind and cluster is
the presumed existence of as yet unknown properties of a natural
kind.
When I said "doubtful cases are rare", I left myself open to misunderstanding.
I meant that in case of chairs in Timothy's experience doubtful cases
are rare. Therefore, for a child to presume a natural kind on hearing
a word or seeing an object is advantageous, and it will also be advantageous
to built AI systems with this presumption.
Finally, a remark concerning the "symbol grounding" discussion. My
problems with it were mainly quantitative - there was just too much
to follow. I suspect that Stevan Harnad's capacity to follow very
long discussions is exceptional. I would welcome a summary of the
different points of view by someone who did follow it and feels himself
sufficiently uncommitted to any single point of view.
------------------------------
Date: Thu, 16 Jul 87 17:18 EDT
From: Nichael Cramer <nichael@JASPER.PALLADIAN.COM>
Reply-to: Nichael Cramer <NICHAEL%JASPER@LIVE-OAK.LCS.MIT.EDU>
Subject: AIList Digest V5 #182
>>
>> Let's take a step back. Is "Computer Science" a science? -- Sam
>>
There is the old chestnut that one should be leery of any disipline that feels
such a need to justify itself that it appends the term "Science" to its own
name. Witness "Social Science". Or more to the point, "Creation Science"
[sic].
[Standard disclaimer concerning personal nature of views applies]
NICHAEL
Rednecks for Rainforest
------------------------------
Date: 14 Jul 87 22:20:56 GMT
From: mcvax!botter!klipper!biep@seismo.css.gov (J. A. "Biep" Durieux)
Subject: Definition of science and of scientific method.
1) I think this discussion belongs in sci.philosophy.tech, and perhaps in
sci.research, but definitely not in any of the other groups. Please let's
move out of the wrong newsgroups. This article is meant as a merger of
two discussions, one in sci.med (and other places), and one in comp.ai.
Followups will go to sci.philosophy.tech *only*.
2) There are multitudes of definitions for science, and even more usages.
Here I talk just about a rather generally accepted stance.
3) There is craft (what engineers and the like do), art (about which I
don't want to speak), science (the methodically unraveling of the
secrets of the world ("world" in a broad sense), and philosophy (the
necessary building of footholds, standing on which science can be done).
4) Philosophy starts with quarreling about whether God exists, then whether
I exist (some say the other way round - for "God" some read "anything at all"),
then whether an outside world exist, then how we should look at that world
(yielding things like epistemology, ethics, aesthetics, etc.), and,
choosing epistemology, which ways of getting knowledge are there and which
ones have which value. One of these methods (as many philosophers hold)
is reason, and there come logic and mathematics around the corner.
Still much dispute (intuitionism for example - could you give us an intro,
Lambert Meertens? - or "what constitutes a proof", "what is `mathematical
rigour'", etc.) and uncertainty (liars paradox) around, as the means of
thinking are still being defined, so they cannot be used freely yet.
Perhaps that is a good working definition of science: thinking there where
the means for thinking are not yet finished.
5) Science starts (or: sciences start) from the results of the philosophers'
work (unhappily the philosophers aren't ready yet, so those results are
not as sure as they should be, and certainly not as sure as they are often
thought to be by non-philosophical scientists) exploring the world.
6) The definition of "science", and of scientific method, is by its very
nature a philosophical, not a scientifical matter. Otherwise one would
get paradoxes like:
Ockhams razor tells us to throw away any non-necessary principles.
The principle of Ockhams razor is non-necessary.
So let's throw away Ockhams razor.
(Happily, the director of the British Museum will not let you touch it,
but anyway, the case is clear.)
7) The above is highly simplified, but I believe that simple introductions
are wanting on usenet. Too often I fall into a discussion which supposes
knowledge I don't have, of I see some participants don't have.
8) If this spawns serious discussion (only in sci.philosophy.tech, please!)
I would be more than pleased.
--
Biep. (biep@cs.vu.nl via mcvax)
Unix is a philosophy, not an operating system. Especially the latter.
------------------------------
Date: 15 Jul 87 15:45:00 GMT
From: apollo!laporta@beaver.cs.washington.edu (John X. Laporta)
Subject: Re: The symbol grounding problem: "Fuzzy" categories?
In article <3183@venera.isi.edu> smoliar@vaxa.isi.edu.UUCP (Stephen
Smoliar) writes:
>There are probably any number of bindings for BAR
>for which "What is a BAR?" runs >into ... difficulty and for which
>"How can I use a FOO as a BAR?" is the more useful >question. > >In
>an earlier posting, Harnad gave the example of how we classify works
>of >art ... Such classifications may also be susceptible to this
>intermediate level of >interpretation. Thus, you may or may not
>choose to view a particular tapestry >as an allegory ... [or] as a
>pastoral. Such decisions influence the way you see it and >"parse" it
>as part of your artistic appreciation, regardless of whether or not
>your >particular view coincides with that of the creator!
>
>I suspect there is a considerable amount of such relativity in the way we
>detect categories. That relativity is guided not by what the categories
>are or what their features are but by how we intend to put those
>categories to use. (In other words, the issue isn't "What features
>are present?" but "What features do we want to be present?")
Umberto Eco writes in "Euge`ne Sue and _Les Myste`res de Paris_" about this
problem. Sue was a sort of gentleman pornographer in post-Napoleonic France.
One of his series, about a character like the Shadow who worked revenge on
decadent aristocratic evildoers, with a lot of bodice-ripping along the way,
caught on with the newly literate general working public. They consumed his
book in vast quantities and took it as a call to arms so seriously that Paris
was barricaded by people inspired by it. A sex-and-violence pornographic
thriller became a call to political reform and the return of morality.
The relevant semiotic category is "closure." Roughly speaking, a
closed work is one that uses a tight code to tell a tale to an
audience sharply defined by their sharing of that code. Superman
Comics is an example of a closed work. (There is an entertaining study
somewhere of explanations offered by New Guinean tribesmen of a
Superman Comic.) Closed works don't ring, so to speak, with the
resonance of the entire semiotic continuum, while open works do.
Closed works are thus easily subject to gross misinterpretation by
readers who don't share the code in which those works are written.
Open works, on the other hand, enforce their own interpretation. While
there is drift over time in these interpretations, it is far smaller
than the vastly divergent interpretations offered of closed works by
varying interpreters in the same era. Open works connect to the
entire semiotic continuum - indeed, the (broadly) rhetorical methods
(tropoi) they use bespeak a purpose of educating the reader about the
subjects (topoi) they treat. _Remembrance of Things Past_ is an
example of an open work. While a great deal of unfamiliar material and
controversial analysis is offered to any reader of those 3000 pages,
the mere act of reading them enforces what is, for the purpose of
semiotics, a uniform interpretation (read disambiguated topical
hypothesis).
It is very easy to 'use' a closed work by correlating the elements of
an external symbol system with the opaque code the work presents. Of
course, if the 'grounding' of one's symbol system bears no relation to
that which the work employs, one is just as much 'used' by the work as
a consequence. (Imagine, for example, using a rectangular bar of
plastic explosive as a straightedge.)
It is far more difficult to impose an arbitrary interpretation on an
open work, since it contains material that tends to contradict
incorrect or incomplete hypotheses about its topos. For example,
while we are 'told' that Superman comes from the planet Krypton, etc.,
we learn by watching Marcel what his origins are, and while Superman
comes as a given from space, Marcel's character defines itself in our
consciousness by our 'observation' of his life. Furthermore, while
Superman is always Superman, Marcel has an origin and a destiny.
Marcel changes with time, he breaks with Albertine; Superman always
almost, but actually never marries Lois Lane. (Spiderman's recent
marriage to Mary Jane is an interesting twist. Certainly by comparison
with Superman's, Spiderman's story is an open work.)
Historians who based hypotheses about 20th century American atittudes
on an analysis of Superman comics would have to confirm them by
considerable reference to external sources, while students of early
20th century France would likely use _Remembrance of Things Past_ to
confirm their ideas.
IN SUMMARY: The relativity of categorization is an inverse index of
the 'openness' of the thing categorized. Dr. Morbius in "Forbidden
Planet" was able to divine the purpose of Krell instrumentation
because the science on which it was founded, while more advanced than
his own, shared the same basis in physical reality and hypothesis
testing. The space-given monolith in "2001" is indecipherable (a real
'black box', but with undefined input and output), and thus can be
'used' for any purpose at all.
------------------------------
Date: 13 Jul 87 18:16:06 GMT
From: linus!philabs!sbcs!bnl!allard@husc6.harvard.edu (rick allard)
Subject: Re: The symbol grounding problem: Again... grounding?
In article <931@mind.UUCP> harnad@mind.UUCP (Stevan Harnad) writes:
>Categorization preformance (with all-or-none categories) is highly reliable
>(close to 100%) and MEMBERSHIP is 100%. ...
Why add this clause about "real" membership? Isn't the bulk of the
discussion about us humble humans doing the categorizing? If we do
start wondering about this larger realm, does it bear on categorizing?
Rick
--
ooooooooooooootter#spoon in bowl
!!!!!!!!!!!!& RooM &
!!!!!!!!!!!!R oooo M
------------------------------
Date: 15 Jul 87 19:08:35 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem meta-discussion
Since I will shortly be posting a follow-up to Harnad's last reply to me on
the SGP, I guess I ought to address the meta-discussion.
I think that different standards apply in the two domains in which this
discussion has been taking place.
I recognize that AI-List subscribers rightfully expect some selectivity from
an edited digest, and I will understand completely if the moderator chooses
not to redistribute my follow-up because the volume on this subject has
exceeded the limits demanded by his readership.
On the other hand, I see no justification for attempting to squelch the
discussion on the Usenet side of things (from which I am participating). This
unmoderated forum is avowedly anarchic, and the wishes of a supposed majority
are irrelevant -- perhaps no single topic interests a majority of readers. If
you're not interested in a discussion that's clearly appropriate for this
newsgroup, the right thing to do is just ignore it. The software makes it
easy to "kill" a topic you don't care about; do so, and you'll never even
*see* the messages. I really don't understand the problem.
Anders Weinstein
BBN Labs
------------------------------
Date: 15 Jul 87 20:00:29 GMT
From: diamond.bbn.com!aweinste@husc6.harvard.edu (Anders Weinstein)
Subject: Re: The symbol grounding problem
In a previous message, I was prompted by Stevan Harnad's postings to try to
explain something I find very interesting, namely, why the psychology of
categorical perception won't do much to illuminate the difficult question of
how formal symbols should be semantically interpreted, i.e. what the symbols
really *mean*. Harnad sent a long reply (message 972@mind.UUCP) explaining
the nature of his approach in great detail. The upshot, I think, is that in
spite of some of the rhetoric about "symbol grounding", Harnad's project is
not really *attempting* to do any such thing. It merely aims to discover the
mechanisms underlying certain recognition skills. Since this more modest aim
was precisely what I was urging, I am satisfied that there is no major
disagreement between us.
I want to make clear that I am not here trying to pose any *objection* to
Harnad's model considered as a bit of psychology. I am only trying to
downplay its significance for philosophical issues.
Remember that the traditional conception of "meanings" or "concepts" involves
certain properties: for example, meanings are supposed to contain a criterion
which determines the correct application of the term, in effect defining the
metaphysical essence of the concept in question; they are supposed to serve
as elementary constituents of more complex concepts and thoughts; and they
are supposed to license analytic implications, such as "all bachelors are
unmarried". Since none of these properties seem to be required of the
representations in Harnad's theory, it is in a philosophical sense *not* a
theory of "concepts" or "meanings" at all. As Harnad should be be happy to
concede.
But I want to emphasize again an important reason for this which Harnad
seemed not to acknowledge. There is a vast difference between the
quick, observational categorization that psychologists tend (rightly) to
focus on and the processes involved in what might be called "conclusive"
classification. This is the difference between the ability to recognize
something as fish-like in, say, 500 milliseconds, and the ability to
ascertain that something *really* is a fish and not, say, an aquatic mammal.
Now the former quick and largely unconscious ability seems at least a
plausible candidate for revealing fundamental cognitive mechanisms. The
latter, however, may involve the full exercise of high-level cognition --
remember, conclusive classification can require *years* of experiment,
discussion and debate, and potentially involves everything we know. The
psychology of conclusive categorization does *not* deal with some specialized
area of cognition -- it's just the psychology of all of science and human
rationality, the cognitive scientist's Theory of Everything. And I don't
expect to see such a thing any time soon.
Confusion can result from losing sight of the boundary between these two
domains, for results from the former do not carry over to the latter. And I
think Harnad's model is only reasonably viewed as applying to the first of
these. The rub is that it seems that the notion of *meaning* has more to do
with what goes on in the second. Indeed, what I find most interesting in all
this is the way recent philosophy suggests that concepts or meanings in the
traditional sense are essentially *outside* the scope of forseeable psychology.
Some other replies to Harnad:
Although my discussion was informed by Quine's philosophy in its reference to
"meaning holism", it was otherwise not all that Quinean, and I'm not sure
that Quine's highly counter-intuitive views could be called "standard." Note
also that I was *not* arguing from Quine's thesis of the indeterminacy of
translation; nor did I bring up Putnam's Twin-Earth example. (Both of these
arguments would be congenial to my points, but I think they're excessively
weighty sledgehammers to wield in this context). The distinction between
observational and "conclusive" classification, however, does bear in mind
Putnam's points about the the non-necessity of stereotypical properties.
I also don't think that philosophers have been looking for "the wrong thing
in the wrong way." I think they have made a host of genuine discoveries about
the nature of meaning -- you cite several in your list of issues you'd prefer
to ignore. The only "failure" I mentioned was the inability to come up with
necessary and sufficient definitions for almost anything. (Not at all, by the
way, a mere failure of "introspection".)
I *do* agree that the aims of philosophy are different than those of
psychology. Indeed, because of this difference of goals, you shouldn't feel
you have to argue *against* Quine or Putnam or even me. You merely have to
explain why you are side-stepping those philosophical issues (as I think you
have done). And the reason in brief is that philosophers are investigating
the notion of meaning and you are not.
Anders Weinstein
BBN Labs
------------------------------
End of AIList Digest
********************
∂20-Jul-87 0003 LAWS@Stripe.SRI.Com AIList Digest V5 #184
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 20 Jul 87 00:03:12 PDT
Date: Sun 19 Jul 1987 21:41-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #184
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 20 Jul 1987 Volume 5 : Issue 184
Today's Topics:
Queries - Cooperating Expert Systems & Garbage Collection Suppression,
Comments - Expert System for Rocket Launching &
Automatic Implementation of Abstract Specifications &
ANIMAL in BASIC & Immortality via Computer,
Correction - Spang Robinson Report, June 1987,
Perception - Natural Kinds
----------------------------------------------------------------------
Date: Wed, 15 Jul 87 01:24 EDT
From: Arnold@DOCKMASTER.ARPA
Subject: Query - Cooperating Expert Systems
I am looking for information on cooperating expert systems. Any pointers,
references, etc would be appreciated.
Terry S. Arnold
Merdan Group
4617 Ruffner St.
San Diego
CA 92111
Arnold -at Dockmaster
(619) 571-8565
------------------------------
Date: Fri, 17 Jul 87 08:32:41 edt
From: nancy@grasp.cis.upenn.edu (Nancy Orlando)
Subject: Garbage Collection Suppression
Are there any "accepted" methods of writing code that minimize a LISP's
tendancy to garbage-collect? I don't mean a switch to turn it off;
just a means of minimizing the need for it. I'm dealing particularly with
DEC VAX lisp. I have assumed that iteration as opposed to recursion was
one way; is this correct? Are there other techniques?
Nancy Sliwa
nancy@grasp.cis.upenn.edu or nesliwa%telemail@orion.arpa
------------------------------
Date: 15 Jul 87 16:42:47 GMT
From: jbn@glacier.STANFORD.EDU (John B. Nagle)
Reply-to: jbn@glacier.UUCP (John B. Nagle)
Subject: Re: bm654 - Spang Robinson 3#6, 6/87
>Rome Air Force Development Center is building a system to help decide
>if foreign rocket launches are threats.
I saw the RFP for that one go by when I was at Ford Aerospace.
I recommended that we not bid, pointing out that an expert system to
make launch-on-warning decisions was a singularly bad idea. Seen
in that light, no one at Ford wanted to have anything to do with the program.
Nevertheless, RADC apparently found somebody willing to spend their money.
Fortunately, most of what RADC funds never gets deployed.
John Nagle
------------------------------
Date: 14 Jul 87 16:00:32 GMT
From: eagle!icdoc!esh@ucbvax.Berkeley.EDU (Edward Hayes)
Subject: Re: Automatic implementation of abstract specifications
I just saw an article giving an inexact reference to an MIT technical report
by MK Srivas, The exact reference (I just happened to have it on my desk) is:
MIT/LCS/TR-276
Automatic Synthesis of Implementations
for
Abstract Data Types from
Algebraic Specifications
Mandayam K Srivas
June 1982
- hope this is of help.
------------------------------
Date: 17 Jul 87 06:30:19 GMT
From: psivax!polyslo!mshapiro@seismo.CSS.GOV (Mitch Shapiro)
Reply-to: psivax!polyslo!mshapiro@seismo.CSS.GOV (Mitch Shapiro)
Subject: Re: ANIMAL in BASIC ???
In article <8707090304.AA15222@humu.ARPA> dbrauer@humu.UUCP (David L.
Brauer) writes:
>Somewhere in the darkest reaches of my memory I recall seeing a listing
>of the game ANIMAL in BASIC. It's that old standby introduction to rule-based
>reasoning that tries to deduce what animal you have in mind by asking
>questions like "Does it have feathers?", "Does it have hooves?" etc.
There was originally shipped with the Apple II's (maybe for subsequent
machines as well) that very program written in BASIC. It learned new
animals and stored them in a text file (I think). But it did learn
learn them. Find someone you know who has an Apple II. I believe this
was shipped with DOS 3.1. -- Yes, I have a pretty old Apple. #7919
just in case anyone out there cares.
Mitch Shapiro
mshapiro@polyslo (well, for all of another 3 days, that is.)
"It has been said that when Science climbs the crest of the hill,
it will see that religion has been sitting there all along."
--- Dr. Harry Wolper
------------------------------
Date: 15 Jul 87 19:12:42 GMT
From: David L. Brauer <humu!dbrauer%nosc.UUCP@sdcsvax.ucsd.edu>
Reply-to: dbrauer@humu.nosc.mil.UUCP (David L. Brauer)
Subject: Re: ANIMAL in BASIC ???
Thanks to all who responded to my request for pointers to Animal in
BASIC. The listing can be found in 101 BASIC Games by David H. Ahl.
There also may be a version on one of the Apple DOS distributions,
although I haven't found it yet. Please, no more lectures on why
Animal should not be called a rule-based or expert system. I'm aware
that it is a simple tree traversal algorithm. Merely a misnomer on
my part. I thought I had seen the listing in an "Intro to AI" slick,
that is why I worded the request that way.
David C. Brauer
MilNet: dbrauer@NOSC.mil
------------------------------
Date: Fri, 17 Jul 87 08:39 EST
From: MNORTON%rca.com@RELAY.CS.NET
Subject: Re: Immortality via Computer
Concerning the AP story on attaining immortality via computers, readers
of AIList intrested in thinking more about this may wish to read
Fredrick Pohl's new book, "Annals of the Heechee", the forth book in
the series which began with "Gateway." Mr. Pohl explores some of the
implications of computer subsumption of consciousness, which he calls
'vastening' in the story. Some of the topics touched on include
altered preception of reality, differing time-rates between biologicals
and computers, and non-corporeal being.
Mark J. Norton, RCA Advanced Technology Laboratories, AI Lab.
------------------------------
Date: Wed, 15 Jul 1987 19:31 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Corrections
Response to errors discovered by Linda Mead:
In the summary of the June 1987 Spang Robinson Report, the following
corrections should be noted:
1) "The pilot's associate project aims to produce a refrigerator
sized computing system, having functionality comparable to a
3-inch by 5-inch checklist card." The d in "card" was missing.
2) Charles Anderson was not precisely identified:
He is a Lt. Col., deputy of technology development for SDI in the
Command and Control Directorate at Rome Air Development Center at
Griffis Air Force Base.
3) The statment regarding "AI research for SDI" was that it "would
be relatively nil for awhile." No specific statement on it's "use"
was made by Spang Robinson Report.
(The paragraph on this subject in the summary had an extraneous
double quote character due to a typo. A direct quote was not
made.
------------------------------
Date: 17 Jul 87 13:33:46 GMT
From: mcvax!botter!hansw@seismo.css.gov (Hans Weigand)
Subject: Re: natural kinds
It seems to me that _at least_ three kinds of "natural kinds" should be
distinguished:
(1) genetic kinds, existing by virtue of reproduction
("a horse is a horse because it is born from a horse")
Examples: animal and vegetable species
(2) mimetic kinds, existing by virtue of imitation, to be
subdivided in
(a) iconic kinds (by causally determined representation)
(the "Xerox-principle" of Dretske: an image of an image of x is
again an image of x)
Examples: all linguistic symbols (graphic or phonemic)
(b) artificial kinds (by imitation on purpose),
existing by virtue of preconceived design followed by
numerous production (the "Ford-principle" |-) )
Examples: car models, coins
(c) fashion kinds (by copying behavior, largely uncontrolled)
Examples: social groups (punks, yuppies, ..), styles of art, etc.
(3) anthropic/functional kinds, existing by virtue of readiness_to_hand
Examples: chair, cup, house, knife, game
The last one needs some comments. Each human being needs
certain things in order to survive and live in a satisfactory way.
These things are mainly determined by the functioning of the
human body and community, although there are also environmental and
historical-cultural influences. Thus we may recognize an
Eskimo iglo, and an African pile-dwelling both as "houses".
I think it is not so much the form (iconicity) that matters,
but rather that we feel that, when we would live in Greenland
(resp. the jungle), we would naturally appreciate or use these things
as houses too (to protect us against cold, dangers). Similar
arguments can be made for chair etc.. Moreover, (3) combines
with (2). We are born into a human society. Our parents
had the same needs as we have, so each generation copies these
"anthropic kinds" and transfers them to a next generation. This
makes it the more easy to recognize a (say Western) house. [In
most discussions on "family kinds" and so on, (2) and (3) are
not properly distinguished].
"Don't ask what a kind _is_, but rather how it _persists_"
Hans Weigand (hansw@cs.vu.nl)
------------------------------
Date: Sat 18 Jul 87 15:17:43-CDT
From: Robert L. Causey <AI.CAUSEY@R20.UTEXAS.EDU>
Subject: Natural Kinds
In a message posted 7/15, John McCarthy says that philosophers
have recently introduced the concept of natural kind, and he
suggests how this concept may be useful in AI. I think this
deserves serious comment, both historical and substantive. The
following is lengthy, but it may illustrate some general
characteristics about the relationships between philosophy and AI.
HISTORY
In their messages, Ken Laws and others are correct -- the idea of
natural kinds is not new. It is at least implicit in some
Pre-Socratic Greek philosophy, and Aristotle extensively
developed the idea and applied it in both philosophy and biology.
Aristotle's conception is too "essentialist" to fit what McCarthy
refers to.
In the late 1600's John Locke developed an impressive empiricist
analysis of natural kinds. Further developments were contributed
in the 1800's in J. S. Mill's, _A_System_Of_Logic_. Mill also
made important contributions to our understanding of inductive
reasoning and scientific explanation; these are related to
natural kinds.
In our century a number of concepts of natural kinds have been
proposed, ranging from strongly empiricist "cluster" approaches
(which need NOT preclude expanding the cluster of attributes
through the discovery of new knowledge, cf. McCarthy 7/17), to
various modal analyses, to some intermediate approaches. Any of
these analyses may have some value depending on the intended
application, but the traditional notion of natural kinds has
almost always been connected somehow with the idea of natural
laws.
SUBSTANTIVE ISSUES
1. Whatever one's favorite analysis might be, it is important to
distinguish between a NATURAL kind (e.g., the compound silicon
dioxide, with nomologically determined physical and chemical
attributes), and a functional concept like "chair". There is
generally not a simple one-to-one correspondence between our
functional classifications of objects and the classification
systems that are developed in the natural sciences. This is true
in spite of the fact that we can learn to recognize sand,
penguins, and chairs. But things are not always so simple -
Suppose that Rip van Winkle learns in 1940 to recognize at sight
a 1940-style adding machine; he then sleeps for 47 years. Upon
waking in 1987 he probably would not recognize at sight what a
thin, wallet calculator is. Functional classifications are
useful, but we should not assume that they are generated and
processed in the same ways as natural classifications. In
particular, since functional classifications often involve an
abstract understanding of complex behavioral dispositions, they
are particularly hard to learn once one gets beyond simple things
like chairs and tables.
2. Even discovering the classic examples of NATURAL kinds (like the
classification of the chemical elements) can be a long and
difficult process. It requires numerous inductive
generalizations to confirm that the attributes in a certain Set
of attributes each apply to gold, and that the attributes in some
other Set of attributes apply to iodine, etc. We further
recognize that our KNOWLEDGE of what are the elements of these
Sets of attributes grows with the general growth of our
scientific knowledge. Also, we need not always use the same set
of attributes for IDENTIFICATION of instances of a natural kind.
Most of this goes back to Locke, and philosophers have long
recognized the connection between induction and classification;
Carnap, Hempel, Goodman, and others, have sharpened some of the
issues during the last 50 years.
3. Now, getting back to McCarthy's suggestion -- in his second
message (7/17) he writes: "...for a child to presume a natural
kind on hearing a word or seeing an object is advantageous, and
it will also be advantageous to built (sic) AI systems with this
presumption." His 7/15 message says, "When an object is named,
the system should generate a gensym, e.g., GOO137. To this
symbol should be attached the name and what the system is to
remember about the instance." This is an interesting suggestion,
but it prompts some comments and questions:
i) Assuming that children do begin to presume natural kinds at
some stage of development, what inductive processes are they
using, what biologically determined constraints are affecting
these processes, and what prior acquired knowledge is directing
their inductions. These are interesting psychological questions.
But, depending on our applications, we may not even want to build
robots that emulate young children. We can attach a name
to a gensym, but it is not at all easy to decide "...what the
system is to remember about the instance," or to specify how
it is to process all of the stuff it generates in this manner.
ii) Children receive much corrective feedback from other people;
how much feedback will we be willing or able to give to the
"maturing" robots? Will the more mature robots help train the
naive ones?
iii) Given that classification does involve complex inductive
reasoning, we need to learn a lot more about how to implement
effective inductive procedures, where "induction" is understood
very broadly.
iv) If the AI systems (robots, etc.) are to learn, and reason with,
functional concepts, then things get even more complex. Ability
to make abstractions and perform complex analogical reasoning
will be required. In my judgment, we (humans) still have a lot
to learn just about the representation of functional knowledge.
If my Rip van Winkle story seems farfetched, here is a true
story. I know a person who is familiar with the appearance and
use of 5 1/4 inch floppy diskettes. Upon first seeing a 3.5 inch
mini-diskette, she had no idea what it was until its function was
described. Knowledge of diskettes can extend to tracks, sectors,
etc. The concept of natural kinds is relatively simple (though
often difficult to apply); functional concepts and their
relations with physical structures are harder subjects.
------------------------------
Date: 18 Jul 87 2315 PDT
From: John McCarthy <JMC@SAIL.STANFORD.EDU>
Subject: re: [Robert L. Causey <AI.CAUSEY@R20.UTEXAS.EDU>: Natural
Kinds]
[In reply to message from AI.CAUSEY@R20.UTEXAS.EDU sent Sat 18 Jul 87.]
I agree with Bob Causey's comments and agree that the open questions he
lists are unsolved and important. I have one caveat. The distinction
between nomological and functional kinds exists in sufficiently elaborate
mental structures, but I don't think that under 2 year olds make the
distinction, i.e. have different mechanisms for learning them. For this
reason, it is an open question whether it should be a primary distinction
for robots. In a small child's world, chairs are distinguished from other
objects by appearance, not by function. Evidence: a child doesn't refer
to different appearing objects on which he can also sit as chairs.
Concession: there may be such a category "sittable" in "mentalese", and
languages with such categories might be as easily learnable as English.
What saves the child from having to make the distinction between kinds
of kinds at an early age is that so many of the kinds in his life are
distinguishable from each other in many ways. The child might indeed
be fooled by the different generations of calculator, but usually he's
lucky.
I hope to comment later on how robots should be programmed to identify
and use kinds.
------------------------------
End of AIList Digest
********************
∂20-Jul-87 0235 LAWS@Stripe.SRI.Com AIList Digest V5 #185
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 20 Jul 87 02:35:14 PDT
Date: Sun 19 Jul 1987 21:52-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #185
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 20 Jul 1987 Volume 5 : Issue 185
Today's Topics:
Perception - Seeing-Eye Robots,
Philosophy - Searchability in Humans vs. Machines
----------------------------------------------------------------------
Date: 16 Jul 87 17:54:49 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Seeing-Eye robots
Suppose one wanted to build a robot that does what a Seeing-Eye dog
does (that is, helping a blind person to get around), but communicates
in the blind person's own language instead of by pushing and pulling.
Clearly this robot does not have to imitate a human being. But it does
have to recognize objects and associate them with the names that humans
use for them. It also has to interpret certain situations in its
owner's terms: for instance, walking in one direction leads to danger,
and walking in another direction leads to the goal.
What problems will have to be solved to build such a robot? Will its
hypothetical designers have to deal with the problem of mere
recognition, or the deeper problem of grounding symbols in meaning?
Could it be built by hardwiring sensors to a top-down symbolic
processor, or would it require a hybrid processor?
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 17 Jul 87 19:31:00 GMT
From: ihnp4!inuxc!iuvax!merrill@ucbvax.Berkeley.EDU
Subject: Re: Seeing-Eye robots
In comp.ai, marty1@houdi (M.B. Brilliant) writes:
> Suppose one wanted to build a robot that does what a Seeing-Eye dog
> does (that is, helping a blind person to get around), but communicates
> in the blind person's own language instead of by pushing and pulling.
> [Commentary on some of the essential properties of the robot.]
> What problems will have to be solved to build such a robot? Will its
> hypothetical designers have to deal with the problem of mere
> recognition, or the deeper problem of grounding symbols in meaning?
> Could it be built by hardwiring sensors to a top-down symbolic
> processor, or would it require a hybrid processor?
I seriously doubt that recognition itself would be adequate. As
Brilliant observes, one of the functions that the robot must perform
is the detection of "danger to its master." Consider the problem of
crossing a street. Is it enough to recognize cars (and trucks, and
motorcycles, and other already--known objects?) No.
The robodog has to generalize beyond simply cars and trucks and
busses, since their shapes change, to "things travelling along this
stretch of road {and what's a stretch of road?} which are a) moving
{and what does it mean to move?} b) fast {and what is fast? Why,
fast enough to be dangerous...which begs the question} c) in this
direction." At this point, I think that we have exceeded the bounds
of recognition and entered a realm where "judgement" is required, but,
if not, I imagine that I can probably extend this situation to meet most
specific objections. (I assume that the blind woman needs to cross roads
without undue delay. Traffic lights don't eliminate these problems,
since the robodog must "recognize" drivers who are turning, some of
whow would be safe, since they're either stopped or slow--moving, but some
of whom (at least, here in Bloomington) would run *any* pedestrian
down. !-))
BTW: I like this example very much. It raises quite nicely the
underlying issue in the symbol grounding problem discussion without
using the terminology that many of the readers of comp.ai seem to have
objected to. Congratulations, Mr. Brilliant!
John Merrill
merrill@iuvax.cs.indiana.edu UUCP:seismo!iuvax!merrill
Dept. of Comp. Sci.
Lindley Hall 101
Indiana University
Bloomington, Ind. 47405
------------------------------
Date: 14 Jul 87 21:21:33 GMT
From: berke@locus.ucla.edu
Subject: An Unsearchable Problem of Elementary Human Behavior
An Unsearchable Problem of Elementary Human Behavior
Peter Berke
UCLA Computer Science Department
The Artificial Intelligence assumption that all human behavior
can eventually be mimicked by computer behavior has been stated
in various ways. Since Newell stated his Problem Space
Hypothesis in 1980, it has taken on a clearer, and thus, more
refutable form. Newell stated his hypothesis thus:
"The fundamental organizational unit of all human goal-oriented
symbolic activity is the problem space." - Newell, 1980.
In the 1980 work, Newell says his claim "hedges on whether
all cognitive activity is symbolic." Laird, Rosenbloom, and
Newell (1985) ignore this hedge and the qualification "goal-
oriented symbolic" when they propose: "Our approach to
developing a general learning mechanism is based on the
hypothesis that all complex behavior - which includes
behavior concerned with learning - occurs as search in problem
spaces." They reference Newell (1980), but their claim is larger
than Newell's original claim.
The purpose of this note is to show that, to be true, Newell's
hypothesis must be taken to mean just that goal-search in a
state-space is a formalism that is equivalent to computing. Then
Newell's Problem Space Hypothesis is simply a true theorem. The
reader is invited to sketch a proof of the mutual
simulatability of Turing computation and a process of goal-search
in a state space. Such a proof has been constructed for every
other prospective universal formalism, e.g., lambda calculus,
recursive function theory, and Post tag systems. That such
universal formalisms are equivalent in this sense led Church
(1936, footnote 3) to speculate that human calculating activity
can be given no more general a characterization.
But human behavior is not restricted to calculating activity
(though it seems that at least some human behavior is
calculating). If the Problem Space Hypothesis is taken to
be a stronger statement, that is, as a statement about human
behavior rather than about the formalism of goal-search in a
state-space, then I claim that the following counter-example
shows it to be false.
Understanding a name is an inherently unsearchable problem; It
cannot be represented as search in a state or problem space.
Well, it can be so represented, but then it is not the same
problem. In searching our states for our goal we are solving a
different problem than the original one.
To understand that understanding is (or how it can be) inherently
unsearchable, it is necessary to distinguish between ambiguity
and equivocacy. At first the distinction seems contrived, but
it is required by the assumption that there are discrete
objects called 'names' that have discrete meaning (some other
associated object or objects, see Church 1986, Berke 1987).
An equivocal word/image has more than one clear meaning, an
ambiguous word/image has none. What is usually meant by the
phrase "lexical ambiguity" is semantic equivocacy. Equivocacy
occurs even in formal languages and systems, though in setting up
a formal system one aims to avoid equivocacy. For example, an
expression in a computer language may be equivocal ("of equal
voices"), such as: 'IF a THEN IF b THEN c ELSE d'. The whole
expression is equivocal depending on which 'IF' the 'ELSE' is
paired with. In this case there are two clear meanings, one for
each choice of 'IF'.
On the other hand, 'ELSE' taken in isolation, is ambiguous
("like both"), it's meaning is not one or many alternatives, but
it is like all of them. [The reader, especially one who may
claim that 'ELSE' has no meaning in isolation, may find it
valuable to pause at this point to write down what 'ELSE' means.
Several good attempts can be generated in very little time,
especially with the aid of a dictionary.]
Resolving equivocacy can be represented as search in a state
space; it may very well BE search in a state space. Resolving
ambiguity cannot be represented as search in a state space.
Resolving environmental ambiguity is the problem-formulation
stage of decision making; resolving objective ambiguity is the
object-recognition phase of perception.
The difference between ambiguity and equivocacy is a reason why
object-recognition and problem-formulation are difficult
programming and management problems, only iteratively
approximable by computation or rational thought. A state space
is, by definition, equivocal rather than ambiguous. If we
confuse ambiguity with equivocacy, ambiguity resolution may
seem like search in goal space, but this ignores the process of
reducing an ambiguous situation to an equivocal one much
the way Turing (1936) consciously ignores the transition of a
light switch from OFF to ON.
A digital process can approximate an analog process yet we
distinguish the digital process from the analog one. Similarly,
an equivocal problem can approximate an ambiguous problem, but
the approximating problem differs from the approximated one.
Even if a bank of mini-switches can simulate a larger light
switch moving from OFF to ON, we don't evade the problem of
switch transition, we push it "down" a level, and then ignore
it. Even if we can simulate an ambiguity by a host of
equivocacies, we don't thereby remove ambiguity, we push it
"down" a level, and then ignore it.
Ambiguity resolution cannot be accomplished by goal-search in a
state space. At best it can be pushed down some levels.
Ambiguity must still be resolved at the lower levels. It doesn't
just go away; ambiguity resolution is the process of it going
away. Representation may require ambiguity resolution, so the
general problem of representing something (e.g., problem solving,
understanding a name) as goal-search in a state space can not
be represented as goal-search in a state space.
This leads me to suspect what may be a stronger result:
"Representing something" in a given formalism cannot be
represented in that formalism. For example, "representing a
thought in words," that is, expression, cannot be represented in
words. "What it is to be a word" cannot be expressed in words.
Thus there can be no definition of 'word' nor then of 'language'.
Understanding a word, if it relies on some representation of
"what it is to be a word" in words, cannot be represented in
words.
The meaning of a word is in this way precluded from being (or
being adequately represented by) other words. This agrees with
our daily observations that "the meaning of a word," in a
dictionary is incomplete. Not all words need be impossible to
completely define, just some of them for this argument to hold.
It also agrees with Church's 1950 arguments on the contradictions
inherent in taking words to be the meaning of other words.
If understanding cannot be represented in words, it can never be
well-defined and cannot be programmed. In programming, we can
and must ignore the low-level process of bit-recognition because
it is, and must be, implemented in hardware. Similarly,
hardware must process ambiguities into equivocacies for
subsequent "logical" processing.
We are thus precluded from saying how understanding works, but
that does not preclude us from understanding. Understanding a
word can be learned as demonstrated by humans daily. Thus
learning is not exhausted by any (word-expressed) formalism.
One example of a formalism that does not exhaust learning
behavior is computation as defined (put into words) by Turing.
Another is goal-search in a state-space as defined (put into
words) by Newell.
References:
Berke, P., "Naming and Knowledge: Implications of Church's
Arguments about Knowledge Representation," in revision for
publication,1987.
Church, A., An Unsolvable Problem of Elementary Number Theory
(Presented to the American Mathematical Society, April 19, 1935),
Journal of Symbolic Logic, 1936.
Church, A., "On Carnap's Analysis of Statements of Assertion
and Belief," Analysis, 10:5, pp. 97-99, April, 1950.
Church, A., "Intensionality and the Paradox of the Name
Relation," Journal of Symbolic Logic, 1986.
Laird, J.E., P.S. Rosenbloom, and A. Newell, "Towards Chunking as
a General Learning Mechanism," CMU-CS-85-110.
Newell, A. "Reasoning, Problem Solving, and Decision Processes:
The problem space as a Fundamental Category. Chapter 35 in R.
Nickerson (Ed.), Attention and Performance VIII. Erlbaum, 1980.
Turing, A.M., On Computable numbers, with an application to the
Entscheidungsproblem. Proceedings of the London Mathematical
Society 42-2 (1936-7), 230-265; Correction, ibid., 43 (1937),
544-546.
------------------------------
Date: 16 Jul 87 09:23:07 GMT
From: mcvax!botter!roelw@seismo.css.gov (Roel Wieringa)
Subject: Berke's Unsearchable Problem
In article 512 of comp.ai Peter Berke says that
1. Newell's hypothesis that all human goal-oriented symbolic activity
is searching through a problem-space must be taken to mean that human
goal-oriented symbolic activity is equivalent to computing, i.e. that
it equivalent (mutually simulatable) to a process executed by a Turing
machine;
2. but human behavior is not restricted to computing, the process of
understanding an ambiguous word (one having 0 meanings, as opposed to
an equivocal word, which has more than 1 meanings) being a case in
point. Resolving equivocality can be done by searching a problem
space; ambiguity cannot be so resolved.
If 1 is correct (which requires a proof, as Berke says), then if 2 is
correct, we can conclude that not all human behavior is searching
through a problem space; the further conclusion then follows that
classical AI (using computers and algorithms to reach its goal)
cannot reach the goal of implementing human behavior as search
through a state space.
There are two problems I have with this argument.
First, barring a quibble about the choice of the terms "ambiguity" and
"equivocality", it seems to me that ambiguity as defined by Berke is really
meaninglessness. I assume he does not mean that part of the surplus
capacity of humans over machines is that humans can resolve meaninglessness
whereas machines cannot, so Berke has not said what he wants to say.
Second, the argument applies to classical AI. If one wishes to show
that "machines cannot do everything that humans can do," one should
find an argument which applies to connection machines, Boltzmann
machines, etc. as well.
Supposing for the sake of the argument that it is important to show
that there is an essential difference between man and machine, I
offer the following as an argument which avoids these problems.
1. Let us call a machine any system which is described by a state
evolution function (if it has a continuous state space) or a state
transition function (discrete state space).
2. Let us call a description explicit if (a) it is communicable to an
arbitrary group of people who know the language in which the
description is stated, (b) it is context-independent, i.e. mentions
all relevant aspects of the system and its environment to be able to
apply it, (c) describes a repeatable process, i.e. whenever the same
state occurs, then from that point on the same input sequence will
lead to the same output sequence, where "same" is defined as
"described by the explicit description as an instance of an input
(output) sequence." Laws of nature which describe how a natural process
evolves, computer programs, and radio wiring diagrams are explicit
descriptions.
Now, obviously a machine is an explicitly described system.
The essential difference between man and machine I propose is that
man possesses the ability to explicate whereas machines do not. The
*ability* to explicate is defined as the ability to produce an
explicit description of a range of situations which (i.e. the range
is) not described explicitly. In principle, one can build a machine
which produces explicit descriptions of, say, objects on a conveyor
belt. But the set of kinds of objects on the belt would then have to
be explicitly described in advance, or at least it would in
principle be explicitly describable, even though the description
would be large, or difficult to find. the reason for this is that a
machine is an explicitly described system, so that, among others, the
set of possible inputs is explicitly described.
On the other hand, a human being in principle can produce
reasonably explicit descriptions of a class of systems which has no
sharp boundaries. I think it is this capability which Berke means
when he says that human beings can disambiguate whereas algorithmic
processes cannot. If the set of inputs to an explication process carried
out by a human being is itself not explicitly describable, then
humans have a capability which machines don't have.
A weak point in this argument is that human beings usually have a
hard time in producing totally explicit descriptions; this is why
programming is so diffcult. Hence, the qualification "reasonably
explicit" above. This does not invalidate the comparison with
machines, for a machine built to produce reasonably explicit
descriptions would still be an explicitly described system, so that
the sets of inputs and outputs would be explicitly described (in
particular, the reasonableness of the explicitness of its output
would be explicitly described as well).
A second argument deriving from the concepts of machine and
explicitness focuses on the three components of the concept of
explicitness. Suppose that an explication process executed by a human
being were explicitly describable.
1. Then it must be communicable; in particular the initial state must be
communicable; but this seems one of the most incommunicable mental states
there is.
2. It must be context-independent; but especially the initial stage
of an explication process seems to be the most context-sensitive
process there is.
3. It must be repeatable; but put the same person in the same
situation (assuming that we can obliterate the memory of the previous
explication of that situation) or put identical twins in the same
situation, and we are likely to get different explicit descriptions
of that situation.
Note that these arguments do not use the concept of ambiguity as
defined by Berke and, if valid, apply to any machine, including
connection machines. Note also that they are not *proofs*. If they
were, they would be explicit descriptions of the relation between a
number of propositions, and this would contradict the claim that the
explication process has very vague beginnings.
Roel Wieringa
------------------------------
End of AIList Digest
********************
∂22-Jul-87 0051 LAWS@Stripe.SRI.Com AIList Digest V5 #186
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 22 Jul 87 00:51:36 PDT
Date: Tue 21 Jul 1987 22:25-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #186
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 22 Jul 1987 Volume 5 : Issue 186
Today's Topics:
Queries - AI Application for DBase of New Chemical Substances &
Software Reuse,
Science Fiction - Immortality via Computer,
Techniques - Garbage Collection Suppression,
Philosophy - Natural Kinds,
Courses - Philosophy Courses on Artificial Intelligence &
Logic and Computability, AI and Formal Learning Theory
----------------------------------------------------------------------
Date: 20 Jul 1987 1220-EDT
From: Holger Sommer <SOMMER@C.CS.CMU.EDU>
Subject: AI/Expert system application for DBase of New Chemical Substances
I am involved in an EPA/NIOSH sponsered project with the title :
"Engineering and Toxic Characterisation Studies and Development of Unit
Operations Predictive Models for New Chemicals"
This project intends to develop an intelligent database and predictive
models to help EPA in the evaluation of premanufacture notices.
The research is directed and conducted to establish data base model for
use in predicting workplace releases and exposures resulting from
manufacturing , processing , use or disposal of new chemical substances.
The main activities of this project are :
* Formulation of conceptual data base models for filtration and drying
unit operation
* Assessment and characterization of worker exposure in manufacturing
plants and pilot plants
* Incorporation of sampling data and other relevant information into
the data base framework
* Development and validation of computerized predictive models for
assessment of workplace releases and exposures.
What we try to accomplish in this project is to automate the evaluation
process for premanufacture notices and provide a systematic data base to
assist in this evaluation.
My questions to the AI-list audience are :
1) Are there projects underway with similar content ( not particular
related to chemicals but other domains ) ?
2) We need information about existing data base programs which
interface with predictive models. We are looking for a flexible
programming tool to accomplish the above described assignments.
Thank you for any information I will receive through this network.
Please send responses to : H.T. Sommer .... Sommer@c.cs.cmu.edu
------------------------------
Date: 18 Jul 87 15:17:05 GMT
From: cbmvax!vu-vlsi!ge-mc3i!sterritt@RUTGERS.EDU (Chris Sterritt)
Subject: Re: Software Reuse (short title)
Hello,
I've been following the discussion of this avidly, but am new to the
programming languages (?) ML, SML, and LML. Could someone (ideally mail
me directly so as not to clog the net!) send me information on these langauges,
so that I might find out more?
Along the ideas of the discussion, if I remember my Computability
theory correctly -- doesn't it make some sense that to show an algorithm
(either computable or to prove it) you need to give an almost algorithmic
description, as in an inductive proof? So isn't this what Lisp is (I'm a lisp
hacker at work). I'd think that Church's Lambda Calculus would shed some light
on this discussion, as I believe that that was what he was trying to do with
the calculus. Generally, I agree that to specify an algorithm IN ENOUGH DETAIL,
you will probably wind up writing at least as much information down as the code
itself. I think that 'Requirements' as we define them in 'Software Engineering'
presume a *lot* of human intelligence.
Any comments?
Chris Sterritt
------------------------------
Date: 20 Jul 87 13:21:39 GMT
From: sunybcs!rapaport@RUTGERS.EDU (William J. Rapaport)
Reply-to: sunybcs!rapaport@RUTGERS.EDU (William J. Rapaport)
Subject: Re: Immortality via Computer
In article <8707200504.AA05729@ucbvax.Berkeley.EDU> MNORTON@rca.COM writes:
>
>Concerning the AP story on attaining immortality via computers, readers
>of AIList intrested in thinking more about this may wish to read ...
... or Justin Leiber's _Beyond Rejection_. Leiber is a philosopher and
also the son of SF writer Fritz Leiber. The novel is about a society in
which brain tapes are made and installed in new bodies; the minds tend
to reject the bodies.
------------------------------
Date: Mon, 20 Jul 87 21:43:00 EDT
From: Chester@UDEL.EDU
Subject: Re: Garbage Collection Suppression
The direct way to avoid garbage collection in lisp is to define your own `cons'
function that prefers to get cell pairs from an `available list', calling the
regular `cons' only when the `available list' is empty. A `reclaim' function
that puts cell pairs on the `available list' (using `rplacd') will be needed
also. See any book on data structures. The technique can be used for cell
pairs and gensym atoms, if needed, but in my experience, not with strings or
numbers. String manipulations can usually be avoided, but a program that
crunches a lot of numbers cannot avoid consuming memory and eventually
triggering garbage collection (at least in VAX lisp). I wish there were some
way for a user to reclaim numbers so that they could be reused as cell pairs
can. If so, I could write all my lisp programs so that they don't need to
garbage collect. It would also be nice to have a built-in `reclaim' function
that would work in conjunction with the built-in `cons'; it would be dangerous
for novices, but handy for the experienced.
By the way, recursion in itself doesn't cause garbage collection; VAX lisp is
smart enough to reclaim the memory used for the function stack automatically.
Daniel Chester
chester@dewey.udel.edu
------------------------------
Date: 21 Jul 87 17:05:53 GMT
From: rlw@philabs.philips.com (Richard Wexelblat)
Reply-to: rlw@philabs.philips.com (Richard Wexelblat)
Subject: Re: Natural Kinds
It is amusing and instructive to study and speculate on children's language
and conceptualization. (Wow! That construct's almost Swiftean!) For those
who would read further in this domain, I recommend:
Brown, Roger
A First Language -- The Early Stages
Harvard Univ. Press, 1973
MacNamara, John
Names for Things -- A Study of Human Learning
MIT Press, 1984
------------------------------
Date: 21 Jul 87 16:56:08 GMT
From: rlw@philabs.philips.com (Richard Wexelblat)
Reply-to: rlw@briar.philips.com (Richard Wexelblat)
Subject: Re: Natural Kinds
In article <8707161942.AA13065@nrl-css.ARPA> mclean@NRL-CSS.ARPA
(John McLean) writes:
>However, I think the issue being raised about recognizing penguins,
>chairs, etc. goes back to Wittgenstein's _Philosophical_Investigations_:
Actually, the particular section chosen is a bit too terse. Here is more
context:
Consider, for example the proceedings that we call `games.' I mean board-
games, card-games, ball-games, Olympic games, and so on. What is common to
them all?--Don't say: ``There must be something common, or they would not be
called `games' ''--but look and see whether there is anything common to all.
--For if you look at them you will not see something that is common to all,
but similarities, relationships, and a whole series of them at that ... a
complicated network of similarities overlapping and criss-crossing; sometimes
overall similarities, sometimes similarities of detail.
I can think of no better expression to characterize these similarities
than ``family resemblances''; for the various resemblances between the
members of a family: build, features, colour of eyes, gait, temperament,
etc. etc. overlap and criss-cross in the same way.--And I shall say: `games'
form a family.
* * *
This sort of argument came up in a project on conceptual design tools a few
years ago in attempting to answer the question: ``What is a design and how
do you know when you have one?'' We attempted to answer the question and got
into the question of subjective classifications of architecture. What is a
``ranch'' or ``colonial'' house? If you can get a definition that will
satisfy a homebuyer, you are in the wrong business.
* * *
Gratis, here are two amusing epigrams from W's Notebooks, 1914-1916:
There can never be surprises in logic.
~~~~~
One of the most difficult of the philosopher's tasks is to
find out where the shoe pinches.
------------------------------
Date: 17 Jul 1987 1505-EDT
From: Clark Glymour <GLYMOUR@C.CS.CMU.EDU>
Subject: Philosophy Courses on Artificial Intelligence
SEMINAR IN LOGIC AND COMPUTABILITY:
ARTIFICIAL INTELLIGENCE AND FORMAL LEARNING THEORY
- Offered by: Department of Philosophy, Carnegie-Mellon University
- Instructor: Kevin T. Kelly
- Graduate Listing: 80-812
- Undergraduate Listing: 80-510
- Place: Baker Hall 131-A
- Time: Wednesday, 1:30 to 4:30 (but probably not the full period).
- Intended Audience: Graduate students and sophisticated undergraduates
interested in inductive methods, the philosophy of science,
mathematical logic, statistics, computer science, artificial
intelligence, and cognitive science.
- Prerequisites: A good working knowledge of mathematical logic and
computation theory.
- Course Focus: Convergent realism is the philosophical thesis that the
point of inquiry is to converge (in some sense) to the truth (or to
something like it). Formal learning theory is a growing body of
precise results concerning the possible circumstances under which
this ideal is attainable. The basic idea was developed by Hilary
Putnam in the early 1960's, and was extended to questions in
theoretical linguistics by E. Mark Gold. The main text of the
seminar will be Osherson and Weinstein's recent book Systems that
Learn. But we will also examine more recent efforts by Osherson,
Weinstein, Glymour and Kelly to apply the theory to the inductive
inference of theories expressed in logical languages. From this
general standpoint, we will move to more detailed projects such as
the recent results of Valiant, Pitt, and Kearns on polynomial
learnabilitly. Finally, we will examine the extent to which formal
learning theory can assist in the demonstrable improvement of
learning systems published in the A.I. machine learning literature.
There is ample opportunity to break new ground here. Thesis topics
abound.
- Course Format: Several introductory lectures, Seminar reports, and a
novel research project.
PROBABILITY AND ARTIFICIAL INTELLIGENCE
- Offered by: Department of Philosophy, Carnegie-Mellon University
- Instructor: Kevin T. Kelly
- Graduate Course Number: 80-312
- Undergraduate Course Number: 80-811
- Place: Porter Hall, 126-B
- Time: Tuesday, Thursday, 3:00-4:20
- Intended Audience: Graduate students and sophisticated undergraduates
interested in inductive methods, the philosophy of science,
mathematical logic, statistics, computer science, artificial
intelligence, and cognitive science.
- Prerequisites: Familiarity with mathematical logic, computation, and
probability theory
- Course Focus: There are several ways in which the combined system of
a rational agent and its environment can be stochastic. The agent's
hypotheses may make claims about probabilities, the agent's
environment may be stochastic, and the agent itself may be
stochastic, in any combination. In this course, we will examine
efforts to study computational agents in each of these situations.
The aim will be to assess particular computational proposals from the
point of view of logic and probability theory. Example topics are
Bayesian systems, Dempster-Shafer theory, medical expert systems,
computationally tractable learnability, automated linear causal
modelling, and Osherson and Weinstein's results concerning
limitations on effective Bayesians.
- Course Format: The grade will be based on frequent exercises and
possibly a final project. There will be no examinations if the class
keeps up with the material.
------------------------------
Date: 17 Jul 87 16:54:45 EDT
From: Terina.Jett@b.gp.cs.cmu.edu
Subject: Seminar - Logic and Computability, AI and Formal Learning
Theory
SEMINAR IN LOGIC AND COMPUTABILITY
ARTIFICIAL INTELLIGENCE AND FORMAL LEARNING THEORY
Offered by: Department of Philosophy
Instructor: Kevin T. Kelly
Grad Listing: 80-510
Undergrad Listing: 80-510
Place: Baker Hall 131-A
Time: Wed, 1:30 - 4:30
Intended Audience: Graduate students and sophisticated undergraduates
interested in inductive methods, the philosophy of science, mathematical
logic, statistics, computer science, artificial intelligence, and cogni-
tive science.
Prerequisites: A good working knowledge of mathematical logic and comp-
utation theory.
Course Focus: Convergent realism is the philosophickal thesis that the
point of inquiry is to converge (in some sense) to the truth (or to
something like it). Formal learning theory is a growing body of precise
results concerning the possible circumstances under which this ideal is
attainable. The basic idea was developed by Hilary Putnam in the early
1960's, and was extended to questions in theoretical linguistics by E.
Mark Gold. The main text fo the seminar will be Osherson and Weinstein's
recent book Systems That Learn. But we will also examine more recent
efforts by Osherson, Weinstein, Glymour and Kelly to apply the theory to
the inductive inference of theories expressed in logical languages. From
this general standpoint, we will move to more detailed projects such as
the recent results of Valiant, Pitt, and Kearns on polynomials learn-
abilitly. Finally, we will examine the extent to which formal learning
theory can assist in the demonstrable improvement of learning systems
published in the A.I. machine learning literature. There is ample
opportunity to break new ground here. Thesis topics abound.
Course Format: Serveral introductory lectures, Seminar reports, and
a novel research project.
------------------------------
End of AIList Digest
********************
∂27-Jul-87 0208 LAWS@Stripe.SRI.Com AIList Digest V5 #187
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 27 Jul 87 01:44:03 PDT
Date: Sun 26 Jul 1987 23:31-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #187
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 27 Jul 1987 Volume 5 : Issue 187
Today's Topics:
Journal Issue - Planning (Int. J. for AI in Engineering),
Seminar - Abstraction in Knowledge-Based Systems (MCC),
Course - Probability and AI (CMU),
Conferences - CD-ROM & 7th Distributed Computing Systems &
R&D in Information Retrieval &
International Neural Network Society
----------------------------------------------------------------------
Date: Fri, 24 Jul 87 09:29:43 EDT
From: sriram@ATHENA.MIT.EDU
Subject: Journal Issue - Planning (Int. J. for AI in Engineering)
INTERNATIONAL JOURNAL FOR AI IN ENGINEERING
SPECIAL ISSUE ON PLANNING
APRIL 1988
The April 1988 issue of the International Journal for AI in
Engineering will be dedicated to Planning. The guest editors for this
issue are: Prof. Chris Hendrickson, Dept. of Civil Engineering, C-MU,
Pittsburgh, PA 15213 (hendrickson@cive.ri.cmu.edu) and Mrs Julie
Gadsden, Admiralty Research Establishment, Procurement Executive,
XCC5.2, Portsdown, Portsmouth, Hants PO6 4AA, UK. Papers in all areas
of engineering, as related to planning, are solicited. Each paper
should not exceed 10,000 words (roughly 30 doubly spaced pages),
including figures. The deadline for submission is September 1, 1987.
Please send the papers to either of the guest editors.
Sriram & McCallum (Editors)
------------------------------
Date: Fri 24 Jul 87 11:59:41-CDT
From: Betti Bunce <Ai.Betti@MCC.COM>
Subject: Seminar - Abstraction in Knowledge-Based Systems (MCC)
All interested parties are invited to attend the following:
TALK BY: B. Chandrasekaran
Laboratory for AI Research
Department of Computer and Information Science
The Ohio State University
Columbus, OH 43210
DATE: August 5, 1987
TIME: 10:00 a.m.
WHERE: MCC Auditorium
3500 West Balcones Center Drive
CONTACTS: Charles Petrie - MCC
Ben Kuipers - UT
TITLE: THE GENERIC TASK TOOLKIT FOR KNOWLEDGE-BASED SYSTEMS:
BUILDING BLOCKS AT THE ``RIGHT'' LEVEL OF ABSTRACTION
ABSTRACT:
The first part to the talk is a critique of the level of abstraction
of much of the current discussion on knowledge-based systems. It will
be argued that the discussion at the level of
rules-logic-frames-networks is the ``civil engineering'' level, and
there is a need for a level of abstraction that corresponds to what
the discipline of architecture does for construction of buildings.
The constructs in architecture, viewed as a language of habitable
spaces, can be implemented using the constructs of civil engineering,
but are not reducible to them. Similarly, level of abstraction that
we advocate is the language of generic tasks, types of knowledge and
control regimes.
In the second part of the talk, I will outline the elements of a
framework at this level of abstraction for expert system design that
we have been developing in our research group over the last several
years. Complex knowledge-based reasoning tasks can often be
decomposed into a number of generic tasks each with associated types
of knowledge and family of control regimes. At different stages in
reasoning, the system will typically engage in one of the tasks,
depending upon the knowledge available and the state of problem
solving. The advantages of this point of view are manifold: (i)
Since typically the generic tasks are at a much higher level of
abstraction than those associated with first generation expert system
languages, knowledge can be represented directly at the level
appropriate to the information processing task.
(ii) Since each of the generic tasks has an appropriate control
regime, problem solving behavior may be more perspicuously encoded.
(iii) Because of a richer generic vocabulary in terms of which
knowledge and control are represented, explanation of problem solving
behavior is also more perspicuous. We briefly describe six generic
tasks that we have found very useful in our work on knowledge-based
reasoning: classification, state abstraaction, knowledge-directed
retrieval, object synthesis by plan selection and refinement,
hypothesis matching, and assembly of compound hypotheses for
abduction.
Finally, we will describe how the above approach leads naturally to a
new technology: a toolbox which helps one to build expert systems by
using higher level building blocks. We will review the toolbox, and
outline what sorts of systems can be built using the toolbox, and what
advantages accrue from this approach.
------------------------------
Date: 20 Jul 87 12:15:08 EDT
From: Terina.Jett@b.gp.cs.cmu.edu
Subject: Course - Probability and AI (CMU)
PROBABILITY AND ARTIFICIAL INTELLIGENCE
Offered by: Department of Philosophy, CMU
Instructor: Kevin T. Kelly
Grad Course No: 80-312
Undergrad Course No: 80-811
Place: Porter Hall, 126-B
Time: Tuesday, Thursday, 3:00-4:00
Intended Audience: Graduate students ans sophisticated undergraduates
interested in inductive methods, the philosophy of science, mathematical
logic, statistics, computer science, artificial intelligence, and
cognitive science.
Prerequisites: Familiarity with mathematical logic, computation, and
probability theory.
Course Focus: There are several ways in which the combined system of a
rational agent and its environment can be stochastic. The agent's
hypotheses may make claims about probabilities, the agent's environment
may be stochastic, and the agent itself may be stochastic, in any com-
bination. In this course, we will examine efforts to study computational
proposals from the point of view of logic and probability theory. Example
topics are Bayesian systems, Dempster/Shafer theory, medical expert systems,
computationally tractable learnability, automated linear causal modelling,
and Osherson and Weinstein's results concerning limitations on effective
Bayesians.
Course Format: The grade will be based on frequent exercises and possibly
a final project. There will be no examinations if the class keeps up with
the material.
------------------------------
Date: Fri, 17 Jul 1987 14:58 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Conferences - CD-ROM & 7th Distributed Computing Systems
AI at Upcoming Conferences
CD-ROM Expo, New York City September 21-23
T-8 Using CD-RoM in Expert Systems
H-1 Helping the Non-Expert Use CD-ROM, Artificial Intellgience and Expert
Systems
Seventh International Conference on Distributed Computing Systems
Berlin (West), 21-25th September 1987
Thursday, 24 Sep 1987, 11.00-12.30
On the Application of AI in Decentralized Cnotrol: An Illustration by
Mutual Exclusion
1987 International Conferenceon Parallel Processing
Tutorial 10:30AM Dr. Benjamin W. Wah, Computers for Artificial Intelligence
Processing.
A Parallel Model and Architecture and Architecturee for Production Systems
by A. O. Oshisanwo and P. P. Dasiewicz
Parallel Link Resolution of Connection Graph Refutation and its Implementation
by R. Loganantharaj (Logan)
Combinators as Control Mechanisms in Multiprocessing Systems by D. L. Knox
and C. T. Wright
An AND-OR Parallel Execution System for Logic Program Evaluation
by N. S. Woo and R. Sharma
PESA I - A Parallel Architecture for Production Systems
by F. Schreiner and G. Zimmermann
A New Parallel Graph Reduciton Model and its Machine Architecture
by M. Amamiya
Parallel Garbage Collection on a Virtual Memory System by S. G. Abraham
and J. H. Patel
A Knowledge-Based Parallelization Tool in a Programming Environment
by T. Brandes and M. Sommer
A Heuristic Algorithm for Conflict Resolution Problem in Multistage
Interconnection Networks
by J. S. Deogun and Z. Fang
Exploiting Locality of Reference in MIMD Parallel Symbolic Computation
by Y. Eisenstadter and G. Q. McGuire, Jr.
Efficient Image Template Matching on Hypercube SIMD Arrays
by V. K. P. Kumar and V. Krishnan
Practical Algorithms for Image Component Labeling on SIMD Mesh Connected
Computers
by R. E. Cypher, J. L. C. Sanz and L. Snyder
A Parralel O(logN) algorithm for Finding Connected Components in Planar
Images by A. Agrawal, L. Nekludova and W. LIM
Large Scale Unification Using a Mesh-Connected Array of Hardware Unifiers
by Shih and K. B. Irani
On Source to Source Transformation of Sequential Logic Programs to AND-
parallelism
by A. K. Bansal and L. S. Sterling
An Overlapping Unification Algorithm and its Hardware Implementation
by W. T. Chen and K. R. Hseih
Pipelined Evaluation of Conjunctive PRoblems by S. C. Sheu
Analysis and Design of Parallel Aglortihms and Implementations for Some
Image Processing Operations
by M. Yasrebi, J. C. Browne and D. P. Agrawal
parallel Image Processing on enhanced Arrays
by V. K. P. Kumar and D. Reisis
Parallel Pattern Clustering on a Multiprocessor with Orthogally Shared
Memory
by K. Hwang and D. Kim
A General Purpose VLSI Array for Efficient Signal and Image Processing
by S. Sastry and V. K. P. Kumar
Computing the Two-Dimensional Discrete Fourier Transforma on the ASPEn
Paralle Computer Architecture by A. L. Gorin, A. Silberger
and L. Auslander
------------------------------
Date: Mon, 20 Jul 87 13:40:35 CDT
From: Don <kraft%lsu.edu@RELAY.CS.NET>
Subject: Conference - R&D in Information Retrieval
I have just received a travel grant for twenty or so stipends covering airfare
from the National Science Foundation so that U.S. residents can attend the
ACM/SIGIR International Conference on Research and Development in Information
Retrieval, to be held in Grenoble, France on June 13-15, 1988.
The conference will include the topics of retrieval system modeling, artificial
intelligence and information retrieval, evaluation techniques, hardware
developments for retrieval systems, natural language processing, database
management and information retrieval, user interfaces, and advanced
applications.
Anyone interested in receiving a travel stipend should contact me. The deadline
for applying for a travel stipend is March 1, 1988.
Submission of papers (four copies of either a full paper of not more than 20-25
pages, or an extended abstract of about ten pages) with a complete author
identification and an abstract of about one hundred words must be submitted
by January 15, 1988 to:
Professor Gerard Salton
Department of Computer Science
4130 Upson Hall
Cornell University
Ithaca, NY 14853-7501
USA
Final copy is due May 16, 1988, with acceptance notification coming by March 21,
1988.
Don Kraft
kraft@lsu.edu
------------------------------
Date: Tue, 21 Jul 87 09:39 EDT
From: MIKE%BUCASA.BITNET@wiscvm.wisc.edu
Subject: Conference - International Neural Network Society
INTERNATIONAL NEURAL NETWORK SOCIETY
1988 ANNUAL MEETING
September 6--10, 1988
Boston, Massachusetts
The International Neural Network Society (INNS) is an association of
scientists, engineers, students, and others seeking to learn about and advance
our understanding of the modelling of behavioral and brain processes, and the
application of neural modelling concepts to technological problems. The INNS
invites all those interested in the exciting and rapidly expanding field of
neural networks to attend its 1988 Annual Meeting. The planned conference
program includes plenary lectures, symposia on selected topics, contributed
oral and poster presentations, tutorials, commercial and publishing
exhibits, a placement service for employers and educational institutions,
government agency presentations, and social events.
Individuals from fields as diverse as engineering, psychology, neuroscience,
computer science, mathematics, and physics are now engaged in neural network
research. This diversity is reflected in both the 1988 INNS Annual Meeting
Advisory Committee and in the Editorial Board of the INNS journal, Neural
Networks. In order to enhance the effectiveness of these multidisciplinary
ventures and to inform a wide audience, organization of the INNS Annual
Meeting will be carried out with the active participation of several
professional societies.
Meeting Advisory Committee includes:
Demetri Psaltis---Meeting Chairman
Larry Jackel---Program Chairman
Gail Carpenter---Organizing Chairman
Shun-ichi Amari
James Anderson
Maureen Caudill
Walter Freeman
Kunihiko Fukushima
Lee Giles
Stephen Grossberg
Robert Hecht-Nielsen
Teuvo Kohonen
Christoph von der Malsburg
Carver Mead
Edward Posner
David Rumelhart
Terrence Sejnowski
George Sperling
Harold Szu
Bernard Widrow
CALL FOR ABSTRACTS: The INNS announces an open call for abstracts to be
considered for oral or poster presentation at its 1988 Annual Meeting.
Meeting topics include:
--Vision and image processing
--Speech and language understanding
--Sensory-motor control and robotics
--Pattern recognition
--Associative learning
--Self-organization
--Cognitive information processing
--Local circuit neurobiology
--Analysis of network dynamics
--Combinatorial optimization
--Electronic and optical implementations
--Neurocomputers
--Applications
Abstracts must be typed on the INNS abstract form in camera-ready format.
An abstract form and instructions may be obtained by returning the
enclosed request form to: Neural Networks, AT&T Bell Labs, Room 4G-323,
Holmdel, NJ 07733 USA.
In order to be considered for presentation at the INNS 1988 Annual Meeting,
an abstract must be POSTMARKED NO LATER THAN March 31, 1988. Acceptance
notifications will be mailed by June 30, 1988. An individual may make at
most one oral presentation during the contributed paper sessions. Abstracts
accepted for presentation at the Meeting will be published as a supplement
to the INNS journal, Neural Networks. Published abstracts will be available
to participants at the conference.
***** ABSTRACT DEADLINE: MARCH 31, 1988 *****
CONFERENCE SITE: The 1988 Annual Meeting of the International Neural Network
Society will be held at the Park Plaza Hotel in downtown Boston. A block of
rooms has been reserved for the INNS at the rate of $91 per night plus tax
(single or double). Reservations may be made by contacting the hotel directly.
Be sure to give the reference "Neural Networks". A one-night deposit will be
requested.
HOTEL RESERVATIONS:
Boston Park Plaza Hotel
"Neural Networks"
1 Park Plaza at Arlington Street
Boston, MA 02117 USA
(800) 225-2008 (continental U.S.)
(800) 462-2022 (Massachusetts only)
Telex 940107
INTERNATIONAL RESERVATIONS:
Steigenberger, Utell International
KLM Golden Tulip, British Airways
REF: "Neural Networks"
Please note that other nearby hotel accomodations are typically more expensive
and may also sell out quickly.
CONFERENCE REGISTRATION: To register for the 1988 INNS Annual Meeting, return
the enclosed conference registration form, with registration fee; or contact:
UNIGLOBE---Neural Networks 1988, 40 Washington Street, Wellesley Hills, MA
02181 USA, (800) 521-5144 or (617) 235-7500.
The great interest and attention now being devoted to the field of neural
networks promises to generate a large number of meeting participants.
Conference room size and hotel accomodations are limited. Therefore early
registration is strongly advised.
For information about INNS membership, which includes a subscription to the
INNS journal, Neural Networks, write: Dr. Harold Szu---INNS, NRL Code 5756,
Washington, DC 20375-5000 USA, (202) 767-1493.
ADVANCE REGISTRATION FEE SCHEDULE
INNS Member Non-member
Until March 31, 1988 $125 $170*
Until July 31, 1988 $175 $220*
Full-time student $50 $85*
* Includes the option of electing one-year INNS membership and subscription
to the INNS journal, Neural Networks, free of charge.
The conference registration fee schedule has been set to cover abstract
handling costs, the book of abstracts, a buffet dinner reception, coffee
breaks, informational mailings, and administrative expenses. Anticipated
financial support by government and corporate sponsors will cover additional
basic meeting costs.
Tutorials and other special programs will require payment of additional fees.
STUDENTS AND VOLUNTEERS: Students are particularly welcome to join the INNS
and to participate fully in its Annual Meeting. Reduced registration and
membership rates are available for full-time students. In addition, financial
support is anticipated for students and meeting volunteers. To apply, please
enclose with the conference registration application a letter of request and a
brief description of interests.
-----ABSTRACT REQUEST FORM-----
INTERNATIONAL NEURAL NETWORK SOCIETY
1988 ANNUAL MEETING
September 6--10, 1988
Boston, Massachusetts
Please send an abstract form and instructions to:
Name:
Address:
Telephone(s):
All abstracts must be submitted camera-ready, typed on the INNS abstract form
and postmarked NO LATER THAN March 31, 1988.
MAIL TO:
Neural Networks
AT&T Bell Labs
Room 4G-323
Holmdel, NJ 07733 USA
-----REQUEST FOR INFORMATION-----
INTERNATIONAL NEURAL NETWORK SOCIETY
1988 ANNUAL MEETING
September 6--10, 1988
Boston, Massachusetts
Please send information on the following topics to:
Name:
Address:
Telephone(s):
( ) Placement/Interview service
( ) Employer
( ) Educational institution
( ) Candidate
( ) Hotel accomodations
( ) Travel and discounted fares
Discounts of up to 60% off coach fare can be obtained on conference
travel booked through UNIGLOBE: (800) 521-5144 or (617) 235-7500.
( ) Volunteer and student programs
( ) Proposals for symposia and special programs
( ) Exhibits
( ) Commercial vendor
( ) Publisher
( ) Government agency
( ) Tutorials
( ) Press credentials
( ) INNS membership
MAIL TO:
Center for Adaptive Systems---INNS
Boston University
111 Cummington Street, Room 244
Boston, Massachusetts 02215 USA
ELECTRONIC MAIL TO:
mike@bucasa.bu.edu
------------------------------
End of AIList Digest
********************
∂27-Jul-87 0335 LAWS@Stripe.SRI.Com AIList Digest V5 #188
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 27 Jul 87 03:35:27 PDT
Date: Sun 26 Jul 1987 23:37-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #188
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 27 Jul 1987 Volume 5 : Issue 188
Today's Topics:
Queries - Graphics/AI Bibliography &
Blackboard Architectures in Prolog &
VPExpert Parameters &
Knowledge Representation in Sanskrit,
Techniques - Garbage Collection Suppression,
Philosophy - Natural Kinds & AI, Science, and Pseudo-Science
----------------------------------------------------------------------
Date: 22-JUL-1987 15:13:29
From: THOWARD%graphics.computer-science.manchester.ac.uk@Cs.Ucl.AC.UK
Subject: Graphics-AI bibliography
I am currently investigating what work has been done on connecting/integrating
AI methods and computer graphics. I would be very grateful if anyone can
send me any references, or bibliographies (or comments!) etc in this area.
If there's enough interest, I will summarise responses. Thanks...
______________________________________________________________________________
- Toby Howard -
Computer Graphics Unit, Department of Computer Science
Manchester University, England, M13 9PL. Phone: 061 273 7121 x5429/5406
Janet: thoward@uk.ac.man.cs.cgu
ARPA: thoward%cgu.cs.man.ac.uk@cs.ucl.ac.uk
------------------------------
Date: Wed 22 Jul 87 11:52:28-CDT
From: OLIVIER J. WINGHART <CS.WINGHART@R20.UTEXAS.EDU>
Subject: Blackboard architectures in Prolog
I am looking for natural ways of implementing a blackboard architecture
in Prolog. Has anyone already thought about this, and are there any papers
that I could look at ? I would appreciate any pointer.
Olivier
cs.winghart@utexas.edu
------------------------------
Date: Fri, 24 Jul 87 18:00:05 EDT
From: Brady@UDEL.EDU
Subject: VPExpert Parameters
The VPExpert manual says that data can be passed to a batch
file, and that this is the only way to directly pass parameters
to an external program. But when I try to do this, the system
tells me the syntax of my call is wrong. I am sure my error is
not in the call to the batch file itself, since I am able to call
and execute a batch file that does not require parameters.
Anyone out there using this shell who has figured
out how to pass parameters to a batch file, please send me
mail. I will post answers back to the net. Thank you.
/////////
joe brady
------------------------------
Date: Thu, 23 Jul 87 10:54:47 PDT
From: bwidlans%zodiac@ads.arpa (Bob Widlansky)
Subject: Knowledge Representation in Sanskrit
Recently, I read a short intriguing article in AI magazine about the
First International Conference on Knowledge Representation and
Inference in Sanskrit (held in Bangalore, India between December
20-22, 1986).
Does anyone know where I can get a copy of the proceedings?
If you do, please contact me at bwidlans@ads.ARPA
Thank you,
Bob Widlansky
------------------------------
Date: 22 Jul 87 14:28:51 GMT
From: "J. A. \"Biep\" Durieux" <mcvax!cs.vu.nl!biep@seismo.CSS.GOV>
Reply-to: "J. A. \"Biep\" Durieux"
<mcvax!cs.vu.nl!biep@seismo.CSS.GOV>
Subject: Re: Garbage Collection Suppression
In article <8707202143.aa23792@Dewey.UDEL.EDU> Chester@UDEL.EDU writes:
>The direct way to avoid garbage collection in lisp is to define your own `cons'
>function that prefers to get cell pairs from an `available list' (...).
Also handy in many cases (small functions like append, alist-functions, subst)
is icons: (defun icons (a d cell)
(cond ((and (eq (car cell) a) (eq (cdr cell) d)) cell)
(t (cons a d))))
In this way whenever it turns out the new cells weren't really needed, the
old ones are used again (as in (append x nil)). Be aware, however, that your
copy-function may not work any more if it's defined as (subst nil nil x)!
--
Biep. (biep@cs.vu.nl via mcvax)
Never confound beauty with truth!
------------------------------
Date: Wed, 22 Jul 1987 10:43 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: Natural Kinds (Re: AIList Digest V5 #186)
About natural kinds. In "The Society of Mind", pp123-129, I propose a
way to deal with Wittgenstein's problem of defining terms like "game"-
or "chair". The basic idea was to probe further into what
Wittgenstein was trying to do when he talked about "family
resemblances" and tried to describe a game in terms of properties, the
way one might treat members of a human family: build, features, colour
of eyes, gait, temperament, etc.
In my view, Wittgenstein missed the point because he focussed on
"structure" only. What we have to do is also take into account the
"function", "goal", or "intended use" of the definition. My trick is
to catch the idea between two descriptions, structural and functional.
Consider a chair, for example.
STRUCTURE: A chair usually has a seat, back, and legs - but
any of them can be changed in so many ways that it is hard
to make a definition to catch them all.
FUNCTION: A chair is intended to be used to keep one's bottom
about 14 inches off the floor, to support one's back
comfortably, and to provide space to bend the knees.
If you understand BOTH of these, then you can make sense of that list
of structural features - seat, back, and legs - and engage your other
worldly knowledge to decide when a given object might serve well as a
chair. This also helps us understand how to deal with "toy chair" and
such matters. Is a toy chair a chair? The answer depends on what you
want to use it for. It is a chair, for example, for a suitable toy
person, or for reminding people of "real" chairs, or etc.
In other words, we should not worship Wittgenstein's final defeat, in
which he speaks about vague resemblances - and, in effect, gives up
hope of dealing with such subjects logically. I suspect he simply
wasn't ready to deal with intentions - because nothing comparable to
Newell and Simon's GPS theory of goals, or McCarthy's meta-predicate
(Want P) was yet available.
I would appreciate comments, because I think this may be an important
theory, and no one seems to have noticed it. I just noticed, myself,
that I didn't mention Wittgenstein himself (on page 130) when
discussiong the definition of "game". Apologies to his ghost.
------------------------------
Date: Wed, 22 Jul 87 12:40:58 EDT
From: mckee%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: AI, science, and pseudo-science
In AIlist Digest v5 #171, July 6, 1987, Don Norman
<norman%ics@sdcsvax.ucsd.edu> wrote:
> [Here's why] many of us otherwise friendly folks in the sciences that
> neighbor AI [are] frustrated with AI's casual attitude toward theory:
> AI is not a science and its practitioners are woefuly untutored in
> scientific method."
[ 15 lines deleted ]
> AI worries a lot about methods and techniques, with many books and
> articles devoted to these issues. But by methods and techniques I
> mean such topics as the representation of knowledge, logic,
> programming, control structures, etc. None of this method includes
> anything about content. And there is the flaw: nobody in the field of
> Artificial Intelligence speaks of what it means to study intelligence,
> of what scientific methods are appropriate, what emprical methods are
> relevant, what theories mean, and how they are to be tested. All the
> other sciences worry a lot about these issues, about methodology,
> about the meaning of theory and what the appropriate data collection
> methods might be. AI is not a science in this sense of the word.
[ 22 more lines deleted ]
I think he's found an issue of critical importance here, so I'm going
to pull it out of context even further and repeat it again:
"nobody in the field of Artificial Intelligence speaks of what it means
to *study* intelligence" (my emphasis).
No wonder those of us outside the field have trouble figuring out
what AI is really about. My impression is that AI researchers try
to study intelligence by building artifacts that will make a convincing
show of intelligent behavior. This might be why books on AI methods are all
about sophisticated representations and fancy program structures -
they're techniques of building more complex (hopefully more intelligent)
programs. But this is nearsighted. Intelligence is the *difference*
between unintelligent and intelligent behavior. The study of intelligence
begins when the programming stops. And on what to do then, the AI textbooks
are silent.
Now I don't want to spend time talking about the consequences
of this failure, Don did that much better than I can. (However, I can't
resist throwing in my excuse: programming is fun; science is hard, often
boring, work. Science is far more rewarding, though.) What I'm going to
discuss in the rest of this note stems from his remark that AI workers
are "woefully untutored in scientific method". Assuming for the purposes
of discussion that we know enough about intelligence to make principled
distinctions between it and stupidity (counterintelligence?), what would
the scientific study of intelligence look like?
One way of answering this question is to look at some of the enterprises
that claim to be scientific, but aren't. The main distinction in the
list below is between those fields that are unarguably sciences, and those
that fail to be scientific in one way or another. True science, the authentic,
natural sciences, are ones like astronomy, geology, biology, physics, or
chemistry. False sciences are harder to characterize, but here goes:
Here's a list of examples of different claimants to the name "science";
mostly impostors, all of them can be called "quasi-sciences". By looking
at them, we can gain some sense of what qualities are necessary for
real sciences, since the quasi-sciences don't have them.
* Fraudulent sciences: Creation Science, Lysenkoism, Scientology
(the most generous thing I can say about these is that they
appear to proceed by trusting exceptional, one-of-a-kind
reports, and denying persistent, repeated, quantitative,
skeptical observations. In rhetoric this is called "appeal
to authority.")
* Trivial sciences: Clairol Science, barbeque science, accelerator science
(Clairol Science has discovered a new way to make your
hair silkier and more full-bodied. Barbeque science has
conclusively determined that mesquite smoke is superior to
hickory smoke. We need to build the superconducting supercollider
so America won't fall behind in accelerator science.)
* Semi-sciences: Theoretical Physics, Descriptive Linguistics
(complementary halves of their respective fields.)
* Interdisciplinary Sciences: Materials Science, Neuroscience
(characterized by their subject matter not yielding coherently
to any single experimental technique or theoretical paradigm.)
* Artifact Sciences: Economics, Political Science, Anthropology
(Herbert Simon's "sciences of the artificial" - these study artifacts
of human society - without civilization, they wouldn't exist.
However, civilization is big and complex enough that techniques
developed to deal with natural phenomena give useful insights.)
* Synthetic Sciences: Mathematics, Computer Science
(These study the consequences of small sets of fundamental concepts.
Mathematics under Russell&Whitehead and Bourbaki has been "nothing
but" an incredibly vast and elegant elaboration of set theory,
while [I claim with a certain trepidation] that the fundamental
basis of the scientific part of computer science lies in the
elaboration of the consequences of the notion of an algorithm.)
The authentic, natural sciences, on the other hand, are the body of analytic,
experimental studies of phenomena that go on whether or not the experimenter
is there to observe them, [philosophers can complain about "naive realism" --
I'll confess to the realism, but not not the naivete] and the results,
conclusions, and theoretical relations that tie the studies together.
The key concepts here are "experimental" and "objective". If a researcher
(or a team of them) isn't doing experiments on some external phenomenon,
then it ain't real science.
What do you get from real science? Reality. Not wishful thinking,
not hallucinations, not mythology, not common sense. (Strictly speaking,
what you get is the most compact model of reality consistent with the
most reliable, most detailed, widest ranging set of observations.)
Uncommon sense.
What you don't get is completeness, or even closure. First of all,
there's too much knowledge, as anyone with a Ph.D. in a natural science will
tell you. Second of all, the universe isn't closed under observation: there's
always more detail to examined, further frontiers to be explored, greater
complexities to be explained. And most exciting of all, there's the
possibility of revolution - that a new model will explain more data,
resolve old inconsistencies, or be statable more succinctly, hopefully
all at once.
The natural sciences generate an interconnected web of explanations
that should contain a place for AI, if AI is a science. It's in this
explanatory web that people claim to see the bugaboo of reductionism
(without which no discussion of scientific method would be complete).
Stripped of the argumentative mumbo-jumbo that keeps philosophers in business,
a reductionist would claim that a pile of parts on the floor is equivalent to
an assembled machine, while a holist would claim that the parts are irrelevant
to any description of the machine. Both views are incomplete, but there is
indeed an ordering by "is explained in terms of" that reductionists
have grabbed onto. Because it's only a partial ordering, I'd like to borrow
a term from evolutionary biology and suggest that scientific knowledge has
the same kind of familial, clade structure as do charts of the genetic
relations among organisms. Reading "<--" as "is used to explain", we have
One path through a Cladistic epistemology:
Particle Physics <--
Condensed-matter physics <--
Quantum Chemistry <--
Organic Chemistry <--
Molecular Biology/Genetics <--
Developmental Biology <--
Neuroscience <--
Ethology <--
Psychology <--
Cognitive Science <--
Mathematics
I would put intelligence in at the same level as mathematics. Congratulations!
Scientific AI would be among the most complex of sciences. However,
in reality the picture isn't this clean. Aside from those sciences that
aren't in a direct explanatory line to intelligence, there are shortcuts
among levels due to the logic of experimental science, that makes it possible
to do things like manipulate genetic structure and get a behavioral result.
But this note is already too long to go into this further, and I've barely
alluded to the formal role of the hypothesis.
Hope this helps,
- George McKee
College of Computer Science
Northeastern University, Boston 02115
CSnet: mckee@Corwin.CCS.Northeastern.EDU
Phone: (617) 437-5204
Usenet: in New England, it's not unusual to have to say
"can't get there from here."
------------------------------
End of AIList Digest
********************
∂27-Jul-87 0605 LAWS@Stripe.SRI.Com AIList Digest V5 #189
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 27 Jul 87 06:04:52 PDT
Date: Sun 26 Jul 1987 23:42-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #189
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 27 Jul 1987 Volume 5 : Issue 189
Today's Topics:
Bibliography - Leff File a55AB
----------------------------------------------------------------------
Date: Sat, 18 Jul 1987 10:37 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Bibliography - Leff File a55AB
%A Rudolph E. Seviora
%T Knowledge-Based Program Debugging Systems
%J IEEE Software
%V 4
%N 3
%D May 1987
%P 20-32
%K AA08
%X Divides debugging, whether done by human or by computer into three
categories:
a) those that look at the code and compare to specifications
b) those that look at the output
c) those that look at the internal trace
In the latter category, there exists only one system, MTA which is
a PROLOG based system to view internal traces from communication
based software which is often done using finite-state machines.
Falosy is an example of a system that tries to debug by comparing
the output and then reasoning to the program. Proust, Laura, and Pudsy
are example of systems that look at the code and compare it to the
specification.
%T New Products
%J ComputerWorld
%D APR 13, 1987
%V 21
%N 15
%P 44
%K H01 AT02 AI06
%X AST's new read right software associated with it's page scanner
will handle mixed fonts, variable character sizes and spacing and
reduced and enlarged photocopies.
%T Breaking the Lisp Language Barrier with COBOL
%J Mini-Micro Systems
%D May 1987
%P 27
%V 20
%N 5
%K AA06 AT02
%X Cullinet has announced a series of expert system programs based on
COBOL, OrderEXL, SalesEXL, VoiceEXL and DMS applications expert.
%A John Goach
%T Coming: A System for Real Time Dialog
%J Electronics
%D APR 30, 1987
%P 38-39
%K AI05
%V 60
%N 9
%X Spicos, handles 1000 word vocabulary, in continuous speech. The system
gives spoken answers and also uses the context of the word to help identify it.
%A Henry Eric Firdman
%T Which Comes First -- Development Or Specs
%J ComputerWorld
%D APR 13, 1987
%V 21
%N 15
%P 69-73
%K O02 AI01 rapid prototyping AA08
%X Discusses whether a prototype model of development is appropriate
for expert systems as well as software projects in general and what actions
are appropriate and not appropriate under such a model of development.
%A Jean S. Bozman
%T MDBS Develops Guru for VAX
%J ComputerWorld
%V 21
%D May 25, 1987
%N 21
%K H01 T03 AI09 AT02
%X GURU, which currently runs on PC's, will be ported to
both VMS and Ultrix with costs of $17,000 to $60,000
%A Charles Babcock
%T Quick and Dirty Fixes May Work Best
%J ComputerWorld
%V 21
%D May 25, 1987
%N 21
%P 25
%K AA08
%X A study has shown that advanced development techniques leads to more
costly maintenance, not less. "Programmers who perform impromptu fixes
without checking documentation may be just as effective as those who
follow more structured approaches." They also found that a greater
percentage of the requests made by users were implemented in systems
where the user under the system.
%A Rosemary Hamilton
%T DG Courts LISP Machine
%J ComputerWorld
%D APR 13, 1987
%V 21
%N 15
%P 93+
%K H02 AT16 Lisp Machine Inc. LMI Data Bankruptcy General
%X Data General made an offer to buy Lisp Machine, which is subject
to approval of an LMI creditor's committee. Lisp Machine has filed
under Chapter 11 of the U. S. Bankruptcy Law
%A Paul Wallich
%T Putting Speech Recognizers to Work
%J IEEE Spectrum
%D APR 1987
%P 55-57
%K AI05 H01
%V 24
%N 4
%X List of current products available.
.DS L
SSB-1000, Speaker dependent isolated word, 144 words, 95% accuracy, $250
VoDialer, Speaker Dependent isolated word, 48 words, 95% accuracy, $349
(for allowing cellular telephone users to dial numbers)
Dragon Systems Voice Scribe, Speaker-dependent, isolated word, 1000 words, $1195
IBM, Speaker-dependent isolated word, 64 words, 95-98% accuracy, $1195
Intel, Speaker Dependent Isolated Word, 200 words
Interstate Voice Products, Speaker-dependent, connected speech, 400 words,
98% accuracy, $395
Interstate Voice Products, Speaker-dependent continuous speech, 100 words,
99% accuracy, $4000
Kurzweil Applied Intelligence, Speaker-dependent, isolated word, 1000 words,
$6000
NEC, SAR 10, Speaker-dependent, isolated word, 250words , 98% accuracy, $599
NEC, SR10, Speaker-Dependent, isolated words, 128 words, 98% accuracy, $600
NEC, DP-200, Speaker-Dependent, connected speech, 150 words, $7500
Speech Systems, speaker-dependent, connected speech, 20000 words, 90% accuracy,
$5000.00
TI, speaker-dependent, isolated word, 1000 words, $995.00
Voice Connection, speaker-dependnet, isolated-word, 400 words, 98% accuracy,
$495.00
Voice Control Systems, Speaker-independent, isolated word, 40 words, 98.5%
accuracy, $1000.00
Votan, Speaker-independent isolated-word, 13 words, 98% accuracy, $1350
Votan, speaker-dependnet, continuous speech, 640 words, 94 percent, $1200.00
.DE
%A H. Sardar Amin Saleh
%T Artificial Intelligence and Computer Aided Design in Civil Engineering
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 781-789
%K AA05 AI01 T02
%A Shuichi Fukuda
%T Development of an Expert System for the Design Support of an Oil Storage
Tank
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 791-796
%K AA05 AI01 GA01
%X This system copes with such as issues, corrosions, local regulations
and interfaces with numerical software to assist in the design of oil
storage tanks.
%A John F. Brotchie
%A Ron Sharpe
%A Bertil Marksjo
%A Michael Georgeff
%T Introducing Intelligence and Knowledge Into CAD
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 797-810
%K AA05 optimization quadratic programming
%X discusses applications of AI to quadratic programming with nonconvex
solutions.
%A U. Flemming
%A R. Coyne
%A T. Glavin
%A M. Rychener
%T A Generative Expert System for the Design of Building Layouts
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 811-821
%K AA05 kitchen bathroom generate and test AI09 DENDRAL
%X This system designs kitchen and bathrooms using an approach based
upon DENDRAL with a generator generating possible layouts and a
tester evaluating them against the constraints.
%A S. F. Jozwiak
%T Applications of Artificial Intelligence in Structural Optimization
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 823-834
%K AA05 AI04
%X AI techniques are used to reduce the computer time in determining
the optimal positions of the nodes in a
three dimensional truss. This type of optimization is done by setting up
a constraint corresponding to each member of the truss insuring that
that member does not bear unacceptable stresses. This work compares
known truss structures against the one being optimized to determine
which elements are likely to have stresses lower than adjacent
stresses so they don't need to have their stresses computed.
Same content as a paper appearing in \fIComputers
in Structures\fR by the same author.
%A T. J. Ross
%A F. S. Wong
%T Structural Damage Assessment Using AI Techniques
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 835-846
%K AI01 AA05 AA18
%X This system helps assess the possible damage to buried concrete
boxes from nearby nuclear explosions
%A Peter W. Mullarkey
%T A Geotechnical KBS Using Fuzzy Logic
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 843-860
%K AA05 AI01 O04
%X This system helps interpret the results of cone penetrometer tests in
determining the soil conditions where some structure will have its foundation.
%A Kenneth R. Maser
%T Automated Interpretation of Sensor Data for Evaluating In-Situ Conditions
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 861-888
%K AA05 radar signal interpretation AI06 AI01
%X The system helps model bridge deck deterioration using ground penetrometer
studies. The expert system deals with considerations from radar signal
analysis, radar/concrete physics, and bridge engineering.
%A Yoon-Pin Foo
%A Hideaki Kobayashi
%T A Framework for Managing VLSI CAD Data
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 889-898
%K AA05 AA09 AA16
%X compares a frame based system using is-a type inheritance with
INGRES database approach showing that operations are performed
about sixty percent faster in their frame based system.
%A Nikhil Balram
%A William P. Birmingham
%A Sean Brady
%A Robert Tremain
%A Daniel P. Siewiorek
%T The MICON System for Single Board Computer Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 899-910
%K AA04 AI01
%X This system constructions microcomputer boards. It deals with
the problems of interfacing IO chips from one family such as a
Z80 SIO chip to some other microprocessor. The system also handles
analog type constraints such as bus propagation, etc.
%A Jeffrey L. Dawson
%T Excirsize - An Expert System for VLSI Transistor Sizing
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 911-916
%K AA04 AI01
%X Describes how to size transistors for NMOS fabrication where
the goal is to achieve some propagation constraint at minimum
power consumption.
%A Ravi Malhotra
%A Ken Chao
%A Osama Mowafi
%T A Knowledge-Based System for Network Communication Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 917-924
%K AA08
%X discusses applications to designing the backbone part of a network
consisting of high speed communication paths and the access part consisting
of low speed lines connecting to various cities.
%A Stuart C. Shapiro
%A Sargur N. Srihari
%A Ming-Ruey Taie
%A James Geller
%T VMES: A Network-Based Versatile Maintenance System
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 925-936
%K AA21
%X Shows how in a structure based diagnostic expert system, to save
memory for common parts. I. E., if there are several op-amps in
the circuit, one doesn't want to store the capacitors, etc. for each
op-amp in the memory that comprise the op-amps. Techniques are developed
to phase in the detailed description of a part when needed to save computer
time. The article also discussed the graphic interface to the VMES
and shows how the system chooses what to display and how to arrange
these items on the screen.
%A Tao Li
%T Heuristic Search in Digital System Diagnosis
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 937-946
%K AI03 AA04
%X shows a variation of the A* algorithm for use in detecting
faults in sequential circuits. The article also shows how to handle
circuits that are not "resettable," there is no signal that is
guaranteed to force the system into a known state.
Various theoretical results regarding such fault detections are also
provided.
%A William P. C. Ho
%T A Plan Patching Approach to Switchbox Routing
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 947-958
%K AA04 AI09
%X When a conventional routing system reports failure, i. e. all the
rules that it has available have been tried, this system will come in
and try and patch the almost completed solution into a successful
routing of the switchbox.
%A Bryant W. York
%T KBTA: An Expert Aid for Chip Test
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 959-970
%A Jozsef Vancza
%T CODEX: A Coding Expert for Programmable Logic Controllers
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 971-984
%K AA05
%X This system takes a generic description of the control task
to be performed and translates it into the language for a specific
make and model of programmable controller.
%A Ernesto Guerrieri
%A Vinod Grover
%T Octtree Solid Modeling with Prolog
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 985-1002
%K T02 AA05
%X Shows how the OCTTREE data structure for representing objects can be
entered as Prolog acts and unions, interference checking and
neighbor finding are performed upon them.
%A G. Goldbogen
%A D. Ferrucci
%T Extending the Octree Model to Include Knowledge for Manufacturing
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1003-1012
%K T01 T02 AA26
%X Describes feature extraction algorithms on octtrees for
features such as hole boundaries.
%A C. B. Bouleeswaran
%A H. G. Fischer
%T A Knowledge Based Environment for Process Planning
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1013-1028
%K AA26 AI01
%X describes a system that generates process plans for rotational parts
such as screws. The system supports integrated design of the part
to be machined and the manufacturing process to use on it.
%A Joao P. Martins
%A Stuart C. Shapiro
%T Hypothetical Reasoning
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1029-1042
%K AI16
%X Discusses a generic purpose tool to allow users to raise hypotheses,
reason from them, discard various hypotheses and perform the appropriate
truth maintenance. The system uses contexts to avoid backtracking.
%A Robert Milne
%T Fault Diagnosis Using Structure and Function
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1043-1054
%K AA19 AI01
%X A troubleshooting paradigm called the "Theory of Responsibilities"
is introduced and applied to testing circuits. It works from "second
principles" in assigning responsability for various parts of the output
waveform to various components of the circuit.
%A D. Sharma
%A B. Chandrasekaran
%A D. Miller
%T Dynamic Procedure Synthesis, Execution, and Failure Recovery
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1055-1072
%K AA05 nuclear power plant AI01 AI09
%X Describes a system for planning failure recovery, synthesis,
monitoring for nuclear power plants. A comparison of the "event-oriented"
and "function oriented" approaches to nuclear power plant management
is provided. The nuclear industry is shifting to the latter in reaction
to the TMI difficulties. The implications of this for expert system
applications and an example from reactor scram concerns are also
provided. Various plan templates and blackboards are used in processing.
The final expert system consists of system specialists, specialists in
various kind of undesirable events and specialists in various kind of goals
such as reducing radioactivity.
%A B. Demo
%A M. Tilli
%T Expert System Functionalities for Database Design Tools
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1073-1082
%K AI01 AA09
%X Discusses the CARS system, an expert system for the design of databases.
%A Geoffrey D. Gosling
%A Anna M. Okseniuk
%T SLICE - A System for Simulation Through a Set of Cooperating Experts
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1083-1096
%K This paper describes simulation tools to investigate the application
of expert systems to aircraft control environments.
%A T. J. Grant
%T Maintenance Engineering Management Applications of Artificial Intelligence
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1097-1122
%K AA21 AI01 AA05
%X This is a survey of potential applications of artificial intelligence
to managing the maintenance of aircraft. An interesting comment is
that twenty percent of all faults are novel (noone ever saw them before).
These faults required twice as many repair hours to fix as the average
fault. For any given diagnostician, the number of faults that he never
saw before approaches sixty percent. It is interesting to note that
63 percent of the Royal Air Force's manpower is employed doing maintenance.
%A Benoit Faller
%T Expert Systems in Meteorology
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1123-1127
%K AA16 AI01
%X presents expert systems for forecasting airport fog-in conditions,
storm forecasting and avalanche risks. Fogs are predicted in the afternoon
for the following morning.
%A Karl-Erik Arzen
%T Expert Systems for Process Control
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1127-1138
%K AA05 AI01
%X Uses of expert systems with various control systems concepts such
as the Ziegler-Nichols auto-tuner, smart PID controller and the Nichols
auto-tuner.
%A Atsumi Imamiya
%A Akoio Kondoh
%A Akiyoshi Miyatake
%T An Artificial Intelligence Approach to the Modeling of the User-Computer
Communications
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1139-1151
%K AA08 AA15 AI01
%X describes a system to automate the production of help systems
for software.
%A John R. Hogley
%A Alan R. Korncoff
%T Artificial Intelligence in Engineering: A Revolutionary Change
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1155-1160
%K AA05 AI01
%X This is a general article devoid of technical content.
%A Kai-li Kan
%T Expert Systems in Telecommunications Network Planning and Design
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1161-1165
%K AI01 AA08
%X discusses the implications of expert system in design networks.
The gentleman belongs to the "Strategic Technology Assessment" department
of Pacific Bell.
%A Ye-Sho Chen
%T Expert System for On-Line Quality Control
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1165-1174
%K AI01 AA05 AA21 automotive O04 Pareto
%X Discusses a diagnostic system for automobile brakes.
The system uses Pareto optimality to assist in uncertainty calculus.
%A K. M. Chalfan
%T An Expert Executive Which Integrates Heterogenous Computational Programs
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1175-1174
%K AI01 AA05 aerospace preliminary design
%X Discusses a proposed system to automate weight, aerodynamics,
propulsion and performance codes in the preliminary design of airplanes.
%A A. Kissil
%A A. Kamel
%T An Expert System Finite Element Modeler
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1179-1186
%K AI01 AA05
%X Discusses an expert system for use in generating meshes for
finite elements. Includes a discussion of heuristics that will generate
a mesh with a desired accuracy. This is done by comparing a parametric
distortion of a region whose stresses are known with the unknown region.
%A Paul F. Monaghan
%A James G. Doheny
%T Knowledge Representation in the Conceptual Design Process for Building
Energy Systems
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1187-1192
%K HVAC AA05 AI01
%X discusses using expert systems and hierarchies in the design of
HVAC systems (Heating, Ventilation and Air Conditioning)
%A Prem Kumar Kalra
%T Development of Expert System for Fault Diagnosis in HVDC Systems Using
Spectral Approach
%B Applications of Artificial Intelligence in Engineering Problems
%E D. Sriram
%E R. Adey
%V 2
%I Computational Mechanics Publications
%C Woburn, Massachussetts
%D 1986
%P 1193-1198
%K AA21 AA05 AI01
%X discusses using Fast Fourier Transform, Fast Walsh Transform
and expert systems to help diagnose
high voltage DC and analog systems
------------------------------
End of AIList Digest
********************
∂29-Jul-87 0121 LAWS@Stripe.SRI.Com AIList Digest V5 #190 - Msc.
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Jul 87 01:20:53 PDT
Date: Tue 28 Jul 1987 23:21-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #190 - Msc.
To: AIList@STRIPE.SRI.COM
AIList Digest Wednesday, 29 Jul 1987 Volume 5 : Issue 190
Today's Topics:
Queries - AI/Graphics & Examples of KEE Frames &
Problem Recognition in Prolog Databases &
NLP Front Ends to INGRES,
Policy - Virtual Sublists,
Philosophy - Natural Kinds
----------------------------------------------------------------------
Date: Mon, 27 Jul 87 14:03:36 BST
From: mcvax!ux.cs.man.ac.uk!arnold@seismo.CSS.GOV
Reply-to: thoward@uk.ac.man.cs.cgu
Subject: AI/Graphics: help wanted
I am currently investigating what work has been done on connecting/
integrating AI methods and computer graphics. I would be very grateful
if anyone can send me any references, or bibliographies (or comments!)
etc in this area. If there's enough interest, I will summarise responses.
Please mail to me directly, *not* to the source of this posting, as it's
not my own account. Thanks...
Toby Howard Janet: thoward@uk.ac.man.cs.cgu
University of Manchester ARPA: thoward%cgu.cs.man.ac.uk@cs.ucl.ac.uk
Computer Graphics Unit Phone: +44 61 273 7121 x5429/5406
------------------------------
Date: 28 Jul 87 04:46:37 GMT
From: munnari!uqcspe.OZ!twine@uunet.UU.NET (Steven Twine)
Subject: Examples of KEE frames Requested
I am currently revising a semantic analysis of KEE's frame language.
By semantic analysis, I mean trying to answer the question
What facts does X encode about the current Universe of Discourse
where X is each of the syntactic ingredients in a KEE knowledge base
(units, slots, links etc).
This is not as simple as it seems, because a given KEE construct can
represent many different things (as Brachman showed for IsA links).
Anyway, in revising this paper, I would like to add many more examples
of KEE structures that have been used in practice, for the
purpose of analysing the facts that they encode. I am particularly
interested in any ambiguous or otherwise tricky examples that I can
test my interpretations out on. I would appreciate any examples of
KEE units etc that people could send me for this purpose (examples in
other frame languages may also be useful, but KEE is preferred)
All senders will get a lovely acknowledgement at the end of the paper
(what an incentive!) as well as my heartfelt gratitude.
Thanks in advance, folks!
=========================================================================
Steven Twine, ARPA: twine%uqcspe.oz@seismo.css.gov
Department of Computer Science, ACSnet: twine@uqcspe.oz
University of Queensland, UUCP: seismo!munnari!uqcspe.oz!twine
St Lucia, 4067. CSNET: twine@uqcspe.oz
AUSTRALIA. JANET: uqcspe.oz!twine@ukc
------------------------------
Date: 26 Jul 87 20:37:16 GMT
From: dartvax!balu.UUCP@seismo.css.gov (Balu Raman)
Subject: Problem recognition in Prolog database
I am working on recognizing problem instances in Prolog database. The problems
can be typical Graph-color, Linear Programming Problem, Critical Path Problems
etc.etc. Does anybody in the netland have references, pointers ,prolog programs
to do what I am trying to do.
thanks in advance.
Balu Raman.
------------------------------
Date: Mon, 27 Jul 87 08:37:24 PDT
From: vor!cris%esosun.UUCP@sdcsvax.ucsd.edu (Cris Kobryn)
Subject: NLP Front-Ends to INGRES
I am interested in developing an NLP front-end to INGRES. Lest I
reinvent: Is there any "stock" software which already does this?
(INTELLECT does not *currently* accommodate INGRES; I've heard "DataTalker"
mentioned as a possibility, but have no details--capabilities, company name,
phone#, etc.)
Re building an NLP front-end: Prolog's DCG's (Definite Clause Grammars)
seem to provide an attractive tool to construct an NLP front-end. I would
appreciate feedback re their effectiveness, and pointers to work done or
being done relevant to this interest.
I will be glad to summarize and post if the response merits it.
-- Cris Kobryn
+----------------------------------------------------------------------------+
| Cris Kobryn UUCP: {sdcsvax|seismo}!esosun!cris |
| Geophysics Division, MS/22 ARPA: esosun!cris@seismo.css.gov |
| SAIC SOUND: (619)458-2697 |
| 10210 Campus Point Drive |
| San Diego, CA 92121 |
+----------------------------------------------------------------------------+
------------------------------
Date: 27 Jul 87 14:28 PDT
From: Ghenis.pasa@Xerox.COM
Subject: PROPOSAL: We need "virtual sublists"
The recent meta-discussion on what to include in the Digest was rather
similar to the one about whether to include the AI Expert code listings.
At that time I made a proposal that may have drowned in the noise. I
still think it would solve the filtering problem so here it goes:
PROBLEM:
You can't tell what is inside the digest until you start reading it. The
title is non-descriptive. How does an AIList reader filter unwanted
topics?
If a reader has an unsophisticated mail reading channel, there is an
irritating time cost to opening an unwanted 20,000 character message.
This is even worse for folks who read their mail through a modem
connection.
Proposing the creation of a new list for each topic that generates a
large mail volume is not only unrealistic but also unnecessary.
SOLUTION:
The moderator is already thoughtful enough to segregate topics so that
each digest is fairly homogeneous. Now if only the "Subject:" line could
read
AIList V5 #183 - Symbol Grounding
instead of
AIList Digest V5 #183
then it would be easy to filter topics even with the crudest of mail
programs, and our personal archives would also be much more descriptive
at the table-of-contents level.
I believe that this scheme would address the objections of folks who
voted against continuing to distribute symbol grounding messages or
source code listings.
MODERATOR: Would this be a difficult change to implement?
FELLOW READERS: Is this proposal missing the point? Is there anything
else we could do to better prepare for the next large discussion? Should
we move this discussion to the META-META-DISCUSSIONS list? :-)
Pablo Ghenis
Xerox Artificial Intelligence Systems
Educational Services
[This has been suggested several times, by several people, so
I might as well give it a try. I am reminded, though, of a
parody of Reader's Digest that condensed an entire Hemmingway
novel to the word "Bang!". A good many digests will have to
be tagged as "Msc.", including this one.
I really don't see the advantage in the longer subject line,
but perhaps that is because my mailer clips the subject at about
40 characters. The cost of examining the full Topics section
is only about one page of data. (Are there really mailers out
there that let you read the subject line without the cost of
"pulling in" the entire digest?)
What is really needed here is an intelligent mail-reading system.
I'm sure that special digest-reading commands could -- but
probably won't -- be added to any of our mailers. Even better
would be an intelligent Information Lens system. Won't someone
take this on as an AI project? -- KIL]
------------------------------
Date: 27 Jul 87 09:45:19 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Natural Kinds (Re: AIList Digest V5 #186)
Your functional description of "chair" does capture more of "what's
essential to chairs" than the structural description could. Some
quibbles, however. First, it includes couches since it doesn't say
that it's for exactly one person. Second, it doesn't seem to include
"Balenz" chairs, those kind in which the person rests on his/her
shins, since the "support for one's back" is rather indirect -- what
they do is to make it easier to balance the spine by tilting the
pelvis forward. Third, some people might say that Balenz chairs
aren't chairs at all, but stools, because the back support is indirect
-- the point being that the functional description might have to take
into account who's saying what about chairs to whom. Probably, other
Ailist readers will come up with more borderline cases, which brings
me to the speculation that functional descriptions may end up with as
many exceptions as structural descriptions do.
------------------------------
Date: Mon, 27 Jul 1987 11:16 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: Natural Kinds (Re: AIList Digest V5 #186)
I agree:
1. Yes, I think we'd all agree that a chair is for 1 person to sit on.
2. The boundary is fuzzy, indeed, and some people might not
consider a Balenz chair to be a chair.
3. Yes, indeed, the "functional description" does indeed depend on
whose "intention" is ivolved, and upon who is saying what to whom.
My point is not that such terms can be defined in foolproof, clear-cut
ways. There are really two sorts of points.
1. You can get much further in making good definitions by squeezing
in from both structural and function directions - and surely others as well.
2. In Society of Mind, section 30.1 I discuss how meanings must depend on
speakers, etc.
As Ken Laws remarked, we should not be too hasty to thank philosophers
for concept of "natural kind". McCarthy make useful remarks about
penguins, which form a clear-cut cluster because of the speciation
mechanism of sexual reproduction. The class is un-fuzzy even though,
as McCarthy notes, penguins have properties that scientists have not
yet discovered.
But then, I think, McCarthy defeats this clarity by proceeding to
discuss how children learn about chairs - and tries to subsume this,
too, into natural kinds. He describes what seems clearly to be not
"natural" aspects of chairs, but the clustering and debugging
processes a child might use.
My conclusion - and, I'd bet, Ken Laws would agree - is that the
concept of "natural kind" has an illusory generality. It seems to me
that, rather than good philosophy, it is merely low-grade science
contaminated by naive, traditional common sense concepts. The
clusters that have good boundaries, in the world, usually have them
for good - but highly varied reasons. Animals form good clusters
because of Darwinian speciation of various sorts. Certain metals,
like Gold, have "natural" boundaries because of the Pauli exclusion
principle which causes things like periodic tables of elements.
Philosophers like to speak about gold - but their arguments won't work
so well for Steel, whose boundary is fuzzy because there are so many
ways to strengthen iron. All in all, the clusters we perceive that
have sharp boundaries are quite important, pragmatically, but exist
for such a disorderly congeries of reasons that I consider the
philosophical discussion of them to be virtually useless in this
sense: the class of clusters with "suitable sharp boundaries" to
desaerve the title "natural kinds" is itself too fuzzy a concept to
help us clarify the nature of how we think about things.
------------------------------
Date: Mon, 27 Jul 87 09:57:26 MDT
From: shebs@cs.utah.edu (Stanley Shebs)
Reply-to: cs.utah.edu!shebs@cs.utah.edu (Stanley Shebs)
Subject: Re: Natural Kinds (Re: AIList Digest V5 #186)
In article <MINSKY.12320404487.BABYL@MIT-OZ> MINSKY@OZ.AI.MIT.EDU writes:
>About natural kinds. In "The Society of Mind", pp123-129, I propose a
>way to deal with Wittgenstein's problem of defining terms like "game"-
>or "chair". The basic idea was to probe further into what
>Wittgenstein was trying to do when he talked about "family
>resemblances" and tried to describe a game in terms of properties, the
>way one might treat members of a human family: build, features, colour
>of eyes, gait, temperament, etc.
>[... details of Wittgenstein vs Minsky :-) ...]
>I would appreciate comments, because I think this may be an important
>theory, and no one seems to have noticed it. [...]
I recently finished reading "Society of Mind", and quite enjoyed it.
There are a lot of interesting ideas. There are also many that are
familiar to people in the field, but with new syntheses that make the
ideas much more plausible than in the past. I had been getting cynical
about AI, but after reading this, I wanted to go and hack out programs
to test the hypotheses about action, and memory, and language. But there's
a serious problem; how *can* these hypotheses be tested? The society of
mind follows human thinking so closely that any implementation is going
to be a model of human minds rather than minds in general, and will probably
be handicapped by being too small and simple to be recognizably human-like
in its behavior. Tracing a mind society's behavior will generate lots
of data but little insight. So my ardor has been replaced by odd moments
speculating on tricky but believable tests, and a greater appreciation for
people interested in a more formal approach to minds.
Getting down to specifics, the theory about recognition of objects by either
structure or functions was one of the parts I really liked. A robot should
be able to sit on a desk without getting neurotic, or to sit carefully on
a chair that's missing one leg...
stan shebs
------------------------------
End of AIList Digest
********************
∂30-Jul-87 0010 LAWS@Stripe.SRI.Com AIList V5 #191 - LISP Techniques
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 Jul 87 00:10:13 PDT
Date: Wed 29 Jul 1987 21:51-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #191 - LISP Techniques
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 30 Jul 1987 Volume 5 : Issue 191
Today's Topics:
Techniques - Graphics-AI References &
Garbage Collection Suppression
----------------------------------------------------------------------
Date: Tue, 28 Jul 87 13:56:14 pdt
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Re: Graphics-AI bibliography
>I am currently investigating what work has been done on connecting/integrating
>AI methods and computer graphics. I would be very grateful if anyone can
>send me any references, or bibliographies (or comments!) etc in this area.
> - Toby Howard -
Computer graphics: get the current edition of ACM Computer Graphics (the
Quarterly). It has the yearly bibliography in computer graphics (June 1987).
There is a biblio for June 1986 which over the year 1985. Recently, we
had a meeting where we had a speaker from SRI cover some of the common
ground (Sandy Pentland) because we perceived that the AI people were
reinventing what the graphics people invented 20 years ago.
--eugene miya
Bay Area ACM/SIGGRAPH
------------------------------
Date: Wed, 29 Jul 87 11:58 PDT
From: nesliwa%telemail@ames.arpa (NANCY E. SLIWA)
Subject: Garbage Collection Suppression (Response Summary)
My thanks to all the respondants to my question about garbage
collection suppression. As several people asked for the results, I'm
posting it for all:
Date: Friday, 17 July 1987 07:32-CDT
From: nancy at grasp.cis.upenn.edu (Nancy Orlando)
Are there any "accepted" methods of writing code that minimize a LISP's
tendancy to garbage-collect? I don't mean a switch to turn it off;
just a means of minimizing the need for it. I'm dealing particularly with
DEC VAX lisp. I have assumed that iteration as opposed to recursion was
one way; is this correct?
From: Chester@UDEL.EDU
Subject: Re: Garbage Collection Suppression
The direct way to avoid garbage collection in lisp is to define your own `cons
function that prefers to get cell pairs from an `available list', calling the
regular `cons' only when the `available list' is empty. A `reclaim' function
that puts cell pairs on the `available list' (using `rplacd') will be needed
also. See any book on data structures. The technique can be used for cell
pairs and gensym atoms, if needed, but in my experience, not with strings or
numbers. String manipulations can usually be avoided, but a program that
crunches a lot of numbers cannot avoid consuming memory and eventually
triggering garbage collection (at least in VAX lisp). I wish there were some
way for a user to reclaim numbers so that they could be reused as cell pairs
can. If so, I could write all my lisp programs so that they don't need to
garbage collect. It would also be nice to have a built-in `reclaim' function
that would work in conjunction with the built-in `cons'; it would be dangerous
for novices, but handy for the experienced.
By the way, recursion in itself doesn't cause garbage collection; VAX lisp is
smart enough to reclaim the memory used for the function stack automatically.
Daniel Chester
chester@dewey.udel.edu
Date: Mon, 20 Jul 87 01:36:44 PDT
From: woutput@ji.Berkeley.EDU (Andrew Purshottam)
Subject: Re: Garbage Collection Suppression
Forgive me if my response is too trivial, but you ommited
the most important technqiue for reducing gc use, limiting the use,
implict and explict, of cons. Particularly nasty is the use of
append or append1 (not sure what that is called in CL) to build up a list
by adding elements to its end. This method uses O(n↑2) cons cells,
where n is the length of list built. Standard solutions include the use
of "accumulators", arguments which hold a partial result which
is modified in inner recursions and finally returned as
value when the function returns; building the list backword
and maybe reversing it at end; nconc, which uses O(n↑2) time but
only O(n) space; or tconc structures, which keep a pointer to
the end of the list. (In prolog we have a cute method avail,
putting an uninstantiated element at the end of the list, effectively
a "hole" that can be filled by an element and another hole).
Not also that some popular functional programming techniques,
particularly those involving streams and higher order procedures
are quite greedy in cons cells, as they build intermediate lists,
most of whose elements are thrown away. The apply-append-mapcar
trick, the set functions like (filter 'pred 'list), union, and intersect
all do this if implemented in the obvious way, with the sets represented
and fully computed lists. The Black Book (Charniak/McDerrmot, AI Programming)
discusses more eff. ways to deal with this using generators, where
no more elements are computed than needed. (See also Abelson/Sussman
for a very readable (we inflict it on freshman!) discussion of delay
and force).
Again, excuse if this is too simple, no offense intended.
Andy
--
Cheers, Andy (...!ucbvax!woutput woutput@ji.berkeley.edu)
(cond ((lovep you (quote LISP)) (honk)) (t (return ())))
Date: Mon, 20 Jul 1987 05:32 CDT
From: AI.DUFFY@R20.UTEXAS.EDU
Subject: Garbage Collection Suppression
No. You make garbage when you create data structures. Recursion v.
iteration has nothing to do with it, unless VAXlisp is more
brain-damaged than I already know it to be.
Are there other techniques?
Use destructive list operations (e.g., NCONC instead of APPEND) when
you can. If you have any arrays, structures, etc., that you are using
temporarily, you can resource them (make a bunch of them and push them
onto a list, pop one off when you want to use it, and when you are
finished with it, nullify its slots and push it back onto the list).
Your best bet, of course, is to get more memory.
Date: 20 Jul 87 09:32:01 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Garbage Collection Suppression
Iteration vs. Recursion is orthogonal. By using recursion where you
could have used iteration, you may be using _stack_ space, but that's
trivially `garbage collected' every time you return from a function
(this is non-tail recursion I'm talking about). The only surefire way
to reduce garbage collection is to call CONS and and MAKE-ARRAY (and
things that call them) less often. There are a number of implications
of that for coding style (e.g. pass functions down instead of passing
consed structures up), but using iteration is not one of them.
Date: Mon, 20 Jul 1987 10:12 EDT
From: "Scott E. Fahlman" <Fahlman@C.CS.CMU.EDU>
Subject: Consing
Nancy,
In order to avoid GC's, you have to write your code in a way that avoids
consing up data structures, especially in inner loops. In the Vax
Common Lisp, I think that recursion is faster than the equivalent
iteration, but consing is not the reason; what you're seeing is the
difference between access to just a few variables (in registers or in
the cache) versus spreading out copies of those registers on the stack,
with all the associated memory references for pushing and popping.
How to avoid consing in any given Comon Lisp is a complex topic.
Perhaps the DEC people have some training materials on how to do this in
their Lisp. But there are a few things to watch for:
Make sure all your code is compiled. A lot of Lisps cons furiously in
the interpreter while consing very much less in compiled code.
If you are consing up vectors and strings in some inner loop solely for
communication with other routines, consider passing the info in a single
pre-allocated vector instead.
Some Lisps cons when passing &rest args and &keyword args. Check this.
Often a bit of Consing can make code clearer and easier to maintain.
Find who is doing the consing that is bothering you and squeeze that
part of the code for maximum efficiency; don't just squeeze everything,
because maintainability will be harmed.
-- Scott Fahlman
Date: Mon, 20 Jul 87 10:15:53 EDT
From: Mario O. Bourgoin <mob@MEDIA-LAB.MEDIA.MIT.EDU>
Subject: Re: Garbage Collection Suppression
Hello,
What you want to do is avoid storage allocation operations.
Most of the methods for doing this are implementation dependant. For
example, in Scheme iteration constructs expand to tail-recursive calls
so there's no point in trying to change function calls to do-loops.
Furthermore, good Lisp implementations optimize function calls since
they are the most used operation; they are usually cheaper than the
looping alternatives.
Lisp compilers can usually do excellent optimizations if you
use the implemetation's features. For example, ZetaLisp offers a LOOP
iteration macro which allows the programmer to communicate to the
compiler the necessary information for the latter to produce the most
efficient code possible.
What you can do reliably is to avoid using operations that
cons a lot such as `append' and use their structure modifying
alternatives such as `nconc'. You should be careful to write your
programs with the modifying operations from the beginning to avoid
encountering problems with them if you change over from the consing
operations.
Remember that operations such as the arithmetic functions must
allocate storage for their result. It might be worth your while to
code basic operations and inner loops in another language such as `C'
to avoid allocation.
--Mario O. Bourgoin
(This next was is response to a follow-up request of mine, asking if call-outs
to non-lisp external routines helped decrease garbage collection.)
Date: Thu, 23 Jul 87 9:11:18 EDT
From: Chester@UDEL.EDU
Subject: Re: garbagecollection
We have no experience with calling out to another language just to do
number crunching. My guess is that the overhead of switching languages
and of communicating between them and lisp would be too much, but that is
just a guess. If you find out differently, let me know.
Date: 22 Jul 87 14:28:51 GMT
From: "J. A. \"Biep\" Durieux" <mcvax!cs.vu.nl!biep@seismo.CSS.GOV>
Subject: Re: Garbage Collection Suppression
In article <8707202143.aa23792@Dewey.UDEL.EDU> Chester@UDEL.EDU writes:
>The direct way to avoid garbage collection in lisp is to define your own `con
>function that prefers to get cell pairs from an `available list' (...).
Also handy in many cases (small functions like append, alist-functions, subst)
is icons: (defun icons (a d cell)
(cond ((and (eq (car cell) a) (eq (cdr cell) d)) cell)
(t (cons a d))))
In this way whenever it turns out the new cells weren't really needed, the
old ones are used again (as in (append x nil)). Be aware, however, that your
copy-function may not work any more if it's defined as (subst nil nil x)!
--
Biep. (biep@cs.vu.nl via mcvax)
*****************************************************************************
I also noticed that the current (Aug.-Sept. 87) issue of LISP Pointers
has two good articles about garbage collection: "Overview of Garbage
Collection in Symbolic Computing," by Timothy J. McEntree (TI) and
"Address/Memory Management For A Gigantic LISP Environment or, GC
Considered Harmful," by Jon L. White (MIT). LISP Pointers subscriptions
are available from:
LISP Pointers
Mary S. Van Deusen, Editor
IBM Watson Research
PO Box 704
Yorktown Heights, NY 10598
------------------------------
End of AIList Digest
********************
∂30-Jul-87 0200 LAWS@Stripe.SRI.Com AIList Digest V5 #192
Received: from STRIPE.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 Jul 87 02:00:22 PDT
Date: Wed 29 Jul 1987 21:59-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #192
To: AIList@STRIPE.SRI.COM
AIList Digest Thursday, 30 Jul 1987 Volume 5 : Issue 192
Today's Topics:
Philosophy - Philosophy-Bashing & AI as a Science &
Natural Kinds & Iconic Representation
----------------------------------------------------------------------
Date: Mon, 27 Jul 87 15:40:12 pdt
From: ladkin@kestrel.ARPA (Peter Ladkin)
Subject: philosophy-bashing
i wish contributors to the ailist who indulge in philosophy could
refrain from including diffuse comments alluding to the lack of
worth of philosophy. philosophers do the same thing, so it's hard
to keep track of who's who.
peter ladkin
ladkin@kestrel.arpa
------------------------------
Date: 29 Jul 87 15:58:46 GMT
From: sbrunnoc@hawk.CS.ULowell.Edu (Sean Brunnock)
Reply-to: sbrunnoc@hawk.cs.ulowell.edu (S. Brunnock)
Subject: Re: Why AI is not a science
Gentlemen, please! (my apologies to any women reading this)
AI is a very young branch of science. Computer science as a whole
is only a little more than 40 years old. How can you compare AI with
mathematics or physics which are thousands of years old?
Aristotle made some of the first stabs at elemental chemistry and
gravitation. From our enlightened viewpoint, can we call him a scientist?
Give it time, its too early to tell.
S. Brunnock
------------------------------
Date: 29 July 1987, 14:55:35 EDT
From: Andrew Taylor <ATAYLOR@ibm.com>
Subject: in defence of penguins (natural kinds)
Penguins have been the topic of some discussion. I'd like to correct some
some misconceptions. Penguins are not one species, currently they
are classified into 18 species. Their inability to fly is not a
deficiency. Their wings are merely adapted to a more dense medium, water.
They are not the only flightless birds there are 40+ species
of flightless birds (0.5% of all bird species).
It is not certain penguins are birds. In the past it was believed
that they were independently descended from the reptiles. It is possible
fossils will be found which will cause this belief to rise again.
Penguins may form a clear cut group (order) to ornithologists but
people less expert could easily classify other birds of similar
appearance and habits (e.g auks) into the same group.
Unfortunately species are sometimes not clear cut either.
When two populations are separated, then it can be difficult to decide
whether they are 1 or 2 species. Biologists often merge or split
species in new classifications.
People living close to nature (e.g Amazon Indians) have "kinds"
which mostly correspond to species. Most of us are content with
kinds which lump together a number of species on the basis
of superficial similarities. These kinds often differ from
the classifications biologists make.
Andrew Taylor
------------------------------
Date: Wed, 29 Jul 87 08:43:05 -0200
From: Eyal mozes <eyal%wisdom.bitnet@jade.berkeley.edu>
Subject: Re: natural kinds
An important theory that has so far not been mentioned in the
discussion on "natural kinds" is the Objectivist theory of concepts.
In essence, this theory regards universal concepts, such as "chair" or
"bird", as the result of a process of "measurement-omission", which
mentally integrates objects by omitting the particular measurements of
their common characteristics. The theory takes into account the point
mentioned in Minsky's recent message about structure and function, and
completely solves Wittgenstein's problem.
The theory is presented in the book "Introduction to Objectivist
Epistemology" by Ayn Rand, and, more recently, in the paper "A theory
of abstraction" by David Kelley (Cognition and Brain Theory, vol. 7
no. 3&4, summer/fall 1984, pp. 329-357).
Eyal Mozes
BITNET: eyal@wisdom
CSNET and ARPA: eyal%wisdom.bitnet@wiscvm.wisc.edu
UUCP: ...!ihnp4!talcott!WISDOM!eyal
------------------------------
Date: Wed, 29 Jul 87 08:03:56 EDT
From: powell%mwcamis@mitre.arpa
Subject: Natural Kinds
Minsky's notion of natural types involving both structure and function
does seem plausible. One could think of each natural type as a
bipartite graph where one node class represents structural components
and where the other node type represents each function of the natural
type. Connections between the two node classes would represent
(in a crude way) the way in which portions of each class relate to
the nodes of the other class.
Even more specifically, the entire design foundations
as would be recorded in the data dependency net of an ATMS recording
the design process (function to structure) would capture still more about
the natural type. This seems
like a bizarely specific way to define a hazy notion like natural types,
but it does appear to follow naturally from Minsky's proposal.
------------------------------
Date: Wed 29 Jul 87 11:28:26-PDT
From: Ken Laws <Laws@Stripe.SRI.Com>
Subject: Structure, Function, and Intention
Minsky's initial message described function (of a chair) in terms
of intended use. I don't believe he elaborated, but it seems
obvious that it could be either the designer of the chair or the
user who provides the intention. (For instance, a chair designed
for one person does not become a couch just because two kids sit
on it at the same time.) Semantic classification thus requires
at least three viewpoints: structure, intended function, and
perceived or implemented function.
-- Ken
------------------------------
Date: Wed, 29 Jul 87 16:11:23 edt
From: amsler@flash.bellcore.com (Robert Amsler)
Subject: Re: Structural and Functional descriptions
Another division of information which I find significant is that of
visual vs. the combined structural and functional descriptions. While a
visual description might be termed `structural' I think there is a
significant difference. Visual information, i.e. information
obtained from looking at a visual still or moving image of an object,
is often not available in pre-recorded structural form. It `may' be
possible to describe visual information in symbolic text, but it
can prove very hard to extract it from existing descriptions because
there is so much visual information to represent and often the
description doesn't contain the key element needed to answer a
question.
I first encountered this when looking at the information dictionaries
present for a word such as `horse'. They give definitions of all the
parts of a horse, but you cannot assemble a horse from these part
definitions accurately enough to answer a simple question such as
whether the horse's head is higher than its tail? (Dictionaries
almost universally have an illustration for a horse, which suggests
they know something about how hard it is to describe one by
definitions only). Initially I saw this as demonstrating the
complimentarity of visual and definitional information, much in the
same manner that Minsky sees the complimentarity of the structural
and functional descriptions. But now, it looks to be a more basic
problem. Even if you could assemble a horse from the definition plus
the static visual knowledge (e.g. add coordinates and a wire frame model of
a horse to the description), I can't animate it well enough to
answer questions (Are all the feet ever off the ground simultaneously
while running?)
This probably suggests a simulation as the correct representation,
but often a simulation is really just a means of displaying the
visual representation of the object so you can perform the
observation needed on the simulated entity rather than on the real
entity. What this seems to imply is that ultimately the `description'
of an object should be a simulation accurate enough to permit direct
observation and generation of the functional and structural
information we know about the object?
------------------------------
End of AIList Digest
********************
∂04-Aug-87 1606 LAWS@SRI.Com AIList V5 #193 - Natural Kinds (Philosophy)
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 4 Aug 87 16:06:19 PDT
Date: Sun 2 Aug 1987 20:40-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@STRIPE.SRI.COM>
Reply-to: AIList@STRIPE.SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #193 - Natural Kinds (Philosophy)
To: AIList@STRIPE.SRI.COM
AIList Digest Monday, 3 Aug 1987 Volume 5 : Issue 193
Today's Topics:
Philosophy - Natural Kinds
----------------------------------------------------------------------
Date: 30 Jul 87 16:25:29 GMT
From: aweinste@bbn.com (Anders Weinstein)
Reply-to: aweinste@bbn.com (Anders Weinstein)
Subject: Re: Natural Kinds (Re: AIList Digest V5 #186)
In article <MINSKY.12321721233.BABYL@MIT-OZ> MINSKY@OZ.AI.MIT.EDU writes:
>
>My conclusion - and, I'd bet, Ken Laws would agree - is that the
>concept of "natural kind" has an illusory generality. It seems to me
>that, rather than good philosophy, it is merely low-grade science
>contaminated by naive, traditional common sense concepts.
I think there's some confusion about what natural kinds are in this
discussion. Most of the talk has focussed on the alleged sharpness of the
kind's boundaries. But I don't think this is what's at issue, at least in the
contemporary philosophical usage.
The point is that you can't do science without imposing some taxonomy on the
objects under study. "Natural kinds" are simply the kinds that figure in
scientific generalizations (aka Laws of Nature). Thus "bird" is perhaps a
natural kind, but "thing that is either furry or made of clay" is not.
Some people like to argue about whether these classification systems are "out
there" in Nature waiting to be discovered (the "realist" view) or are
invented by the mind and imposed on some undifferentiated reality (an
"idealist" or "constructivist" picture). Happily, we can ignore this debate.
What we can't ignore is the fact that a notion of natural kinds is
*essential* for induction, as demonstrated by Nelson Goodman's classic "grue
vs green" puzzle. Without some sense of what kinds are "natural", you're
liable to go off projecting "grue", or looking for laws governing "furry or
clay things". This would be the antithesis of intelligence.
Of course, coming up with suitable taxonomies is an empirical matter. I once
heard Kuhn emphasize that Aristotle's concept of "motion" included things
like the growth of trees. Progress in physics had to await a more useful
concept of motion.
But this shouldn't be taken to imply that natural kinds are only relevant to
sophisticated scientific theorizing -- the same principles apply to the
inductions that are part of common-sense understanding. And it seems that we
are blessed with pretty accurate innate intuitions about which kinds or
similarities are natural (eg. "green") and which are ludicrously artificial
("grue"). The philosophy of induction thus suggests that you can't make an
intelligent system without somehow building into it an equivalent sense of
the naturalness of kinds.
Anders Weinstein
BBN Labs
------------------------------
Date: Thu, 30 Jul 87 11:39:00 n
From: Paul Davis <DAVIS%EMBL.BITNET@wiscvm.wisc.edu>
Subject: Natural Kinds
As the list of different aspects important in the recognition
of a natural kind grows, I'd like to throw in a comment inspired by
the mention of Balans chairs, amongst other things.
My experience of Balans chairs, apart from extreme comfort, is
that peoples recognition of them tend to be via contextual means
rather than anything else - ie; "that thing in front of the desk must
be a chair" (implicitly - "chairs occur in front of desks and that
thing looks sufficiently chair-like, and insufficiently
anything-else-that-I've-ever-seen-like, to be an example of a
chair"). Interestingly though, people do not initially know how to
*use* the chair (unless they've used one before or seen it in use).
This suggests to me that contextual information is at least as
important as structural or functional types in identifying a `natural
kind'.
To support this a little further, I have my own experience of
living in a country where I have a very limited grasp of the language.
Although clearly language understanding could be argued to be a
different case to that of natural kinds, I take my ability to deduce
the 'kind' of a notice or message written in German from a very
limited vocabulary but a very large `database' (yuk) of contexts to
indicate, perhaps, the kind of thing thats going on. This ability
arises because I know from past experience what kinds of signs and
messages occur in what kind of contexts, and with a few known words, a
few vague resemblances between German and English, its pretty easy to
figure out a reasonable guess at the meaning.
Both of these examples seem to me to point towards a more
general recognition of the Dreyfus's theory of skill acquisition.
Herbert and Stuart Dreyfus argue that contrary to many (most ?)
current notions of skill acquisition, the move from novice (baby ?) to
expert (adult ?) proceeds by moving from abstract understanding to a
position reliant on having a large repetoire of specific experiences.
Why should the recognition of `natural kinds' differ from
this ? So far, most commentators have been focusing on an attempt to
arrive at an abstract definition of a natural kind. Why should this reflect
reality better than the alternative - that we recognise a natural
kind, or anything else for that matter, simply by having sufficient
past experience to do so. Of course, the definition-by-recognition of
a natural kind will actually be a consequence of the interaction of
past experiences and a pattern recognition ability, but I can see no
reason to believe that the classification of natural kinds is any
different to the potentially more general question of how do we
recognise similarity. Natural kinds differ only in that they represent
the ability to group a large number of experiences rather than just
two or three.
Why do I get the feeling that I've missed the point ?
Paul Davis
Biocomputing, EMBL, Postfach 10.2209, 6900 Heidelberg, West Germany
bitnet/earn: davis@embl.bitnet
arpa: davis%embl.bitnet@wiscvm.wisc.edu
uucp: ...!psuvax1!embl.bitnet!davis
------------------------------
Date: 30 Jul 87 18:30:32 GMT
From: aweinste@bbn.com (Anders Weinstein)
Reply-to: aweinste@bbn.com (Anders Weinstein)
Subject: Re: Natural Kinds (The Putnam/Kripke analysis)
In an earlier posting, McCarthy referred to Putnam's work on natural kinds. I
think what is important about this work is not the mere notion of a "natural
kind," which is ancient, but rather the new *analysis* of the semantics of
natural kind terms made by Putnam and Kripke. And, as McCarthy suggested,
this analysis may well be relevant to terms other than scientific kind
predicates.
In brief, the important point is that the marks by which we identify members
of a kind are *not* in general definitive. Gold may be identified as a yellow
metal, but even if we suppose that this description *uniquely* refers to
gold, still "gold" is not synonymous with "yellow metal". Put another way, it
is not a necessary truth that gold is yellow or that gold is a metal: it
could conceivably turn out that we were mistaken on either of these points.
By extending such examples, Putnam and Kripke make the claim is that there is
initially *no* criterial definition of gold; neither a simple definition nor
some weighted disjunctive cluster of properties will do. On the causal
history view of reference, a statement like "gold is F" is not semantically
equivalent to any assertion about "a yellow metal". It is rather a little bit
like waving a rope in the air and saying "the stuff on the end of this rope
is F", where the "rope" is a chain of reference-preserving causal links
stretching back in time to the introduction of the term.
A couple of other points in Putnam's analysis are also relevant. First, he
claims that although definitive criteria for natural kind terms are not
initially known, they may be uncovered in time by scientific investigation.
Thus, today we believe we have found the "essence" of gold, namely being an
element with a certain atomic number. This is information the Greeks didn't
have; nevertheless, we generally regard our word "gold" as having the same
meaning as the ancients' word for it.
But even after a criterial definition is discovered, still there is a
"division of linguistic labor" -- the precise definition may only be known by
experts. Lay members of the language community are judged to be competent
users of the concept as long as they possess certain (non-definitive)
stereotypical information about the kind in question. Knowing that an elm is
some kind of deciduous tree is enough to be credited with understanding
"elm", even if you can't distinguish elms from beeches or any other trees.
Well, what is the significance of all this for cognitive science? At first,
it seems to demonstrate that meanings are partly extra-psychological, because
of the role of the causal history in fixing the reference of a term. As
Putnam puts it, "meanings just ain't in the head." And this might suggest
that apart from the demand for stereotypes, Putnam's points are just
irrelevant to the psychology of concept understanding, insofar as psychology
is limited to dealing with what *is* in the head.
Nevertheless, the theory does have *some* implications for psychological
theories. Broadly speaking, it implies that a cognitive system must be
prepared to deal appropriately with the phenomena that Putnam describes. That
is, it must "understand" that the marks by which it identifies things need
not constitute a *definition*, so it can make sense of the possibility of,
say, a blue lemon. This suggests that there is more to knowing the meaning
of a term than merely having an inner criterion of application -- one must
also be able to make sense of situations where the criterion fails.
Also, the system must understand that relevant experts may know more about
the term than it does, and that a truly essential criterion may yet be
discovered. In a good paper on this subject by Georges Rey (I will dig up the
citation when I get a chance), Rey puts the point in AI-style language: the
representation of a concept must have a "slot" for the definitive criterion
which may initially be unfilled. Although this formulation seems to me to
involve a vast (but typical) over-simplification of understanding, it does
indicate how the Putnam analysis is relevant to cognitive theories.
Anders Weinstein
BBN Labs
------------------------------
Date: 30 Jul 87 18:49:24 GMT
From: aweinste@bbn.com (Anders Weinstein)
Reply-to: aweinste@bbn.com (Anders Weinstein)
Subject: Natural Kinds (The Putnam/Kripke analysis)
BTW, I just reread McCarthy's original posting on kinds and it seems that the
consequences of the Putnam analysis that I gave are substantially the same as
the points McCarthy was making. However, subsequent respondants seem to have
concentrated exclusively on the supposed sharpness of kind boundaries.
Although this is alluded to in McCarthy's message, I don't think it's germane
to the main points about concept understanding and definitions.
Anders Weinstein
------------------------------
Date: Thu, 30 Jul 1987 22:43 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList Digest V5 #190 - Msc.
Stan Shebs asks "how *can* these hypotheses be tested?" and suggests
that many of the ideas in Society of Mind follow human thinking rather
than minds in general. Yes, I focussed on trying to make a large
scale theory of human psychology. As for testing it, "implementation"
in a computer model is one possibility, but for the near future at
least, as Stan says, "that would probably be handicapped by being too
small and simple to be recognizably human-like in its behavior."
My answer is simple and direct: we must work toward building
instruments to help us see what is happening in the brain! In a few
decades I hope we shall see, for example, SQUID quantum-based magnetic
scanners that can map current flow, at least in the cerebral cortex,
to a resolution of better than a millimeter. That will tell us a
great deal about activities during thinking. Ultimately, we need
probes that smap down to better than that, at least in a significant
region. My point is that we ought not assume that we shall always be
limited to the crude psychological-response methods presently
available, or low resolution brain-wave or PETT-scan instruments.
------------------------------
Date: 31 Jul 87 20:48:51 GMT
From: aweinste@bbn.com (Anders Weinstein)
Reply-to: aweinste@bbn.com (Anders Weinstein)
Subject: Reference on concepts & natural kinds
For those interested in the implications of the Putnam/Kripke philosophy of
natural kinds for the psychology of concepts, I recommend the article I
alluded to in a previous message, Georges Rey's "Concepts and Stereotypes",
Cognition 15:1-3 (1983).
This piece is a philosophically informed critique of Smith & Medin's book
"Categories and Concepts" (1981). Medin & Smith offer a reply in Cognition
17:3 (1984), and Rey answers their reply in Cognition 19:3 (1985).
Naturally the bibliographies of these articles point to many other relevant
papers; I won't list them here.
Anders Weinstein
BBN Laboratories
------------------------------
End of AIList Digest
********************
∂05-Aug-87 0031 LAWS@SRI.Com AIList V5 #194 - Msc., Image Tracking, Seminars
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 5 Aug 87 00:31:12 PDT
Date: Tue 4 Aug 1987 22:17-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #194 - Msc., Image Tracking, Seminars
To: AIList@SRI.COM
AIList Digest Wednesday, 5 Aug 1987 Volume 5 : Issue 194
Today's Topics:
Administrivia - New Host Computer,
Queries - Request for Bibliographic Data &
Common Lisp OPS5 & Kyoto Common Lisp &
Image Feature Tracking,
AI Tools - NLP Front-Ends to INGRES,
Journal - Journal of Automated Reasoning,
Seminars - Comparative Analysis (SRI) &
Uncertainties in Robot Planning (SU),
Conference - Logic in Computer Science
----------------------------------------------------------------------
Date: Tue 4 Aug 87 21:27:51-PDT
From: Ken Laws <Laws@SRI.Com>
Subject: New Host Computer
SRI has moved AIList from STRIPE.SRI.COM to a new computer,
now known as SRI.COM. The old address will continue to work,
but you may use the shorter form if you prefer.
It took me a couple of days to get the hang of the new system,
but the mailer seems to be working for me again. Let me know
if any new problems show up at your end.
-- Ken
------------------------------
Date: 30 Jul 87 13:39:42 GMT
From: mcvax!dnlunx!lippolt@seismo.css.gov (Ben Lippolt)
Subject: Request for bibliographic data
Does anyone know where I could get files with bibliographic data
(in "refer" format) of the following proceedings:
IJCAI '79 '81 '83 '85 (and '87)
AAAI '80 '82 '83 '84 '86 and '87
Just the titles, authors and pagenumbers would be enough (although
keywords and abstracts would also be nice).
----
Ben Lippolt, tel: +31 70 435439
PTT - Dr. Neher Labs, telex: 31236 dnl nl
P.O. Box 421, telefax: +31 70 436477
2260 AK Leidschendam, UUCP: ..!mcvax!dnlunx!lippolt
Netherlands.
------------------------------
Date: Thu 30 Jul 87 08:32:07-EDT
From: John C. Akbari <AKBARI@CS.COLUMBIA.EDU>
Subject: request for cl ops5
anyone know of, or willing to give out, a reasonably good (fast) common
lisp interpreter [for OPS5]? an efficient version for symbolics (release 7.1)
would be ideal.
ad...THANKS...vance!
-*- Mode: Text -*-
John C. Akbari
380 Riverside Drive, No. 7D
New York, New York 10025
Tele. 212.662.2476
ARPANET & Internet akbari@CS.COLUMBIA.EDU
BITnet akbari%CS.COLUMBIA.EDU@WISCVM.WISC.EDU
UUCP columbia!cs.columbia.edu!akbari
------------------------------
Date: 3 Aug 87 14:52:51 GMT
From: astroatc!murphy@rsch.wisc.edu (Kathy Murphy)
Subject: Kyoto Common Lisp
We are in the process of selecting a Lisp package to port to a new
computer system (target market is NOT the AI community but we would
like to have a Lisp compiler and interpreter available on the
system). At the moment our choice is limited to either Kyoto
Common Lisp or the pd version of FRANZ LISP. KCL appears to be
much simpler to port and maintain but we have no idea how potential
users view KCL vs pd FRANZ. I would appreciate comments on the
following:
General experience with KCL.
KCL vs pd FRANZ LISP.
The importance of Lisp compiler speed - KCL's compiler is very slow.
Please mail replies directly to me. If there is enough interest I
can summarize results. Thank you.
--
Kathleen Murphy ...!uwvax!astroatc!murphy
Astronautics Technology Center
5800 Cottage Grove Rd. (608) 221-9001, x137
Madison, WI 53716
------------------------------
Date: 1 Aug 87 19:18:48 GMT
From: jbn@glacier.stanford.edu (John B. Nagle)
Subject: Low-level feature extraction and interframe matching
software wanted
Does software exist for following moving objects from frame to frame
in video images? I'm looking for something that works by finding low-level
features such as edges and corners and matches them from one frame to the
next. I'm aware of "optical flow" calculation, but the usual numeric
method for doing this is differentiation-oriented and too noise-sensitive
to be useful on real-world images, I am told by someone who has tried it.
So I'd like something that finds many low-level features and tries to
match them up.
The intended application is a vision system for a robot vehicle. But it
is possible that techniques used for colorizing B/W films would be useful
for this purpose. So I'd like to hear from people who know how colorizing
is done.
Software, algorithms, hardware, or indications of research activity
would be useful.
John Nagle
Center for Design Research, Stanford
------------------------------
Date: Tue 4 Aug 87 22:00:54-PDT
From: Ken Laws <Laws@SRI.Com>
Subject: Feature Tracking
John Nagle asked about image processing systems for tracking
scene features. Such systems do exist, but are often tied to
specific applications. A system for tracking missiles or stars
against a simple background will be quite different from one
for tracking vehicles in a street scene. Robotic applications
can be anywhere in between, depending on the robot's environment
and function. SRI currently has a robot vehicle that can navigate
hallways by detecting the door frames and other simple linear
features. We also have more elaborate systems for doing edge
matching or correlation matching in stereo pairs. I'm working
combined segmentation/classification/tracking. Others here are
doing matching in range imagery, including model-based matching
of the type useful in industrial inspection and bin picking.
Similar work has been done at Stanford, where Tom Binford would
be a good contact, and at CMU and most vision labs. The work
of Hans-Hellmut Nagel and of Moravec come to mind for the tracking
of low-level features, but there are many relevant papers in any
conference on computer vision or robotics.
-- Ken
------------------------------
Date: 31 Jul 87 07:06:54 GMT
From: ihnp4!lll-lcc!esl.ESL.COM!ssh@ucbvax.Berkeley.EDU (Sam)
Reply-to: ssh@esl.UUCP (Sam)
Subject: Re: NLP Front-Ends to INGRES
->vor!cris@esosun.UUCP (Cris Kobryn) sez ->
->I am interested in developing an NLP front-end to INGRES. Lest I
->reinvent: Is there any "stock" software which already does this?
->(INTELLECT does not *currently* accommodate INGRES; I've heard "DataTalker"
->mentioned as a possibility, but have no details--capabilities, company name,
->phone#, etc.)
->-- Cris Kobryn
Datatalker is from Natural Language, Incorporated. Their phone number
is 415-841-3500, and I believe their address is 1759 Fifth Street,
Berkeley. Founders are Jerrold Ginsparg and John Manferdelli.
Product is good, and accommodates Ingres. Tell 'em Sam sent you -- Sam
------------------------------
Date: Thu, 30 Jul 87 22:07:29 cdt
From: stevens@anl-mcs.ARPA (Rick L. Stevens)
Subject: Journal of Automated Reasoning
Because of the rapidly growing interest in the interconnected
fields of automated reasoning, automated theorem proving, logic
programming, and artificial intelligence, the following information
might be of particular interest.
The Journal of Automated Reasoning, which is very inexpensive
compared to most computer science journals, now includes in each issue
two interesting columns: The Problem Corner, which presents test
problems from the world of puzzles, from mathematics, and from various
applications; and Basic Research Problems, which presents open problems
for research in automated reasoning.
The journal is published quarterly, each issue containing
approximately 110 pages. Beginning next year, each issue will contain
approximately 20% more material. Subscription costs are lower for
individuals that are members of the Association of Automated Reasoning.
The Journal of Automated Reasoning published its first issue in
February, 1985. It is an interdisciplinary journal that maintains a
balance between theory and application. The spectrum of material
ranges from the presentation of a new inference rule with proofs of its
logical properties to a detailed description of a computer program
designed to solve some problem from industry. The papers published in
this journal are from, among others, the fields of automated theorem
proving, logic programming, expert systems, program synthesis and
validation, artificial intelligence, computational logic, robotics, and
various industrial applications. The papers share the common feature
of focusing on some aspect of automated reasoning.
The journal provides a forum and a means for exchanging
information for those interested in theory, in implementation, and
in specific industrial or commercial applications.
For subscription information write to
Kluwer Academic
PO Box 358, Accord Station
Hingham, MA 02018-0358
For outside the U.S. and Canada:
Kluwer Academic Publishers Distribution Center PO Box 322 3300 AH
Dordrecht The Netherlands
$97 for institutions, $39 for private non-members of AAR,
$29.50 for members of AAR
AAR, Association for Automated Reasoning
The Association for Automated Reasoning is an organization for
disseminating and exchanging information. It is international in form,
and publishes a newsletter acyclically to announce workshops, discuss
software advances, present problem sets, etc.
To Join send a $5 check to Larry Henschen 780 S. Warrington
Road Des Plaines, IL 60016
------------------------------
Date: Mon, 3 Aug 87 15:42:27 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Comparative Analysis (SRI)
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
Note: Change in day of week and location.
COMPARATIVE ANALYSIS
Dan Weld (WELD@XEROX.ARPA)
MIT and Xerox PARC
11:00 AM, WEDNESDAY, August 5
SRI International, Building E, Room EK242
Comparative analysis is the problem of predicting how a system will
react to perturbations in its parameters, and why. For example,
comparative analysis could be asked to explain why the period of an
oscillating spring/block system would increase if the mass of the
block were larger. This talk formalizes the problem of comparative
analysis and presents a technique, differential qualitative (DQ)
analysis, which solves the task.
DQ analysis uses inference rules to deduce qualitative information
about the relative change of system parameters. Multiple perspectives
are used to represent relative change values over intervals of time.
Differential analysis has been implemented, tested on a dozen
examples, and proven sound. Unfortunately, the technique is
incomplete; it always terminates, but does not always return an
answer.
------------------------------
Date: Thu, 30 Jul 87 10:39:47 PDT
From: Jutta McCormick <jutta@whitney.stanford.edu>
Subject: Seminar - Uncertainties in Robot Planning (SU)
Thursday, August 6, 2:30 p.m.
Robotics Lab Conference Room, Cedar Hall, A6.
DEALING WITH UNCERTAINTIES IN ROBOT PLANNING
USING PROGRAM PROVING TECHNIQUES
Dr. Jocelyne Pertin-Troccaz
LIFIA Laboratory - INPG
46, Avenue Felix Viallet
38031. Grenoble Cedex - France
(uucp: lifia!jocelyne@seismo.css.gov)
Abstract: A global approach for dealing with uncertainties using
program proving in Robotics is presented. We consider a manipulation
program automatically generated by a planner according to spatial and
geometric criteria and ignoring uncertainties. Such a program is
correct only if, at each step, uncertainties are smaller than the
tolerances imposed by the assembly task. We propose an approach which
consists in verifying the correctness of the program with respect to
uncertainties in position and possibly modifying it by adding
operations in order to reduce uncertainties. These two steps based on
a forward and a backward propagation borrowed from formal program
proving techniques are described in a general framework suitable for
robotics environments. Forward propagation consists in computing
successive states of the robot world from the initial state and in
checking for the satisfaction of constraints. If a constraint is not
satisfied, backward propagation infers new constraints on previous
states. These new constraints are used for patching the program. The
approach is described in technical details in the case of a simple
manipulation language and of a relational model of the world including
a representation of uncertainties.
Thanks.
-Jutta
------------------------------
Date: Fri, 31 Jul 87 11:58:02 +0300
From: Moshe Vardi <MAVARDI%WEIZMANN.BITNET@wiscvm.wisc.edu>
Subject: Conference - Logic in Computer Science
CALL FOR PAPERS
THIRD ANNUAL SYMPOSIUM ON
LOGIC IN COMPUTER SCIENCE
5-8 July 1988
University of Edinburgh, Edinburgh, Scotland
Concepts and methods from Logic are influential throughout Computer
Science. The Annual IEEE Symposium on Logic in Computer Science (LICS)
aims to attract broad participation of Computer Scientists, whose design
or research activities involve Logic, and Logicians interested in Computer
Science. Suggested (but not exclusive) topics of interest include:
abstract data types, computer theorem proving, concurrency, data base
theory, knowledge representation, finite model theory, lambda and
combinatory calculi, logic programming, modal and temporal logics,
program logic and semantics, software specification, types and categories,
constructive mathematics, verification.
PROGRAM COMMITTEE: M. Dezani, Y. Gurevich (chair), J. Halpern, C.A.R.
Hoare, G. Huet, P. Kanellakis, J.-L.Lassez, J. Mitchell, R. Platek,
G. Plotkin, S. Rosenschein, P. Sistla, J. Tiuryn, M. Wand
PAPER SUBMISSION: Send 14 copies of an extended abstract to the
program chairman:
Yuri Gurevich - LICS (313) 971-2652
Electrical Engineering and Yuri_Gurevich@um.cc.umich.edu
Computer Science Department
University of Michigan
Ann Arbor, Michigan 48109-2122
The package must be airmail postmarked by 27 NOVEMBER 1987 or received by
4 DECEMBER 1987. The abstract should be clearly written and provide
sufficient detail to allow the program committee to assess the merits of
the paper. References and comparisons with related work should be
included where appropriate. The entire extended abstract should not
exceed 10 double-spaced pages in 10 or 12-point font. Late abstracts or
those departing significantly from these guidelines run a high risk of
not being considered. If a copier is not available to the author, a
single copy of the abstract will do.
The authors will be notified of acceptance or rejection by 27 JANUARY
1988. Accepted papers, typed on special forms for inclusion in the
symposium proceedings, will be due 14 MARCH 1988.
The symposium is sponsored by the IEEE Computer Society, Technical
Committee on Mathematical Foundations of Computing , and the University
of Edinburgh, in cooperation with ACM SIGACT, ASL, and EATCS.
ORGANIZING COMMITTEE: J. Barwise, W. Bledsoe, A. Chandra (chair),
E. Dijkstra, E. Engeler, J. Goguen, D. Gries, D. Kozen, Z. Manna,
A. Meyer, R. Parikh, G. Plotkin, D. Scott
GENERAL CHAIRMAN: LOCAL ARRANGEMENTS:
Ashok K. Chandra George Cleland
IBM T. J. Watson Research Center Department of Computer Science
P.O. Box 218 The King's Buildings
Yorktown Heights, NY 10598 University of Edinburgh
(914) 945-1752 Edinburgh EH9 3JZ, SCOTLAND
ashok@ibm.com 011 44 31 667 1081 ext. 2775
glc%lfcs.edinburgh.ac.uk@ucl-cs.arpa
------------------------------
End of AIList Digest
********************
∂10-Aug-87 0205 LAWS@KL.SRI.Com AIList V5 #195 - Macsyma, FBRL, Philosophy
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Aug 87 02:04:58 PDT
Date: Sun 9 Aug 1987 22:34-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #195 - Macsyma, FBRL, Philosophy
To: AIList@SRI.COM
AIList Digest Monday, 10 Aug 1987 Volume 5 : Issue 195
Today's Topics:
Queries - Reviews of Dreyfus and Dreyfus? & Natural Language Inc. &
Multiple Copies of a Clause & Macsyma Sources,
AI Tools - Macsyma Sources & FBRL in Prolog,
Philosophy - Natural Kinds & AI and Science
----------------------------------------------------------------------
Date: 5 Aug 87 09:20 EDT
From: WAnderson.wbst@Xerox.COM
Subject: Reviews of Dreyfus & Dreyfus?
I am looking for reviews of the Dreyfus & Dreyfus book "Mind Over
Machines." Any and all references appreciated. Thanks,
Bill Anderson
<WAnderson.wbst@Xerox.COM>
[There was, of course, the preview by the brothers Dreyfus themselves
in the January 1986 Technology Review; that has been discussed at
length in AIList. Another review by Theodore Roszak appeared in
the April 3, 1986, New Scientist, pp. 46-47. Roszak doesn't add much
personal perspective, but views the book favorably: "AI's record of
barefaced public deception is unparalleled in the annals of academic
study." -- KIL]
------------------------------
Date: Wed, 5 Aug 87 09:49:05 EDT
From: Bruce Nevin <bnevin@cch.bbn.com>
Subject: Nat Lg Inc
A colleague asks me by Email about an outfit called Natural Language Inc.
He hears they claim to process `virtually unrestricted English text'
to create a relational database for query systems. He says they are
located in Berkeley. Anybody know more?
------------------------------
Date: Fri, 7 Aug 87 09:54:13 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: multiple copies of a clause in the DB
I'm studying various ways to extend Prolog's simple model of the
database (e.g. a flat, global collections of clauses) to a richer
hierarchical one with inheritance. I am trying to decide whether to
allow multiple instances of a clause in a resulting database view.
Most Prolog implementations, at least those descendant from DEC-10
Prolog, do allow the database to contain two identical clauses. Most
of the non-Prolog logic programming languages that I am familiar with
do not. I am interested in discovering what use, if any, people have
made of the ability to assert multiple copies of a clause into the
database.
I, for one, have never found a use for this in practice. In fact, it
has only effected my life by being a source of bugs. It is easy
enough to accidentally get multiple copies of a clause in the database
by consulting a file instead of reconsulting it or by defining the
same predicate in two different files. This can easily mess up your
program unless you use a rather pure logic programming style which
doen't depend on the order in which the clauses are stored in the
database.
Has anyone out there found a good use for this Prolog "feature"?
Tim
------------------------------
Date: 4 Aug 87 01:44:25 GMT
From: amdahl!meccts!cimcor!mike@ames.arpa (Michael Grenier)
Subject: Macsyma Sources
I'm looking for any PD or commercial sources or binaries of Macsyma
that will run on this Microport Unix System on the 286. Any ideas?
-Mike
ihnp4!meccts!cimcor!mike
------------------------------
Date: 5 Aug 87 17:55:52 GMT
From: jbn@glacier.stanford.edu (John B. Nagle)
Subject: Re: Macsyma Sources
A competing package is MuMath, from
Soft Warehouse
3615 Harding Av
Honolulu Hawaii 96816
808-734-5801
This is a symbolic math package written in a quaint but charming dialect
of LISP, for which an interpreter is provided. There are versions for the
Apple II and IBM PC, and recently a modern version for the PC has been
released. I've used the older version on some messy vector calculus problems
in my solid modelling work, and found it quite useful in dealing with the
grunt work of algebra and calculus. The heuristics aren't very powerful,
but the algorithms for the standard solution methods all seem to work.
Microsoft resells this package, when they remember it is in their product
line, but the developers are in Hawaii and one may as well deal directly
with them. Sometimes one of the developers answers the phone.
John Nagle
------------------------------
Date: Sat, 8 Aug 87 23:21:33 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: FBRL in Prolog
Date: Wed, 5 Aug 87 12:18 EDT
From: The Mad Debugger <emerson@uvm-gen.UUCP>
Subject: FBRL in Prolog
Does anyone know of any FBRL's written in Prolog or that support logical
inference? I know HSRL (from Carnegie-Mellon) and KRYPTON (from
XEROX PARC) have a logical basis to them, but both are written in LISP.
I am currently writing a FBRL interpreter embedded in C-Prolog, and would
like to ''compare notes'' with other such systems, if they're out there.
I would also appreciate any thoughts on the implementation of frame theory
in Prolog.
Thanks in advance,
Tom E.
You may want to start by looking at Pat Hay's paper "The Logic of
Frames" from the mid to late seventies. He gives a logical account
for the semantics underlying the basic ideas in FBRL's. The paper is
reprinted in Brachman and Levesque's book "Readings in Knowledge
Representation" published by Morgan Kaufmann (1985).
I can point you toward three things involving FBRLs in Prolog that you
may want to look at:
[1] WIth a group from RCA, I built a frame-based representation
language in prolog called PINE. We used it to build an expert system
for diagnosing faults in ATE equipment. It is described in:
FOREST - An Expert System for Automatic Test Equipment; Tim Finin, Pamela
Kleinosky and John McAdams; Proceedings of the First Conference on
Artificial Intelligence Applications; (IEEE), Denver, Colorado, 1984.
A somewhat longer version is available as
technical report MS-CIS-84-09, Dept. of Computer and Information Science,
University of Pennsylvania, Philadelphia PA 19104
[2] Arity Corp offers an expert systems building toolkit (written by
David Drager) which is based on a FBRL. It's written in Arity Prolog,
of course. It is really quite powerful. I'd characterize it as a
cross between EMYCIN and KEE.
[3] The AI research group at UNISYS's Paoli Research Lab has been
using a FBRL implemented in Prolog to build many of their expert
systems for quite some time. There system is called KNET and is
similar to KL-ONE. An early reference is:
KNET - A logic Based Associative Network Framework for Expert
Systems"; Freeman, M., L. Hirschman and D. McKay; SDC, A Burroughs
Company; technical memo LBS 12; Sept. 1983.
I believe that there are several descriptions of it in the open
literature, but I'm not sure where they can be found.
Tim
------------------------------
Date: 30 Jul 87 00:34:27 GMT
From: uunet!mnetor!utzoo!dciem!nrcaer!cognos!roberts@seismo.css.gov
(Robert Stanley)
Subject: Re: natural kinds
In article <1526@botter.cs.vu.nl> hansw@cs.vu.nl (Hans Weigand) writes:
> (3) anthropic/functional kinds, existing by virtue of readiness_to_hand
> Examples: chair, cup, house, knife, game
>.... Thus we may recognize an Eskimo iglo, and an African pile-dwelling both
>as "houses". I think it is not so much the form (iconicity) that matters,
>but rather that we feel that, when we would live in Greenland
>(resp. the jungle), we would naturally appreciate or use these things
>as houses too (to protect us against cold, dangers)....
This raises some very interesting points, most particularly the fact that
anthropic kinds cannot generally have simple definitions. A very young child
gets away with calling a crude drawing or sand castle a 'house', but an
architect or construction engineer sees a house in much more specific terms.
In fact, we are entering the realms of the working vocabulary, and what is the
lowest common denominator which allows for completely successful transfer
between two disparate working sets.
Perhaps a strong example will serve. Kenya became an independent nation in
1964, and was faced with the problem of codifying laws, and deciding on
official languages. The two numerically superior tribal groupings were the Luo
and the Kikuyu, each with their own language, but colonial administration had
been exclusively English (at least in writing), and the standard interlingua of
the whole East African coast was Swahili (an Arabic-based patois). To further
complicate the issue, the very powerful, nomadic tribe of the Masai (with their
own language) had do be taken into account.
English and Swahili both were adopted as official languages, and a determined
effort made to create a formal body of law in both. In the Swahili version is
a formal definition of house which runs to some 96 pages of text! Why?
Because the term house has a whole slew of legal meanings in English common
law, on which Kenya's laws are based, which are totally alien to many of the
Kenyan tribes, especially the nomadic Masai. Therefore, each and every such
legal referent has to be precisely defined.
I leave as an exercise to the reader.......
I am not sure that house or any other cultural artifact can be called a natural
object unless its cultural matrix is expressly defined as part of the object's
name. Or that all objects in a given grouping are stated to exist within an
explicitly defined cultural context. I am absolutely sure that when I say
house and an Eskimo says igloo we are not talking about the same thing at all.
In fact the only common denominator appears to be shelter from the elements in
the winter months, albeit those are different for the two of us.
--
Robert Stanley Compuserve: 76174,3024 Cognos Incorporated
uucp: decvax!utzoo!dciem!nrcaer!cognos!roberts 3755 Riverside Drive
or ...nrcaer!uottawa!robs Ottawa, Ontario
Voice: (613) 738-1440 - Tuesdays only (don't ask) CANADA K1G 3N3
------------------------------
Date: 3 Aug 87 20:29:44 GMT
From: smadar@jarre.rutgers.edu (Cabelli)
Subject: Structure, Function and Intention in Natural Kinds
Ken Laws writes:
>Semantic classification thus requires at least three viewpoints:
>structure, intended function, and perceived or implemented function.
There has been alot of research recently in machine learning on
formulating concepts with these viewpoints in mind. I am amazed at
the omittion of any relevant AI work in this discussion on natural
kinds! For example, no mention was made of Winston's work on learning
structural descriptions from functional definitions (AAAI-83), (I was
surprised Minsky omitted that work).
My work on "Formulating Concepts According to Purpose" (AAAI-87)
presents a prototype system which formulates definitions of a "cup" based
on the purpose for which an agent intends to use it (one specialized
notion of intention). If the agent intends to use a cup to drink hot
liquids from, one definition is automatically generated. If on the
other hand, the cup has an ornamental purpose, a different definition
can be formed.
The key idea of the technique is to simulate the plan of actions the
agent will go through in drinking hot liquids from a cup, (say POUR,
GRASP, PICKUP, DRINK). Then, computing the (weakest) preconditions of
this plan derives a functional description (must contain hot liquids,
must be graspable by agent with hot liquid, must be liftable, and so
on). A technique like Winston's is then used to compute the
structural description from the functional one.
Smadar Kedar-Cabelli
Rutgers University
------------------------------
Date: 02 Aug 87 2159 PDT
From: John McCarthy <JMC@SAIL.STANFORD.EDU>
Subject: AI and science
Like mathematics, philosophy and engineering, AI differs
from the (other) sciences. Whether it fits someone's definition
of a science or not, it has need of scientific methods including
controlled experimentation.
First of all, it seems to me that AI is properly part of
computer science. It concerns procedures for achieving goals
under certain conditions of information and possibility for action.
We can even consider it analogous to linear programming. Indeed if
achieving one's goals always consisted finding the values of
a collection of real variables that would minimize a linear
function of these variables subject to a collection of linear
inequalities, then AI would coincide with linear programming.
However, the relation between goals, available actions,
the information initially available and that can later be acquired
is sometimes more complex than in any of the branches of computer
sciences the main character of whose scientific treatment consists
of mathematical theorems. We don't have a mathematical formalization
of the general problem faced in AI let alone general mathematical
methods for their solution. Indeed what we know of human intelligence
doesn't suggest that a conventional mathematical formalization of
the problems intelligence is used to solve even exists. For this
reason AI is to a substantial degree an experimental science.
The fact that a general mathematical formalization of the problems
intelligence solves is unlikely doesn't make mathematics useless in AI.
Many aspects of intelligence are formalizable, and languages of
mathematical logic are useful for expressing facts about the common
sense world, and logical reasoning, especially as extended by non-monotonic
reasoning is useful for drawing conclusions.
In my view a large part of AI research should consist of the
identification and study of intellectual mechanisms, e.g. pattern
matching and learning. The problems whose computer solution exhibits
these mechanisms should be chosen for reasons of scientific perspicuousness
analogously to the fact that genetics uses fruit flies and bacteria.
A. S. Kronrod once said that chess is the {\it Drosophila} of artificial
intelligence. He might have been right, but the organizations that
support research have taken the view that problems should be chosen
for their practical importance. Sometimes it is as if the geneticists
were required to do their work with elephants on the grounds that
elephants are useful and fruit flies are not. Anyway chess has been
left to the sportsmen, most of whom only write programs, not scientific
papers and compete about who can get time on the largest computers or
get someone to support the construction of specialized chess computers.
Donald Norman's complaints about the way AI research is
conducted have some validity, but the problem of isolating
intellectual mechanisms and making experiments worth repeating is
yet to be solved, so it isn't just a question of deciding to
be virtuous.
Finally, I'll remark that AI is not the same as cognitive
psychology although the two studies are allied. AI concentrates
more on the necessary relations between means and ends, while
cognitive psychology concentrates on how humans and animals
achieve their goals. Any success in either endeavor helps the other.
Methodology in AI is worth studying, but acceptance of its results
should be moderated by memory of the behaviorist catastrophe in
psychology. Doctrines arising from methodological studies crippled the
science for half a century. Indeed psychology was only rescued by ideas
arising from the invention of the computer --- and at least partly ideas
originating in AI.
------------------------------
Date: 5 Aug 87 12:23:37 GMT
From: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@seismo.CSS.GOV>
Reply-to: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@seismo.CSS.GOV>
Subject: Re: AI, science, and pseudo-science
In article <8707270710.AA05885@ucbvax.Berkeley.EDU>
mckee@CORWIN.CCS.NORTHEASTERN.EDU writes:
a lot, but his go at describing types of not-quite-sciences is
interesting. For me, AI should be one of the
>
>* Interdisciplinary Sciences: Materials Science, Neuroscience
> (characterized by their subject matter not yielding coherently
> to any single experimental technique or theoretical paradigm.)
>
My criticism of AI is that most of the workers I meet are pretty
ignorant of the CRITICAL TRADITIONS of ESTABLISHED disciplines which
can say much about AI's supposed object of study. When AI folk do stop
hacking (LISP, algebra or logic - it makes no difference, logic finger
and algebra wrist are just as bad as the well known 'computer-bum'),
they may do so only to raid a few concepts and 'facts' from some
discipline, and then go and abuse them out of sight of the folk who
originally developed them and understand their context and deductive
limitations. What some of them do to English is even worse :-)
>(However, I can't resist throwing in my excuse: programming is fun;
> science is hard, often boring, work. Science is far more rewarding, though.)
I think the nail's been hit squarely on the head, but to programming we
should add amateur philosophy and idealist logic/algebra as other fun
pasttimes pursued instead of hard, critical, rigorous argument. I think
the major turn-off of AI work can be summed up as a complete lack of
candid scholarship. The same is unfortunately true for much
applications-driven research in computing. Without reining in AI (or
computer applications research) under proper disciplines, I can't
really see any prospect for workers developing their critical faculties
up to the highest standards of established disciplines.
NB - yes there are uncritical, unimaginative automata and disreputable
charlatans in all disciplines. But these sorts are not the type who
make a DISCIPLINE. AI seems to have few folk who do want it to be a
discipline.
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.aimmi ARPA: gilbert%aimmi.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..!{backbone}!aimmi.hw.ac.uk!gilbert
------------------------------
End of AIList Digest
********************
∂10-Aug-87 0413 LAWS@KL.SRI.Com AIList V5 #196 - Tools: Neural Nets, Image Processing, Grapher
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Aug 87 04:13:15 PDT
Date: Sun 9 Aug 1987 22:41-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #196 - Tools: Neural Nets, Image Processing, Grapher
To: AIList@SRI.COM
AIList Digest Monday, 10 Aug 1987 Volume 5 : Issue 196
Today's Topics:
Queries - XLISP & Kyoto Common Lisp on Unix System V &
Commercial Planning/Scheduling Software? & CL OPS5 &
Connectionist Simulator & Neural Networks,
AI Tools - Neural Network Simulators &
Low-level Feature Extraction and Interframe Matching &
Uncertainty and Belief & ISI Grapher Update
----------------------------------------------------------------------
Date: Fri, 07 Aug 87 12:15:04 GMT
From: Gabriel <GMCDEH88@IRLEARN>
Subject: XLISP
Does anyone out there know where I can get the latest version
of XLISP (public domain), at least version 1.4.
Thanking you in advance,
Gabriel.
------------------------------
Date: Sun, 9 Aug 87 13:49:32 EDT
From: brant@linc.cis.upenn.edu (Brant Cheikes)
Subject: Query: Kyoto Common Lisp on Unix System V
Has anyone successfully ported Kyoto Common Lisp (KCL) to a Unix
System V environment? Anyone trying? If so, I'd really like to
hear about it!
Brant Cheikes
University of Pennsylvania
Department of Computer and Information Science
------------------------------
Date: Sun, 9 Aug 87 13:58:36 edt
From: nancy@grasp.cis.upenn.edu (Nancy Orlando)
Subject: Commercial Planning/scheduling software?
Can anyone give me any information about commercial planning/scheduling
software that is available? I have heard names like Artemis, Plan Plus,
PLANMAN by Sterling Wentwork, and material from Palladian, but would
like specific names, addresses, and/or comments from people who've
used any and what they think of them. Have there been any good magazine
articles about this type of software, particularly any comparisons
of different aspects of performance among them?
I will be happy to summarize responses to AIList if there is sufficient
interest.
Nancy Sliwa
nancy@grasp.cis.upenn.edu or nesliwa%telemail@orion.arpa
------------------------------
Date: Sat, 8 Aug 87 10:54:29 EST
From: munnari!fgp.uq.oz!thor@uunet.UU.NET (A-P.Lian)
Subject: Re: request for cl ops5
Re: request for cl ops5
Me too please!!!!
Thanks
Andrew Lian
Dr A-P. Lian
Director FGPCAL Unit (French/German/Philosophy Computer-Aided Learning Unit)
U of Queensland, St Lucia, Q. 4067, Australia
ACSnet: apl@fgp.uq.oz
UUCP: ...!seismo!munnari!fgp.uq.oz!apl
ARPA: apl%fgp.uq.oz@seismo
CSNET: apl@fgp.uq.oz
JANET: fgp.uq.oz!apl@ukc
------------------------------
Date: Fri, 7 Aug 87 08:37 EDT
From: Andre Marquis <Bodick@cis.upenn.edu>
Subject: Query: Connectionist Simulator
I would like to experiment with connectionist inference mechanisms. Is
there a publically avaialble connectionist simulator? I have a Sun-3/160
with C and Common Lisp, among other things. I'm willing to port code from
other machines.
Also, if you have any good references on inference using connectionist
networks, please send them. Shastri's PhD thesis is the only thorough
treatment I've seen so far.
Thank you.
Andre Marquis
bodick@cis.upenn.edu
------------------------------
Date: 7 Aug 87 20:13:06 GMT
From: ihnp4!inuxc!iuvax!ndmath!milo@ucbvax.Berkeley.EDU (Greg Corson)
Subject: Neural Networks
I am looking for some information and/or demo programs on Neural Networks
and how to simulate them on a computer. Any demo programs would be greatly
appreciated even if they don't do much.
I've heard that someone is selling a Neural Network simulator for the Mac
but I haven't heard much about it. If anyone has details on what the
program can do I would be interested to hear about it.
Also, I could use a few good introductory references on Nerual networks,
how they can be simulated and how to use them for pattern matching type
operations.
Thanks for the help...
Greg Corson
19141 Summers Drive
South Bend, IN 46637
(219) 277-5306 (weekdays till 6 central)
------------------------------
Date: 8 Aug 87 15:14:59 GMT
From: unc!hch@mcnc.org (Hong John Hsieh)
Subject: Re: Neural Networks
In the 1st International Conference on Neural Network held in June,
there were a number of software/hardware products in exhibition.
Below is a short summary. Among the Macintoch-based systems,
Neuronics, inc. gave their contact phone number as 617-367-9254.
_______________________________________________________________________________
organization product host functions
_______________________________________________________________________________
(1) TRW Mark III coprocessor to vax hardware nn
(2) U. Colorodo MacTivation Mac simulator nn
(3) Nestor inc. Nestor PC-AT handwritten char rec.
(4) AIWARE inc. AINET PC process control
(5) Gen. Dynamics - - situation assessment,
weapon control
(6) HNC ANZA ANZA + PC-AT PC-AT/coprocssor
(7) MEIKO Computer net of transputers TSP, Image restoration
surface
(8) Neural Systems AWARENESS PC nn simulation
(9) Neuraltech inc. PLATO/ PC to Cray knowledge processor
ARISTOTLE
(10) Neuronics MacBrain Mac nn simulation
(11) SAIC,AI Tech. GINNI Symbolics 3670/CM,.. nn development tool
(12) SAIC,Tech. Res. Sigma-1 PC-AT nn simulation
(13) TI - Explorer+Odyssey nn simulation
(14) VERAC - BAMS simulation Assoc. Mem.
_______________________________________________________________________________
Cheng-Hong Hsieh (hch@unc.UUCP)
------------------------------
Date: 8 Aug 87 17:54:18 GMT
From: ramones.rutgers.edu!pratt@RUTGERS.EDU (Lorien Y. Pratt)
Subject: Re: Neural Networks
At the Neural Networks tutorial at AAAI in Seattle in July, Terry
Sejnowski said that the third volume of Parallel Distributed Processing
will be released this coming fall. I have confirmed this with the
publisher. Sejnowski also said that the book will come with a disk
containing some sort of a neural network simulator which will run under
UNIX.
--Lorien Pratt
------------------------------
Date: Thu, 6 Aug 87 11:37 EDT
From: Roland Zito-Wolf <RJZ@JASPER.PALLADIAN.COM>
Reply-to: Roland Zito-Wolf <RJZ%JASPER@LIVE-OAK.LCS.MIT.EDU>
Subject: Low-level feature extraction and interframe matching
software wanted
Date: 1 Aug 87 19:18:48 GMT
From: jbn@glacier.stanford.edu (John B. Nagle)
Does software exist for following moving objects from frame to frame
in video images?
...
Software, algorithms, hardware, or indications of research activity
would be useful.
John Nagle
Center for Design Research, Stanford
There was some interesting work done on building and comparing structural
descriptions by J. Connell at MIT. the reference is "Learning Shape
Descriptions: Generating and Generalizing Models of Visual Objects"
AI-TR-853, Sept 85.
The report also discusses methods for pre-processing the visual inputs.
-rjz
Roland Zito-Wolf
Palladian Software
------------------------------
Date: 5 Aug 87 02:15:39 GMT
From: ptsfa!nonvon!apn@ames.arpa (apn)
Subject: Re: Low-level feature extraction and interframe matching
software wanted
In article <17150@glacier.STANFORD.EDU> jbn@glacier.STANFORD.EDU
(John B. Nagle) writes:
>
> Does software exist for following moving objects from frame to frame
>in video images? I'm looking for something that works by finding low-level
>features such as edges and corners and matches them from one frame to the
>
There is a company in Santa Rosa, CA that does something like this
They are called MAC or motion analysis corporation.
Alex P Novickis
--
UUCP: {ihnp4,ames,qantel,sun,amdahl,lll-crg,pyramid}!ptsfa!nonvon!apn
{* Only those who attempt the absurd ... will achieve the impossible *}
{* I think... I think it's in my basement... Let me go upstairs and check. *}
{* -escher *}
------------------------------
Date: Wed, 6 Aug 87 21:51:05 EDT
From: PJURKAT@VAXC.STEVENS-TECH.EDU
Subject: STEVENS SEMINAR IN UNCERTAINTY AND BELIEF - SPRING 1987
This message is to whoever sent me a list of references related to the subject
of the seminar - I got the list from the POSTMASTER account on our VAX - node
SITVXB - from one of our systems programmers - by the time I got it, the source
of the list was no longer evident.
This note is to express my thanks to whoever it was that was so generous with
their time and effort to make the list - it contained about 80 references many
of which were new to me. The list came in a format that was similar to the
Leff bibliographies that appear on the net occassionally - I am totally un-
familiar with how they are generated, where they come from, and what the various
first letters (%A, %T, etc.) mean, although I can guess - If anyoune would
send me a tutorial on what the Leff lists are all about I would appreciate it
- if it is not convenient to do so through the network, my address is
M. Peter Jurkat
Department of Management
Stevens Insitute of Technology
Castle Point Station
Hoboken, NJ 07030
201-420-5371
pjurkat@sitvxa.bitnet
thanks again - peter J.
------------------------------
Date: Fri, 07 Aug 87 19:27:34 PDT
From: Gabriel Robins <gabriel@vaxa.isi.edu>
Subject: The ISI Grapher: an Update
--------
============================================================================
AI/Graphics tool announcement:
"The ISI Grapher: a Portable Tool for Displaying Graphs Pictorially"
============================================================================
Greetings,
Due to the considerable interest drawn by the ISI Grapher so far, I am
posting this abstract summarizing its function and current status, as well
as some new information regarding same. This posting is also for the benefit
of those who missed the first announcement or who are new to the AIList.
We are now able to satisfy European and other foreign requests, so
even if you are not a U.S.-based researcher or company, you may now have
the sources.
I will be giving an invited talk on the ISI Grapher in Symboliikka '87,
Helsinki, Finland, August 17, 1987. The paper describing this effort is
now available (for free) to all: it is entitled: "The ISI Grapher: a Portable
Tool for Displaying Graphs Pictorially."
The CommonLisp sources are also available (for free to all entities who
receive DARPA funds, and for a small fee to all others). It currently runs
on Symbolics versions 6, 7, and 7.1, and on TI Explorers versions 2 & 3.
Efforts are currently underway to port it to other machines.
If you would like the paper and/or the sources, please forward your postal
address to "gabriel@vaxa.isi.edu" or to:
Gabriel Robins
Intelligent Systems Division
Information Sciences Institute
4676 Admiralty Way
Marina Del Rey, Ca 90292-6695
U.S.A.
============================================================================
The ISI Grapher
August, 1987
Gabriel Robins
Intelligent Systems Division
Information Sciences Institute
The ISI Grapher is a set of functions that convert an arbitrary graph
structure (or relation) into an equivalent pictorial representation and
displays the resulting diagram. Nodes and edges in the graph become boxes and
lines on the workstation screen, and the user may then interact with the
Grapher in various ways via the mouse and the keyboard.
The fundamental motivation which gave birth to the ISI Grapher is the
observation that graphs are very basic and common structures, and the belief
that the ability to quickly display, manipulate, and browse through graphs may
greatly enhance the productivity of a researcher, both quantitatively and
qualitatively. This seems especially true in knowledge representation and
natural language research.
The ISI Grapher is both powerful and versatile, allowing an
application-builder to easily build other tools on top of it. The ISI NIKL
Browser is an example of one such tool. The salient features of the ISI
Grapher are its portability, speed, versatility, and extensibility. Several
additional applications were already built on top of the ISI Grapher,
providing the ability to graph lists, flavors, packages, divisors, functions,
and Common-Loops classes.
Several basic Grapher operations may be user-controlled via the specification
of alternate functions for performing these tasks. These operations include
the drawing of nodes and edges, the selection of fonts, the determination of
print-names, pretty-printing, and highlighting operations. Standard
definitions are already provided for these operations and are used by default
if the application-builder does not override them by specifying his own
custom-tailored functions for performing the same tasks.
The ISI Grapher now spans about 100 pages of CommonLisp code. The 120-page
ISI Grapher manual is available; this manual describes the general ideas, the
interface, the application-builder's back-end, the algorithms, the
implementation, and the data structures. A shorter paper is also available,
and includes hardcopy samples of the screen during execution. The ISI Grapher
presently runs on both Symbolics (versions 6, 7, & 7.1) and TI Explorer
workstations (versions 2 & 3); ports to other machines are underway.
If you are interested in more information, the sources themselves, or just
the paper/manual, please feel free to forward your postal address to
"gabriel@vaxa.isi.edu" or write to "Gabriel Robins, Information Sciences
Institute, 4676 Admiralty Way, Marina Del Rey, Ca 90292-6695 U.S.A."
============================================================================
------------------------------
End of AIList Digest
********************
∂14-Aug-87 0038 LAWS@KL.SRI.Com AIList V5 #197 - Macsyma, XLISP, Neural Networks
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 14 Aug 87 00:38:48 PDT
Date: Thu 13 Aug 1987 21:53-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #197 - Macsyma, XLISP, Neural Networks
To: AIList@SRI.COM
AIList Digest Friday, 14 Aug 1987 Volume 5 : Issue 197
Today's Topics:
Queries - OPS5 Benchmarks & Scheme & Xerox 1186 &
AI Abstracts & Region Growing,
Literature - Dreyfus and Dreyfus Reviews & Sanskrit,
Tools - Macsyma Sources & XLISP 1.7 for MS-DOS & Neural Networks,
Msc. - Turing Plays
----------------------------------------------------------------------
Date: Thu, 6 Aug 87 10:52 EST
From: SCAROLA%cgi.com@RELAY.CS.NET
Subject: OPS5 benchmarks
I'm working on a new version of CRL-OPS which is the OPS5-like
component of Knowledge Craft. It's completely written in Common
Lisp but includes a full compiler and some other tricks which
produce a serious speedup over previous versions. Someone informed
me that there exists a standard set of OPS5 benchmarks developed
or collected by Columbia University and I'm interested in running
these. If anyone has these benchmarks or knows who I should contact
to get them please send me mail.
Thank you,
Dave Scarola
Carnegie Group Inc
<SCAROLA%cgi@csnet-relay.csnet>
------------------------------
Date: 10 Aug 87 17:15:24 GMT
From: sundc!hadron!cos!duc@seismo.css.gov (Duc Kim Nguyen)
Subject: Scheme: where to get it ?
Hi,
I am looking for pointers to where to get SCHEME
interpreter/compiler (ala Abelson&Sussman) to run under
UNIX (BSD). Public-Domain distribution would be greatly
appreciated, (written in C or Common Lisp, even better!).
If there are multiple version, please include the pros-cons
of each.
thank you!
duc@COS.COM
------------------------------
Date: 12 Aug 87 14:59:23 +1000 (Wed)
From: "ERIC Y.H. TSUI" <munnari!aragorn.oz!eric@uunet.UU.NET>
Subject: Xerox 1186
I would like to communicate with anyone who has used or is using
Xerox 1186 workstations running Interlisp-D and/or Xerox Quintus Prolog
environments.
CSNET address: eric@aragorn.oz
UUCP address: seismo!munnari!aragorn.oz!eric
decvax!mulga!aragorn.oz!eric
ARPA address: munnari!aragorn.oz!eric@seismo.arpa
- - ---
Many thanks.
Eric Tsui eric@aragorn.oz
------------------------------
Date: 13 Aug 87 04:29:05 GMT
From: ihnp4!chinet!nucsrl!berggeo@ucbvax.Berkeley.EDU (George Berg)
Subject: AI Abstracts info wanted
Earlier this Summer I received some material in the (paper) mail
about something called ARTIFICIAL INTELLIGENCE ABSTRACTS.
Unfortunately, the material ended-up in the wrong pile and I threw
it away. Is there anyone out there who kept the material and who can
give me the pertinent information about it (e.g. how much, whom to
write, etc.)?
*PLEASE*, to avoid cluttering this group, respond to me by e-mail
and I will post a summary of the information I receive. Thanks.
George Berg
berggeo@alpha.eecs.nwu.edu EE/CS Dept.
or berggeo@nucsrl.UUCP Northwestern University
or {gargoyle,ihnp4,chinet}!nucsrl!berggeo Evanston, Il 60208
[The addresses are: Iris Taylor, Journals Department, Basil Blackwell,
108 Cowley Road, Oxford OX41JF England; or Journals Department,
Basil Blackwell Inc., Box 1320, Murray Hill Station, NY 10156.
The special Vol. 1 rate (including a free issue) for individuals
in N. America or Japan is $50; for institutions $104. -- KIL]
------------------------------
Date: Tue, 11 Aug 87 17:23:54 EDT
From: Ali Minai <amres%uvaee.ee.virginia.edu@RELAY.CS.NET>
Subject: Request for Region Growing
A friend of mine is looking for REGION GROWING programs for computer
vision applications. Are there any standard 3- or 2- dimensional
region growing programs around? The references can be e-mailed to
me at
am@uvaee.ee.virginia.EDU
Thanks,
Ali Minai,
EE, University of Virginia
------------------------------
Date: 10 Aug 87 14:23:09 GMT
From: prlb2!ronse@seismo.CSS.GOV (Christian Ronse)
Subject: Re: Reviews of Dreyfus & Dreyfus?
In article <870805-062024-4511@Xerox>, WAnderson.wbst@XEROX.COM writes:
> I am looking for reviews of the Dreyfus & Dreyfus book "Mind Over
> Machines." Any and all references appreciated. Thanks,
>
> Bill Anderson
Review by Timothy D. Koschmann in the V33#1 (Sep.87) issue of ``Artificial
Intelligence'', pp. 135--140. The exact title of the book is: ``Mind over
Machine: The Power of Human Intuition and Expertise in the Era of the
Computer''.
-----
Time is Mona Lisa
--
Christian Ronse maldoror@prlb2.UUCP
{uunet|philabs|mcvax|...}!prlb2!{maldoror|ronse}
------------------------------
Date: Mon, 10 Aug 87 12:56:26 EDT
From: Bruce Nevin <bnevin@cch.bbn.com>
Subject: Review of D&D in Nature
A review of Mind Over Machine appeared in Nature 324.13 (Nov 1986):182-3.
On the same page is a cartoon: a man looking glumly at the CRT in front
of his chair, a woman standing at his side says `It figures. If there's
artificial intelligence, there's bound to be some artificial stupidity.'
------------------------------
Date: Thu, 6 Aug 87 09:40:54 EDT
From: "William J. Rapaport" <rapaport@cs.buffalo.edu>
Subject: Sanskrit
The paper on Sanskrit, cited by Briggs in his AI Magazine article, by
Srihari, Rapaport, and Kumar, ``On Knowledge Representation Using
Semantic Networks and Sanskrit,'' Technical Report 87-03 (Buffalo: SUNY
Buffalo Dept. of Computer Science, February 1987) is available by writing
to Ms. Lynda Spahr, Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260,
USA, or sending email to spahr@buffalo.csnet or spahr@sunybcs.bitnet.
The full papers were to appear in a book. I haven't heard about its status.
William J. Rapaport
Assistant Professor
Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260
(716) 636-3193, 3180
uucp: ..!{ames,boulder,decvax,rutgers}!sunybcs!rapaport
csnet: rapaport@buffalo.csnet
internet: rapaport@cs.buffalo.edu
[if that fails, try: rapaport%cs.buffalo.edu@cs.relay.net]
bitnet: rapaport@sunybcs.bitnet
------------------------------
Date: Mon, 10 Aug 87 16:47 EDT
From: Richard Petti <petti@ALLEGHENY.SCRC.Symbolics.COM>
Subject: Re: Macsyma Sources
From: jbn@glacier.stanford.edu (John B. Nagle)
Subject: Re: Macsyma Sources
A competing package is MuMath, from
Soft Warehouse
3615 Harding Av
Honolulu Hawaii 96816
808-734-5801
This is a symbolic math package written in a quaint but charming dialect
of LISP, for which an interpreter is provided. There are versions for the
Apple II and IBM PC, and recently a modern version for the PC has been re-
leased. I've used the older version on some messy vector calculus problems
in my solid modelling work, and found it quite useful in dealing with the
grunt work of algebra and calculus. The heuristics aren't very powerful,
but the algorithms for the standard solution methods all seem to work.
Microsoft resells this package, when they remember it is in their product
line, but the developers are in Hawaii and one may as well deal directly
with them. Sometimes one of the developers answers the phone.
John Nagle
MACSYMA is being ported to IBM AT class machines, i.e. 80286 with DOS.
It will have the same, or nearly the same functionality as the
standard commercial-grade MACSYMA's available from the Computer Aided
Mathematics Group at Symbolics. If you are interested in beta-tesing
it (starting in October) please call us at 1-800-MACSYMA (622-7962).
With regard to the capabilities you mention above, MACSYMA has a
vector calculus package and two tensor calculus packages.
------------------------------
Date: Tue, 11 Aug 87 22:06:54 MDT
From: t05rrs%mpx1@LANL.GOV (Dick Silbar)
Subject: Where to get XLISP 1.7 for MS-DOS
In V5 #196 Gabriel asks about XLISP 1.4. Version 1.7 is available
on a diskette (#79) from the Pioneer Valley PC User's Group for
$6 (plus $5 membership fee). Address is P.O. Box H, North
Amherst, MA 01059.
------------------------------
Date: 12 Aug 1987 11:27-EDT
From: Alessandro.Forin@speech2.cs.cmu.edu
Subject: Re: XLISP
You should be able to get a copy of XLISP from the author:
David M. Betz
114 Davenport Ave.
Manchester, NH 03103
(603) 625-4691
It is nicely small and easily portable to all sorts of machines, but it
does not perform very well. I tested it running on a Sun3/160 on
Gabriel's benchmarks, and it was roughly 300 (three-hundreds) times
slower than compiled CMU-CommonLisp running on an IBM-RT.
If it is serious work, have you looked at Kyoto CL ?
sandro-
------------------------------
Date: 13 Aug 87 14:34:36 GMT
From: phri!uccba!finegan@nyu.arpa (Mike Finegan)
Subject: Re: Neural Networks
In article <269@ndmath.UUCP>, milo@ndmath.UUCP (Greg Corson) writes:
> I am looking for some information and/or demo programs on Neural Networks
> and how to simulate them on a computer. Any demo programs would be greatly
> appreciated even if they don't do much.
Dr. Dobbs Journal had an article (cover article) on neural networks a
couple months back. There was source in there for a simulator, written
in 'C'. I coded it in (ow - 800 some lines), and it works, except that
some interpretation , and addition of code is necesarry to get what you
succesfully trained it on to recognize anything. It merely required
adapting a pre-existing sub-routine, and forced me to understand the
program. It is public domain, so I guess I can send it to you, but note:
I have added routines (albeit in the same style, etc.). The source can
also be gotten on floppy from the magazine (~$20 ?).
>
> Also, I could use a few good introductory references on Nerual networks,
> how they can be simulated and how to use them for pattern matching type
> operations.
ACASSP (sic), an IEEE Signal Processing magazine, had a fairly comprehensive
introductio to the subject this year. I don't subscribe to it, so I don't
remember if it was April, or later; I just copied the article.
Mike Finegan
Univ. of Cinti.
...hal!uccba!ucece1!finegan
------------------------------
Date: Thu, 13 Aug 87 11:10:34 EDT
From: Peter Beck (LCWSL) <pbeck@ARDEC.ARPA>
Subject: turing plays
RE: TURING PLAYS
The NJ section of the NY Times of Aug 2, 1987 on page 8 had an article on two
plays based on Turing's life. They are: "A MOST SECRET WAR" by Kevin Paterson
which was performed from july 30 - aug 9 at the Philip J Levin Theater in New
Brunswick as part of the Rutgers Summerfest and 'BREAKING THE CODE" by Hugh
Whitmore scheduled to open on Broadway Nov 15.
I have not read nor seen the plays.
peter beck <pbeck@ardec.arpa>
------------------------------
End of AIList Digest
********************
∂14-Aug-87 0250 LAWS@KL.SRI.Com AIList V5 #198 - TRList, Seminars, Conferences
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 14 Aug 87 02:50:31 PDT
Date: Thu 13 Aug 1987 22:09-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #198 - TRList, Seminars, Conferences
To: AIList@SRI.COM
AIList Digest Friday, 14 Aug 1987 Volume 5 : Issue 198
Today's Topics:
Literature - TRLIST Technical Reports,
Seminars - Object-Based Knowledge Representation Systems (Lockheed) &
Evidential Reasoning: Overview and Implementation (SRI),
Conferences - Symposium on Logic Programming &
ACL 1988 Annual Conference CALL FOR PAPERS
----------------------------------------------------------------------
Date: Tue, 16 Jun 1987 17:14 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: TRLIST Technical Reports
[The following is a reminder by Lawrence Leff of the technical
report abstracts that he keep available. -- KIL]
List of Tech Report Files and their contents
award1.x Fiscal Year 1986 Research Projects Funded by Knowledge and
Database Systems Program, IST 8504726 to IST8607303
award2.x Fiscal Year 1986 Research Projects Funded by Knowledge and
Database Systems Program, IST 8644864 to IST8600412
award3.x Fiscal Year 1986 Research Projects Funded by Knowledge and
Database Systems Program, IST 8603407 to IST-8607849
award4.x Fiscal Year 1986 Research Projects Fundeded by Robotics
and Machine Intelligence Program (No Abstracts)
canai1 Canadian AI Tech Report listing part 1 (Courtesy Graeme Hirst)
canai2 Canadian AI Tech Report listing part 2 (Courtesy Graeme Hirst)
cmu-robotics Robotics Institute of Carnegie Mellon University
CMU-RI-TR-85-10 to CMU-RI-TR-85-22
cmu-robotics2 Robotics Institute of Carnegie Mellon University
CMU-RI-TR-84-1 to CMU-RI-TR-85-10
issco Reports from ISSCO, Switzerland (mostly natural language)
japan reports from ICOT, Japan (reprinted from AIList)
mitai MIT AI memos 200 - 334
mitai1 MIT AI memos 335 - 452
mitai2 MIT AI memos 452 - 567
mitai3 MIT AI memos 568 - 641
mitai4 MIT AI memos 642 - 697
mitai6 MIT AI memos 698 - 751
mitai7 MIT AI memos 806 - 868 technical report 219 - 232
mitai8 MIT AI technical report 233 - 860 List of Books and Manuals
mitai9 MIT AI technical report 789 - 860 List of Boioks and Manuals
mitai10 MIT AI memo 752 - 805
robotics3 Robotics Institute of Carnegie Mellon University
CMU-RI-TR-86-1 to CMU-RI-TR-86-8 + (theses and dissertations)
robotics4 Robotics Institute of Carnegie Mellon University
CMU-Ri-TR-86-9 to CMU-RI-TR-86-14
SRI AI materials, sent by Dr. Laws, order from D. Arceo, AI Center,
SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025
st2.x SRI #1 Technical Note 73 to 120
st3.x SRI #13 Technical Note 337 to 354
st4.x SRI #9 Technical Note 280 to 292
st5.x SRI #4 Technical Note 173 to 200
st6.x SRI #12 Technical Note 332 to 336
st7.x SRI #2 Technical Note 121 to 145
st8.x SRI #11 Technical Note 309 to 321
st9.x SRI #6 Technical Note 226 to 245
st10.x SRI #3 Technical Note 151 to 171
st11.x SRI #5 Technical Note 203 to 225
st12.x SRI #7 Technical Note 246 to 263
st13.x SRI #8 Technical Note 264 to 278
st14.x SRI #15 Technical Note 374 to 388
st15.x SRI #14 Technical Note 355 to 373
st16.x SRI #10 Technical Note 293 to 301
ucbcog University of California at Berkeley Cognitive Science
Program
ut-ai Artificial Intelligence Laboratory, University of Texas
at Austin
ut-ai1 Second List from University of Texas at AUSTIN AI lab
+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_
TRLIST is for redistribution of lists of technical reports from Universities
and R&D labs. All tech report lists to be redistributed should include
information on ordering the technical reports themselves. We prefer bib
or refer format but we would rather get a weird format than no list at all.
Administrative matters go to E1AR0002 @ SMUVM1 (bitnet),
trlist-request%smu@csnet-relay, or ihnp4!convex!smu!trlist-request.
Submitted tech report lists go to E1AR0002 @ SMUVM1 (bitnet),
trlist%smu@csnet-relay, or ihnp4!convex!smu!trlist. (Please send large
files to the first or third of these as we are charged by the byte for
mail received via CSNET.)
TRLIST goes out as the moderated group mod.techreports as well as being
mailed to a list of 84 addresses as of April 20, 1986, many of which
correspond to multiple people looking at an electronic bulletin board.
Bib and refer are UNIX products which allow for users to have references
automatically included in text and reformatted as needed for different
journal styles. In addition, they support a primitive information retrieval
function. Refer is produced by AT&T and should be part of most UNIX systems
or their writer's workbench if the system comes unbundled. Refer comes as
user contributed software under BSD 4.2. Contact Dr. Budd
at University of Arizona for more info on bib.
For those wishing to put material in bib or refer format but who do not have
the software, here is an example of the way the text should look. The
abstract and dollar field are optional. Note that each field
begins with a percent followed by a one letter key followed by a space.
Any line not beginning with a percent sign is a continuation of the previous
line. One blank line separates each reference form the next.
We publish materials that are not CS. The majority of materials coming are
CS related and in the event that there is substantial non-CS tech reports
being published, I will split the list as needed.
__________________________________________________________________________
%R CS-84-124
%T SOME CONSIDERATIONS ON INTERCONNECTIONS OF COMPUTER NETWORKS
%A Govind P. Gupta
%A Arjun Gupta
%I Washington State University, Computer Science Department
%X This technical report is a review of the considerations on Interconnection
of Computer Networks. Fundamental concepts of Network architecture,
implementation levels, routing and addressing are also reviewed.
%$ $2.60
%R CS-84-125
%T MOVEMENT COORDINATION FOR SINGLE--TRACK ROBOT SYSTEMS
%I Washington State University, Computer Science Department
%A Michael A. Langston
%A Chul E. Kim
%X We consider problems associated with the coordination of movement within a
multiple robot system in which all motion is restricted to a single track.
Our objective is to minimize the reconfiguration time, that is, the total time
required to move a collection of robots from an initial to a goal
configuration. We show that various models give rise to a wide range of
problem complexities. For these problems we design and analyze optimization
and approximation strategies.
%$ $2.50
------------------------------
Date: Tue, 4 Aug 87 07:35:30 PDT
From: wiley!joe@lll-lcc.ARPA (Joseph Sullivan)
Subject: Seminar - Object-Based Knowledge Representation Systems
(Lockheed)
[Forwarded from the Stanford bboard.]
INTERDEPARTMENTAL COMMUNICATION
TO: DISTRIBUTION
FROM: JOSEPH W. SULLIVAN O/90-06 B/259 354-5213
DATE: 1 August 1987
SUBJECT: AIC COLLOQUIUM
The Lockheed AI Center is pleased to announce a presentation by
Dr. Peter F. Patel-Schneider of the Schlumberger Palo Alto
Research. An abstract of the presentation is provided below.
Weak, Object-Based Knowledge Representation Systems
Dr. Peter F. Patel-Schneider
Recent work in semantics for terminological logics -- logics
about the relationship between classes -- has demonstrated that
the tradeoff between expressive power and computational
tractability in such logics can be circumvented. This indicates
that tractable object-based knowledge representation systems can
be built, albeit at the cost of weakening deduction. These
systems, because of their tractability, could be used in large
knowledge-based systems. Their representational semantics would
provide a cleaner foundation for object-oriented knowledge-based
systems than do object-oriented programming systems, the systems
currently used to build object-oriented knowledge-based systems.
This cleaner foundation means that fewer complications would
arise in the building and analysis of knowledge-based systems,
thus making these difficult tasks easier.
DATE: 19 August 1987
TIME: 3:30
PLACE: Lockheed Artificial Intelligence Center
Main Conference Room
2710 Sand Hill Rd. (Lockheed Bld. #259)
Menlo Park
------------------------------
Date: Thu, 13 Aug 87 10:20:45 PDT
From: lunt@csl.sri.com (Teresa Lunt)
Subject: Seminar - Evidential Reasoning: Overview and Implementation
(SRI)
SRI COMPUTER SCIENCE LAB SEMINAR SERIES ANNOUNCES:
EVIDENTIAL REASONING: OVERVIEW AND IMPLEMENTATION
TOM GARVEY
AI CENTER, SRI INTERNATIONAL
Monday, August 17 at 4:00 pm
SRI International, Computer Science Laboratory, BN182
Evidential reasoning consists of theoretical and practical methods for
reasoning from evidence, the uncertain, imprecise, and sometimes
incorrect information that is typically provided by "real-world"
information sources. This theory evolved in response to the apparent
representational and computational inadequacies of classical probability
methods when dealing with such information in an expert system
framework. Evidential reasoning is (currently) theoretically grounded
in the Shafer-Dempster theory of evidence. Using this theory, we have
developed procedures for fusing multiple, distinct bodies of evidence,
for projecting evidential statements in time, for translating statements
in one vocabulary into a different one, for interpreting selected
propositions based on a given body evidence, and for summarizing and
"gisting" a body of evidence. This seminar will be in the nature of a
high-level tutorial describing the Shafer-Dempster theory and Gister,
our current implementation of evidential reasoning.
------------------------------
Date: Thu 13 Aug 87 17:16:37-CDT
From: "Roger Nasr (MCC-AI)" <AI.NASR@MCC.COM>
Reply-to: Nasr@MCC
Subject: Conference - Symposium on Logic Programming - 1987
This is a last minute call to fill the remaining commercial exhibit booths
at the Fourth IEEE Symposium on Logic Programming to be held August 31st
through September 4th at the Hyatt Union Square, San Francisco, California.
The Symposium is the main gathering event in the United States for the
worldwide Logic Programming community. The program includes 49 research
papers presented by leading researchers from around the world and covering
a wide range of topics in the area. Included in those topics are:
Databases, Language Issues, Applications, Program Development Environments,
and Parallelism in Logic Programming.
Parties interested in getting more information about the commercial
exhibits part of this symposium are urged to contact Roger Nasr on the
network at 'nasr@mcc.com', or by phone at (512)-338-3424.
------------------------------
Date: Tue, 11 Aug 87 23:17:22 edt
From: walker@flash.bellcore.com (Don Walker)
Subject: Conference - ACL 1988 Annual Conference CALL FOR PAPERS
CALL FOR PAPERS
26th Annual Meeting
of the
Association for Computational Linguistics
7-10 June 1988
State University of New York at Buffalo
Buffalo, New York
TOPICS OF INTEREST: Papers are invited on substantial, original, and
unpublished research on all aspects of computational linguistics,
including, but not limited to, pragmatics, discourse, semantics,
syntax, and the lexicon; phonetics, phonology, and morphology;
interpreting and generating spoken and written language; linguistic,
mathematical, and psychological models of language; machine translation
and translation aids; natural language interfaces; message
understanding systems; and theoretical and applications papers of every
kind.
REQUIREMENTS: Papers should describe unique work that has not been
submitted elsewhere; they should emphasize completed work rather than
intended work; and they should indicate clearly the state of completion
of the reported results.
FORMAT FOR SUBMISSION: Authors should submit twelve copies of an
extended abstract not to exceed eight double-spaced pages (exclusive of
references) in a font no smaller than 10 point (elite). The title page
should include the title, the name(s) of the author(s), complete
addresses, a short (5 line) summary, and a specification of the topic
area. Submissions that do not conform to this format will not be
reviewed. Send to:
Jerry R. Hobbs
ACL88 Program Chair
Artificial Intelligence Center
SRI International
333 Ravenswood Avenue
Menlo Park, CA 94025, USA
415:859-2229; hobbs@warbucks.ai.sri.com
SCHEDULE: Papers are due by 4 January 1988. Authors will be notified
of acceptance by 8 February. Camera-ready copies of final papers
prepared in a double-column format, either on model paper or in a
reduced font size using laserprinter output, must be received by 4
April along with a signed copyright release statement.
OTHER ACTIVITIES: The meeting will include a program of tutorials
organized by Ralph Grishman, Computer Science Department, New York
University, 251 Mercer Street, New York, NY 10012, USA; 212:460-7492;
grishman@nyu.arpa. Anyone wishing to arrange an exhibit or present a
demonstration should send a brief description together with a
specification of physical requirements (space, power, telephone
connections, tables, etc.) to Lynda Spahr, Department of Computer
Science, SUNY Buffalo, Buffalo, NY 14260, USA; 716:636-2464 or 3181;
spahr@gort.cs.buffalo.edu, spahr@buffalo.csnet, spahr@sunybcs.bitnet,
or {ames,boulder,decvax,rutgers}!sunybcs!spahr.
CONFERENCE INFORMATION: Local arrangements are being handled by
William J. Rapaport (ACL), Department of Computer Science, SUNY Buffalo,
Buffalo, NY 14260, USA; 716:636-3193, 3180; rapaport@gort.cs.buffalo.edu,
rapaport@buffalo.csnet, rapaport@sunybcs.bitnet, or
{ames,boulder,decvax,rutgers}!sunybcs!spahr. For other information on
the conference and on the ACL more generally, contact Don Walker (ACL),
Bell Communications Research, 445 South Street, MRE 2A379, Morristown,
NJ 07960, USA; 201:829-4312; walker@flash.bellcore.com or
{ucbvax,decvax,allegra}!bellcore!walker.
PROGRAM COMMITTEE: Jared Bernstein, Roy Byrd, Sandra Carberry, Eugene
Charniak, Raymonde Guindon, Lynette Hirschman, Jerry Hobbs, Karen
Jensen, Lauri Karttunen, William Rounds, Ralph Weischedel, and Robert
Wilensky.
------------------------------
End of AIList Digest
********************
∂16-Aug-87 2328 LAWS@KL.SRI.Com AIList V5 #199 - Msc., Neural Nets, Functional Representations
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Aug 87 23:28:06 PDT
Date: Sun 16 Aug 1987 21:29-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #199 - Msc., Neural Nets, Functional Representations
To: AIList@SRI.COM
AIList Digest Monday, 17 Aug 1987 Volume 5 : Issue 199
Today's Topics:
Queries - S and P Puzzle & Frame-Based Database,
Tools - Neural Network Simulator,
Comment - Remote Sensing,
Philosophy - The Science of Pointless Debates & Natural Kinds,
Comment - Object-Oriented Programming,
Review - Turing Plays
----------------------------------------------------------------------
Date: 14 Aug 87 12:03 PDT
From: Shrager.pa@Xerox.COM
Subject: Re: mr. s & mr. p
Someone here is looking for the source of an old logic problem about two
people named Mr. P. and Mr. S. One of these knows the product of some
numbers and the other one knows their sum. Together they can figure out
the numbers. There is a particular conversation that goes on between
them something like:
Mr. P. I don't know the numbers.
Mr. S. I knew you didn't. Neither do I.
...
and they eventually figure out the numbers.
The reference is for a paper going to the publisher in a few days, so if
anyone can help us with an exact reference and the precise text of the
conversation, it would be greatly appreciated. (Although it might be
interesting to talk about the answer, and how it can be figured out,
right now we're pretty desperate for a citation.)
Thanks in advance.
-- Jeff
------------------------------
Date: 15 Aug 87 16:24:56 GMT
From: amdahl!dlb!plx!titn!jordan@ames.arpa (Jordan Bortz)
Subject: Wanted - FRAMES based database in C,LISP, or SMALLTALK
I'm looking for a good frames based expert system in Smalltalk, C, or LISP.
Public-domain, of course. If LISP, it would be nice if it ran under
FRANZ.
Thanks much in advance!
Jordan
--
=============================================================================
Jordan Bortz Higher Level Software 1085 Warfield Ave Piedmont, CA 94611
(415) 268-8948 UUCP: (decvax|ucbvax|ihnp4)!decwrl!sun!plx!titn!jordan
=============================================================================
------------------------------
Date: 14 Aug 87 14:21:01 GMT
From: linus!alliant!sullivan@husc6.harvard.edu (Mike Sullivan)
Subject: Re: Neural Networks
In article <269@ndmath.UUCP>, milo@ndmath.UUCP (Greg Corson) writes:
> I am looking for some information and/or demo programs on Neural Networks
> and how to simulate them on a computer. Any demo programs would be greatly
> appreciated even if they don't do much.
Nerualtech Inc has a product out for beta test which runs on machines from
PC's to Cray's. Dr John Voevodsky is the developer of this product which
is modeled from the biological processes of the human brain cell. You may not
be in the market for such a product, but it might help you to know what other's
are doing.
for info on PLATO/ARISTOTLE contact:
Dr John Voevodsky
Neuraltech Inc
177 Goya Road
Portola Valley, California 94025
#include <std/disclaimer>
______
/ \ \
Michael J Sullivan / \____\ Alliant
sullivan@alliant.uucp / / \ ComputerSystemsCorporation
/____/_______\
------------------------------
Date: Tue, 11 Aug 87 08:31:45 pdt
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Remote Sensing
Subject: Re: Reviews of Dreyfus & Dreyfus? [AI is not alone]
> the April 3, 1986, New Scientist, pp. 46-47. Roszak doesn't add much
> personal perspective, but views the book favorably: "AI's record of
> barefaced public deception is unparalleled in the annals of academic
> study." -- KIL]
Not too shabby a comment. I would say look to satellite remote sensing
as another area which has promised a lot and delivered very little for
the dollars put in. [This comment is not mine but people's in RS.]
It also started about the same time as AI [maybe a tiny bit later than
AI]. Remote sensing offers a basis for comparison of the development
of these two sciences.
--eugene miya
NASA Ames Res Ctr. [ex-RS type]
[I'd say it's not really the "sensing" that's failed, but the
automation of perception. That turned out to be far harder than
anyone imagined -- but has to be solved somehow, regardless of
which research effort funds the work. Much of the research done
under the remote sensing label is of equal interest for missile
guidance, autonomous vehicle and robotic vision, and other military
applications. Billing it all to remote sensing is somewhat unfair.
(Of course the same could be said for much of the AI research.)
-- KIL]
------------------------------
Date: 11 Aug 87 17:24:13 GMT
From: hp-sdd!gt%hpfcmt.HP.COM@sdcsvax.ucsd.edu (George Tatge)
Subject: The science of pointless debates
I am curious... if we do come to a resolution on this riveting issue of
whether or not AI is a science, what have we accomplished? It seems to
me to be the type of nonsense issue that could only flourish in academia.
Are we trying to decide if AI goes into the humanites section of the
course catelogue? Are we arguing over which department will ultimately
receive the benefit of DOD grants? Maybe but probably not. What I imagine
we are doing is carrying on the great tradition of academicians from one
field taking pot shots at academicians of a different field. Granted, tis
quite an enduring tradition but not really an endearing one.
George (I'll be gone before the flames get here) Tatge
Obviously, nothing I ever say has anything whatsoever to do with the
company I work for.
------------------------------
Date: 13 Aug 87 12:52:52 GMT
From: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@seismo.CSS.GOV>
Reply-to: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@seismo.CSS.GOV>
Subject: Re: Natural Kinds (Re: AIList Digest V5 #186)
In article <MINSKY.12320404487.BABYL@MIT-OZ> MINSKY@OZ.AI.MIT.EDU writes:
>
>In my view, Wittgenstein missed the point because he focussed on
>"structure" only. What we have to do is also take into account the
>"function", "goal", or "intended use" of the definition. My trick is
>to catch the idea between two descriptions, structural and functional.
>Consider a chair, for example.
>
> STRUCTURE: A chair usually has a seat, back, and legs - but
> any of them can be changed in so many ways that it is hard
> to make a definition to catch them all.
>
> FUNCTION: A chair is intended to be used to keep one's bottom
> about 14 inches off the floor, to support one's back
> comfortably, and to provide space to bend the knees.
>
>If you understand BOTH of these, then you can make sense of that list
>of structural features - seat, back, and legs - .......[ cut ]......
>........This also helps us understand how to deal with "toy chair" and
>such matters. Is a toy chair a chair? The answer depends on what you
>want to use it for. It is a chair, for example, for a suitable toy
>person, or for reminding people of "real" chairs, or etc.
a toy chair is a chair if people say it is a chair. I didn't vote
for any lexicographer to go and prescribe our language.
Whilst agreement on structure is possible by an appeal to sense-data
mediated by a culture's categories, agreement on function is less
likely. How do we know that an object has a function? Whilst the prime
use of a chair, is indeed for sitting on, this does not preclude it's
use for other functions - now don't these go back to structure? Or are
they related to intention (i.e. when someone hits you on the head with
a chair)?
Function is a dangerous word, as it pretends a closure well-suited to
the description of a well-ordered, unchanging world. I hope that this
new focus doesn't take AI down the path of American post-war sociology,
where Talcott Parson's functionalism recast the great American dream as
the 'natural' functions of all societies.
In short, nothing, no "das ding an Sich", has a function. People give
things functions. Give a polaroid to someone in a part of the world
where cameras aren't understood, and the function is not going to jump
out and reveal the essence of the object. In fact, museums of
ethnography are full of examples of industrial products put to the
strangest uses. There was also once a spate of jokes about what the
Japanese did when faced with a western water-closet, and recently a
book on Japanese etiquette has warned Westerners about using their
hankerchiefs to blow their nose on - we are told that this is not the
function of a hankerchief in Japan!
So, don't ignore the social. It's the only reality there is. Wittgenstein
may have missed your preferred point, but I think you're ignoring his
observations. Had he been alive in the '60s, I've a feeling that the
growth of sociology would have provided him with more substance for
thought than GPS and the Want-P predicate. BTW - what is the function
of a Want-P predicate, and what would a Japanese do with a hankerchief
afterwards? :-)
Times change, the world changes, knowledge-bases stagnate.
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
Date: Fri 14 Aug 87 17:37:51-PDT
From: Ken Laws <Laws@KL.SRI.Com>
Subject: Object-Oriented Programming
Those interested in programming methodology (including expert systems)
will probably enjoy reading Russell Abbott's article on "Knowledge
Abstraction" in the August issue of Communications of the ACM. It
clarifies the role of domain knowledge in programming and suggests
that object-oriented programming may be the wave of the future. This
supports the impression of Jeffrey Stone in the Spring issue of AI
Magazine ("The AAAI-86 Conference Exhibits: New Directions in Commercial
AI") that most of the expert system vendors have found rules too limiting
and are incorporating object-oriented features in future software.
A related, but somewhat different, "knowledge level" view is taken
by B. Chandrasekaran in his Fall 1986 IEEE Expert paper: "Generic
Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for
Expert System Design." While not incompatible with object-oriented
programming, his generic tasks are at a level between that of common
shell languages (rules, frames, nets, etc.) and the full specifics
of real-world domain knowledge.
I sense a new view of AI coalescing ...
-- Ken
------------------------------
Date: 14 Aug 87 07:29:36 PDT (Friday)
From: Messenger.SBDERX@Xerox.COM
Subject: Re: turing plays
>The NJ section of the NY Times of Aug 2, 1987 on page 8 had an article
on two
>plays based on Turing's life. They are: "A MOST SECRET WAR" by Kevin
Paterson
>which was performed from july 30 - aug 9 at the Philip J Levin Theater
in New
>Brunswick as part of the Rutgers Summerfest and 'BREAKING THE CODE" by
Hugh
>Whitmore scheduled to open on Broadway Nov 15."
>
>I have not read nor seen the plays.
>
>peter beck <pbeck@ardec.arpa>
I saw "Breaking The Code" at the Haymarket Theatre in London, with Derek
Jacobi (of "I, Claudius" fame) playing The Man Himself. What similarity
this bears to the Broadway version about to open I don't know.
The authors have attempted to be as factual as possible and have
interviewed everyone they can find who knew Turing. They have included
all of the remaining transcripts of Turings speeches, the most noticable
of which is the "consider a bowl of porridge" speech he gave at his old
school. His life is traced in a series of shortish episodes spanning
from his schooldays to his death, using to good effect quick scene
changing and flash back techniques. His ideas, philosophy and hopes for
the Universal Computing Machine are put across very well, although the
outright technical content is low.
For what would on the face of it appear to be a minority interest play
it attracted a good deal of critical acclaim and played to full houses
for many months. I thouroughly enjoyed it, and found it thought
provoking and not a little disturbing. The portrayal of his
homosexuality, the court case and subsequent "treatment" for his
"illness" was particularly well done. The script is a character actors
dream, and Derek Jacobi took full advantage of it - I came away feeling
that I had met Turing in all his egocentric glory.
Don't miss it.
-- Hugh
------------------------------
End of AIList Digest
********************
∂20-Aug-87 0036 LAWS@KL.SRI.Com AIList V5 #200 - TerminalTalk, GLisp References
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 20 Aug 87 00:36:45 PDT
Date: Wed 19 Aug 1987 22:23-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #200 - TerminalTalk, GLisp References
To: AIList@SRI.COM
AIList Digest Thursday, 20 Aug 1987 Volume 5 : Issue 200
Today's Topics:
Queries - AI References & Frame Language in C & Frames System &
Qualitative Analysis vs Qualitative Simulation &
Multi-Objective Search,
References - GLISP,
Humor - TerminalTalk
----------------------------------------------------------------------
Date: 19 Aug 87 21:38:00 GMT
From: ihnp4!inuxc!iuvax!tenny@ucbvax.Berkeley.EDU
Subject: AI references
I'm building an AI reference database in refer(1) format. Currently
the database has 1,000+ entries. I'm interested in receiving contributions
in refer(1) format from netlanders. For your troubles, I will mail each
contributor the database after it has stabilized and the duplicates have
been removed.
Larry Tenny
tenny@iuvax.cs.indiana.edu
tenny@iubacs (BITNET)
------------------------------
Date: Tue, 18 Aug 87 11:26:59 SST
From: joel loo <ISSLPL%NUSVM.BITNET@wiscvm.wisc.edu>
Subject: Query - Frame Language in C
I wonder anybody anywhere had built any Frame Language in C with any
approach? Either by using a preprocessor, macros, subroutine calls, or by
calling other language routines. I would like to obtain one if possible or
get in touch with some who had developed one to know the cost of building
one. I would be glad to summarize responses for the benefit of all.
Thanks in advance.
ISSLPL@NUSVM.BITNET
------------------------------
Date: 19 Aug 87 00:55:13 GMT
From: plx!titn!jordan@sun.com (Jordan Bortz)
Subject: WANTED - FRAMES SYSTEM
Does anyone have a frames based expert-system that runs under LISP
or Smalltalk? Public domain, of course, and running under Franz
would be nice.
Jordan
--
=============================================================================
Jordan Bortz Higher Level Software 1085 Warfield Ave Piedmont, CA 94611
(415) 268-8948 UUCP: (decvax|ucbvax|ihnp4)!decwrl!sun!plx!titn!jordan
=============================================================================
------------------------------
Date: 18 Aug 87 20:49:14 GMT
From: ihnp4!alberta!calgary!arcsun!roy@ucbvax.Berkeley.EDU (Roy
Masrani)
Subject: qualitative analysis vs qualitative simulation
Hi. I am wondering if anyone has a good idea of the difference
between qualitative analysis and qualitative simulation. I have
not done any extensive search on this but it seems that these
terms are typically used interchangably.
Perhaps, QA refers to a goal directed process to find
possible reasons (or explanations) for some phenomena,
whereas QS is a data driven process used to observe the
consequences of making some changes to the system?
Thanks
--
Roy Masrani, Alberta Research Council
3rd Floor, 6815 8 Street N.E.
Calgary, Alberta CANADA T2E 7H7
(403) 297-2676
e-mail: roy%arcsun.uucp%ubc.csnet@relay.cs.net
------------------------------
Date: 16 Aug 87 18:46:00 GMT
From: uxc.cso.uiuc.edu!osiris!chandra@a.cs.uiuc.edu
Subject: query:multi-objective search??
QUERY: Are there any search algorithms (like A*) that work with
multiple objectives?
I would appreciate references to papers, books etc.
Thanks in Advance,
Navin Chandra
( dchandra@athena.mit.edu )
------------------------------
Date: 17 Aug 87 06:57:11 GMT
From: mcvax!unido!ecrcvax!crcge1!benoit@seismo.css.gov (Christophe
Benoit)
Subject: Re: Looking for GLISP
In article <260@nysernic> weltyc@nic.nyser.net (Christopher A. Welty) writes:
>
> I am looking for some references to G-LISP, something written
>by a guy named Novac (sp?) at Stanford. I don't actually need G-LISP,
>but I would like to see the papers or any other references. Any help
>would be much appreciated. With enough interest I'll post to the
>list..
>
>Christopher Welty - Asst. Director, RPI CS Labs
>weltyc@cs.rpi.edu ...!seismo!rpics!weltyc
You can read the following references:
G.S Novak: "Knowledge-based programming using abstract data types".
Proc. of AAAI'83, August 1983.
"GLISP: a Lisp-based programming system with data abstraction".
A.I Magazine, Vol. 4, No. 3, August 1983.
Christophe Benoit.
benoit@crcge1.cge.fr
------------------------------
Date: Mon, 17 Aug 87 12:29:04 PDT
From: Eduard Hovy <hovy@vaxa.isi.edu>
Subject: terminaltalk (i.e., [| <-> |] )
Who introduced the faces for our bboard language
:-) and :-( and :-|
and how many others were there? (I remember first seeing them
about two or three years ago.)
In what order did these marks develop? As far as I know,
when you wanted to emphasize something, I mean REALLY
EMPHASIZE it, you capitalized...
which, pretty soon, was replaced by
the *much* *more* elegant stars...
Why?
Is emphasis enough? How about that little request for
confirmation, to make sure the audience is with you? Or
just to show a hint of reservation? But perhaps we never
use that noninteractively. (--?)
Do we need the tension-building pause and resolution? How about:
so she slowly opened the door, and inside, she saw...
>>>> Meese <<<<! >>>> Eating cheesecake <<<<!
Does the order of development of these marks mean anything?
What will terminaltalk look like in fifty years' time? Colored
words? How narrow IS (but not *is* (--?)) the bandwidth of the
terminal? Has anyone looked at these questions?
Hmm...
E
[I'm sure many of these typographic conventions have arisen
from the print world. I like to use >>this<< notation for
italics, which seems less obtrusive and easier to pair-match
than ***s. (It was my own invention, although I've had an
editor ask me if I meant "Spanish quotes.") Another emphatic
form you didn't mention was made famous by H*Y*M*A*N K*A*P*L*A*N.
Words can also be s t r e t c h e d on a terminal. Uppercase
is generally taken to mean SHOUTING, although consistent uppercase
often signifies that the sender is on an Army base. University
students often use @i(Scribe) or {\it TeX} notation, which permits
distinguishing italics from boldface but is neither graphic
(i.e., "vivid") nor sufficiently universal.
What does the future hold? Why animated 3-D color graphics, of
course. (Animated text is already a hackers' specialty. Arpanetters
can try the "finger laws@sri.com" command for a simple example.)
I'm looking forward to typing in Oriental brush strokes. See the
last CACM for an interesting article about word processing in Arabic.
I don't recall seeing smiley faces in print, although Reader's
Digest had a note about a -) tongue-in-cheek symbol about twenty
years ago. (Another typographic innovation was the interrobang,
used when ?!??!!! seems appropriate -- but far less >>precise<<,
to my way of thinking.) I once saw a book about making birthday
cakes, faces, and other graphics using red and black typewriter
symbols (including many overstruck characters) -- I still have a
bookplate that I constucted from the illustrated borders, flourishes,
and composite-character alphabets.
Someone at Stanford tried to pin down the origin of the smiley
faces, without success. I'll forward three of the more interesting
messages. -- KIL]
------------------------------
Date: Sat 22 Jun 85 18:04:53-PDT
From: Richard Treitel <TREITEL@SU-SUSHI.ARPA>
Subject: icons, fallen and risen
[Forwarded from the Stanford bboard.]
No, it was not I who proposed the icons. I heard about them in a message from
CMU, which in turn ascribed the original suggestion to someone else whose name
I completely forget. Let me resurrect a few which did not seem to get wide
use:
$ academic job available
$$ industrial job
$$$ job at a startup
[= housing available in Arizona
<= housing available in Minnesota
% bad bicycle accident
O+ feminist message
// downhill skiing
and so on.
- Richard {:-)
------------------------------
Date: 14 Jun 86 1401 PDT
From: Tovar <TVR%CCRMA@SU-AI.ARPA>
Subject: Icons
[Forwarded from the Stanford bboard.]
(Courtesy of Symbolics, Palo Alto. -- TVR)
From: Marc Le Brun <MLB@RUSSIAN.SPA.Symbolics.COM>
From: Steve Strassmann <straz@MEDIA-LAB.MIT.EDU>
Date: Wednesday, 31 August 1983 01:41-EDT
From: Mark Plotnick <MP at MIT-XX>
To: info-cobol at MIT-MC
Re: the last whole smiley face catalog :-)
Awhile back, you may remember some discussion about "smiley face
codes". Well, here are some new ones, culled from netnews
(done@teklabs, rew@hao, ksf@security, msg@houxl, and futrelle@uiucdcs).
[:|] submitter is a robot (or other appropriate AI project)
:>) submitter has a big nose
:<| submitter attends an Ivy League school
:%)% submitter has acne
=:-) submitter is a hosehead
:-(*) submitter is getting sick of most recent netnews articles and
is about to vomit
:-)8 submitter is well dressed
8:-) submitter is a little girl
:-)-{8 submitter is a big girl
%-) submitter is cross-eyed
#-) submitter partied all night
:-* submitter just ate a sour pickle
-:-) submitter sports a mohawk and admires Mr. T
:-'| submitter has a cold
:-)' submitter tends to drool
':-) submitter accidentally shaved off one of his eyebrows this morning
8:] submitter is a gorilla
0-) submitter wearing scuba mask
P-) person submitting is getting fresh
|-) submitter is falling asleep
.-) submitter has one eye
:=) submitter has two noses
:-D submitter talks too much
:-o submitter is shocked
←←←
/ \
| RIP |
|←←←←←| submitter has recently died
------------------------------
Date: Sat, 22 Jun 85 08:24:58 pdt
From: Vaughan Pratt <pratt@Navajo>
Subject: Why do icons fall?
[Forwarded from the Stanford bboard.]
Why do icons need to be "fallen?" Consider:
/|\ highway: messages about routes, rides, car repairs, etc.
/v|↑\ /↑|v\ which side to drive on: right denotes a message agreeing
with someone or taking a conformist position, left denotes
disagreement or nonconformism
--o-O-o-- plane: aviation-related messages (cheap tickets, etc.)
</\> claw: a vindictive ~=
=|= dragonfly: message about insects
\|/ plant: botany, vegetation, etc.
_\|/_ explosion: nonnuclear warfare (messages about 108 mm
recoilless slings and arrows)
|=|=| fence: message about boundaries, also for fence-post errors
db scissors up: a wanted cut, e.g. request to cut off a topic of
discussion
qp scissors down: an unwanted cut - funding cut, etc.
↑↑↑ mountains: hiking/camping/skiing messages
(↑v↑) a user of nonfallen icons, cf. #8↑)
On the one hand the existence of such icons calls into question the
appropriateness of the term "fallen." On the other hand why have
almost all of them to date been of the fallen persuasion?
-v
------------------------------
End of AIList Digest
********************
∂24-Aug-87 0038 LAWS@KL.SRI.Com AIList V5 #201 - Philosophy of Science, AI Paradigms
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 24 Aug 87 00:38:40 PDT
Date: Sun 23 Aug 1987 21:29-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #201 - Philosophy of Science, AI Paradigms
To: AIList@SRI.COM
AIList Digest Monday, 24 Aug 1987 Volume 5 : Issue 201
Today's Topics:
Comments - Programming Paradigms & Qualitative Simulation/Analysis,
Logic - Mr. S and Mr. P,
Philosophy - AI, Science, and Pseudo-Science & Natural Kinds
----------------------------------------------------------------------
Date: Mon, 17 Aug 87 08:49:36 MDT
From: shebs@cs.utah.edu (Stanley Shebs)
Reply-to: cs.utah.edu!shebs@cs.utah.edu (Stanley Shebs)
Subject: Re: Object-Oriented Programming
In article <12326542058.16.LAWS@KL.SRI.Com> Laws@KL.SRI.COM (Ken Laws) writes:
>Those interested in programming methodology (including expert systems)
>will probably enjoy reading Russell Abbott's article on "Knowledge
>Abstraction" in the August issue of Communications of the ACM. It
>clarifies the role of domain knowledge in programming and suggests
>that object-oriented programming may be the wave of the future.
Perhaps I missed the point, but I found this paper rather boring.
It didn't seem to say much new - is there really anybody that doesn't
believe programs are encrypted knowledge, and that making the knowledge
more explicit is a Good Thing? Ditto for OOP - at least in the language
community, it's started to move from fanaticism to realism. Perhaps the
AI community is just getting started on the slide to object fanaticism?
Also, some more explicit examples of what is and is not knowledge abstraction
would have been useful. In fact, the concept of "knowledge" itself is pretty
vague - is "barks(X) :- dog(X)" a piece of knowledge or not, and how crucial
is a context or not? Or putting it in a more practical way, why would a
Silogic Prolog program be considered a "knowlege program" and not a Fortran
program?
>A related, but somewhat different, "knowledge level" view is taken
>by B. Chandrasekaran in his Fall 1986 IEEE Expert paper: "Generic
>Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for
>Expert System Design." While not incompatible with object-oriented
>programming, his generic tasks are at a level between that of common
>shell languages (rules, frames, nets, etc.) and the full specifics
>of real-world domain knowledge.
This same idea may be found amidst all the glitzy results in Lenat's
Eurisko papers - heuristics are objects with their own sorts of hierarchy
and inheritance. The so-called weak methods tend to be near the root of
hierarchies, while more specialized and domain-specific heuristics are
at the leaves.
>I sense a new view of AI coalescing ...
Or at least a new view of AI tools. Some exciting and relevant papers
may be found in a book edited by Gary Lindstrom and Doug DeGroot, called
"Logic Programming: Functions, Relations, and Equations" and published by
Prentice-Hall last year (reviewed in latest Computing Reviews). The papers
speak more to language types than to AI types, but there is much food for
thought...
stan shebs
shebs@cs.utah.edu
------------------------------
Date: Fri, 21 Aug 87 11:17:46 EDT
From: Paul Fishwick <fishwick%bikini.cis.ufl.edu@RELAY.CS.NET>
Subject: Qualitative Simulation/Analysis
In reference to the question on definitions for qualitative simulation
and analysis: the two terms should not be considered identical. If we
temporarily drop the adjective 'qualitative' then we have the terms
simulation and analysis --- simulation includes analysis of data but
also includes the primary area of modeling.
On a slightly different note, though, the term 'qualitative simulation'
is somewhat difficult to define since ultimately all simulations on
digital machinery will be quantitative. Qualitative modeling and
simulation in general seem to reflect the need to represent highly abstract
models using 'qualitative' terms. These terms are mapped onto the
real number space (for instance) and a quantitative simulation ensues.
Paul Fishwick
University of Florida
------------------------------
Date: 19 Aug 87 23:27:00 GMT
From: pur-ee!uicsgva!luke@seismo.CSS.GOV
Subject: Re: mr. s & mr. p
I definitely saw this problem in the "Mathematical
Games" section of Scientific American some years ago. I am
not sure which issue it appeared in, but I am positive that
it came out between 1979 and 1982. I am 90% certain that it
can be found in the range of January 1980 to December 1981.
My first guess would be the October 1980 issue. The article
says that the problem made its debut at a party primarily
attended by mathematicians. I don't remember all the details
of the problem, but here is what I do remember:
Mr. P and Mr. S are experienced mathematicians. X and Y
are two different positive integers (For the benefit of the
reader, it has been disclosed that both X and Y are less
than or equal to 20. This constraint, however, is sup-
posedly unnecessary.) The sum of X and Y has been disclosed
to Mr. S and the product of X and Y has been disclosed to
Mr. P. Neither man knows the value of X or Y, nor are they
allowed to tell the other what their sum or product is.
They are allowed to talk to each other over the phone, and
do so after sufficient time to think about what the other
has said. The dialogue, as far as I remember is as follows:
Mr P to Mr S: I can't tell from the product what X and Y are.
(later....)
Mr S to Mr P: I can't tell what they are either.
(later....)
Mr P to Mr S: I still can't tell what X and Y are.
At this point, my memory fails me. But this is the earliest point
that I could feel comfortable with the following dialogue. I'm
pretty sure that these guys start knowing something within two more
bounces.
Mr ?? to Mr ??: Now I know what X and Y are.
(later)
Mr ?? to Mr ??: In that case, I know what X and Y are too!
According to Scientific American, the answer is 4 and 13.
If anyone finds the article, I would also like to know the
reference.
- Luke Young
Computer Systems Group
University of Illinois
+-------------------------------------------------------------+
| BITNET : LUKE@UIUCVMD CSNET: luke%haydn@uiuc.csnet |
| UUCP : {ihnp4,seismo,pur-ee,convex}!uiucuxc!uicsgva!luke |
| ARPANET : luke@haydn.csg.uiuc.edu or luke%haydn@uiucuxc |
| acoustic: office (217) 333-8164 home (217) 328-4570 |
| physical: 6-123 CSL, 1101 W Springfield, Urbana, IL 61801 |
+-------------------------------------------------------------+
------------------------------
Date: 15 Aug 87 12:29:41 GMT
From: munnari!trlamct.oz!andrew@uunet.UU.NET (Andrew Jennings)
Subject: Re: AI, science, and pseudo-science
In article <108@glenlivet.hci.hw.ac.uk>, gilbert@hci.hw.ac.UK
(Gilbert Cockton) writes:
>
> My criticism of AI is that most of the workers I meet are pretty
> ignorant of the CRITICAL TRADITIONS of ESTABLISHED disciplines which
> can say much about AI's supposed object of study. When AI folk do stop
> hacking (LISP, algebra or logic - it makes no difference, logic finger
> and algebra wrist are just as bad as the well known 'computer-bum'),
> they may do so only to raid a few concepts and 'facts' from some
> discipline, and then go and abuse them out of sight of the folk who
> originally developed them and understand their context and deductive
> limitations. What some of them do to English is even worse :-)
> --
I am afraid I cannot let this pass. It almost appears as if you view
programming as charlatan in itself ! Suffice it to say that if we
view AI as an empirical search then we have some definite criteria : either the
program works or it does not.
Sure I'm in favour of CRITICAL thought and CRITICAL appraisal of work in AI :
its just that I don't want to get buried in a pile of useless Lemmas (no doubt
generated by you and your accomplices).
Why can't you realise the simple truth : a discipline goes through STAGES of
development. First the empirical paradigm dominates, then the engineering
paradigm and last of all the theoreticians replete with armchairs.
--
UUCP: ...!{seismo, mcvax, ucb-vision, ukc}!munnari!trlamct.trl!andrew
ARPA: andrew%trlamct.trl.oz@seismo.css.gov
Andrew Jennings Telecom Australia Research Labs
------------------------------
Date: Tue, 18 Aug 87 07:51:03 PDT
From: Stephen Smoliar <smoliar@vaxa.isi.edu>
Subject: Re: Natural Kinds (Re: AIList Digest V5 #186)
In article <115@glenlivet.hci.hw.ac.uk> Gilbert Cockton
<mcvax!hci.hw.ac.uk!gilbert@seismo.CSS.GOV> writes:
>
>Whilst agreement on structure is possible by an appeal to sense-data
>mediated by a culture's categories, agreement on function is less
>likely. How do we know that an object has a function? Whilst the prime
>use of a chair, is indeed for sitting on, this does not preclude it's
>use for other functions - now don't these go back to structure? Or are
>they related to intention (i.e. when someone hits you on the head with
>a chair)?
There seems to be a bit of confusion between that the function of a perceived
object IS and what it CAN BE. There are very few concepts for which
structure and/or function are unique. The point is that both serve to
guide the classification of our perceptions. Thus, we may recognize a
chair by its structural appearance. Having done so, we can then identify
the surface upon which we should sit, how we should rest our back, where
we can tuck our legs, and so forth. On the other hand, if I walk into a
kitchen and see someone sitting on a step-stool, I recognize that he is
using that step-stool as a chair. Thus, I have made a functional recognition,
from which I conclude that he is using the top step as a seat, he is resting
his legs on a lower seat, and he is managing without a back support. Thus,
one can proceed from structural recognition to functional recognition or
vice versa.
This may be what Cockton means by "intention;" and it is most likely highly
societal in nature. However, we must not confuse the issue. We do not
classify our perceptions merely for the sake of classifying them but for
the sake of interacting with them. Depending on my needs, I may choose
to classify the chair at my dining room table as a place to sit while I
eat, a place to stand while I change a light bulb, or a weapon with which
to threaten (or attack) an intruder.
------------------------------
Date: Fri, 21 Aug 87 13:30:39 EDT
From: mckee%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: Should AI be scientific? If yes, how?
One reason is simple intellectual honesty. If AI researchers
call themselves Computer Scientists (as many of them do), they're implicitly
also claiming to be scientists. And to be perfectly blunt, any scientist
who doesn't use the scientific method is a charlatan. I'd prefer AI to be
serious science, but if you don't want to do science, I won't argue.
Misrepresentation is a different matter: if it's not science, don't call
it science.
Another, more technical reason involves the perennial question
"what is reality?", and how one verifies any answer that might be submitted.
The question is important to AI not only in its "what is intelligence, really?"
aspect, but also because any AI system that interacts with the real world
ought to have an accurate understanding of its environment. Scientific facts
are (almost by definition) the most accurate description of the universe
that we have, and scientific theories the best summaries. And the reason
this is so is because the scientific method is the best way we've yet
discovered for making sure that facts and explanations are accurate.
Besides science, the other significant field with aspirations toward
understanding reality is philosophy, which has even evolved a specialized
subfield, ontology, devoted to the question. Now I haven't studied ontology,
not because the question is unimportant, but because I think philosophical
methodology is fatally flawed, and incapable of convincing me of the substance
of any conclusions that it might obtain. I'm not interested in a discussion
of how philosophy has or has not lost its way since Kant wrote his "Prolegomena
to Any Future Metaphysics Which Will Be Able to Come Forth as Science", but
I think philosophers' methodology has kept them from being as productive of
useful understanding as they could have been.
The critical question in choice of methodology concerns verifiablity.
I'd hate to see AI researchers cast adrift in a sea of notions by thinking
that a solid intellectual structure can be built on "Philosophical Foundations",
so I'm going to attempt to concisely describe a schema of the different ways
a theory can be confirmed. I'm afraid I'll have to leave out a lot of details
and examples, but I hope you'll be able to fill in the rest of the picture
yourself. In this schema, philosophy turns out to use the weakest form of
confirmation, AI as it's currently practiced uses somewhat stronger methods,
and the natural sciences end up as strongest.
To see how this happens, think of the subject matter of a field
of study as a set of statements (observations, facts) connected by a network of
reasons. The reasons can be arbitrarily long (or short) chains of inferences.
What a researcher needs to do to "understand" the field is find a set of
axioms and inference rules that will show the explanatory relation between
any pair of observations. However, the problem is underdetermined -- there's
more than one consistent set of explanations for any set of facts. At the
very least, one can always say "Because!", and define a special rule for
each ill-behaved pair of facts. Doing this everywhere gives your theory
a very simple structure, and Occam's razor decrees that simplicity is important.
If there are always multiple theories that can explain all the observed
data, then one must turn to some confirmation methodology to distinguish
between them, and using anything but the most powerful techniques is a waste
of time and resources. They are all based on prediction -- applying
explanations to facts until one has covered all the facts, then generating
new "potential facts" from incompletely bound explanations. For philosophers,
all that can be done is to compare predictions, since the operations of
the human mind are not externally visible. Worse, the facts of experience
itself are inaccessible to more than one theorist, so that the data
can't be verified, only statements about it. And since Godel proved his
famous incompleteness theorem, we've known that no realistic model of the
world can be derived from a finite set of axioms, so there's no way of telling
if any discrepancy in predictions might be cured by the addition of "just
one more" axiom. [Beyond this my metamathematics doesn't go. It would be
interesting to know if there's any convergence at higher degrees of
metafication. I don't think so, though.]
In AI, one can trace the operation of a theory that's been instantiated
as a program, as long as there's sharing of source code and the hardware is
the same. This gives you operational confirmation as well as implicational
confirmation, since you can watch the computer's "mind" at work, pausing
to examine the data, or single-step the inference engine. The points of
divergence between multiple theories of the same phenomenon can thus be
precisely determined. But theories summarize data, and where does the
data come from? In academia, it's probably been typed in by a grad student;
in industry, I guess this is one of the jobs of the knowledge engineer.
In either case there's little or no standard way to tell if the data that
are used represent a reliable sample from the population of possible data
that could have been used. In other sciences the curriculum usually includes
at least one course in statistics to give researchers a feel for sampling
theory, among other topics. Statistical ignorance means that when an AI
program makes an unexpected statement, you have only blind intuition and
"common sense" to help decide whether the statement is an artifact of sampling
error or a substantial claim.
In the natural sciences, in addition to implicational and operational
confirmation, you'll find external confirmation. Each relation in the theory
is tested by an experiment on the phenomenon itself, often in many ways in
many experiments. It's not easy to think of statements about the content
of AI (as opposed to its practice or techniques) that *could* be validated
this way, much less hypotheses that actually *have* been experimentally
validated. Hopefully, it's my ignorance of the field that leads me to
say this. The best I can think of at the moment is "all intelligent systems
that interact with the physical world maintain multiple representations
for much of their knowledge."
To verify a hypothesis like this, one of the strategies one can
use is to build synthetic intelligent systems and then look at their
structure and performance, remembering that the engineering used during
construction is not the scientific goal. And then, to understand the
structure one would use analytic techniques, and to understand the performance
one would use behaviorist techniques. (Behaviorist anti-theory can safely
be ignored, but don't forget that their methodology allowed them to discover
learning sets when their animals became skilled at finding solutions to
new *kinds* of problems.)
Another strategy is to look at the structure and behavior of the
intelligent systems one finds in nature. One would use the same methods
to validate the behavioral descriptions as in the synthetic case, but
to study natural systems' structure one must use indirect, non-invasive means
or non-human subjects, since ethical considerations forbid destructive
testing of humans except in very special circumstances. However the problem
here is not lack of data but lack of understanding. If I believed that
more data was needed, I'd be back in the lab recording from multiple
microelectrodes, or standing in line for time on a magnetic resonance
imager (which can already give you sub-millimeter resolution in a 3-dimensional
brain image -- why wait for magnetoencephalography which won't tell you
what you want to know anyway?), instead of building and running abstract
models of neural tissue.
Oops, four times as many words as I had hoped for.
Oh well, thanks for your attention.
- George McKee
College of Computer Science [sic]
Northeastern University, Boston 02115
CSnet: mckee@Corwin.CCS.Northeastern.EDU
Phone: (617) 437-5204
Quote of the day: "It's not what you don't know that hurts you,
it's the things you know that ain't so."
- Mark Twain
------------------------------
End of AIList Digest
********************
∂24-Aug-87 0235 LAWS@KL.SRI.Com AIList V5 #202 - Conferences
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 24 Aug 87 02:35:31 PDT
Date: Sun 23 Aug 1987 21:49-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #202 - Conferences
To: AIList@SRI.COM
AIList Digest Monday, 24 Aug 1987 Volume 5 : Issue 202
Today's Topics:
Conferences - Conceptual Graphs & CAPAMI '87 Advance Program
----------------------------------------------------------------------
Date: 21 August 1987, 08:42:59 EDT
From: Anand Rao <ANAND@ibm.com>
Subject: Conference - Conceptual Graphs
SECOND ANNUAL WORKSHOP ON CONCEPTUAL GRAPHS
IBM Paris Scientific Center
2, 3, 4 September 1987
The first workshop on conceptual graphs was held at the IBM Systems
Research Institute in Thornwood, New York, in August 1986. As a result
of that workshop, a number of the participants have been writing
chapters for a forthcoming book, Conceptual Graphs for Knowledge
Systems, edited by John Sowa, Norman Foo, and Anand Rao. It should
appear in print in early 1988. This year, another workshop will be held
at the IBM Paris Scientific Center from September 2 to 4, 1987. The
conference chairman is Dr. Jean Fargues. Following is a preliminary
list of speakers and topics:
James BALDWIN & Anca RALESCU, University of Bristol (UK),
A Conceptual Graph Tool-kit Written in FRIL.
Henri BERINGER, Electronique Serge Dassault Corp (France),
Conceptual Graphs in Prolog.
Kathleen DAHLGREN, IBM Los Angeles Scientific Center (USA),
Commonsense Knowledge as Lexical Knowledge.
Jean FARGUES, IBM Paris Scientific Center (France),
Towards Understanding French Texts Using Conceptual Graphs.
Norman FOO, Anand RAO, & John SOWA, Sydney University and IBM
Systems Research Institute (Australia & USA),
An Abstract Machine for Processing Conceptual Graphs.
Brian J. GARNER, Deakin University (Australia),
Actor Implementations for Cybernetic Reasoning.
Pavel KOCURA, Heriot-Watt University (Scotland),
Thematic Relations Hypothesis and Conceptual Graphs.
Juan MORAN, Educational Testing Service, Princeton (USA),
Modeling the Acquisition of Expertise using Conceptual Graphs.
Jean-Francois NOGIER, Paris VII University, IBM Paris SC (France),
French Natural Language Generation from Conceptual Graphs.
Massimo POESIO, University of Hamburg (Germany),
Modified Case Frame Parsing for a Speech Understanding System.
Stephen REGOCZEI, Trent University (Canada),
Nested Contexts: Stating What We Think They Mean.
John SOWA, IBM System Research Institute (USA),
Contexts and Definite References.
Peter STOCKINGER, C.N.R.S (France),
Conceptual Representations for NL Dynamic and Static Situations.
Anyone who is interested in attending should write to,
Ms. Martine Torres
2nd CG Workshop
IBM Paris Scientific Center
36 avenue Raymond Poincare
73116 Paris, France
In the letter to Ms. Torres, please note the answers to the following
questions:
1. Would you like to give a talk? On what topic?
2. Do you need a hotel reservation? Very comfortable at 700 F per
night or good average at 500 F per night?
3. What are your arrival and departure dates?
For 1988, there are tentative plans for two workshops -- one in
Australia, probably in July, and another in Minneapolis either during
or after the AAAI conference in August.
------------------------------
Date: Mon, 17 Aug 87 09:45:21 CDT
From: dyer@stilton.wisc.edu (Chuck Dyer)
Subject: Conference - CAPAMI '87 Advance Program
CAPAMI '87
1987 WORKSHOP ON COMPUTER ARCHITECTURE FOR
PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Seattle, Washington
October 5 - 7, 1987
CAPAMI '87 will focus on new architectures and associated algorithms for
computer vision, image processing, and artificial intelligence. This
workshop is a successor of the Computer Architecture for Pattern Analysis
and Image Database Management workshops. The program, given below, consists
of high-quality refereed papers, invited speakers, and panel sessions on
the design and implementation of parallel architectures and algorithms for
pattern analysis and machine intelligence. Invited speakers are: Tom
Knight, MIT, George Reeke, Rockefeller University, and Masatsugu Kidode,
Toshiba.
____________________________________________________________________________
WORKSHOP ORGANIZATION
General Chair: Steve Tanimoto, University of Washington
Program Chair: Chuck Dyer, University of Wisconsin
Finance Chair: Yongmin Kim, University of Washington
Local Arrangements Chair: Charlotte Lin, Boeing
Program Committee: Chris Brown Jim Little
Michael Duff Azriel Rosenfeld
Bob Haralick Jorge Sanz
Ramesh Jain Len Uhr
John Kender Jon Webb
H. T. Kung
____________________________________________________________________________
REGISTRATION
Mail check payable to CAPAMI '87 (U.S. currency only) to:
CAPAMI '87 Registration
c/o Ms. Lori Tollefsen
Department of Computer Science, FR-35
University of Washington
Seattle, WA 98195
IEEE Member Non-Member Student
Registration
Before Sept. 8 $110 $140 $60
After Sept. 8 $135 $170 $80
Banquet $ 30 $ 30 $30
Note: Student fee includes proceedings. Requests for refunds must be
received in writing before Sept. 15. Cancellation fee is $15.
____________________________________________________________________________
HOTEL RESERVATION INFORMATION
Reservations must be received by Sept. 14. Mention CAPAMI '87 when making
reservations. To guarantee your reservation for late arrival (after 6 PM),
either a check for one night's lodging or appropriate credit card information
must be given to the hotel.
Westin Hotel
1900 Fifth Avenue
Seattle, WA 98101
(206) 728-1000 / (800) 228-3000 / Telex: 152900
____________________________________________________________________________
FOR MORE INFORMATION
CAPAMI '87
c/o IEEE Computer Society
1730 Massachusetts Ave., N.W.
Washington, DC 20036-1903
(202) 371-0101
____________________________________________________________________________
ADVANCE PROGRAM
MONDAY, October 5
9:00 - 10:00 Invited Talk: TBA
Tom Knight, Massachusetts Institute of Technology
10:00 - 10:30 Coffee Break
10:30 - 12:10 Session 1: Hypercube-based Architectures and Algorithms
Hypercube and Shuffle-Exchange Algorithms for Image
Component Labeling, R. Cypher, J. L. C. Sanz, and L. Snyder
How to Program the Connection Machine for Computer Vision,
J. J. Little, G. Blelloch, and T. Cass
Optical Cellular Logic Architectures based on Binary Image
Algebra, K. S. Huang, B. K. Jenkins, and A. A. Sawchuk
A Parallel Algorithm for Region Labeling, M. H. Sunwoo, B.
S. Baroody, and J. K. Aggarwal
12:10 - 1:45 Lunch Break
1:45 - 3:25 Session 2: Shared-Memory Algorithms
Parallel Algorithms for Dynamic Systems with known
Trajectories, L. Boxer and R. Miller
Shared Memory Algorithms and the Medial Axis Transform, S.
Chandran and D. Mount
Formula Dissection: A Parallel Algorithm for Constraint
Satisfaction, S. Kasif, J. H. Reif, and D. D. Sherlekar
On the Complexity of Incremental Parallel Computations in
Artificial Intelligence, A. Delcher and S. Kasif
3:25 - 4:00 Coffee Break
4:00 - 5:40 Session 3: Linear and Pipeline Architectures and Algorithms
Progress on the Prototype PIPE, R. Goldenberg, W. C. Lau, A.
She, and A. M. Waxman
Heuristic Scheduling Algorithms for PIPE, C. V. Stewart
and C. R. Dyer
Computing the Hough Transform on a Scan Line Array
Processor, A. L. Fisher and P. T. Highnam
A VLSI Implementation of PPPE for Real-Time Image Processing
in Radon Space - Work in Progress, W. B. Baringer, B. C.
Richards, R. W. Broderson, J. L. C. Sanz, and D. Petkovic
TUESDAY, October 6
9:00 - 10:00 Invited Talk: Selection and Perceptual Categorization: New
Architectures for Nonalgorithmic Networks
George Reeke, Rockefeller University
10:00 - 10:30 Coffee Break
10:30 - 12:10 Session 4: Mesh-based Algorithms
Parallel Algorithms for Line Detection on a Mesh, C. Guerra
and S. Hambrusch
Solving the Depth Interpolation Problem on a Parallel
Architecture, D. J. Choi and J. R. Kender
The Hough Transform has O(n) Complexity on SIMD n x n Mesh
Array Architectures, R. Cypher, J. L. C. Sanz, and L.
Snyder
EREW PRAM and Mesh Connected Computer Algorithms for Image
Component Labeling, R. Cypher, J. L. C. Sanz, and L. Snyder
12:10 - 1:45 Lunch Break
1:45 - 3:25 Session 5: Pyramid and Hierarchical Architectures and
Algorithms
Real Time Synchronization in a multi-SIMD Massively
Parallel Machine, P. Clermont and A. Merigot
Iconic Image Analysis with the Pipeline Pyramid Machine
(PPM), P. J. Burt and G. S. van der Wal
Dynamically Quantized Pyramids for Hough Vote Collection,
R. P. Blanford
A VLSI Architecture for a Neurocomputer using Higher-Order
Predicates, R. Geller and D. Hammerstrom
3:25 - 4:00 Coffee Break
4:00 - 5:30 Panel: Which Parallel Architectures are Useful/Useless for
Vision Algorithms
Moderator: Jorge Sanz, IBM Almaden Research Laboratory
6:00 - 10:00 Banquet: Boat cruise on Puget Sound to Blake Island with a
Northwest-Indian-style, Alder-smoked salmon dinner
WEDNESDAY, October 7
9:00 - 10:00 Invited Talk: Image Processing Machines in Japan
Masatsugu Kidode, Toshiba Research and Development Center
10:00 - 10:30 Coffee Break
10:30 - 12:10 Session 6: Mesh-based Architectures and Algorithms
Geometric Algorithms on HMESH Architecture, S. B. Chalasani
and C. S. Raghavendra
Polymorphic-Torus: A new Architecture for Vision Computation,
H. Li and M. Maresca
The OFC Enhanced Mesh Architecture: A Performance Study, A. M.
Jrad and R. W. Hall
Image Processing on VLSI Architectures with Reduced Hardware,
H. M. Alnuweiri and V. K. P. Kumar
12:10 - 1:45 Lunch Break
1:45 - 3:00 Session 7: Loosely-Coupled MIMD Architectures and Algorithms
Some Aspects of an Image Understanding Database for an
Intelligent Operating System, F. Weil, L. Jamieson, and E.
Delp
HBA Vision Architecture: Built and Benchmarked, R. S. Wallace
and M. D. Howard
A Binary-Image Processing Method using Run Length
Representation, K. Nakabayashi
3:00 - 3:30 Coffee Break
3:30 - 5:00 Panel: Research on Pattern Analysis and Machine Intelligence
Architectures in Japan and the U.S.
Moderators: Masatsugu Kidode, Toshiba Research and
Development Center, and Steven L. Tanimoto, University
of Washington
______________________________________________________________________________
------------------------------
End of AIList Digest
********************
∂24-Aug-87 0416 LAWS@KL.SRI.Com AIList V5 #203 - Spang Robinson Review & TerminalTalk
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 24 Aug 87 04:15:58 PDT
Date: Sun 23 Aug 1987 21:53-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #203 - Spang Robinson Review & TerminalTalk
To: AIList@SRI.COM
AIList Digest Monday, 24 Aug 1987 Volume 5 : Issue 203
Today's Topics:
Queries - Applied AI Reporter & CL Planner & Rule-Based Software &
Language-Independent Text on AI,
Comments - TerminalTalk,
Review - Spang Robinson Report on AI, Vol. 3, No. 8
----------------------------------------------------------------------
Date: 22 Aug 1987 06:56:55 PDT
From: Laurence I. Press <SWG.LPRESS@C.ISI.EDU>
Subject: Applied AI Reporter??
I have heard of a publication called the Applied AI Reporter, from the
University of Miami. Can someone give me an address or phone number for
more information on the publication?
Thanks,
Larry
------------------------------
Date: Thu, 20 Aug 87 16:56:29 EDT
From: Kenneth Basye <kjb%cs.brown.edu@RELAY.CS.NET>
Subject: Request for CL planner
I'm looking for a simple Nonlin style planner written in Common Lisp. Source
is essential; documentation would be wonderful, but is not neccesary.
Thanks very much,
Ken Basye
UUCP {ihnp4|allegra|decvax}!brunix!kjb
ARPA kjb%cs.brown.edu@relay.cs.net
CSNET kjb@cs.brown.edu
U.S. MAIL Ken Basye
Box 1910
Dept. of Computer Science
Brown University
Providence, RI 02912
------------------------------
Date: 22 Aug 87 23:30:52 GMT
From: RAMESH-T@OSU-20
Subject: rule-based software
From: journeyman <ramesh-t@OSU-20>
I am interested in obtaining general comments from any of you
who is knowledgeable about rule based systems software, currently available
in the market. We are looking for software that satisfies most or all of the
following requirements :
1. Compatible with commonly available PC's (IBM, Mac)
2. User friendly (not a must if there are other good features).
3. Includes good display facilities, or allows display utilities to be
programmed in.
Here's a list of available software that we've heard of but don't know
much about :
*ADVISOR
*GURU
*RULEMASTER
*1st Class
*WIZDOM XS
*WIZDOM PX
*SAGE
*ESP ADVISOR
*EXPEROPS5
*EXPERTEDGE
*EXSYS
*INSIGHT 1.2
*INSIGHT 2/INSIGHT 2+
*MACKIT
*MICROEXPERT
*PERSONAL CONSULTANT
*TOPS1
*WISDOM XS
*XPER
*XSYS
Any information would be welcome (general, availability, prices, applicability,
will you give it to us free, etc).
ramesh
------------------------------
Date: 21 Aug 87 09:10:32 GMT
From: mcvax!ukc!its63b!dcl-cs!strath-cs!murray@seismo.css.gov
(Murray Wood)
Subject: A good language-independent text on AI ?
I am preparing a set of 24 introductory lectures on AI aimed at presenting
the main concepts, techniques and applications with little regard for
theory. The students are in their second year having only programmed in
Pascal. Although I intend to spend 4/5 lectures discussing the relative
merits of Prolog and Lisp there is no time to actually program in either of
these languages. The course is therefore intended to be programming
language independent. I would like to recommend a textbook to the students
and be able to follow it quite closely in the lectures - can anybody
suggest a good book, ideally costing less than 20 pounds (30 dollars) ?
My current intention is to use the book by Shirai and Tsujii 'Artificial
Intelligence: Concepts, Techniques and Applications'. Does anybody have any
experience and / or views on this book for such a course ?
Thank You
Murray
--
ARPA: murray%cs.strath.ac.uk@ucl-cs.arpa, murray@cs.strath.ac.uk
UUCP: murray@strath-cs.uucp, ...!seismo!mcvax!ukc!strath-cs!murray
JANET: murray@uk.ac.strath.cs
------------------------------
Date: Thu, 20 Aug 87 13:02:22 CDT
From: "Michael T. Gately" <gately%resbld%ti-csl.csnet@RELAY.CS.NET>
Subject: Terminal Talk
With referenc to TERMINAL TALK, another effective
device for highlighting a portion of a message
is _to_surround_it_with_underscores_. I use this
when typing book references without a text formatter.
Another interesting notation is the order of the
characters in a serial interrobang. I feel that there
is a definate difference between ?! and !?. The first
would be appropriate when describing (with disbelief)
a question someone asked. The second is used when
questioning a statement someone made.
------------------------------
Date: 21 Aug 87 17:12:25 GMT
From: petsd!hjuxa!uucp@rutgers.edu
Subject: Re: terminaltalk
I can shed no light on most of Hovy's questions, but I think I can
claim priority on the use of underscores as delimiters:
He's reading _Moby Dick._ He says it's _very_ boring.
An earlier format uses underscores throughout; e.g.,
I need a copy of _The_Art_of_Computer_Programming_, Volume 4.
Personally I prefer *asterisks* for emphasis and _underscores_ for
other applications of italics.
By the way, recently my three-year-old son told me excitedly that there
was a kitty on my home terminal. Actually it was a C-R (carriage-return)
glyph, with the C slightly higher than the R and running into it like a
cat's tail. Can anybody think of a use for such "kitties"?
--
Col. G. L. Sicherman
...!ihnp4!odyssey!gls
------------------------------
Date: Thu, 20 Aug 1987 21:21 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Summary of Spang Robinson Report on Artificial Intelligence
(bm695)
Summary of Spang Robinson Report on Artificial Intelligence
August 1987, Volume 3, No. 8
"AAAI-87: Underwhelming" is the front page leader.
This title is expounded upon by the statment, "There was little
research, or product drama to speak of; no blockbuster announcements or
revolutionary changes. ... Almost uniformly, products presented
were reiterations and refinements."
Teknowledge revealed that the time between initial contact and final
sale went from six to twelve months.
There is also a section on suggestions for future AAAI conferences.
Four hundred people attended the neural network tutorial.
(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?(?
Carnegie Group: A Company in Transition
Carnegie Group will announce the appointment of a new president, Dennis
Yablonsky. He used to be president and Chief Operating Officer
at Cincom. Carnegie group has a relationship with CMU to serve as
the technology transfer outlet for applied computing research.
Carnegie Group will now be selling Knowledge Craft in a series of
modules.
The company is still unprofitable, it is declaring a positive cash flow.
Some of its's projects include
a) system to automate the design of digital circuits
b) a system for assembly path programming
c) a shop planning and scheduling system for Boeing
d) a forger shop scheduler for Ellwood City Forge Co.
e) an autombobile troubleshooting diagnostic system that will be
deployed across Ford Motor's system car dealership network.
f) a telemarketing system
g) a system for a financial insitutution to analyze English language
news stories, financial statements and bank telexes.
&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑&↑
SHORTS (including announcements at the AAAI-87)
TI now has a $1900 utility to convert a Personal Consultant Plus
expert ssytem to one that is embedable in C and runable under UNIX.
Keystone is an expert system can port applications built on Intellicorp's
2.1 to a 286 for delivery.
Expertelligence's Prototyper puts an object or Smalltalk like structure
around Lisp.
Knowledge Garden exhibited a tool that uses hypertext and expert systems.
Knowledge maker is a an $99 inductive-rule generating system that geneerates
rules for KnowledgePro, Insight 2+, M.1 and Micro Expert.
If/then is a $70.00 expert system that runs on top of Lotus. (A product
review for this is also in this Spang Robinson Report.)
Intellicorp has announced a ten percent reduction in staffing and declared
that it will report a substantial loss for the quarter and fiscal year
ending June 30, 1987.
Teknowledge will be selling several products under a Copernicus architecture
including a development Facility, deelivery facility, database integration
system, COBOL integration system and TeKSolutions Applicatin Pakcks.
Artificial Intelligence Corporaiton has formed a consortium of corporations
to develop an expert system shell for IBM mainframes.
APEX has a Computed Text program that generates end user reports from
Common LISP products.
Lucid Common Lisp will be ported to HP's 9000 Series 300 and 800 computers.
Aion and Arthur Anderson will jointly deelop a high-performance version of
Aion's application expecution system. MSA Advanced Manufacturing Inc.
has signed an agreement allowing it to use Aion products to develop
manufacturing expert systems.
Primefax of San Antionio, TX will be developing repair support software.
Nihon Digital Equipment Corporaiton will be distributing Artificial
Intelligence Technologies' AIT Lisp TOOLKIT.
Sun and Schlumberger will be jointly developing AI software for the SUNS.
Sun introduced a Symbolic Programming Environment for its Sun 3 and Sun 4
workstations that will provide the powers of a dedicated LISP system while
remaining a general purpose work station.
Inference Corporationa nd Lockheed-California have introduced a system
to audit medical claims.
Symbolics has introduced a software package that enable susers to deliver
applications packages on its work stations.
Gensym Corporation unveiled a real-time expert system for process control
applications. Prices start at $36,000.
BBN Advanced Computers has a LISP for its Butterfly parallel processing
system costing $12,000.
Quantun InKNOWvations Corporation is sellling a knowledge-base environment
for 386 based machines and includes a relational database.
Bookman Consulting introduced a system to assess the technical knowledge
and proficiency of computer programmers.
-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[-[
New Bindings
Teknowledge named Peter Weber new president and executive officer.
Michael P. Coleman, formerly vice president of Marketing and sales and
McDonnell Douglas Computer Sales was named IntelliCorp vice president
of marketing and sales.
Spencer Leyton was named vice president of business development for
Symantec Corporation of Cupertino, CA. Was vice president of
sales and business development at Borland International.
Randy J. Raynor is manager of development for Inference Corporation
(was vice president of product development at UCCEL)
------------------------------
End of AIList Digest
********************
∂28-Aug-87 0209 LAWS@KL.SRI.Com AIList V5 #204 - S and P Puzzle, AAI Reporter, Msc.
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 28 Aug 87 02:09:13 PDT
Date: Fri 28 Aug 1987 00:10-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #204 - S and P Puzzle, AAI Reporter, Msc.
To: AIList@SRI.COM
AIList Digest Friday, 28 Aug 1987 Volume 5 : Issue 204
Today's Topics:
Queries - GoldWorks & "If-Then" Rules & Conceptual Graphs &
Concept Definitions for Object Classification &
Modeling Creativity & How to Measure Learning Ability?,
Logic - Mr. S and Mr. P,
Review - Understanding AI,
Binding - Applied AI Reporter
----------------------------------------------------------------------
Date: Tue, 25 Aug 87 09:50 EDT
From: TAM%MCOIARC.BITNET@wiscvm.wisc.edu
Subject: GoldWorks by Gold Hill Computers
We have recently purchased GoldWorks expert system development
package, and have just returned from Gold Hill's 5-day training course.
I was wondering if anyone out there used GoldWorks and what is there
opinion of it compared to other PC-based expert system shells. I am
particularly interested in real applications using GoldWorks.
Thanks,
Paul Tam
Medical College of Ohio
bitnet: TAM@MCOIARC
------------------------------
Date: 24 Aug 87 16:38:52 +1000 (Mon)
From: "ERIC Y.H. TSUI" <munnari!aragorn.oz!eric@uunet.UU.NET>
Subject: Request for a set of "if-then" rules
I would like to have access to a set (or sets) of in-use "if-then" rules.
I am encoding a General Purpose Inference Engine (GPIE) for a conceptual
graph (J.F. Sowa's book on Conceptual Structures) system and would like to
ask for a set of "if-then" rules currently used in some typical rule-based
systems. Something between 50 to 200 rules are quite appropriate for testing.
These rules, presumably not written in the CG notation, will be encoded in
the CG formalism and then used for testing the GPIE. The rules,
encoded in the CG notation, can be returned to the original source.
Meta-rules, self-referencing rules and other non base level rules are also
sought, though they may not incorporated into the testbed.
Rules are most preferred in areas like financial and auditing domains,
diagnostic systems, planning and intelligent help/advisory systems.
Others are also welcome.
Does anyone have access to such a set of rules ?
Can someone provide pointers to locate such rules ?
Any other advise ?
Eric Tsui eric@aragorn.oz
Division of Computing and Mathematics
Deakin University
Victoria 3217 AUSTRALIA
------------------------------
Date: 25 Aug 87 10:26:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: conceptual graphs
>
> Date: 21 August 1987, 08:42:59 EDT
> From: Anand Rao <ANAND@ibm.com>
> Subject: Conference - Conceptual Graphs
>
>
> SECOND ANNUAL WORKSHOP ON CONCEPTUAL GRAPHS
>
> IBM Paris Scientific Center
> 2, 3, 4 September 1987
>
> ....
Regarding this recent announcement on AIlist: Are there any articles
currently in print on this topic? Eg, Proceedings of the 1st
conference? I'd be very grateful for any pointers you can give me on
this. Tutorial/basic-overview type articles are especially welcome.
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: 27 Aug 87 12:20:08 +1000 (Thu)
From: "BETTY CHENG" <munnari!aragorn.oz!cheng@uunet.UU.NET>
Subject: Request for a set of Concept Definitions for Object
Classification
I am doing a project on Concept Classification and would like to know
whether anyone has developed, have access to or can provide pointers to
locate a set of concept definitions for real world knowledge.
For example, definitions for physical objects like bus, vehicle,
clothes etc. Definitions for primitive acts are also
sought. For example, definiton for 'open', 'close', 'eat' etc.
These definitions of concepts will be encoded in the conceptual graph
(c.f. Sowa's book on Conceptual Structures) formalism and an interactive
classification program, currently being implemented, will help to
identify instances of existing concepts, insert new concepts into the
knowledge base and in the process of the executing the above two functions,
perform exact and partial matching on existing concepts.
Ideally, these definitions are already presented in a frame-based or
in an attribute-value pair form. However, other forms of presentations will
certainly be considered.
Could anyone possess such a set of definitions of concepts ?
Any idea on where I can locate a set of these definitions ?
Any comment/criticism/idea ?
[A summary of the result of the responses will be posted, given that
there exists sufficient interest in the readership.]
Betty Cheng cheng@aragorn.oz
------------------------------
Date: 27 Aug 87 03:35:52 GMT
From: harnad@princeton.edu
Subject: Modeling Creativity
I would be grateful to receive references to work on modeling
creativity (in any domain -- verbal, mathematical, artistic, motor). I
am also interested in relevant experimental and observational work.
Stevan Harnad harnad@mind.princeton.edu (609)-921-7771
--
Stevan Harnad harnad@mind.princeton.edu (609)-921-7771
------------------------------
Date: 27 Aug 87 20:05:40 GMT
From: berke@locus.ucla.edu
Subject: How to measure learning ability?
I am involved with a project part of which is to teach mime to
learning-disabled children. I maintain that: Mimicry behavior
is integral to or forms the basis for animal learning. Directly
training mimicry should therefore directly train learning
ability.
This is a simple, to me, an obvious claim. The question is, how
to determine whether it is true? If you can answer the following
simple question, I would appreciate hearing from you:
Question 1: Are there any measures of general learning ability
that are commonly accepted? If not, what measures of learning
ability do you use (or know of), whether they purport to measure
verbal learning, skill acquisition, or any other behavior that
can be classified as learning?
In "cognitive science" and related fields there is a lot of hubub
currently about new and better brain models. I have my own which
I call Network Recombination. I refer to "learning and memory" as
a unified process of learning/memory because of the implications
of my model. If you ascribe to a model of how brain activity
produces the phenomenon of learning/memory (or "learning" or
"memory" separately), I would appreciate an answer to the
following question:
Question 2: Does your model make any predictions about
intermodal transfer of abilities? Specifically, say a subject's
verbal skills are poor and so she does poorly on vocabulary tests
which Thorndike (in Human Learning, 1931, p.174) considers "an
excellent intelligence test." Say I now train the subject in
physical skills to increase discrimination, analysis, and
creative abilities (defined primitively below). How much will
these abilities transfer to verbal or quantitative skills? What
form will the transfer take? Or will there be none?
Discrimination ability - seeing different parts in observation
Analytical ability - breaking things into parts
Creative ability - putting parts into new wholes
I appreciate all opinions and advice, especially from people who
have worked with learning-disabled children (and even more from
people to whom this posting seems based on my ignorance and
misconceptions). But I would like to specifically request those
putting forth "mind models" for predictions of their models. I
would like to QUANTIFY increase in general learning ability, and
so the predictions of specific models with specific properties is
necessary.
If there is no such thing as general learning ability, then I
would like to QUANTIFY transfer of abilities from physical to
verbal or intellectual skills, or verify that there is none.
Can you help me?
I have posted this to several news groups. Perhaps it would be
best to reply to me in e-mail, or to decide on a single group for
follow-ups, perhaps sci.research. It has little traffic.
Thank you in advance for all replies.
Peter Berke
berke@cs.ucla.edu
(213) 394 - 6797
------------------------------
Date: Mon, 24 Aug 87 13:37:25 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Mr. S and Mr. P
I don't know the full history of the Mr. S and Mr. P puzzle, but I'm
sure it goes back a long way. I first saw it when Will Dowling of
Drexel University sent it to me with the suggestion that it might be
easy to express the solution in Prolog. I posted it to Prolog-digest
in November or October of 1984. There were several follow up posting,
some of which discussed its history. You could explore the prolog
digest archives at SUMEX-AIM for more information.
Here is the puzzle as it was told to me:
There are 2 integers n and m between 3 and 98 inclusive. Mr. S has
been told their sum and Mr. P their product. The following truthful
conversation occurs:
P: I don't know n and m.
S: I knew you didn't. Neither do I.
P: Now I know them!
S: Now I do, too!!
What are the values of n and m?
By the way, the answer to this version of the puzzle is NOT 4 and 13!
I won't spoil anyone's fun by saying what the answer is, or by
describing how one determines what it is or is not.
This is a simple example of a general problem which requires one to
model and reason about the beliefs and knowledge of other agents, a
topic that has been receiving some attention lately. Halperin (IBM)
and Moses (Stanford) have been using a similar puzzle (variously
called "the cheating wives" and "the dirty children") in their recent
work.
Tim
------------------------------
Date: 23 Aug 87 20:41:00 GMT
From: uxc.cso.uiuc.edu!osiris!goldfain@a.cs.uiuc.edu
Subject: Re: A good language-independent text on
To: murray@cs.strath.ac.uk
Subject: Good AI Survey Book
The book: Understanding Artificial Intelligence, by: Henry C. Mishkoff,
published by Howard W. Sams & Company, a division of MacMillan Inc. (4300
West 62nd Street, Indianapolis, IN 46268 USA) seems to have about the emphasis
and level that you describe. You may want to check into it. Here in the
U.S., I got it for about $15.
It was written for industry audiences more than university students, but you
may consider this a plus, judging from your "application" emphasis. In
addition to a high-quality typesetting, it has a bibliography and glossary in
the back. It's 250 pages. (NOTE: I have no vested interest in whether or not
the author sells a single copy.)
- Mark Goldfain
(ARPA: goldfain@osiris.cso.uiuc.edu)
------------------------------
Date: 24 Aug 87 18:51:13 GMT
From: gatech!pitt!psuvax1!cisunx!wvucsb.UUCP!aw@seismo.CSS.GOV (Ajay
Waghray)
Subject: Re: Applied AI Reporter??
> Approved: ailist@stripe.sri.com
> Xref: wvucsb comp.ai.digest:300
>
> I have heard of a publication called the Applied AI Reporter, from the
> University of Miami. Can someone give me an address or phone number for
> more information on the publication?
>
> Thanks,
> Larry
> -------
The Applied AI Reporter published from the Intelligent Computer
Systems Research Institute, University of Miami.
I do not know any phone numbers but the address for editorial correspondance
is ::
Editor
P.O. Box 248235
Coral Gables
FL 33124
Address for subscriptions and inquiries is ::
ICS RESEARCH INSTITUTE
P.O. Box 1308-EP, Fort Lee
NJ 07024
Hope this helps
Ajay
----
{allegra, cadre, bellcore, psuvax1}!pitt!wvucsb!aw
------------------------------
Date: 25 Aug 87 17:17:22 GMT
From: root@sgi.sgi.com (Superuser)
Subject: Re: Applied AI Reporter??
It is published by the Intelligent Computer Systems Research
Institute, 421C Jenkins Bldg., Stanford Drive, Coral Gables,
FL 33124 (305) 284-5195 BITNET dumics@ser
Mike Bender
sgi!wdl1!mhb
mhb@wdl1.UUCP
------------------------------
Date: Wed, 26 Aug 87 09:47:12 PDT
From: lambert@cod.nosc.mil
Subject: applied ai reporter
Larry,
In response to your request in AIList:
Applied Artificial Intelligence Reporter
Intelligent Computer Ssytems (ICS) Research Institute
University of Miami
P.O. Box 248235
Coral Gables, FL 33124
$98.00 per year.
Dave
------------------------------
End of AIList Digest
********************
∂28-Aug-87 0338 LAWS@KL.SRI.Com AIList V5 #205 - Philosophy
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 28 Aug 87 03:38:39 PDT
Date: Fri 28 Aug 1987 00:19-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #205 - Philosophy
To: AIList@SRI.COM
AIList Digest Friday, 28 Aug 1987 Volume 5 : Issue 205
Today's Topics:
Philosophy - Wittgenstein and Natural Kinds & Fear of Philosophy &
Should AI be Scientific? & Philosophy of Science, AI Paradigms
----------------------------------------------------------------------
Date: 24 August 1987, 23:09:52 EDT
From: john Sowa <SOWA@ibm.com>
Subject: Wittgenstein and natural kinds
Wittgenstein's basic point is that the most important concepts
of ordinary language cannot be defined by a set of necessary and
sufficient conditions. No matter whether you try to give structural
definitions or functional definitions, you cannot state a precise set
of conditions that will admit all relevant instances while ruling out
all irrelevant ones.
In my book, Conceptual Structures (Addison-Wesley, 1984), I made the
distinction between natural types (or kinds) and role types. Something
can be recognized as belonging to a natural type by its own properties.
Examples include MAN, WOMAN, CAT, DOG, NUMBER, or NAIL. A role type
can be recognized only by relationships to something outside of itself:
FATHER, LAWYER, PET, WATCHDOG, QUOTIENT, or FASTENER. The number 4,
for example, can be recognized as a number in isolation, but as a
sum, divisor, quotient, product, etc., only in relation to something
else. A tee shirt had the slogan "Food is the only edible thing in the
universe." That is true by definition, since FOOD is a role type,
defined by its role of being considered edible.
Yet that distinction does not solve Wittgenstein's problem. Every
culture has its own standards of what is considered edible. In
Scandinavia, there is a rotten fish delicacy that requires a mound of
raw onions and garlic to prepare the taste buds and liberal quantities
of aquavit to wash it down. Even for a particular individual, degree of
hunger shifts the boundary line between the roles of FOOD and GARBAGE.
Even mathematical concepts have shifting definitions. Consider what
happened to the concept of number as rational number, irrational number,
complex number, transfinite number, etc., were introduced. If you try
to give a precise definition today, somebody tomorrow is sure to invent
some kind of hyper-quaternary-irresolute number that will violate your
definition, yet be so similar to what mathematicians like to call a
number that they would not want to exclude it.
To handle Wittgenstein's notion of meaning as use, I introduced
schematic clusters (in Section 4.1 of Conceptual Structures) as an
open-ended collection of schemata (or frames) associated with a
concept type. Each schema would represent one pattern of use (or
perspective) for a type, but it would not exhaust the complete meaning
of that type. There would always be the possibility of some new
experience that would add new schemata to the cluster. Consider the
concept ADD: one schema would show its use in arithmetic. But if
someone wants to talk about adding a line to a file, another schema
could be added to the cluster for that use. And then one should add
a new schema for adding schemata to clusters. Every schema in a
cluster represents one valid use of the concept type. The meaning
is determined not by any definition, but by the collection of all
the permissible uses, which can grow and change with time.
Does that solve the problem? Maybe, but we still need criteria
for determining what kinds of uses can legitimately be added to a
cluster. Could I say "To add something means to eat it with garlic
and onions"? What are the criteria for accepting or rejecting a
proposed extension to a concept's meaning?
John Sowa
------------------------------
Date: 25 Aug 87 08:33:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: Fear of philosophy
> From: mckee%corwin.ccs.northeastern.edu@RELAY.CS.NET
> Subject: Should AI be scientific? If yes, how?
>
> ....Besides science, the other significant field with aspirations toward
> understanding reality is philosophy, which has even evolved a specialized
> subfield, ontology, devoted to the question. Now I haven't studied
> ontology, not because the question is unimportant, but because I
> think philosophical methodology is fatally flawed, and incapable of
> convincing me of the substance of any conclusions that it might
> obtain. ...I think philosophers' methodology has kept them from
> being as productive of useful understanding as they could have been.
It's worth noting that the rest of McKee's message consists of nothing
but philosophizing, with particular emphasis on epistemology and the
philosophy of science. Just for instance, his claim, in passing, that
it is verifiability that distinguishes the scientific method, simply
echoes the logical positivist school of thought.
No one doubts that there is a lot of silly philosophy out there, but
simply to ask the questions like: "Why should we believe the results
of a scientific inquiry more than those of an inquiry using non-scientific
methods?" or, more fundamentally, "What constitutes the scientific method?"
is already to begin to philosophize. These are, then, not properly
scientific questions (under what microscope will you find and verify
their answers?), but philosophic questions about science.
The distinction, then is not between a) wooly-headed philosophers and
b) hard-headed scientists, but rather between a) self-conscious
philosophizing, which attempts to learn about and profit from 2000+
years of related efforts, and b) "naive" philosophizing, which
disdains previous experience and usually winds up inventing positions
originally propounded and discussed anywhere from 20-2000 years ago.
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: Tue, 25 Aug 87 10:56:51 MDT
From: shebs@cs.utah.edu (Stanley Shebs)
Reply-to: cs.utah.edu!shebs@cs.utah.edu (Stanley Shebs)
Subject: Re: Should AI be scientific? If yes, how?
In article <8708240436.AA19024@ucbvax.Berkeley.EDU>
mckee@CORWIN.CCS.NORTHEASTERN.EDU writes:
>
>[...] If AI researchers
>call themselves Computer Scientists (as many of them do), they're implicitly
>also claiming to be scientists.
Not necessarily. "Computer Science" is an unfortunate term that should be
phased out. I wasn't there when it got popular, but the timing is right for
the term to have been inspired by the plethora of "sciences" that got named
when the govt started handing out lots of money for science in the 60s.
I prefer the term "informatics" as the best of a bad lot of alternatives.
("Datology" sounds like a subfield of history; the study of dates :-) )
>[... tutorial on scientific method omitted ...]
> In AI, one can trace the operation of a theory that's been instantiated
>as a program, as long as there's sharing of source code and the hardware is
>the same. This gives you operational confirmation as well as implicational
>confirmation, since you can watch the computer's "mind" at work, pausing
>to examine the data, or single-step the inference engine.
Goedel's and Turing's ghosts are looking over our shoulders. We can't do
conventional science because, unlike the physical universe, the computational
universe is wide open, and anything can compute anything. Minute examination
of a particular program in execution tells one little more than what the
programmer was thinking about when writing the program.
>The points of
>divergence between multiple theories of the same phenomenon can thus be
>precisely determined. But theories summarize data, and where does the
>data come from? In academia, it's probably been typed in by a grad student;
>in industry, I guess this is one of the jobs of the knowledge engineer.
>In either case there's little or no standard way to tell if the data that
>are used represent a reliable sample from the population of possible data
>that could have been used. In other sciences the curriculum usually includes
>at least one course in statistics to give researchers a feel for sampling
>theory, among other topics. Statistical ignorance means that when an AI
>program makes an unexpected statement, you have only blind intuition and
>"common sense" to help decide whether the statement is an artifact of sampling
>error or a substantial claim.
I took a course in statistics, but you don't need a course to know that
sampling from a population is not meaningful, if you don't know what the
population is in the first place! In the case of AI, the population is
"intelligent behavior". Who among us can define *that* population precisely?
If the population is more restricted, say "where native-speaking Germans
place their verbs", then you're back in the Turing tarpit. A program that
just says "at the end" (:-) is behaviorally as valid as something that
does some complex inferences to arrive at the same conclusion. Worse,
Occam's razor makes us want to prefer the simpler program, even though
it won't generalize to other natural languages. When we generalize the
program, the population to sample gets ill-defined again, and we're back
where we started.
>[...] It's not easy to think of statements about the content
>of AI (as opposed to its practice or techniques) that *could* be validated
>this way, much less hypotheses that actually *have* been experimentally
>validated. Hopefully, it's my ignorance of the field that leads me to
>say this. The best I can think of at the moment is "all intelligent systems
>that interact with the physical world maintain multiple representations
>for much of their knowledge."
This could only be a testable hypothesis if we agreed on the definition
of "intelligent system". Are gorillas intelligent because they use sign
language? Are birds intelligent because they use sticks? Are thermostats
intelligent? I don't believe the above hypothesis is testable. Almost the
only agreement you'd get is that humans are intelligent (ah, the hubris of
our species), but then you'd have to build a synthetic human, which isn't
going to be possible anytime soon. Even if you did build a synthetic human,
you'd get a lot of disagreement about whether it was correctly built, since
the Turing Test is too slow for total verification.
> - George McKee
> College of Computer Science [sic]
> Northeastern University, Boston 02115
AI people are generally wary of succumbing to "physics envy" and studying only
that which is easily quantifiable. It's like the drunk searching under the
street light because that's where it's easy to see. AI will most likely
continue to be an eclectic mixture of philosophy, mathematics, informatics,
and psychology. Perhaps the only problem is the name of the funding source -
any chance of an "NAIF"? :-)
stan shebs
shebs@cs.utah.edu
------------------------------
Date: 24 Aug 1987 14:50-EDT
From: Spencer.Star@h.gp.cs.cmu.edu
Subject: Re: AIList V5 #201 - Philosophy of Science, AI Paradigms
In V5 #201 Andrew Jenning suggests that AI is empirical research when a
programmer writes a program because we have some definite criteria:
either the program works or it does not. Unfortunately, this view is
rather widespread. Also, it is wrong. Empirical research seeks to
make general statements of a quantitative nature. For example, the
measurement of the speed of light gives us a value that is applicable
in general, not just Tues July 15th in Joe's lab. A psychologist who
measures the reaction time of a person before and after drinking
alcohol is making an empirical statement that should hold in other labs
under other similar experimental conditions. The central ideas of
empirical research is that results be publically repeatably, and lead
to some generalizations. If it happens that the results confirm or
disconfirm some theoretical predictions, so much the better. A
programmer who gets a program to work says nothing more scientific than
a plumber who has cleared a drain or a dentist who has filled a tooth.
In most cases there was no theory being tested, there is no
generalization that can be made, the work is handcrafted and cannot be
repeated in another lab based on the public description of what was
done, and we cannot even be sure that the program works on anything
more than the specific examples used in the demonstration. At best
such a program is an example of craftsmanship and programming skills.
It has nothing to do with scientific research.
Spencer Star
(star@h.cs.cmu.edu)
------------------------------
End of AIList Digest
********************
∂28-Aug-87 0511 LAWS@KL.SRI.Com AIList V5 #206 - Terminal Icons, Meetings
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 28 Aug 87 05:11:13 PDT
Date: Fri 28 Aug 1987 00:30-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #206 - Terminal Icons, Meetings
To: AIList@SRI.COM
AIList Digest Friday, 28 Aug 1987 Volume 5 : Issue 206
Today's Topics:
Linguistics - Terminal Iconography & Paralanguage,
Seminar - An Autonomous Agent (NASA Ames)
Conference - 5th Int. Workshop on Database Machines
----------------------------------------------------------------------
Date: Mon, 24 Aug 87 12:24:02 -0400
From: Andy Latto <alatto@ALEXANDER.BBN.COM>
Subject: terminal iconography
Resent-From: Bruce Nevin <bnevin@cch.bbn.com>
Date: Thu, 20 Aug 87 16:07:17 -0400
From: Stephen Gildea <mit-erl!gildea@EDDIE.MIT.EDU>
The first use of *askerisks* for emphasis that I know of is the game
Adventure, which only assumed one case. This was 1967. Question:
did the authors invent it, or were they using an already-common
notation.
< Stephen
------------------------------
Date: Mon, 24 Aug 87 16:26:24 -0400
From: John Robinson <jr@LF-SERVER-2.BBN.COM>
Reply-to: jr@ALEXANDER.BBN.COM
Subject: Re: terminal iconography
>> From: Stephen Gildea <mit-erl!gildea@EDDIE.MIT.EDU>
>> This was 1967.
Well, maybe 1976.
/jr
------------------------------
Date: 22 AUG 87 10:57-EST
From: ASTEROFF%CUTCV1.BITNET@wiscvm.wisc.edu
Subject: Paralanguage/Terminal Talk
In answer to the recent posting about "Terminal Talk," I recently
completed my doctoral dissertation on Paralanguage in Electronic Mail,
a.k.a. "Terminal Talk" in electronic communication. Below is a formal
definition for paralanguage in computer-mediated communication
and some categories that I developed for my analyses.
/Janet Asteroff
Teachers College
Columbia University
Definition:
Paralanguage is a component of spoken, written, and electronic
communication. It gives to what is being communicated a character
over and above that which is necessary to convey meaning in the
linguistic or grammatical sense. Paralanguage in electronic mail is
positioned between spoken and written paralanguage in its visual and
interpretive structures. Electronic paralanguage, a term developed to
describe paralanguage in computer-mediated communication, is defined
as: features of written language which are used outside of formal
grammar and syntax, and other features related to but not part of
written language, which through varieties of visual and interpretive
contrast provide additional, enhanced, redundant or new meanings to
the message.
Categories of Paralanguage
1. Vocal Spellings. Vocal spellings or contractions can be used
as a time-saving typing device for those who send many messages. In
certain cases, this use may not have any relation to sound qualities.
When used solely to save time or typing, vocal spellings are
"speedwriting" techniques.
r u clogging up the print queue?
2. Vocal Segregates. Sound substitutes to indicate tone of voice
appear often in the public and private electronic mail of some
computer users, usually but not exclusively those who have spent a
great amount of time using computer-mediated communication systems.
Many of these expressions originated in and are borrowed from
cartoons or comics. Vocal segregates such as "wham," "arghh" and *gak*
for instance, can be as common to some (but hardly to all) users of
electronic mail as they are to cartoonists. In that form of print
communication, vocal segregates function to convey a great deal of
information in a small space, such as in a single drawing or in one
frame of a longer strip.
3. Manipulation of Grammatical Markers. The use of ??? .... ( ) etc.
4. Manipulation of Special Symbols. This includes any symbol on the
computer keyboard used to mark off various parts of a message by
surrounding certain words or phrases. Like the manipulation of
grammatical markers these symbols, in order to be paralinguistic
features, are used outside of their traditional or formal meaning, e.g.,
Apartment #2K uses the number sign for its traditional meaning, but in
the expression @@!#%↑* it becomes a paralinguistic feature. Like
grammatical markers, special symbols indicate degrees of stress, show
pause, signal a shift in tone or changes of subject.
Most often they are found on the top (number) row of the computer
keyboard by shifting to uppercase, although any symbol on the keyboard
can be used. This includes the asterisk (*), number sign (#), up-arrow
(↑), plus sign (+) and ampersand (&), as well as right and left angle
brackets (< >) and the or bar (|). Like grammatical markers, special
symbols serve many different functions. An asterisk placed at the
beginning and end of a word, like uppercasing, shows stress, and a
string of asterisks in the middle of a message signals a change in
subject. When grouped together special symbols can be the entire
communication, as indicated in the first example below, where the
function is to indicate extreme stress and in some cases to substitute
for obscenities.
5. Spatial Arrays. A spatial array is defined in this research as
the systematic spatial arrangement of characters to create a graphic
or an identifiable image...
This definition of spatial arrays is supported by examples of the more
recent use on the computer of symbols, letters and numbers to create
"faces" or face symbols, popularly and generically referred to as a
"smiley face." Various combinations of symbols, letters, and numbers
create several different kinds of faces which when viewed sideways
create an image. Face symbols, particularly the "smiley-face" and the
"frowney-face" originated in print and mass media in the early 1970's,
and were not created by computer users. The many variations on the
basic "smiley-face" however, would appear to be unique to
computer-mediated communication.
6. Text Forms. Text Forms describe the types of paralinguistic
features made possible through certain kinds of basic
and technically sophisticated text manipulation, the latter
accomplished using a text editor. These features can provide a
contrast and indicate stress, pause, or different kinds of tones
within a message. Text Forms provides a way of looking at certain
types of presentations of text on the screen, including the entire
message or individual parts. In most cases a Text Form is not as
dramatic or as systematically patterned as a spatial array.
Text Forms include different types of text arrangements such as
spacing between letters and words, the justification of paragraphs or
blocks of text, numbered or unnumbered lists, outlines, and "the
absence of certain features or expected work in composition" such as
the lack of paragraphing (Carey, p. 68).
7. Text Movement. Text, or any symbol, can be made to appear to
move across the screen, horizontally from left to right, by
overwriting one letter on top of another. This places the same
characters in different parts of the screen. By its very nature,
text movement indicates that these words should be read differently
from stationary text. Text movement indicates emphasis, and in some
cases demonstrates extreme stress. Several kinds of text movement
and combinations also make possible different features. Text
movement can be smooth and constant if the spacing between each
appearance is even, or choppy and inconsistent with uneven spacing.
Regular or constant text movement creates a regular rhythm, while
uneven text movement creates long or short pauses.
------------------------------
Date: Tue, 25 Aug 87 13:39:14 pdt
From: plu..jared@ames-pioneer.arpa
Subject: Seminar - An Autonomous Agent (NASA Ames)
NASA, Ames Research Center, Seminar Announcement
An Autonomous Agent
Steven Vere
Lockheed AI Center
Abstract:
The goal of the autonomous agent project is the creation within the next 5
years of an integrated AI artifact with the following capabilities:
1) Limited natural language understanding and generation in a core vocabulary
of 1900 words. The vocabulary is approximately the union of Ogden's Basic
English and 1000 most frequent English words. Syntax coverage will be limited.
2) Common sense knowledge about the concepts and actions underlying the core
vocabulary.
3) Reasoning, plan synthesis, and plan execution capability.
4) A personal event episodic memory system.
Work is in progress to write the semantics and common sense knowledge for the
core vocabulary. This is based on a set of about 50 relational semantic
primitives, such as LOCATION, EXISTS, CAN, etc. For compatibility with
planning, verbs are described in a state change semantics ultimately
expandible into primitive relations. However, the primary concern is with the
content rather than the form of this knowledge. A graphics simulation package
is being developed to exercise the agent in a simulated Seaworld involving an
autonomous unmanned submarine. In this way, distracting and (for us)
uninteresting perception and low level control problems are bypassed, allowing
the project to focus on cognitive level problems.
Biography:
Dr. Vere is the developer of the DEVISER planning and scheduling system.
Those of us who have done some work in AI planning should be familiar
with his system since it was the first AI plannerto consider "time" in
the course of planning. Vere developed DEVISER while at JPL. He has
recently joined Lockheed AI center and would be talking to us about his
plans for the construction of "An Autonomous Agent".
Date: Thursday, August 27, 1987
Time: 3:00 to 4:30 PM
Location: Bldg. 244, Room 103
Inquires: Hamid Berenji, (415) 694-6525, berenji@ames-pluto.arpa
*****************************************************************************
------------------------------
Date: Tue, 25 Aug 1987 17:19 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Conference - 5th Int. Workshop on Database Machines (bm707)
AI at Upcoming Conferences
Fifth International Workshop on Database Machines
October 6-8, 1987, Karuizawa, Japan
ICM3: Design and Evaluation of an Inference Crunching Machine
J. C. Syre, J. Noye et. al (ECRC, FRG)
Knowledge Base Machine Based on Parallel Kernel Language
H. Itoh, T. Takewaki, (ICOT, Japan)
KEV-A - A Kermenl for Bubba
W. K. Wilkinsont (Bell Communications Research),
H. Boral (MCC)
A Stream-Oriented Approach to Parallel Processing for Deductive Databases
Y. Kiyoki, K. Kato, N. Yamaguchi, T. Masuda
University of Tsukuba, Japan
DDC: A Deductive Database Machine
R. Gonzalez-Rubio, J. Rohmer, A. Bradier, B. Bergsten
(Bull sa Centre dde Recherche, France)
An Inference Model and a Tree-Structured Multicomputer System for Large
Data-Intensive Logic Bases
G. Z. Qadah (Northwestern University)
Knowledge-Based System for Conceptual Schema Design on a Multi-Model
Databse Machine
E. Ozkarahan (Arizona State Univer., USA), A. Bayle (Honeywell Bull)
An Algebraic Deductive Database Managing a Mass of Rule Clauses
T. Ohmori, H. Tanaka, University of Tokyo Japan
A Shared Memory ARchitecture for MAJI Production System Machine
J. Miyazaki, H. Amano, K. Takeda, H. Aiso (Keio Univ., Japan)
A Real Time Production System Architecture Using 3-D VLSI Technology
S. Fujita, R. Aibara, T. Ae (Hiroshima Univ., Japan)
Architectural Evaluation of a Semantic Network Machine
T. Furuya, T. Niguchi, H. Kusumoto, K. Handa, A. Kokubu (ETL, Japan)
A Superimposed Code Scheme for Deductive Databases
M. Wada, H. Yamazaki, S. Yamashita, N. Miyazaki, Y. Morita, H. Iotoh
(Oki and ICOT of Japan)
An Architecture for Very Large Rule Bases Based on Surrogate Files
D. Shin, P. B. Berra (Syracuse Univ., USA)
A Simulation STudy of a Knowledge Base Machine Architecture
H. Sakai, S. Shibayama
Implementing Parallel Prolog System on Multiprocessor System PARK
H. Matsuda (Kobe Univ., Japan), K. Kohata (Okayama Univ. of Science, Japan),
T. Masuo, Y. Kaneda, S. Maekawa (Kobe University)
Search Strategy for Prolog Data Bases
G. B. Sabbatel, W. Dang (INPG, France)
The Unification Processor by Pipeline Method
M. Tanabe, H. Aiso (Keio Univ., Japan)
------------------------------
End of AIList Digest
********************
∂30-Aug-87 2323 LAWS@KL.SRI.Com AIList V5 #207 - Neural Networks
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 Aug 87 23:23:18 PDT
Date: Sun 30 Aug 1987 21:31-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #207 - Neural Networks
To: AIList@SRI.COM
AIList Digest Monday, 31 Aug 1987 Volume 5 : Issue 207
Today's Topics:
Queries - OPS for the IBM-PC,XT,AT,
AI Tools - Neural Network Simulator
----------------------------------------------------------------------
Date: 28 Aug 87 10:31
From: Julian Lebensold <lebensold%capone.crim.cdn%ubc.csnet@RELAY.CS.NET>
Subject: OPS for the IBM-PC,XT,AT
Has anyone had experiences (good, bad, indifferent) with versions of
OPS for the IBM PC environment?
We are looking to port a small application from the DEC VAX OPS5 to a micro,
and we have little information on the comparative virtues of various
implementations of OPS 5.
Thanks in advance for your replies.
Julian Lebensold
Lebensold@capone.crim.cdn
------------------------------
Date: 29 Aug 87 01:04:34 GMT
From: moritz@tub.UUCP
Subject: OPS5 for PC - that's what I need!!! - (nf)
Article-I.D.: tub.66300001
*** I'm posting this for a friend without direct access to this group ! ***
OPS5 for PC ?
I'm looking for a full-blown version of OPS5 for the IBM-PC. Working
with the VAX-VMS version of OPS5, I'd like to experiment on my (not
so terribly loaded) private PC.
TOPSI - as far as I know - does not support the essential features
which make OPS5 unique: RETE-match and therefor no recency conflict
resolution, terrible effects of rule growth on the resources (time!).
Without Rete-Match, a program developed will not be portable to
serious environments which is what I want.
Does anybody have an idea where to get (buy or public domain) ?
If nobody knows I might try to make my own (with Turbo-prolog or Pascal).
But it might take me a long time...... @(↑!↑)@.
Thank you very much in advance,
Thomas Muhr, Berlin, W-Germany
UUCP: ...!pyramid!tub!netmbx!morus (Germany: ...!unido!tub!netmbx!morus)
"unido!tub!moritz"@seismo.CSS.GOV
PS.: I would also like contact with anybody interested in or working
with OPS5 or interested in ai-applications like configuration
problems etc.
------------------------------
Date: 24 Aug 87 21:59:18 GMT
From: mtune!io!jr@RUTGERS.EDU (j.ratsaby)
Subject: Re: Neural Networks
first,is this the right newsgroup for Neural Nets or is there
a more specific one for it ?
second,is there anyone out there experimenting in stochastic neural nets
i would like to contact you in private.
thanks much
joel
[Try neuron-request%ti-csl.csnet@RELAY.CS.NET, being careful to use
lowercase where indicated. -- KIL]
------------------------------
Date: Thu, 27 Aug 87 10:01 EDT
From: Andre Marquis <Bodick@cis.upenn.edu>
Subject: Responses to connectionist simulator/inference query
Here is an edited summary of the replies I received for my query:
In article <8708071233.AA29422@linc.cis.upenn.edu> you write:
I would like to experiment with connectionist inference mechanisms.
Is there a publically avaialble connectionist simulator? I have a
Sun-3/160 with C and Common Lisp, among other things. I'm willing to
port code from other machines.
Also, if you have any good references on inference using connectionist
networks, please send them. Shastri's PhD thesis is the only thorough
treatment I've seen so far.
SIMULATORS:
>From: C Lynne D'Autrechy <mimsy!lynne@mimsy.umd.edu> on Mon 10 Aug
> 1987 at 9:49, 20 lines
>Stat: Read/Answered/Network
>To: bodick@cis.upenn.edu
>Subj: Re: Query: Connectionist Simulator
>A group of us here have developed a general-purpose simulator for developing
>and evaluating connectionist models. The system is currently written in Franz
>Lisp and runs on a MicroVAX (and should also run on a SUN supporting Franz
>Lisp).
>Lynne D'Autrechy
>From: mcvax!unizh!fuchs@seismo.CSS.GOV on Tue 11 Aug 1987 at 12:44, 19 lines
>Stat: Read/Network
>To: Bodick@cis.upenn.edu
>Subj: Re: Query: Connectionist Simulator
>Zoltan Schreter, Genetic Artificial Intelligence and Epistemics Laboratory,
>Faculty of Psychology and Educational Sciences, University of Geneva,
>Switzerland, has what he calls "a poor man's connectionist system" running -
>if I remember correctly - on an IBM PC.
> --- nef
>From: "John C. Akbari" <AKBARI@CS.COLUMBIA.EDU> on Thu 13 Aug 1987 at
> 22:46, 65 lines
>Stat: Read/Answered/Network
>To: bodick@cis.upenn.edu
>Subj: [Mail Delivery Subsystem <mailer-daemon@columbia.edu>: Returned mail:
> Host unknown]
> univ. rochester has a simulator for the sun & butterfly. you need to
>fill out a license agreement. costs about $150 (as of a few montsh ago,
>anyway). looks pretty neat from the description they sent. writen in c; uses
>sun graphics pacakge. contact: john costanzo (costanzo@cs.rochester.edu).
> univ. california (san diego) has a spiffy-looking simulator
>for the symbolics running release 7.1. costs $500 (educational rate). i
>believe the commericial rate is $2000 (!). for "quickie" overview, see
>chapter 13 in PDP. written in flavors, i think, so probably not too portable.
>contact
> kathy farrelly
> institute for cognitive science, c-015
> cognitive mechanisms group
> ucsd
> la jolla ca 92093
> 619.534.3359
> sorry, no email address
>please be advised that i haven't worked with either of these simulators.
>
>ainet-1 & ainet-2: call andy chun at brandeis (617.671.3652 or
>hon@brandeis.csnet) regarding these. about $150 for ainet & $300 for ainet-2.
>andy says ainet-1 is primarily a graphics tool & ainet-2 is for development.
>neither supports learning. also, THESE RUN UNDER RELEASE 6.1 ONLY.
REFERENCES:
My own:
%A Jerome A. Feldman
%A Dana H. Ballard
%A Christopher M. Brown
%A Gary S. Dell
%T Rochester Connectionist Papers: 1979-1985
%R University of Rochester Department of Computer Science Technical Report 172
%D December, 1985
%A Lokendra Shastri
%T Evidential Reasoning in Semantic Netowrks: A Formal Theory and its Parallel
Implementation
%R University of Rochester Department of Computer Science Technical Report 166
%D September, 1985
%A Lokendra Shastri
%A Jerome A. Feldman
%T Semantic Networks and Neural Nets
%R University of Rochester Department of Computer Science Technical Report 131
%D June, 1984
%A David E. Rumelhart
%A James L. McClelland
%T Parallel distributed processing
%V 1 & 2
%C Cambridge, Massachusetts
%P The MIT Press
%D 1987
%K Human information processing, cognition
>From: George Berg <berggeo@eecs.NWU.EDU> on Mon 10 Aug 1987 at 23:24, 74 lines
>Stat: Read/Answered/Network
>To: bodick@cis.upenn.edu
>Subj: Inference on Connectionist Networks
> I saw your posting to the net this afternoon. I don't know if this
>is exactly what you want but I saw two papers recently which roughly
>fit the category of "inference in a connectionist framework". Both of
>them are by Mark Derthick of the Department of Computer Science at
>Carnegie-Mellon University.
> "Counterfactual Reasoning with Direct Models," Proceedings of AAAI-87.
> "A Connectionist Architecture for Representing and Reasoning about
>Structured Knowledge," Proceedings of the Ninth Annual Conference of
>the Cognitive Science Society (1987).
>
> George Berg
> EECS Dept.
> Northwestern University
> Evanston, IL 60208
> berggeo@alpha.eecs.nwu.edu
> or
> berggeo@nucsrl.UUCP
> or
> ...!ihnp4!nucsrl!berggeo
>From: "John C. Akbari" <AKBARI@CS.COLUMBIA.EDU> on Thu 13 Aug 1987 at
> 22:46, 65 lines
>Stat: Read/Answered/Network
>To: bodick@cis.upenn.edu
>Subj: [Mail Delivery Subsystem <mailer-daemon@columbia.edu>: Returned mail:
> Host unknown]
>Two books not yet published:
>mcClelland & rumelhart. explorations in pdp: a handbook
>of models, programs & exercises. mit press.
>supposed to have some c programs to accompany the pdp books.
>
>macgregor, r.j. neural & brain modelling. academic press, nov. 87.
>supposed to have some fortran programs to simulate neuroelectrical activity.
>From: sdcsvax!ics.UCSD.EDU!cottrell@ucbvax.Berkeley.EDU on Fri 21 Aug
> 1987 at 0:01, 33 lines
>Stat: Read/Network
>To: CIS.UPENN.EDU!Bodick@ucbvax
>Subj: Re: Query: Connectionist Simulator
>Try my IJCAI 85 paper for an alternative way of doing inheritance inferences.
Andre Marquis
Department of Pathology and Lab Medicine
2 Gibson Building
Hospital of the University of Pennsylvania
3600 Spruce Street
Philadelphia, PA 19106
bodick@cis.upenn.edu
------------------------------
Date: 26 Aug 87 20:25:11 GMT
From: hao!boulder!mikek@ames.arpa (Mike Kranzdorf)
Subject: Neural Network Simulator
I have seen inquiries around here about neural net simulators. I have
written a program called Mactivation which simulates single and double
layer networks which can be viewed as matrix-vector multipliers. If this
doesn't make sense you can still probably use the program. It assumes
minimal knowledge of things like activation values, state vectors, and
connection matrices. Things like delta rule, normalization, etc. are
included. Activation curves are (almost) completely under your control.
A nine page manual is included in the form of a MacWrite 4.5 document.
Version 2.0c was distributed at the ICNN conference in San Diego in June.
Since then I have made many improvements but not completed it as a product.
Since I have to get back to my research, I am releasing version 2.01 as is.
The program runs on any Mactintosh, as far as I know. It is public domain,
so you may be able to find it around. If you would like a copy, send either
1) a blank 3.5" disc and a 39 cent stamp or
2) a check for five dollars made out to me
to the address below. I format single-sided to be safe. Foriegn orders
are fine. I will probably upload it one of these days, or someone else
can when they get one. Source code is not available now, but it might
be someday. Happy trails.
Mike Kranzdorf
University of Colorado
Center for Opto-electronic Computing Systems
Campus Box 425
Boulder, Colorado 80309
(303) 492-8238
CSNET: mikek@boulder.colorado.edu
ARPA: mikek%boulder.colorado.edu@relay.cs.net
BITNET: mikek%boulder.colorado.edu@wiscvm.bitnet
UUCP: {hao, nbires}!boulder!mikek
Mactivation(tm) copyright 1987 Joint Optical Laboratory
"Once in while you get shown the light
in the strangest of places
if you look at it right"
------------------------------
Date: 25 Aug 87 01:56:52 GMT
From: cbosgd!mandrill!hal!uccba!finegan@ucbvax.Berkeley.EDU (Mike
Finegan)
Subject: Neural Network Simulator
An Adaptive Template Matching Image Categorizer
(An Experimental Computer Vision Program)
[I can't forward the entire 72K file, particularly since I had to
set an AIList policy against sending out code. Those who want the
simulator can probably get it from the message author. -- KIL]
Hi,
Thanks for the response, this will be brief, but feel
free to send mail about neural nets, or anything related. It
may be that different machines require other header files ...
I have since been told that the original source is on Compuserve
in DDJFORUM -> C Chest DL. I have never used Compuserve ...
- Mike ...hal!uccba!finegan
I don't have a shell archiver, or anything like that, so
just cut out file 1, and then file 2. The remembered pattern
is identical to the training pattern format except for no
first (hdr) line. It will become clear if you read the Dr. Dobbs
article and this (or the original) program. Modified program
is followed by the original. I typed the original in by hand -
if there are uncorrected typo's, I apologize. I copied it and
then modified it (there were some typo's originally).
This file is ~69K, ~1/2 for each ...
#define PGM_ID "SILOAM CI-C86 Ver. 0f 11/22/86 for PC-DOS 2.x+"
/*
* An Adaptive Template Matching Image Categorizer
* (An Experimental Computer Vision Program)
*
* This program implements a trainable pattern classifier as
* a committee network of threshold logic units. It learns to
* recognize patterns by being trained from a set of prototype
* patterns presented in a training file. The training file is
* organized as a set of visual images represented as an orthogonal
* array of picture elements, or pixels. Each pixel is a number
* representing the gray-scale value of that point in the image.
* Associated with each pattern is a number, or tag, that
* represents the category to which that pattern belongs.
*
* R. J. Brown
* Elijah Laboratories International
* 5225 N.W. 27th Court
* Margata, Fl. 33063
* (305) 979-1567
*
* Ownership: I hereby place this program in the public domain.
*
* System: Red River ATlas 10 Mhz 80286 IBM-PC/AT clone
*
* Compiler: C86 Version 2.30H; Computer Innovations, Inc.
*
*/
------------------------------
End of AIList Digest
********************
∂01-Sep-87 2330 LAWS@KL.SRI.Com AIList V5 #208 - Philosophy of Science, Logic Puzzles
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 1 Sep 87 23:29:55 PDT
Date: Tue 1 Sep 1987 20:56-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #208 - Philosophy of Science, Logic Puzzles
To: AIList@SRI.COM
AIList Digest Wednesday, 2 Sep 1987 Volume 5 : Issue 208
Today's Topics:
Queries - Hypertext & Humble Expert System Shell &
Prolog on the Sun & VM Lisp,
Database - AI References,
Logic - Beyond Mr.P and Mr.S.,
Humor - The House of (Knowledge) Representatives,
Philosophy - Programming as Experimental Science
----------------------------------------------------------------------
Date: Mon Aug 31 16:35:16 1987
From: omepd!littlei!foobar!sdp!sdp@seismo.CSS.GOV
Subject: Hypertext
Hello,
Source code from _AI_Expert_ magazine used to be available in the newsgroup
comp.ai. They seem to have stoppped posting them. Does anyone know what
happened?
[I had to drop code listings from the AIList subject matter.
David Streiff%HARTFORD.BITNET took over Bitnet distribution.
I don't know a good source for other networks. -- KIL]
I'm looking for a program called HYPE. It's a small hypertext editor written
in Turbo Pascal.
Anyone know of any other interesting PD hypertext code?
Is there a hypertext mailing list or discussion group anywhere on the net?
Is there demand for one?
Thanks,
Scott Peterson
OMO Software
Intel, Hillsboro OR
sdp.hf.intel.com!sdp
omepd.intel.com!littlei!foobar!sdp!sdp
------------------------------
Date: 31 Aug 87 16:21:32 GMT
From: umnd-cs!umn-cs!umdcs@ucbvax.Berkeley.EDU (The UMD Guy .. )
Subject: Humble Expert System Shell
I am interested in hearing from anyone who is using Smalltalk/Humble
particularly (especially) on a Mac. A few questions:
Is one meg of memory enough?
Are there any bugs that can't be worked around?
(e.g. Tracing forward and backwards for rule explanation)
Does Humble integrate with any other packages, if so, which?
Thanks in advance ..
-Jeff
------------------------------
Date: 1 Sep 87 21:22:37 GMT
From: mtune!mtgzy!mas@RUTGERS.EDU (m.a.shariff)
Subject: Prolog on the Sun
Does anybody out there have a list of Prolog's available
for a Sun machine, preferably with comparative performance ?
Thanks
Masood Shariff
AT&T Middletown, NJ 07748
(201) 957-5479
...!mtgzy!mas
------------------------------
Date: 31 AUG 87 11:04-EDT
From: TEACH07%UC780.BITNET@wiscvm.wisc.edu
Subject: VM Lisp
I have a friend, Ron Jewell, who has devoted considerable time
and energy to developing a readable user manual for VM Lisp.
The manual is being used by an instructor at the University of
Maryland for teaching Lisp. Ron is interested in making contact
with other sites using VM Lisp in order to share information on
the product and his manual. Anyone out there using VM Lisp?
------------------------------
Date: 31 Aug 87 15:17:00 GMT
From: ihnp4!inuxc!iuvax!tenny@ucbvax.Berkeley.EDU
Subject: AI references
Many thanks to all those kind-hearted netlanders who contributed to the
AI reference database. Unfortunately, some of you provided return addresses
to which all reply attempts failed. In an effort to get the database to
these contributors (and everyone else), the database is now available via
anonymous ftp from iuvax.cs.indiana.edu.
The file of interest is: pub/references/ai.bib
Larry Tenny
tenny@iuvax.indiana.edu
------------------------------
Date: 28 Aug 87 22:05:37 GMT
From: vanhove@XN.LL.MIT.EDU (Patrick Van Hove)
Subject: Beyond Mr.P & Mr.S.
I had a somewhat different story of the same type.
A door-to-door vacuum cleaner sales person tries his pitch to
this uncompassionate mother-at-home-with-kids-screaming-behind
and after two minutes, the following dialog ensues
mother: Before you go any further, I just want to see if you are really
as much >mister-smart< as you pretend. Let's see.
My husband noticed a while ago that since the last birthday,
the product of the ages of my three daughters is exactly
the number on our house. If I add that the sum of their ages
is 13, can you figure out how old they are?
(Note:
integer ages;
integer house-numbers;)
salesman (after thinking for a while):
Well, I think I'm sorry I can't
mother: OK, you're right, I made it tough on you, but I have to go
now and drive my oldest daughter to her piano lesson.
salesman:
Your oldest daughter? Well then, I think I know the answer now:
their ages are >CENSORED<, >CENSORED< and >CENSORED<.
mother: Now I'm impressed! I'll get a dozen of those cleaners of yours.
Well, reader, can you figure it out now? Of course you don't even
know the number on the house, but who said this was going to be easy?
Patrick
"No wind today, so I'm hacking"
------------------------------
Date: Fri, 28 Aug 87 22:58:12 EDT
From: "Keith F. Lynch" <KFL@AI.AI.MIT.EDU>
Subject: S and P Puzzle
I first saw it in November 1978, in a slightly different form.
...Keith
------------------------------
Date: 1-SEP-1987 15:34:25
From: UBACW59%cu.bbk.ac.uk@Cs.Ucl.AC.UK
Subject: The House of (Knowledge) Representatives.
It is proposed that the legislature be replaced by expert systems.
The only problem seems to be that there might be a lack of discourse,
since each system would be a perfect model of human intelligence, and
therefore the house could not fail be of one mind.
The Joka.
------------------------------
Date: Fri, 28 Aug 87 13:00:41 bst
From: Mike Wilson <mdw%vax-d.rutherford.ac.uk@Cs.Ucl.AC.UK>
Subject: Empirical AI ?
In V5 #201 Andrew Jenning suggested that AI is empirical research.
In V5 #205 Spencer Star countered that it is not since programs do not
confirm or disconfirm theories and do not yield replicable quantitative
results.
Programs are implementations of models. Models are instantiations of
theories. Theories suggested by a large range of cognitive scientists
can be empirically tested by writing programs (e.g. Newell, Anderson,
Johnson-Laird, the PDP group, Norman and Rumelhart etc...). If the theory
states that certain phenomina can be produced from a set of
processing assumptions and a set of data, and a program embodying
these assumptions and using such data cannot produce the phenomina
to an level of abstraction acceptable to the theory, then the
theory is disproved.
The requirement that enables programs to
act as tests is that the instantiating and implementational
tradeoffs made are not contrary to any part of the theory. The
instantiation and implementation processes may involve the recruitment
of additional assumptions to those in the theory, which the theorist
may wish to add to the theory, but this is optional; these additional
assumptions specify a program which is one of a set of programs which
could be derived from the theory. The test can be replicated using
other programs derivable from the theory. The use of models (implemented
in programs or toy construction sets) can act as tests of theories.
Michael Wilson
SERC Rutherford Appleton Laboratory
U.K.
------------------------------
Date: 28 Aug 87 13:22:12 GMT
From: Michael P. Smith <mps@duke.cs.duke.edu>
Reply-to: mps@duke.UUCP (Michael P. Smith)
Subject: Re: Should AI be scientific? If yes, how?
Article-I.D.: duke.10112
In article <8708251656.AA14266@cs.utah.edu> cs.utah.edu!shebs@cs.utah.edu
(Stanley Shebs) writes:
>
>Goedel's and Turing's ghosts are looking over our shoulders. We can't do
>conventional science because, unlike the physical universe, the computational
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
>universe is wide open, and anything can compute anything. Minute examination
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
>of a particular program in execution tells one little more than what the
>programmer was thinking about when writing the program.
>
[emphasis added]
Would you please explain this tantalizing remark? Surely not every
formal system can compute every function (what about the ghost of
Chomsky?). Are you alluding to the mutual emulatability of Turing
machines? Or maybe the moral is functionalism (as philosophers use
the term): that in matters computational, it's form and not matter
that matters. And how does Goedel fit in? I suspect it's his
completeness theorem and not his incompleteness results you have in
mind. Finally, how does the third sentence follow from the second?
Thanks.
"Just as a vessel is a place that can be carried around, so place is a
vessel that cannot be carried around." Aristotle
Michael P. Smith ARPA: mps@duke.cs.duke.edu
------------------------------
Date: Fri, 28 Aug 87 11:34 EDT
From: rjz@JASPER.Palladian.COM
Reply-to: rjz%JASPER@LIVE-OAK.LCS.MIT.EDU
Subject: Re: Natural kinds
In McCarthy's message of Jul 10, he talks of the need for AI
systems to be able to learn and use "natural kinds",
meaning something like "empirically determined categorizations
of objects and phenomena in the experience of an individual".
A response by Causey (Jul 18) describes a "natural kind"
as something with "nomologically determined attributes",
and specifically distinguished this from a "functional concept"
such as a chair.
First: what is the correct definition of a "natural kind"
in philosophical usage? What precisely does it cover,
and why can't a "functional definition" define a natural kind?
Second: Sidestepping the terminological issue,
McCarthy's original point is the more crucial:
that people seem to be able to classify objects in the
absence of precise information.
This is important if individuals are to "make sense" of their world,
meaning they are able to induce any significant
generalizations about how the world works. It seems clear
that such generalizations must allow "functional definitions";
how else would we learn to recognize chairs, tables, and
other artifacts of civilization?
Perhaps we could call this expanded notion an "empirical kind".
Third: Such "kinds" are especially important for communicating with other
individuals, since communication cannot proceeed without
mutually-accepted points of
reference, just as induction cannot proceed without "natural kinds".
Being based on individual experience, no two persons' conceptions of
a given concept can be assumed to correspond
_exactly_. Yet communication is for the most part not deterred
by this. It would be a great convenience,implementation-wise,
if this meant that precise definitions of "kinds" are
unnecessary in [AI] practice.
Roland J. Zito-wolf
Palladian Software
Cambridge, Mass 02142
RJZ%JASPER@LIVE-OAK.LCS.MIT.EDU
------------------------------
Date: Fri, 28 Aug 87 13:04:19 pdt
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Re: AIList V5 #201 - Philosophy of Science, AI Paradigms
In article <556829438.star@h.gp.cs.cmu.edu> Spencer Star wrote:
>In V5 #201 Andrew Jenning suggests that AI is empirical research when a
>programmer writes a program because we have some definite criteria:
>either the program works or it does not. Unfortunately, this view is
>rather widespread. Also, it is wrong.
It fact, it was a rather well known AI researcher who reinforced this
view. I liked Stan Steb's posting just before this one which took a
more forward looking view [I had minor disagreements, but who cares].
What AI SHOULD be: more concern with the empirical, more experimental in
the traditional sense of the word, let's at least give these reviewers
and Don Norman a positive nod, and try to improve the WAY we do our
work, as well as try to improve our work.
--eugene
------------------------------
End of AIList Digest
********************
∂04-Sep-87 0145 LAWS@KL.SRI.Com AIList V5 #209 - Neural Networks, Planning/Scheduling Systems
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 4 Sep 87 01:45:35 PDT
Date: Thu 3 Sep 1987 23:37-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #209 - Neural Networks, Planning/Scheduling Systems
To: AIList@SRI.COM
AIList Digest Friday, 4 Sep 1987 Volume 5 : Issue 209
Today's Topics:
Query - Researchers in Neural/Connectionist Robotics &
Neural Networks Simulations in Smalltalk/LISP/(Prolog) &
Neural Networks & Unaligned fields,
Database - AI Expert Magazine Source Code,
AI Tools - Commercial Planning/Scheduling Systems
----------------------------------------------------------------------
Date: Thu, 3 Sep 87 09:05 PDT
From: nesliwa%telemail@ames.arpa (NANCY E. SLIWA)
Subject: Researchers in neural/connectionist robotics?
A colleague of mine is attempting to organize a session for the
American Controls Conference in neural/connectionist approaches/applications
to robotics (other that strictly image processing). Could anyone
suggest the names/addresses/phone numbers of researchers in this area?
Particularly other than Kuperstein, Jorgensen, and Pellionisz.
Thanks in advance.
Nancy Sliwa
MS 152D
NASA Langley Research Center
Hampton, VA 23665-5225
(804)865-3871
nancy@grasp.cis.upenn.edu
nesliwa%telemail@orion.arpa
------------------------------
Date: 2 Sep 87 20:11:21 GMT
From: plx!titn!jordan@sun.com (Jordan Bortz)
Subject: NEURAL NETWORKS SIMULATIONS IN Smalltalk/LISP/(prolog)
Has anyone implemented any neural network simulations in any of the
above languages?
Huh?
Jordan
--
=============================================================================
Jordan Bortz Higher Level Software 1085 Warfield Ave Piedmont, CA 94611
(415) 268-8948 UUCP: (decvax|ucbvax|ihnp4)!decwrl!sun!plx!titn!jordan
=============================================================================
------------------------------
Date: 3 Sep 87 21:53:45 GMT
From: hao!boulder!mikek@husc6.harvard.edu (Mike Kranzdorf)
Subject: Re: NEURAL NETWORKS SIMULATIONS IN Smalltalk/LISP/(prolog)
>Has anyone implemented any neural network simulations in any of the
>above languages?
Try P3 from UCSD Institute of Cognitive Science (LISP)
Contact David Zipser
You can find out more about it from the PDP books (Ch. 13 I believe)
--mike
------------------------------
Date: 2 Sep 87 19:18:10 GMT
From: ihnp4!inuxc!iuvax!ndmath!milo@ucbvax.Berkeley.EDU (Greg Corson)
Subject: Neural Networks & Unaligned fields
Ok, here's a quick question for anyone who's getting into Neural Networks.
If you setup the type of network described in BYTE this month, or the
type used in the program recently posted to the net, what happens if you
feed it an input image that is not aligned right?
For example, in the Byte article they demonstrate correct recall of an image
corrupted by randomly flipping a number of bytes, simulating "noise". What
would happen if they just shifted the input image one or two bits to the left?
Would the network still recognize the pattern?
Greg Corson
...seismo!iuvax!ndmath!milo
------------------------------
Date: Thu 3 Sep 87 10:01:52-PDT
From: Ken Laws <Laws@KL.SRI.Com>
Reply-to: AIList-Request@SRI.COM
Subject: Re: Neural Networks & Unaligned fields
The current networks will generally fail to recognize shifted patterns.
All of the recognition networks I have seen (including the optical
implementations) correlate the image with a set of templates and then
use a winner-take-all subnetwork or a feedback enhancement to select
the best-matching template. Vision researchers were doing this kind
of matching (for character recognition, with the character known to
be centered in the visual field) back in the 50s and early 60s. Position
independence was then added by convolving the image and template, essentially
performing the match at every possible shift. This was rather expensive,
so Fourier, Hough, and hierarchical matching techniques were introduced.
Then came edge detection, shape description, and many other paradigms.
We don't have all the answers yet, but we've come a long way from the
type of matching currently implemented in neural networks.
The advantage of the networks, particularly those implemented in analog
hardware, is speed. IF you have a problem for which alignment is known,
or IF you have time or hardware to try all possible alignments, or IF
your network is complex enough to store all templates at a sufficient
number of shifts, neural networks may be able to give you an off-the-shelf
recognizer that bypasses the need to research all of the pattern recognition
literature of the last decade.
I suspect that the above conditions will actually hold in a fair number
of engineering situations. Indeed, many of these applications have already
been identified by the signal processing community. Neural networks offer
a trainable alternative to DSP or acoustic convolution chips. Where rules
and explanations are appropriate, designers will use expert systems; otherwise
they will neural networks and similar systems. Only the most difficult
and important applications will require development of customized reasoning
systems such as numerical or object-oriented simulations.
-- Ken
------------------------------
Date: 3 Sep 87 15:41:53 GMT
From: hao!boulder!mikek@husc6.harvard.edu (Mike Kranzdorf)
Subject: Re: Neural Networks & Unaligned fields
I am not familiar with the net in Byte, but I assume it is a two layer net,
like the one that was posted. If this is the case, shifted patterns will
not be recognized. It takes at least three layers for a net to have an
internal representation of the structure of an input pattern. A good
overview paper describing these kinds of conditions can be found in the
IEEE ASSP (Acoustics, Speech, and Signal Processing) Magazine April 1987,
Volume 4, Number 2, "An Introduction to Computing with Neural Nets" by
Richard P. Lippmann. The article focuses on catagorizers, but is
informative about nets in general.
--mike
------------------------------
Date: 2 Sep 87 15:04:26 GMT
From: ecsvax.uucp!burgin@mcnc.org (Robert Burgin)
Subject: AI Expert Magazine Source Code
I believe that the source code from AI EXPERT magazine is
available on a New York City BBS:
303-273-3989
1200-N-8-1
--rb
------------------------------
Date: Wed, 2 Sep 87 12:03 PDT
From: nesliwa%telemail@ames.arpa (NANCY E. SLIWA)
Subject: Commercial planning/scheduling systems survey
I recently asked for information about any commercially available products
that provided computer assistance to planning/scheduling problems. I had
far more requests for a copy of the responses than actual responses, so
I'm posting the responses I did receive:
> Date: Wed, 12 Aug 87 11:40 EST
> From: KENYON%cgi.com@relay.cs.net
> Subject: Planning/Scheduling software
>
> This may not be what you had in mind, but Carnegie Group (in Pittsburgh)
> offers Knowledge Craft, an extremely powerful tool with which several
> advanced planning and scheduling systems have been built. One of the
> founders of the company is Mark Fox, who has done considerable research
> in the area of applying AI to planning and scheduling problems.
>
> If you're interested in a toolkit, rather than a canned (and probably
> restrictive) program, I'd suggest that you give Jay Ferguson, the
> Knowledge Craft product manager a call; he can give you more technical
> information on how the product might fill your needs.
>
> Our address here is:
>
> Carnegie Group Inc
> 650 Commerce Court at Station Square
> Pittsburgh, PA 15219
> (412) 642 6900
>
> Jeff Kenyon
> Educational Services
> Carnegie Group
>
> P.S. I know, I work for them, so I'm biased. But it really is a great
> product.
>
> Date: Tue, 11 Aug 87 14:57:55 BST
> Message-Id: <714.8708111357@soay.aiva.ed.ac.uk>
> To: nesliwa <@orion:nesliwa@telemail>
> Subject: Your Commercial Planning/scheduling software? survey
>
>
> My research is in the area of AI planning systems. I like the idea of doing
> a survey of commercially available systems, and would like to hear the
> results of your survey.
>
> A company called Consilium produces a Work In Progress Tracking system
> which ties in with some scheduling software. Address:
>
> Consilium
> 1945 Charleston Rd.
> Mountain View CA 94043
> (415) 940 1400
>
>
> -- Mark Drummond
>
> ARPA: med%uk.ac.ed.aiva@ucl.cs
> JANET: med@uk.ac.ed.aiva
> Paper Mail:
> AI Applications Institute
> University of Edinburgh
> 80 South Bridge
> Edinburgh, U.K. EH1 1HN
>
>
> Date: Mon, 10 Aug 87 14:17 EDT
> From: Scott Garren <garren@STONY-BROOK.SCRC.Symbolics.COM>
> Subject: Planning Systems
>
> There is a very good package called XPM from:
>
> Expert Management Systems
> 2432 West Peoria, Suite 1050
> Phoenix, Arizona 85029
> 602-870-1001
>
> Date: Mon, 10 Aug 87 13:20:32 PDT
> From: Michael Shafto <shafto@ames-aurora.arpa>
>
> The AI Magazine, Volume VII, Number 5 (Winter, 1986)
> ISSN 0738-4602 [this references the Callistro Project and OPGEN]
>
> Best regards,
>
> Mike Shafto
>
> Date: Friday, 21 August 1987 14:19:27 EDT
> From: Perry.Zalevsky@isl1.ri.cmu.edu
> Subject: Request for Planning and Scheduling Software
>
> Nancy,
> I saw your request for commercially available planning and scheduling
> software and was wondering if you could pass the information that you
> received on to me. Did you get info about InterFase or Factrol? Send me mail
> and I can respond about the above two packages if you want.
>
> Perry Zalevsky
I am following up these pointers with requests to the referenced companies
for more specific information (also to companies I was already aware of that
provided such products). Since there seems to be some interest in this area,
I will post a summary of these responses when available.
If any of you that did not previously respond have some additional pointers,
I'd sincerely appreciate your relaying them to me!
Nancy Sliwa
MS 152D
NASA Langley Research Center
Hampton, VA 23665-5225
(804)865-3871
nancy@grasp.cis.upenn.edu
nesliwa%telemail@orion.arpa
------------------------------
End of AIList Digest
********************
∂07-Sep-87 2325 LAWS@KL.SRI.Com AIList Digest V5 #210
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 7 Sep 87 23:24:56 PDT
Date: Mon 7 Sep 1987 21:41-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #210
To: AIList@SRI.COM
AIList Digest Tuesday, 8 Sep 1987 Volume 5 : Issue 210
Today's Topics:
Seminars - Proving Completeness of Inference Rules (SRI) &
NIAL: A Programming Language for AI (SRI),
Conferences - Site and Officers for IJCAI-91 &
OOPSLA 88
----------------------------------------------------------------------
Date: Mon, 31 Aug 87 10:08:31 PDT
From: lunt@csl.sri.com (Teresa Lunt)
Subject: Seminar - Proving Completeness of Inference Rules (SRI)
SRI COMPUTER SCIENCE LABORATORY SEMINAR ANNOUNCEMENT:
PROVING COMPLETENESS OF INFERENCE RULES
JEAN-PIERRE JOUANNAUD
LABORATOIRE DE RECHERCHE EN INFORMATIQUE
UNIVERSITE PARIS-SUD-ORSAY
Tuesday, September 8 at 4:00 pm
SRI International, Computer Science Laboratory, IS109
Many problems described by means of algorithms should be described by a set of
inference rules plus a search plan (strategy). Not only does this viewpoint
improve our understanding, but it also makes completeness proofs easier and
eventually mechanizable in the following way:
1. Give a complete algebraic specification of the underlying notion of proof.
2. Associate with the inference rules a rewrite system on proofs, considered
as terms.
3. Prove termination of the rewrite system on proofs.
4. Characterize proofs in normal form.
5. Show for each particular strategy that the set of normal forms is the same.
This last property has been called "fairness" in term rewriting. It is actually
a very general notion in theorem proving, whose proof turns out to be a
non-trivial task as soon as there are "destructive" inference rules. For that
reason, very few inference systems containing such rules are proved.
A number of applications of this methodology will be given, including
unification.
NOTE: Non-SRI visitors please arrive at least 10 minutes early
to be escorted to the conference room.
------------------------------
Date: Thu, 3 Sep 87 09:38:16 PDT
From: lunt@csl.sri.com (Teresa Lunt)
Subject: Seminar - NIAL: A Programming Language for AI (SRI)
SRI COMPUTER SCIENCE LAB SEMINAR ANNOUNCEMENT:
NIAL: A Programming Language for Artificial Intelligence
Janice I. Glasgow
Queen's University, Kingston, Canada
Friday, September 18 at 10:30 am
SRI International, Computer Science Laboratory, IS109
Nial is a high-level, interactive programming language that synthesizes
many semantic concepts from LISP, Prolog and APL in one notational framework.
It is based on the formal theory of the nested, rectangular array as a
mathematical data object. Q'Nial is a portable implementation of Nial developed
at Queen's University and available on many architectures including large
timesharing machines, Unix systems and personal computers.
One of the principal application areas of Nial is artificial intelligence.
The goal of research in this area has been to provide high level tools
in the language from which tailored knowledge based systems can be constructed.
These tools include logic programming primitives, inference engines, a frame
language, a rule interpreter and a natural language parser.
This seminar will include a description Nial with particular emphasis
on the application of the language to decision support and knowledge
based systems.
NOTE: Non-SRI visitors please arrive at least 10 minutes early
to be escorted to the conference room.
------------------------------
Date: Wed, 2 Sep 87 17:09:55 GMT
From: Alan Bundy <bundy%aiva.edinburgh.ac.uk@Cs.Ucl.AC.UK>
Subject: Conference - Site and Officers for IJCAI-91
At its meeting during IJCAI-87, the 1987 IJCAI Executive
Committee took the following decisions about IJCAI-91.
Site: Sydney, Australia.
Conference Chair: Barbara Grosz, University of Harvard.
Program Chairs (joint): Ray Reiter & John Mylopoulos, University of
Toronto.
The conference is provisionally scheduled for the 3rd week of
August 1991.
Alan Bundy
Executive Committee Chair
------------------------------
Date: 29 Aug 87 17:05:54 GMT
From: hp-pcd!uoregon!omepd!intelisc!littlei!ogcvax!maier@hplabs.hp.com
(Prof. David Maier)
Subject: Conference - OOPSLA 88
OOPSLA-87 invites you to attend the second annual conference devoted to
applications, research and implementation of object-oriented systems,
October 4 - 8, 1987, in Orlando, Florida.
OOPSLA-87 includes tutorials, technical sessions, panels, and vendor exhibits.
Conference Schedule
-------------------
Sunday, 4 October - Tutorials
1A - Introduction to Obj. Oriented Concepts - Oct 4, 9AM
1B - Object Oriented Databases - Oct 4, 9AM
2A - Survey of Object-Oriented Systems - Oct 4, 1:30PM
2B - Object Oriented Programming in AI - Oct 4, 1:30PM
Monday, 5 October - Tutorials
3A - Introduction to Obj. Oriented Concepts - Oct 5, 9AM
3B - Develelopment of Large Applications - Oct 5, 9AM
4A - Survey of Object-Oriented Systems - Oct 5, 1:30PM
4B - Obj. Oriented Application Frameworks - Oct 5, 1:30PM
Tuesday,6 October
9 AM Keynote Address - Barbara Liskov, MIT
10:30 AM Sessions: (1A) Applications (1B) Tools/Environment
2 PM Sessions: (2A) Database (2B) Theory
4:30 PM Panels: (P1) Teaching OOP (P2) Forms of Inheritance
5:30 PM Reception in the Vendor Exhibit area
Wednesday, 7 October
9 AM Panels: (P3) Use of OOP in Commercial Settings
(P4) Adding OOP to Existing Languages
10:30 AM Sessions: (3A) Software Engineering (3B) Languages
2 PM Sessions: (4A) User Interfaces (4B) Implementation
4:30 PM Panels: (P5) Usability of OOP Systems (P6) Future of OOP
7 PM Banquet , speaker: Michael Jackson, Jackson Systems Ltd.
Thursday, 8 October
9 AM Report: OOP Standardization Efforts
10:30 AM Sessions: (5A) Applications (3B) Software Engineering/Tools
2 PM Sessions: (4A) Database/Languages (4B) Theory
Vendor Exhibits will be open Tuesday, Wednesday and Thursday.
Conference Prices
ACM Member $ 215
non-member $ 255
student $ 50
Tutorials are scheduled in two parallel tracks, the introductory (A) track,
and the intermediate (B) track. You may register for only one session
in any half-day time slot, or a maximum of 4 tutorial sessions.
Tutorial price per half-day session:
ACM Member $ 125
non-member $ 145
student $ 125
Extra Banquet tickets $ 30
Telex confirmation option $ 10
Pay by check or money order. Checks or money orders must be payable
through a U.S. bank, and must have machine-readable account numbers.
Confirmation will be sent by Telex, upon payment of the extra charge.
Send registrations and requests for more information to:
OOPSLA-87
P.O. Box 3845
Portland, OR 97208-3845 USA
Telex: 159265412
FAX: 503 643 5931
UUCP mail: ..tektronix!ogcvax!servio!otisa
ATTMAIL: aotis
Send hotel reservations to:
Hyatt Orlando
6375 West Space Coast Parkway
Kissimmee, Florida 32741
Tel 305 396 1234 Telex 567436
Discounted airline fares are offered by Continental and Eastern .
Call 800-468-7022 and mention account number EZ10T83.
The Hyatt Orlando is adjacent to Walt Disney World, with shuttle bus service
available from the hotel.
---------------------------------------------------------
Please respond to Alan Otis, not me
--Dave Maier
--
David Maier, Oregon Graduate Center <maier@ogcvax.OGC.EDU>
...tektronix!ogcvax!maier
------------------------------
End of AIList Digest
********************
∂08-Sep-87 0114 LAWS@KL.SRI.Com AIList V5 #211 - Neural Networks & OPS5 & Philosophy
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 8 Sep 87 01:14:30 PDT
Date: Mon 7 Sep 1987 21:55-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #211 - Neural Networks & OPS5 & Philosophy
To: AIList@SRI.COM
AIList Digest Tuesday, 8 Sep 1987 Volume 5 : Issue 211
Today's Topics:
Queries - FLEXIGRID & Quote & Mactivation,
Neural Networks - Unaligned Fields,
AI Tools - OPS5 for PC,
Linguistics - Interrobangs,
Philosophy - Wittgenstein and World Description Nets &
Should AI be Scientific? & Leibniz on Philosophy
----------------------------------------------------------------------
Date: 3 Sep 87 18:34:38 GMT
From: imagen!atari!portal!cup.portal.com!tony_mak_makonnen@ucbvax.Berk
eley.EDU
Subject: cognitive research tool
I am going to meet Finn Tschudi in Norway sometime around Sept 17
I'll be looking at the newest version of his FLEXIGRID program ,
originally intended as computerized application of Kelly Rep Grid
on psychological constructs ; also found useful by knowledge
engineers in understanding the process of knowledge acquisition etc
Anyone with any questions you want me to put to Finn ; or interest
in purchasing the latest version etc let me know before that time
Ciao .
------------------------------
Date: 5 Sep 87 01:34:38 GMT
From: munnari!trlamct.oz!andrew@uunet.UU.NET (Andrew Jennings)
Subject: quote : attributable to ?
Recently somebody on comp.ai.digest suggested the following (or close to it) :
"Give an AI researcher the task of banging in a nail. First he'll
study hammers. Before you know it he'll be studying advanced
metallurgy"
Can anyone remember (preferably the author) : a) the exact words b) the author
Thanks : I want to quote this in a talk, and obviously for all concerned its
better if its correct.
--
UUCP: ...!{seismo, mcvax, ucb-vision, ukc}!munnari!trlamct.trl!andrew
ARPA: andrew%trlamct.trl.oz@seismo.css.gov
Andrew Jennings Telecom Australia Research Labs
(Postmaster:- This mail has been acknowledged.)
------------------------------
Date: 4 Sep 87 02:41:49 GMT
From: hao!boulder!mikek@husc6.harvard.edu (Mike Kranzdorf)
Subject: Mactivation
> I have seen inquiries around here about neural net simulators. I have
> written a program called Mactivation which simulates single and double
> layer networks which can be viewed as matrix-vector multipliers.
Would some who has recieved a copy of Mactivation please post it?
My Mac doesn't talk to the net yet (no modem cord for my new SE).
Preferably someone with 2.02 - it's a little faster but no big deal.
I suppose comp.binaries.mac and comp.doc are the right places.
You are all still welcome to write to me for it; posting will just make
it more accessible. I'll be sure to post when there's an update.
Thanks much.
--mike mikek@boulder.colorado.edu
------------------------------
Date: 4 Sep 87 16:13:31 GMT
From: boulder!mikek@boulder.colorado.edu (Mike Kranzdorf)
Reply-to: boulder!mikek@boulder.colorado.edu (Mike Kranzdorf)
Subject: Re: Neural Networks & Unaligned fields
The second reference above is correct, but fails to mention work
by Fukishima and Mozer. These multi-layer networks are able to form
an internal distributed representation of a pattern on an input retina.
They demonstrate very good shift and scale invariance. The new and
improved neocognitron (Fukishima) can even recognize multiple patterns
on the retina.
--mike mikek@boulder.colorado.edu
------------------------------
Date: 7 Sep 87 05:47:19 GMT
From: maiden@sdcsvax.ucsd.edu (VLSI Layout Project)
Reply-to: maiden@sdcsvax.ucsd.edu (VLSI Layout Project)
Subject: Re: Neural Networks & Unaligned fields
In article <12331701930.42.LAWS@KL.SRI.Com> AIList-Request@SRI.COM writes:
>The current networks will generally fail to recognize shifted patterns.
>All of the recognition networks I have seen (including the optical
>implementations) correlate the image with a set of templates and then
>use a winner-take-all subnetwork or a feedback enhancement to select
>the best-matching template.
[some lines deleted]
> -- Ken
>-------
There are a number of networks that will recognize shifts in position.
Among them are optical implementations (see SPIE by Psaltis at CalTech)
and the Neocognitron (Biol. Cybern. by Fukushima). The first neocognitron
article dates to 1978, the latest article is 1987. There have been a
number of improvements, including shifts in attention.
Edward K. Y. Jung
------------------------------------------------------------------------
1. If the answer to life, the universe and everything is "42"...
2. And if the question is "what is six times nine"...
3. Then God must have 13 fingers.
------------------------------------------------------------------------
UUCP: {seismo|decwrl}!sdcsvax!maiden ARPA: maiden@sdcsvax.ucsd.edu
------------------------------
Date: 31 Aug 87 17:25:38 GMT
From: Walter Maner<gatech!psuvax1!pitt!bgsuvax!maner@RUTGERS.EDU>
Subject: Re: OPS5 for PC - that's what I need!!! - (nf)
> Approved: ailist@stripe.sri.com
>
> I'm looking for a full-blown version of OPS5 for the IBM-PC. Working
> with the VAX-VMS version of OPS5, I'd like to experiment on my (not
> so terribly loaded) private PC.
> TOPSI - as far as I know - does not support the essential features
> which make OPS5 unique: RETE-match and therefor no recency conflict
One year ago, the full RETE algorithm existed in a beta version of
TOPSI. It may have migrated to the regular release by now.
--
CSNet : maner@research1.bgsu.edu | CS Dept 419/372-2337
UUCP : {cbatt,cbosgd}!osu-cis!bgsuvax!maner | BGSU
Generic : maner%research1.bgsu.edu@relay.cs.net | Bowling Green, OH 43403
Opinion : "If you're married, you deserve a MARRIAGE ENCOUNTER weekend!"
------------------------------
Date: 7 Sep 87 19:20:09 GMT
From: "Gregory J.E. Rawlins"
<gjerawlins%watdaisy.waterloo.edu@RELAY.CS.NET>
Reply-to: gjerawlins@watdaisy.waterloo.edu (Gregory J.E. Rawlins)
Subject: Re: Terminal Talk
In article <8708240530.AA19550@ucbvax.Berkeley.EDU>
gately%resbld@ti-csl.CSNET ("Michael T. Gately") writes:
>Another interesting notation is the order of the
>characters in a serial interrobang. I feel that there
>is a definate difference between ?! and !?. The first
>would be appropriate when describing (with disbelief)
>a question someone asked. The second is used when
>questioning a statement someone made.
In chess annotations "!?" is used to indicate an interesting but
dubious move and "?!" is used to indicate a dubious but
interesting move. Chess also uses !,?,!!, and ??.
greg.
--
GJE Rawlins gjerawlins%watdaisy@waterloo.csnet gjerawlins@watdaisy.waterloo.edu
------------------------------
Date: 2 Sep 1987 00:22 EDT (Wed)
From: Wayne McGuire <Wayne%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU>
Subject: Wittgenstein & World Description Nets
> Date: 24 August 1987, 23:09:52 EDT
> From: john Sowa <SOWA@ibm.com>
> Subject: Wittgenstein and natural kinds
>
> Every schema in a cluster represents one valid use of the concept
> type. The meaning is determined not by any definition, but by the
> collection of all the permissible uses, which can grow and change with
> time.
>
> Does that solve the problem? Maybe, but we still need criteria
> for determining what kinds of uses can legitimately be added to a
> cluster. Could I say "To add something means to eat it with garlic
> and onions"? What are the criteria for accepting or rejecting a
> proposed extension to a concept's meaning?
Under the assumption that language (and all human semiotic systems),
and the concepts they label, are in great part a social contract, a
collection of arbitrary conventions momentarily accepted in a ceaseless
process of interaction by a particular group of people in a particular
space and time and culture, perhaps what is permissible is anything
that any human group, through _actual usage_, indicates they find
useful as a tool of communication.
Human societies are much like Humpty Dumpty in _Alice in Wonderland_:
"When _I_ use a word," Humpty Dumpty said in rather a scornful
tone, "it means just what I choose it to mean--neither more nor
less."
"The question is," said Alice, "whether you _can_ make words mean
so many different things."
"The question is," said Humpty Dumpty, "which is to be master--
that's all."
An ideal program with general intelligence would closely monitor
the actual language usage and semiotic behavior of its target domain,
and assimilate as new schemata in its world model those new words,
signs, and concepts which reach a user-settable level of usage or which
are assigned by social fiat roles as fixed conventions (fixed for the
time being, of course, for the life of this particular cultural phase).
One can easily imagine wanting one's world model to be more
comprehensive, however, and to include highly idiosyncratic language
uses that are not social conventions. Integrating the detailed mental
models and private languages of all the world's leading imaginative
writers, from Homer to Norman Mailer, could be valuable for the
purposes of some people and with the object of constructing a humanist
superintelligence.
A speculation: how many new schemata enter the set of all human
discourse in a year? Probably professional dictionary-makers and
terminology-compilers have given some thought to this question.
I recently came across an apt passage in Wittgenstein's _Tractatus
Logico-Philosophicus_:
I can place over the world a unified descriptive net through which
I bring everything to a unitary form. According to the kind of net
that I choose there results a kind of world description. If I take
various nets then I produce various world descriptions.
Wittgenstein then chooses mechanics as a sample world description net,
and notes: "Mechanics determines one form or description of the world
by saying that all propositions used in the description of the world
must be obtained in a given way from a given set of propositions--the
axioms of mechanics."
But there are at least as many distinct world description nets as there
are persons, living and dead, and probably many more, taking into
account the changing mental model of an individual over time, and the
sets of unique mental models of an individual in different roles and
social domains. There is much redundancy in all these models, but
there is also a subset of each net that is special and which includes
schemata that are the only ones of their kind. Clearly artificial
intelligence researchers need to pay much more attention to pragmatics
and sociolinguistics: the notion that intelligence is reducible to a
set of universal principles or context-free grammar rules is misguided.
Ultimately AI might seek to model and integrate, in a Supreme World
Net, as many Wittgensteinian world description nets as possible, to map
their literal and metaphoric relations, and to track their evolution
and devolution in real time. (And while we are at it, it would be
nice to build a working perpetual motion machine.)
Wayne McGuire
------------------------------
Date: Thu, 3 Sep 87 09:03:22 MDT
From: shebs@cs.utah.edu (Stanley Shebs)
Reply-to: cs.utah.edu!shebs@cs.utah.edu (Stanley Shebs)
Subject: Re: Should AI be scientific? If yes, how?
In article <8708281322.AA27689@duke.cs.duke.edu> duke!mps
(Michael P. Smith) writes:
>In article <8708251656.AA14266@cs.utah.edu> cs.utah.edu!shebs@cs.utah.edu
>(Stanley Shebs) writes:
>>
>>Goedel's and Turing's ghosts are looking over our shoulders. We can't do
>>conventional science because, unlike the physical universe, the computational
> ↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
>>universe is wide open, and anything can compute anything. Minute examination
> ↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
>>of a particular program in execution tells one little more than what the
>>programmer was thinking about when writing the program.
>>
> [emphasis added]
>
>Would you please explain this tantalizing remark? Surely not every
>formal system can compute every function (what about the ghost of
>Chomsky?). Are you alluding to the mutual emulatability of Turing
>machines?
This is basic computer science. Any formalism sufficiently powerful
to compute all the computable things we know of is equivalent to a Turing
machine (Church-Turing Hypothesis), and formalisms of that power are
all incomplete (Goedel's Incompleteness Theorem). Incompleteness rears
its ugly head when we find that our most sophisticated programs cannot be
tested completely.
Simpler formal systems such as CFGs are too weak to model human intelligence,
although some aspects of human behavior have been asserted to be context-free
(for instance, Presidents that don't learn from their predecessors :-) ).
>Finally, how does the third sentence follow from the second?
This is the empirical consequence of Turing equivalence. I can write
Eurisko or XCON in Lisp, Forth, or IBM 1401 assembler, and they will all
behave the same. Assertions about the details about a program are worthless
from a theoretical point of view, details of algorithms are somewhat better,
but the algorithms appearing in AI programs are either too simple (searching
for instance) or too complicated to be analyzable (the abovementioned large
programs).
>Michael P. Smith ARPA: mps@duke.cs.duke.edu
stan shebs
shebs@cs.utah.edu
------------------------------
Date: 7 Sep 87 16:59:27 GMT
From: jbn@glacier.stanford.edu (John B. Nagle)
Subject: Leibniz on philosophy
"Philosophy is the discipline where you kick up a lot of dust and then
complain you can't see."
(as paraphrased by the physicist John Bahcall)
------------------------------
End of AIList Digest
********************
∂10-Sep-87 2333 LAWS@KL.SRI.Com AIList V5 #212 - Philosophy, Neural Networks
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Sep 87 23:33:47 PDT
Date: Thu 10 Sep 1987 21:11-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #212 - Philosophy, Neural Networks
To: AIList@SRI.COM
AIList Digest Friday, 11 Sep 1987 Volume 5 : Issue 212
Today's Topics:
Queries - AAAI Presidential Address Recordings & LISP/VM &
PD OPS5 & LISP Chess Program & Conceptual Graphs &
Neural Network Email Addresses,
Philosophy - Is Computer Science Science? & Leibniz on Philosophy,
Neural Networks - Unaligned Fields & Speech Analysis
----------------------------------------------------------------------
Date: Thu, 10 Sep 87 12:08:17 PDT
From: AAAI <AAAI-OFFICE@SUMEX-AIM.STANFORD.EDU>
Subject: HELP!
During AAAI-87, we normally tape the Presidential Address by Pat Winston.
This year, the tapes were scrambled. If anyone made a tape of Patrick
talk, we would really appreciate if we could receive a copy?
Also, Marvin Minsky has asked us if anyone still has retained a tape
of his 1982 Presidential Address in Pittsburgh. He would also like
a copy, if it is still available.
Thank you for any help you may provide.
Sincerely,
Claudia Mazzetti
AAAI
445 Burgess Drive
Menlo Park, CA 94025
------------------------------
Date: Tue, 08 Sep 87 12:46:31 FIN
From: Heikki Pesonen <LK-HPE%FINOU.BITNET@wiscvm.wisc.edu>
Subject: LISP/VM
=========================================================================
I will be pleased to here peoples opinion about IBM:s LISP/VM.
We have it, but not many seems to be interested in it. I like it,
so what is wrong with LISP/VM? What is good with it?
We have LISP/VM to the end of this year, not longer, if it do not
interest people more (I am afraid of ..).
Unfortunately LISP/VM is not very compatible with Common Lisp and its
usually slow in our IBM 3083 VM/CMS, but it has many usefull features.
Becouse I am no Lisp Guru I would like to get the opinions of those
who are. I know that LispGurus usually reside near a Lispmachine
/Xerox etc.) and they do not appreciate mainframe lisps. So may be
a vain effort ..
Yours sincerely, Heikki Pesonen, EDP-Centre,
University of Oulu, 90570 OULU, Finland
========================================================================
------------------------------
Date: 9 Sep 87 00:28:26 GMT
From: clyde!watmath!utgpu!tmsoft!mason@RUTGERS.EDU (Dave Mason)
Subject: Is there a Public Domain/Shareware version of OPS5 ?
A colleague of mine is interested in this for a Comparative Languages
course & an Expert Systems course. Any leads appreciated.
Thanks
../Dave Mason, Ryerson Polytechnical Institute
best: ..!{utzoo seismo!mnetor utcsri utgpu lsuc}!tmsoft!mason
FCTY7053@RYERSON.BITNET
------------------------------
Date: Thu, 10 Sep 87 14:29:09 cdt
From: Glenn Manuel <manuel%home%ti-csl.csnet@RELAY.CS.NET>
Reply-to: Glenn Manuel <home!manuel%ti-csl.csnet@RELAY.CS.NET>
Subject: Wanted: LISP Chess Program
Does anyone know of a pretty good Chess program written in LISP,
either commercially available or (preferably) public domain?
I'll be running it on a TI Explorer driving an external display
(possibly a dumb terminal via RS-232 -- don't ask why), so I'm
mostly interested in the algorithms, not fancy graphics for
displaying the game pieces.
Thanks in advance,
--
Glenn Manuel (214) 575-5231
Texas Instruments, Inc., PO Box 869305 MS 8473, Plano, Tx. 75086
USENET: {ctvax,im4u,texsun,rice}!ti-csl!manuel CSNET: Manuel@TI-CSL
------------------------------
Date: 9 Sep 87 22:35:25 GMT
From: plx!titn!jordan@sun.com (Jordan Bortz)
Subject: conceptual graphs
Has anyone played with Conceptual Networks, as documented in
Conceptual Structures, by Sowa? In what language? What kinds of
things did you try to implement? How did it work?
Jordan
--
=============================================================================
Jordan Bortz Higher Level Software 1085 Warfield Ave Piedmont, CA 94611
(415) 268-8948 UUCP: (decvax|ucbvax|ihnp4)!decwrl!sun!plx!titn!jordan
=============================================================================
------------------------------
Date: 10 Sep 87 23:15:30 GMT
From: jr@io.att.com (j.ratsaby)
Subject: Need email names
I would like to get email names of persons who deal with neural-nets
in CS dept of university of Toronto and/or in CS dept of John Hopkins
university in Baltimore.
thanks in advance,
joel
------------------------------
Date: 8 Sep 87 16:53:54 GMT
From: decvax!sunybcs!rapaport@ucbvax.Berkeley.EDU (William J.
Rapaport)
Subject: Is Computer Science Science?
A colleague of mine in a philosophy department recently asked me if
I could give him "some major causal laws, principles or regularities
that are special to Computer Science.... (Every science has its special
laws, so what are some for Computer Science?)"
I vaguely recall a recent discussion on one of the nets about this. If so,
is there some way I could get a copy of it (hard or soft)? If not,
would anyone like to take a stab at answering this?
William J. Rapaport
Assistant Professor
Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260
(716) 636-3193, 3180
uucp: ..!{ames,boulder,decvax,rutgers}!sunybcs!rapaport
csnet: rapaport@buffalo.csnet
internet: rapaport@cs.buffalo.edu
[if that fails, try: rapaport%cs.buffalo.edu@cs.relay.net]
bitnet: rapaport@sunybcs.bitnet
------------------------------
Date: 10 Sep 87 05:38:05 GMT
From: voder!apple!corwin@ucbvax.Berkeley.EDU (Entomology Lab)
Subject: Re: Is Computer Science Science?
In article <5113@sunybcs.UUCP> rapaport@sunybcs.UUCP (William J. Rapaport)
writes:
>
>A colleague of mine in a philosophy department recently asked me if
>I could give him "some major causal laws, principles or regularities
>that are special to Computer Science.... (Every science has its special
>laws, so what are some for Computer Science?)"
>
"Anything that can go wrong will go wrong."
"There is always one more bug"
"The differnce between a bug and a feature is that a feature is documented"
-cory
--
corwin@apple.[UUCP, CSNET]
Disclaimer: The preceding message is not based on reality.
------------------------------
Date: 10 Sep 87 23:48:20 GMT
From: shafto@ames-aurora.arpa (Michael Shafto)
Subject: Re: Is Computer Science Science?
I just saw a tech report by Peter J. Denning on the topic
"Is computer science science?"
The tech report was issued through RIACS here at Ames.
It will allegedly appear as an editorial in the Oct., 1987,
CACM. The title is something like "Paradigms Crossed" --
referring to the crossed paradigms of design vs. experimentation,
or engineering vs. science.
I would rate this "real good" on a scale of 1 to 10, and I
urge interested parties to watch for and read it.
Mike Shafto
------------------------------
Date: 9 Sep 87 00:37:12 GMT
From: psuvax1!vu-vlsi!ge-mc3i!sterritt@husc6.harvard.edu (Chris
Sterritt)
Subject: Re: Leibniz on philosophy
In article <17172@glacier.STANFORD.EDU> jbn@glacier.STANFORD.EDU
(John B. Nagle) writes:
> "Philosophy is the discipline where you kick up a lot of dust and then
>complain you can't see."
As long as we're slamming philosophy, why not:
"Philosophy is a blind man in a dark room looking for a black cat...
THAT ISN'T THERE"
------------------------------
Date: 9 Sep 87 13:54:23 GMT
From: PT!cadre!geb@cs.rochester.edu (Gordon E. Banks)
Subject: Re: Neural Networks & Unaligned fields
In article <3523@venera.isi.edu> smoliar@vaxa.isi.edu.UUCP
(Stephen Smoliar) writes:
>In article <277@ndmath.UUCP> milo@ndmath.UUCP (Greg Corson) writes:
>>Ok, here's a quick question for anyone who's getting into Neural Networks.
>>If you setup the type of network described in BYTE this month, or the
>>type used in the program recently posted to the net, what happens if you
>>feed it an input image that is not aligned right?
I didn't see the Byte article, but the simple neural networks that
I have seen (such as the one that solves the T-C problem by Hinton
& Rummelhart in the PDP book) do not generalize very well. You can
train the hidden units with a given input, but then if you shift the
pattern, it won't work. I asked Rummelhart about this, and he said
that once the hidden units develop the patterns (such as edge detectors
and center-surround, etc.) you do not need to retrain for each translation
of the pattern, but you need to add more units to the network. These
units have the same weights as the previously trained units, but they
have a different field of view. You have to have another set of units
for each region which can possibly contain the image. Alternatively,
you have to have a scheme for making sure the image is "centered" in
the field of view. Sounds like there is some room for interesting
research here, maybe a thesis.
------------------------------
Date: 9 Sep 87 15:00:36 GMT
From: caasi%sdsu.UUCP@sdcsvax.ucsd.edu (Richard Caasi)
Subject: Re: neural net conference
In response to those who asked and because email didn't work too well,
there was a session devoted to Speech Recognition and Synthesis at the
neural net conference (San Diego, June '87).
The papers were:
Issues and Problems in Speech Processing with Neural Networks
Learning Phonetic Features Using Connectionist Networks: An
Experiment in Speech Recognition
A Neural Network Model for Speech Recognition Using the Generalized
Delta Rule for Connection Strength Modification
Neural Networks for the Auditory Processing and Recognition of Speech
Multilayer Perceptrons and Automatic Speech Recognition
Neural Net Classifiers Useful for Speech Recognition
Isolated Word Recognition with an Artificial Neural Network
Recent Developments In a Neural Model of Real-Time Speech Analysis and
Synthesis
Concentrating Information in Time: Analog Neural Networks with
Possible Applications to Speech Recognition
Guided Propagation Inside a Topographic Memory
The Implementation of Neural Network Technology
------------------------------
End of AIList Digest
********************
∂16-Sep-87 0058 LAWS@KL.SRI.Com AIList V5 #213 - Queries
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Sep 87 00:58:13 PDT
Date: Tue 15 Sep 1987 22:33-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #213 - Queries
To: AIList@SRI.COM
AIList Digest Wednesday, 16 Sep 1987 Volume 5 : Issue 213
Today's Topics:
Queries - Program for AIDA-87 & OPS5 for PC & Object-Oriented PROLOG &
Neural-Net Proceedings & Qualitative Models and Discrete Simulaiton &
Procedures and Data & OOPSLA-87 Roommate & Speech Databases &
Lisp to C Conversion & ICAI for Literacy Training & Unix Prolog
----------------------------------------------------------------------
Date: 10 Sep 87 13:24:06 GMT
From: mcvax!enea!erix!olle@seismo.css.gov (Olle Wikstrom)
Subject: Program for AIDA-87 conference requested
Has anyone seen the program for the AIDA-87 - "the third annual
conference on Artificial Intelligence & Ada" George Mason University,
October 14-15, 1987? If so would you please send a copy of it to me,
preferably using e-mail.
Olle Wikstrom UUCP: olle@erix.UUCP
Ericsson Radio Systems AB or: ..seismo!mcvax!enea!erix!olle
Box 1001
S-431 26 Molndal
Sweden
------------------------------
Date: 10 Sep 87 16:47:00 GMT
From: uiucdcs!pur-ee!bucc2!brian@seismo.CSS.GOV
Subject: Re: OPS5 for PC - that's what I nee
> > Approved: ailist@stripe.sri.com
> >
> > I'm looking for a full-blown version of OPS5 for the IBM-PC. Working
> > with the VAX-VMS version of OPS5, I'd like to experiment on my (not
> > so terribly loaded) private PC.
> > TOPSI - as far as I know - does not support the essential features
> > which make OPS5 unique: RETE-match and therefor no recency conflict
>
> One year ago, the full RETE algorithm existed in a beta version of
> TOPSI. It may have migrated to the regular release by now.
I'm interested in TOPSI. What company offers it? Could you send me
information on how I might order it?
{ bucs1!brian
Brian Michael Wendt {uiucdcs,cepu,ihnp4}!bradley! { brian
{ bucc2!brian
------------------------------
Date: Sun, 13 Sep 87 14:55:07 EDT
From: lakshman@ATHENA.MIT.EDU
Subject: Object oriented PROLOG
Hi! Does anybody have a source code for creating objects with
inheritence capabilities and other standard stuff in PROLOG that
can be made available in the public domain ?
Jaideep Ganguly
------------------------------
Date: 14 Sep 87 00:03:18 GMT
From: munnari!latcs1.oz!suter@uunet.UU.NET (David Suter)
Subject: proceedings wanted
Has anyone (or any university library) obtained a copy of the
proceedings of the San Diego conference on neural nets
(this year). I would like to obtain a copy of the index and a few of the
papers of interest. If anyone can help, could they please e-mail me.
---------------------
David Suter ISD: +61 3 479-2596
Department of Computer Science, STD: (03) 479-2596
La Trobe University, ACSnet: suter@latcs1.oz
Bundoora, CSnet: suter@latcs1.oz
Victoria, 3083, ARPA: suter%latcs1.oz@uunet.uu.net
Australia UUCP: ...!uunet!munnari!latcs1.oz!suter
TELEX: AA33143
FAX: 03 4785814
------------------------------
Date: Mon, 14 Sep 87 09:09:34 cdt
From: Jane Malin <malin%nasa-jsc.csnet@RELAY.CS.NET>
Subject: Query:qualitative models and discrete simulaiton
A group here have been exploring combining qualitative modeling and
discrete event simulation (rather than constraint propagation)
methodologies for the purpose of analyzing system effects of component
faults and failures. The purpose of such analysis would be to support
failure modes And effects analysis and model-based development of fault
management systems (including knowledge-based systems). The
application area is space subsystems, especially of the process control
type, such as power management and distribution, thermal control, or
air and water purification. In this area, there is a need to model
multiple operating modes of system components, including multiple
failure modes. In fact, the system behaviors of most interest are
changes from normal to faulty behavior that are consequences of faults
and failures elsewhere in the system. We have a promising working
prototype, which I reported on at the AI and Simulation workshop at
AAAI-87.
First, generally, I would like to know of others with ideas or
experience in combining the two methodologies, and of technical
problems encountered in their efforts. I would also like to get some
ideas on approaches to the technical issues that arise from the need to
model multiple modes, including failure modes, explicitly.
Thanks in advance, Jane Malin.
(malin%nasa-jsc.csnet@relay.cs.net).
------------------------------
Date: 14 Sep 87 04:25:10 GMT
From: mtune!codas!killer!usl!elg@RUTGERS.EDU (Eric Lee Green)
Subject: procedures and data
Values, data, and procedures:
Can we building a consistent world view in Lisp-like languages?
Overview:
We know what data is. Symbols have a value cell. This value cell
contains data. The process of evaluation returns this value.
But how do we reconcile this with procedures?
Procedures are data. They are stored in memory just like any other
data. The value-cell of symbols should be able to point to procedure
objects, if we are to be consistent, allowing interchangability and
not having special classes of symbols.
Evaluating a symbol with a procedure-value should, to be consistent
with the action of eval upon data objects, return the value of the
data cell of the symbol.
But wait, how do we actually execute the procedure!
Lisp does this with hand-waving and head-nodding, by making programs
consist of lists, the first element of which is always assumed to be a
procedure which needs executing.
In other words, we are introducing "syntactic sugar" to work around
the problem of having to explicitly indicate what we wish to be
executed.
Lisp and Scheme do this kind of hand-waving in many places. For
example,
(defun urgh (junk foo) (blah1) (blah2))
defines a procedure "urgh" in your symbol table. "urgh", (junk foo),
etc., are actually literal data input to the define-a-function
routine. Yet the form of the call to "defun" is virtually identical to
that of
(+ a b)
where we feed the VALUES of "a" and "b" to the "+" function.
Questions:
Can this dichotomy between value and execution be mended for
procedure-objects without hand-waving?
Would requiring literal data to be quoted be too big an imposition
upon the programmer, and would it be worth the gain in expressiveness?
(just imagine macros without the mess).
A possible but kludgy scheme:
When procedure symbols are encountered in the eval stream, they are
called with the next list in the eval stream as the parameter list. A
special prefix character is necessary to explicitly access the
procedure-object, to, for example, assign it to another variable.
A program might look like
+ (2 2)
print ( / (2 f))
etc.
In other words, the effect would be to move the parentheses around, in
comparison with traditional Lisp dialects.
Why this is kludgy:
We are, again, attaching special considerations to the evaluation of
symbols whose value is a procedure-object.
I would appreciate any discussion or references about this subject.
-- Eric
--
Eric Green {ihnp4,cbosgd}!killer!elg
{ut-sally,killer}!usl!elg
elg@usl.CSNET
------------------------------
Date: Mon, 14 Sep 87 16:38 EST
From: SHAPIRO%cgi.com@RELAY.CS.NET
Subject: Roommate (Female) at OOPSLA-87
I am looking for a female roommate at OOPSLA-87 in Orlando at the Hyatt.
I will be there Oct. 4 - 7 and would be willing to share the room
any of those nights. I do not know what the savings would be and
do not have reservations yet but I would be glad to take care of
those details if anyone responds.
Thank you,
Alison Shapiro
SHAPIRO%CGI.COM@RELAY.CS.NET
or, if you have trouble with the address, I can be reached
at Carnegie Group Inc (412) 642-6900 ex. 248 days.
------------------------------
Date: 15 Sep 87 13:19:45 EST (Tue)
From: "Steven J. Nowlan" <nowlan%ai.toronto.edu@RELAY.CS.NET>
Subject: Online Databases of Speech Data
We are starting a large speech project and are interested in getting
a quick survey of publically available databases of speech data. What
we are interested in for each such database you know of is:
1. who to contact to get access to the database
2. what format data is available in
3. content of speech samples (digits, vowels, e-group etc)
4. multi-speaker or single speaker
5. how much data is available for each speaker
6. is the data time aligned
7. is there labelling of data, and if so how accurate is it
I would appreciate any information you could forward to us.
- thanks
Steve Nowlan
Arpanet: nowlan%ai.toronto.edu@relay.cs.net
CSNet,Bitnet: nowlan@ai.toronto.edu
EAN,X.400: nowlan@ai.toronto.cdn
UUCP: {uunet,watmath}!ai.toronto.edu!nowlan
------------------------------
Date: Tue, 15 Sep 87 16:01:05 PDT
From: BERENJI%PLU@ames-io.ARPA
Subject: Lisp to C conversion!!
A friend of mine at USC asked me if I know of any programs for conversion of
Lisp code to C for micros. The only one I know is Sapiens Software. If
anyone knows more on this subject, I would appreciate it if you can let me know.
with many thanks in advance,
Hamid Berenji
berenji@ames-pluto.arpa
(415) 694-6070
------------------------------
Date: 15 Sep 87 21:52:12 GMT
From: brillig!sanborn@mimsy.umd.edu (Jim Sanborn)
Subject: ICAI for Literacy Training (request for info)
I've had a request for some info on the subject of computer-based literacy
training. As this is not currently one of my longer suits, perhaps someone
will be able to fill me in on one or more of the following:
(1) the Center for Instructional Development & Evaluation,
(2) videodisc-based training,
(3) an IBM product known as PALS,
(4) any ICAI literature specific to ``literacy training.''
Any and all information may be helpful, particularly regarding #4 above.
Please respond to me directly via e-mail. I'll sift through what I receive,
post a summary to comp.ai.edu, and hopefully spurn some discussion there.
-Jim Sanborn
Internet: sanborn@brillig.umd.edu Computer Science Dept.
Usenet: ...!uunet!mimsy!sanborn University of Maryland
Phone: (301)454-1516,2002 College Park, MD 20742
-Jim Sanborn
Internet: sanborn@brillig.umd.edu
Usenet: ...!uunet!mimsy!sanborn CS Dept, U of Maryland
Phone: (301)454-1516,2002 College Park, MD 20742
------------------------------
Date: Mon, 14 Sep 87 09:54 CDT
From: Herndon@HI-MULTICS.arpa
Subject: prolog
[Forwarded from Info-UNIX.]
Does anyone know where in netland I can find a public domain Prolog
environment. I got a copy of SBProlog from uunet but found that it is
heavily dependent on having BSD UNIX as the underlying OS. I am running
SysV 2.0 on a AT&T 3b1.
Please send any responses to me directly. My receipt of "info-unix" is
not very reliable.
Thanks in advance.
Sincerely,
William R. Herndon
------------------------------------------------------------------
William R. Herndon Secure Computing Technology Center
Honeywell
ARPA: Herndon@hi-multics.arpa
AT&T: (612) 782-7108
US MAIL: 2855 Anthony Ln. So. - Suite 130
St. Anthony, Mn. 55418
------------------------------
End of AIList Digest
********************
∂16-Sep-87 0238 LAWS@KL.SRI.Com AIList V5 #214 - Neural Networks, P = NP?, Science, Security
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Sep 87 02:38:32 PDT
Date: Tue 15 Sep 1987 22:52-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #214 - Neural Networks, P = NP?, Science, Security
To: AIList@SRI.COM
AIList Digest Wednesday, 16 Sep 1987 Volume 5 : Issue 214
Today's Topics:
Neural Networks - Bindings & Generalization,
Theory - P = NP?,
Philosophy - Is Computer Science Science?,
Programming - inSecurity
----------------------------------------------------------------------
Date: Fri, 11 Sep 87 22:20:38 EDT
From: Peter Sandon <sandon%dartmouth.edu@RELAY.CS.NET>
Subject: Re: Neural Networks & Unaligned fields
I did not read the Byte article either. However, assuming that
the network under discussion had no way to represent the similarity
relationship among different nodes that represent translated
versions of the same feature, it is not surprising that it would
have a difficult time generalizing from a given pattern to
an 'unaligned' version of that pattern.
Rumelhart pointed out to Banks that what is needed are many sets
of units having similar weight patterns, that is, weights that
are sensitive to translated versions of a given pattern. In addition,
the relationship between these similar units must be represented.
Rumelhart suggests adding units as needed but does not mention how
to relate these additional units to the trained unit. Fukushima did
something similar in his Neocognitron, by broadcasting a learned
weight set to an entire layer of units which were then all connected
to an OR unit. This OR unit then represented the fact that all the
units represented the same feature, modulo translation. Of course,
broadcasting weights requires more global control than many would
like, and the OR is not quite the relation we want for patterns of
any complexity.
In 1981, Hinton suggested a means of separately representing shape and
translation in a network, such that 'unaligned' patterns could be
recognized. In my thesis, I implemented a modified version of that
network scheme, in order to demonstrate that a network can generalize
object recognition across translation. The network that I implemented
is five layers deep, which proved too much for standard backpropagation
(the generalized delta rule) and for my extensions to the GDR.
However, generalization across translation can be demonstrated in
a subnetwork of this network. I am working on further improvements
to backpropagation that will allow the entire network to be trained.
It is important to recognize that there are many useless
generalizations that might be made, and a few useful ones. The
Hamming distance between two 'T's that are offset from one another
is much greater than that between a 'T' and a 'C' that is offset such
that it overlaps much of the 'T'. What is the 'correct' generalization
to be made when trying to classify these patterns? In order to get
the desired generalization, the network must be biased toward
developing representations in which the Hamming distances (of the
intermediate representations) between within-class patterns is
small compared to that between other patterns. Generalization based
on similarity will then be appropriate. Without such biases, 'good'
generalization would be quite surprising.
--Pete Sandon
------------------------------
Date: 15 Sep 87 21:31:50 GMT
From: jr@io.att.com (j.ratsaby)
Subject: need email addresses
Would you have email addresses of some graduate fellows or
professors that deal with neural-nets in the university of
Toronto and Cambridge (England)?
I would really appreciate it since I'm engaged in research
on stochastic neural-nets,
I recieved some answers from a few of you but unfortunately
there was a fatal shutdown here and I lost the email addresses.
thanks in advance,
joel
------------------------------
Date: 12 Sep 87 06:30:36 GMT
From: ihnp4!alberta!mnetor!genat!maccs!leb@ucbvax.Berkeley.EDU
(Anthony Hurst )
Subject: P may indeed = NP !!
I normally do not keep track of mathematics papers, but I happened
to notice an interesting news item that jumped right out at me. It
was reported in a recent issue of the University of Guelph's "Alumnus"
magazine. (Guelph is in Ontario, Canada).
Included here are three excerpts from the authoress Mary Dickieson.
She writes:
"One of the most perplexing problems in computer science may have
been solved by Professor Ted Swart, who has a joint appointment in
the departments of Mathematics & Statistics and Computing & Infor-
mation Science. He has written a paper offering proof that P = NP.
...
"Dr. Swart cautions that the jury is still out on whether his approach
will be proved or disproved by his peers, but already his pronouncement
has caused a stir in the computer world."
...
"Dr. Swart's problem establishes that the Hamilton circuit problem can
be solved in polynomial time by converting a mathematical programming
formulation of the problem into a linear programming formulation and
using existing polynomial time algorithms as established by Kachiyan
and Karmarkar."
What I should like to know is, has Swart's paper "caused a stir in
the computer world" and if not, why not?
--
seismo!mnetor!{genat,lsuc}!maccs!leb Anthony Hurst
McMaster Dept. of Comp. Sci. & Systems (416)-525-9140 x4030
Will there be cigarettes in heaven?
------------------------------
Date: 14 Sep 87 12:25:56 GMT
From: necntc!linus!faron!bs@eddie.mit.edu (Robert D. Silverman)
Subject: Re: P may indeed = NP !!
In article <761@maccs.UUCP] leb@maccs.UUCP (Anthony (Tony) Hurst) writes:
]
]"One of the most perplexing problems in computer science may have
]been solved by Professor Ted Swart, who has a joint appointment in
]the departments of Mathematics & Statistics and Computing & Infor-
]mation Science. He has written a paper offering proof that P = NP.
]...
No one, repeat no one who does serious research in computational complexity
really belives P=NP. I have seen several such 'proofs'. All are basically
the same: Some imaginative person formulates a problem in NP as a linear
program. Unfortunately, most of these people fail to realize that their
'formulation' requires a number of variables that is exponential in the
size of the problem. Poof goes the proof.
I had already heard of Prof. Swart's purported proof and heard that it
suffers from the same defect.
Bob Silverman
------------------------------
Date: 15 Sep 87 00:23:49 GMT
From: jaw@ames-aurora.arpa (James A. Woods)
Subject: Re: P = NP (review article in The Economist, Sept. 4, 1987)
# "The average mathematician should not forget that
intuition is the final authority." -- J. Barkley Rosser
"There's only one two." -- local TV station slogan
An informative synopsis of P=NP? here is surprising for those
accustomed to the usual style of general-purpose business periodicals.
One would expect something like this to appear in the more outre
New Scientist (hooray for British science writing!), where it might be
by-lined by John Maddox. But the enormity of the question, coupled
with its tight connection to operations research, makes it all
the more important that a general audience is exposed to the art.
The treatment comes complete with mention of revealing Cook/Karp/Levin
history, the role of random oracles, circuit complexity, and the solution
of the old Chomsky grammar chestnut by Neil Immerman. As they say in
the Southern states, "check it out" (of your local public library).
Also entertaining is Steven Johnson's plea for a halt to bogus P=NP
proofs, a cease fire perhaps encouraged by a monetary pot to contain a
$1000 bond for each submission posted before publication, which would then
be forfeited after a bug is found, and thence to the eventual prize
winner, Goedel notwithstanding. It's too bad that a team of "grunt
mathematicians" (*) must still filter the fluff.
Thoughts of anyone other than a Blum or a Karmarkar or a Matyasevich
or an Adelman coming through with a solution may be disturbing to some
workers in the field. Indeed, history has shown repeated lack of faith
with similar assaults [the Bieberbach Conjecture (De Branges), the Poincare
Conjecture (still unresolved), and Fermat's Last Theorem, where episodic
premature announcements in AMS Notices leave no one with even the hope that
a counterexample would fit on a T-shirt.]
As for P=NP, again, refer to the discussion in The Economist for
the week ending 4 September 1987.
-- James A. Woods (ames!jaw)
(*) Term first seen in the seminal paper by DeMillo, Lipton, and Perlis,
CACM, May 1979 -- "Social Processes and Proofs of Theorems and Programs",
well worth your attention for wry commentary and mathematics anecdotes.
------------------------------
Date: 15 Sep 87 06:51:20 GMT
From: maiden@sdcsvax.ucsd.edu (VLSI Layout Project)
Subject: Re: P = NP (review article in The Economist, Sept. 4, 1987)
In article <1035@aurora.UUCP> jaw@aurora.UUCP (James A. Woods) writes:
>Indeed, history has shown repeated lack of faith
>with similar assaults [the Bieberbach Conjecture (De Branges), the Poincare
>Conjecture (still unresolved), and Fermat's Last Theorem, where episodic
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
Only unresolved in three dimensions. Resolved for all
others.
------------------------------
Date: 15 Sep 87 12:11:07 GMT
From: bloom-beacon!gatech!hubcap!steve@think.com ("Steve" Stevenson)
Subject: Re: P = NP subclasses
I once heard a commment that most instances of "NP-complete" problems
encountered in practice do not exhibit the pathological behavior of
the exponential growth function.
Take your favorite characterization of the NP-complete problem.
Questions:
What is the largest subclass of instances (decidable or not) which does
not exhibit the exponetial? What is the largest Turing-decidable
subclass?
--
Steve (really "D. E.") Stevenson steve@hubcap.clemson.edu
Department of Computer Science, (803)656-5880.mabell
Clemson University, Clemson, SC 29634-1906
------------------------------
Date: 10 Sep 87 09:27:00 GMT
From: johnson@p.cs.uiuc.edu
Subject: Re: Is Computer Science Science?
There is a general rule that disciplines with names like XXX Science are
not a science. In spite of that, there are some general laws that arise
out of CS. My favorite are all from computability and complexity theory,
though I do not do that kind of research and don't plan to.
Undecideability -- just because a question has an answer doesn't mean
that there is a method to answer it. E.g. all programs will either
terminate or not terminate, but the halting problem is undecideable.
NP complete problems -- just because a proposed answer is very easy to
check for correctness does not mean that the question is easy to solve.
NP complete problems are those whose answer can be checked in polynomial
time but where any method for finding the solution must essentially
check all possible solutions, taking exponential time. In a similar
manner, a proof can be easily checked for correctness, but it is
undecideable (in any interesting theory) whether there exists a proof
or not for a particular theorem.
------------------------------
Date: 14 Sep 87 12:06:24 GMT
From: uunet!mnetor!yetti!geac!daveb@seismo.css.gov (Brown)
Subject: inSecurity (was Re: Is Computer Science Science?)
In article <8300004@osiris.cso.uiuc.edu> goldfain@osiris.cso.uiuc.edu writes:
>IN SPITE OF RESEARCH, THE FOLLOWING ARE TENETS OF THE CURRENT WORKPLACE:
>"There is no such thing as real computer security."
>"There is always one more bug."
These two tenets are related to each other in an interesting way:
provably secure operating systems exist (so-called "A1" systems), but
the proof merely demonstrates that
a) An externally specified standard is met, and
b) Certain insecure features have a diminishingly small bandwidth.
(a) is related to the buggyness theorem by one level of indirection: there
is no proof in the system that the extra-systemic security policy does not
contain bugs.
--dave (and I can point one out, oh orange-bookers) c-b
--
David Collier-Brown. {mnetor|yetti|utgpu}!geac!daveb
Geac Computers International Inc., | Computer Science loses its
350 Steelcase Road,Markham, Ontario, | memory (if not its mind)
CANADA, L3R 1B3 (416) 475-0525 x3279 | every 6 months.
------------------------------
Date: 14 Sep 87 16:06:37 GMT
From: kodak!elmgate!ram@cs.rochester.edu (Randy Martens)
Subject: Re: Is Computer Science Science?
I am of the firm opinion that there is NO such thing as
computer science. To quote (and I have forgotten the attribution)
"Computer Science bears the same relationship to Real Science, that
plumbing bears to Hydrodynamics."
There is, however, Computer Engineering. (and Software Engineering,
and Systems Engineering etc.). Science is the discovery of the new.
Engineering takes what the scientists have found, and finds ways
to do useful things with it. The two are like Yin and Yang, closely
interrelated, but not the same, and each dependant on the other.
I am a computer engineer.
Randy Martens
"Reality - What a Concept !" - R.Williams
------------------------------
End of AIList Digest
********************
∂16-Sep-87 0520 LAWS@KL.SRI.Com AIList V5 #215 - Bibliography
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Sep 87 05:20:26 PDT
Date: Tue 15 Sep 1987 23:02-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #215 - Bibliography
To: AIList@SRI.COM
AIList Digest Wednesday, 16 Sep 1987 Volume 5 : Issue 215
Today's Topics:
Bibliography - Leff File a60C
----------------------------------------------------------------------
Date: Mon, 14 Sep 1987 07:42 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: definitions
Definitions for A60C
D MAG136 IEEE Transactions on Geoscience and Remote Sensing\
%V 25\
%N 3\
%D MAY 1987
D MAG137 Soviet Journal of Computer and Systems Sciences\
%V 24\
%N 6\
%D NOV-DEC 1986
D MAG138 Pattern Recognition Letters\
%V 5\
%N 5\
%D MAY 1987
D MAG139 Pattern Recognition Letters\
%V 6\
%N 1\
%D JUN 1987
D MAG140 International Journal of Man Machine Studies\
%V 26\
%N 1\
%D JAN 1987
D MAG141 Pattern Recognition\
%V 20\
%N 3\
%D 1987
D MAG142 Computer Vision, Graphics and Image Processing\
%V 39\
%N 2\
%D AUG 1987
D MAG147 Fuzzy Sets and Systems\
%V 23\
%N 1\
%D JUL 1987
D MAG144 IEEE Transactions on Systems, Man, and Cybernetics\
%V 17\
%N 3\
%D MAY-JUN 1987
D MAG145 International Journal of Man-Machine Studies\
%V 26\
%N 2\
%D FEB 1987
------------------------------
Date: Mon, 14 Sep 1987 07:48 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: a60C
%A D. Tsichritzis
%A E. Fiume
%A S. Gibbs
%A O. Nierstrasz
%T KNOs: Knowledge Acquisition, Dissemination, and Manipulation Objects
%J ACM Transactions on Office Information Systems
%V 5
%N 1
%D JAN 1987
%P 96
%K AA06
%A S. Baronti
%A R. Carla
%A V. M. Sacco
%T Digital Filtering of APT Images from NOAA Series Satellites
%J Alta Frequenza
%V 55
%N 6
%D NOV-DEC 1986
%P 391-394
%K AI06 AA03
%A S. W. Wharton
%T A Spectral-Knowledge-Based Approach for Urban Land-Cover Discrimination
%J MAG136
%P 272-282
%K AA03 AI06
%A T. Lee
%A J. A. Richards
%A P. H. Swain
%T Probabilistic and Evidential Approaches for Multisource Data Analysis
%J MAG136
%P 283-293
%K AA03 O04 AI06
%A T. D. Garvey
%T Evidential Reasoning for Geographic Evaluation for Helicopter Route
Planning
%J MAG136
%P 294-304
%K O04 AA03 AA19 AA18
%A T. Matsuyama
%T Knowledge-Based Aerial Image Understanding Systems and Expert Systems
for Image Processing
%J MAG136
%P 305-316
%K AI06 AI01 AA18
%A D. M. Mckeown
%T The Role of Artificial Intelligence in the Integration of Remotely
Sensed Data with Geographic Information Systems
%J MAG136
%P 330-348
%K AI06 AA03
%A D. G. Goodenough
%A M. Goldberg
%A G. Plunkett
%A J. Zelek
%T An Expert System for Remote Sensing
%J MAG136
%P 349-359
%K AI01 AA03
%A Donnie R. Ford
%A Bernard Schroer
%T An Expert Manufacturing Simulation System
%J Simulation
%V 48
%N 5
%D MAY 1987
%P 193-200
%K AA26 AA28 AI01
%A Joseph M. Mellichamp
%A Ahmed F. A. Wahab
%T An Expert System for FMS Design
%J Simulation
%V 48
%N 5
%D MAY 1987
%P 201-209
%A R. R. Yager
%T Towards a General Theory of Reasoning with Uncertainty. Part II:
Probability
%J International Journal of Man-Machine Studies
%V 25
%N 6
%D DEC 1986
%P 613-632
%K O04
%A G. S. Pospelov
%A A. M. Razin
%T Principle Trends in the Development of Modern Expert Systems (Review
of Foreign Studies)
%J Nauchno-Tekhnicheskaya Informatsiya, Seriya II - Informatsionnye
Protessy I Sistemy
%N 2
%D 1987
%P 1-11
%K AI01 AT08
%A Alasdair Urquhart
%T Hard Examples for Resolution
%J Journal of the Association for Computing Machinery
%V 34
%N 1
%D JAN 1987
%P 209
%K AI11
%A Yoshihito Toyama
%T On the Church-Rosser Property for the Direct Sum of Term Rewriting
Systems
%J Journal of the Association for Computing Machinery
%V 34
%N 1
%D JAN 1987
%P 128-143
%K AI11 AI14
%A C. Asmuth
%T An Application of Group Representation Theory to Picture Recognition
%J Computers and Mathematics with Applications
%V 13
%N 4
%D 1987
%P 363-366
%K AI06
%A S. M. Yefimova
%A Ye. V. Suvorov
%T A $PI$-Graph Model for Representing Knowledge and a Method for Its
Hardware Realization on the Basis of the Labelled Arrays Method
%J MAG137
%P 1-14
%K AI16
%A V. B. Borshchev
%T Logic Programming
%J MAG137
%P 15-32
%K AI10
%A V. Ye. Zhukovin
%T Fuzzy Multicriterial Decision-Masking Problems
%J MAG137
%P 33-37
%K AI13 O04
%A Ye. P. Balashov
%A M. S. Kupriyanov
%A L. G. Loginskaya
%T Construction and Interpretation of Fuzzy Algorithms
%J MAG137
%P 33-37
%K O04
%A Kh. I. Tani
%T Interfaces for Intelligent Computing Systems
%J MAG137
%P 44-57
%K O01
%A A. A. Dmitriyev
%A S. L. Zenkevich
%T Logic Control of an Adaptive Robotic System
%J MAG137
%P 100-106
%K AI07 AI10
%A G. G. Ananiaskhvili
%A N. N. Bichinashvili
%A Z. I. Mundzhishvili
%A T. L. Khomeriki
%T A Method for Identifying Natural Language Words in Dialogue
Systems
%J MAG137
%P 160
%K AI02
%A P. A. Bakut
%A E. F. Baburov
%A A. M. Varfolomeev
%A T. K. Vinstyuk
%A N. S. Gritsenko
%A V. V. Gritsyk
%A A. A. Demin
%A B. V. Kisil
%A L. M. Krasnov
%A V. P. Loginov
%A A. Yu Lutsyk
%A V. K. Marigodov
%A R. M. Palenichka
%A A. N. Svenson
%A K. N. Sviridov
%A N. D. ustinov
%A N. Yu Khomich
%A G. T. Cherchyk
%T Parallel Methods for Pattern Recognition
%I Naukova Dumka
%C Kiev
%D 1985
%K H03 AI06 AT15
%A P. I. Balk
%T Application of Demonstration Calculations on a Computer in the Study of the
Properties of Linear Mappings in Finite-Dimensional Spaces
%J Kibernetika
%D 1986
%N 5
%P 106-112
%K AI16
%X Russian with English Summary
%A James Bezdeck
%A Richard J. Hathaway
%A Ralph E. Howard
%T Coordinate Descent and Clustering
%J Control Cybernet.
%V 15
%D 1986
%N 2
%P 195-204
%K AI03 O06
%A Gildas Brossier
%T Study of Rectangular Proximity Matrices with a View to Classification
%J Rev. Statist. Appl
%V 34
%D 1986
%N 4
%P 43-68
%A E. V. Dyukova
%T Complexity of Realization of Some Pattern Recognition Procedures
%J Zh. Vychisl. Mat. i. Mat. Fiz
%V 27
%D 1987
%N 1
%P 114-127
%K AI06
%X Russian
%A Claude Kirchner
%A Helene Kirchner
%T REVEUR-3: The Implementation of a General Completion Procedure
Parameterized by Builtin Theories and Strategies
%J Sci. Comput. Programming
%V 8
%D 1987
%N 1
%P 69-86
%K AI14
%A G. D. Penev
%T Method for Constructing Pairs of Identical Points of Retinas
%J Vestnik Leningrad. Univ. Mat. Mekh. Astronom.
%D 1986
%V 4
%P 78-82
%K AI06
%X Russian with English Summaries
%A Olga Stepanokova
%A Petr Stepanek
%T Estimation of the Complexity of Transformed Logic Programs
%J Acta Polytech. Prace CVUT Praze Ser. IV Tech. Teoret.
%V 1986
%N 3
%P 51-66
%K AI10
%A T. M. V. Janssen
%T Foundations and Applications of Montague Grammar. Part 2.
Applications to Natural Language
%S CWI Tract
%V 28
%I Stichting Mathematisch Centrum. Centrum voor Wiskunde en Informatica
%C Amsterdam
%D 1986
%X ISBN 90-6196-3067-0
%A O. S. Agaronyan
%T Image Segmentation Using the Paving of a Plane by Voronoi Polygons
%J Avtomat. i. Telemekh.
%V 1986
%N 10
%P 95-100
%K AI06 O06
%A Daniel Leven
%A Micha Sharir
%T Planning a Purely Translational Motion for a Convex Object in
Two-Dimensional Space Using Generalized Voronoi Diagrams
%J Discrete Computational Geometry
%V 2
%D 1987
%N 1
%P 9-31
%K AI09 AI07 O06
%A Akiria Nakamura
%A Kunio Aizawa
%T Detection of Interlocking Components in Three-Dimensional Digital
Pictures
%J Inform. Sci
%V 40
%D 1986
%N 2
%P 143-153
%K AI06 O06
%A E. Vi-Tong
%A P. Gaillard
%T An Algorithm for Non-Supervised Sequential Classification of Signals
%J MAG138
%P 307-316
%K AI06 O06
%A I. D. Longstaff
%A J. F. Cross
%T A Pattern Recognition Approach to Understanding the Multi-Layer Perceptron
%J MAG138
%P 315-320
%K AI06 AI12
%A Z. Aviad
%A E. Lozinskskii
%T Semantic Thresholding
%J MAG138
%P 321-328
%K AI16
%A K. C. Markham
%T Some Segmentation Processes for Application with a Spoke Filter
%J MAG138
%P 329-336
%K AI06
%A S. Chang
%A L. S. Davis
%A S. M. Dunn
%A J. O. Eklundh
%A A. Rosenfeld
%T Texture Discrimination by Projective Invariations
%J MAG138
%P 337-342
%K AI06
%A P. G. Selfridge
%T Using a Simple Shape Measure to Improve Automatic 3D Reconstruction
%J MAG138
%P 343-346
%K AI06
%A B. Bhanu
%A C. C. Ho
%A T. Henderson
%T 3-D Model Building for Computer Vision
%J MAG138
%P 349-356
%K AI06
%A J. P. Gambotto
%A T. S. Huant
%T Motion Analysis of Isolated Targets in Infrared Image Sequences
%J MAG138
%P 357
%K AI06
%A S. F. Rushinek
%A A. Rushinek
%T The Effects of Sources of Applications Programs on User Satisfaction-
An empirical Study of Micro, Mini and Mainframe Computers
Using an Interactive Artificial Intelligence Expert System
%J Cybernetica
%V 30
%N 1
%D 1987
%P 75
%K AA15 AI01
%A Curtis P. Langlotz
%A Lawrence M. Fagan
%A Samson W. Tu
%A Branimir I. Sikic
%A Edward H. Shortliffe
%T A Therapy Planning Architecutre that combines Decision Tehory and Artificial
Intelligence Techniques
%J Computers and Biomedical Research
%V 20
%N 3
%D JUN 1987
%K AA13 AA01 AI01
%A G. S. Blair
%A J. A. Mariani
%A J. R. Nicol
%A D. Shepherd
%T A Knowledge-Based Operating System
%J The Computer Journal
%V 30
%N 3
%D JUN 1987
%P 193-200
%K AA08
%A Donald Sannella
%A Andrzej Tarlecki
%T On Observational Equivalence and Algebraic Specification
%J Journal of Computer and System Sciences
%V 34
%N 2-3
%D APR-JUN 1987
%P 150-178
%K AA08
%A J. A. Kakowsky
%T Why Horn Formulas Matterin Computer Science: Initial Structure and Generic
Examples
%J Journal of Computer and System Sciences
%V 34
%N 2-3
%D APR-JUN 1987
%P 150-179
%K AI10
%A E. R. Davis
%T A New Framework for Analyzing the Properties of the Generalized Hough
Transform
%J MAG139
%P 1-8
%K AI06
%A E. R. Davies
%T A New Parameterisation of the Straight Line and its Application for
the Optimal Detection of Objects with Straight Lines
%J MAG139
%P 9-14
%K AI06
%A A. I. Watson
%T A New Method of Classification for Landsat Data using 'Watershed' Algorithm
%J MAG139
%P 15-20
%K AA03 AI06
%A P. D. L. Williams
%T Results from a Sideways Looking Radar (SLAR) with a Very Low Pulse
Repetition Frequency
%J MAG139
%P 21-26
%K AI06
%A J. Kittler
%A J. Eggleton
%A J. Illingsworth
%A K. Paler
%T An Averaging Edge Detector
%J MAG139
%P 27-32
%K AI06
%A K. Paler
%A K. M. Crennell
%A J. Kittler
%A B. N. Dobbins
%A B. L. Button
%A C. Wykes
%T Identification of Fringe Minima in Electronic Speckle Pattern Images
%J MAG139
%P 33-44
%K AI06
%A D. Chetverikov
%T Texture Imperfections
%J MAG139
%P 45-50
%K AI06
%A A. Blake
%A A. Zisserman
%T Localizing Discontinuities Using Weak Continuity Constraints
%J MAG139
%P 51-60
%K AI06
%A J. Skingley
%A A. J. Rye
%T The Hough Transform Applied to SAR Images for Thin Line Detection
%J MAG139
%P 61-69
%K AI06
%A D. T. Berry
%T Colour Recognition Using Spectral Signatures
%J MAG139
%P 69-76
%K AI06
%A S. Tominaga
%T Expansion of Color Images Using Three Perceptual Attributes
%J MAG139
%P 77-86
%K AI06
%A K. Ozawa
%T A Picture Synthesizing System with a Database of Semantic Picture
Elements of 'Ukiyoe' Colour Woodprinted Pictures
%J MAG139
%P 87
%K AA025
%A N. Heaton
%T Review of Artificial Intelligence, Vol 2, Bibliographic Summaries of
the Select Literature by H. R. Rylko
%J Applied Ergonomics
%V 18
%N 2
%D JUN 1987
%P 162
%K AT07
%A P. P. Das
%A P. P. Chakrabarti
%A B. N. Chatterji
%T Generalized Distances in Digital Geometry
%J Information Sciences
%V 42
%N 1
%D JUN 1987
%P 51-68
%K AI06
%A A. Sengupta
%A A. Sen
%T On the Diagnosability Problem for a General Model of Diagnosable Systems
%J Information Sciences
%V 42
%N 1
%D JUN 1987
%P 83
%K AA21
%A Frank K. Soong
%A Aaron E. Rosenberg
%A Bing-Hwang Juang
%A Lawrence E. Rabiner
%T A Vector Quantization Approach to Speaker Recognition
%J AT&T Technical Journal
%V 66
%N 2
%D MAR-APR 1987
%K AI05
%A Jacques Cohen
%A Timothy J. Hickey
%T Parsing and Compiling Using Prolog
%J TOPLAS
%P 125-163
%V 9
%N 2
%K AA08 T02
%A C. Alec Chang
%A Jay Goldman
%A Jove M. Pan
%T Part Positioning with Feature Marks for Computer Vision Systems
%J IEEE Transactions
%V 19
%N 2
%D JUN 1987
%P 182-189
%K AA26 AI06
%A K. Lien
%A G. Suzuki
%A A. M. Westerberg
%T The Role of Expert Systems Technology in Design
%J Chemical Engineering Science
%V 42
%N 5
%D 1987
%P 1049-1072
%K AA05 AI01
%A Brian L. Schmidt
%T A Natural Language System for Music
%J Computer Music Journal
%P 25-34
%V 11
%N 2
%D SUMMER 1987
%K AA25 AI02
%A Wojcech Busskowski
%T Categorial Grammars in the Eyes of Logic
%B BOOK83
%P 163-174
%K AA08
%A L. Cairmaz
%T Nonstandard Logics of Programs
%B BOOK83
%P 285-295
%K AA08 AI11
%A J. Dassow
%T Comparison of Some Types of Regulated Rewriting
%B BOOK83
%P 301-313
%K AI11
%A I. Guessarian
%T Algebraic Semantics and Logics of Programs
%B BOOK83
%P 423-431
%K AA08 AI11
%A K. P. Jantke
%T Terminal Algebraic Semantic as a Basis for Program Synthesis
%B BOOK83
%P 479-490
%K AA08
%A M. Kudlek
%T Languages Defined by Semi-Thue and Regular Systems
%B BOOK83
%P 537-553
%K AA08
%A G. Mirkowska
%A L. Stapp
%T Algorithmic Logic Can Express Progressive Behavior of Programs
%B BOOK83
%P 615-622
%K AI10 AA08
%A Sara Porat
%A Nissim Francez
%T Full Commutation and Fair Termination in Equational (and Combined)
Term Rewriting Systems
%B BOOK82
%P 21-41
%K AI14
%A Donald Sannella
%A Andrzej Tarlecki
%T Extended ML: An Institution-Independent Framework for Formal
Program Development
%B BOOK84
%P 364-389
%K AA08
%A M. A. Suchenek
%T Compactness in Logic of Programs
%B BOOK82
%P 803-810
%K AA08
%A John R. Dixon
%A Eugene C. Libardi
%A Steven C. Luby
%A Mohan Vaghul
%A Melvin K. Simmons
%T Expert Systems for Mechanical Design - Examples of Symbolic
Representations of Design Geometries
%J Engineering with Computers
%V 2
%N 1
%D 1987
%P 1-10
%K AA05
%A David G. Ullman
%A Thomas A. Dietrich
%T Mechanical Design Methodology - Implications on Future Developments of
Computer-Aided Design and Knowledge-Based Systems
%J Engineering with Computers
%V 2
%N 1
%D 1987
%P 21-29
%K AA05 AI09
%A William J. Rasdorf
%A Karen J. Ulberg
%A John W. Baugh
%T A Structure-Based Model of Semantic Integrity Constraints for Relational
Databases
%J Engineering with Computers
%V 2
%N 1
%D 1987
%P 31-39
%A H. Schwartzel
%A L. Wiesbaum
%T New Computer Structures for AI Real Time Applications
%B Yearbook 1986 I: DGLR, Annual Meeting
%C Munich, West Germany
%D Oct 8-10 1986
%P 201-208
%K O03
%A NurErol
%A Christian Freksa
%T An Approach to Structuring Knowledge for a Design Support System
%B Yearbook 1986 I: DGLR, Annual Meeting
%C Munich, West Germany
%D Oct 8-10 1986
%P 201-208
%K A05 Structural Design aircraft design STUDEL
%A S. M. Alexander
%T An Expert System for the Selection of Scheduling Rules in a Job Shop
%J Computers and Industrial Engineering
%V 12
%N 3
%D 1987
%P 167-172
%K AA05 AI01
%A M. Fitting
%T Partial Models and Logic Programming
%J Theoretical Computer Science
%V 48
%N 2-3
%D 1986
%P 229-256
%K AI10
%A Y. Toyama
%T Counterexamples to termination for the Direct Sum of Term Rewriting Systems
%J Information Processing Letters
%P 141-144
%V 25
%N 3
%D MAY 29, 1987
%K AI11
%A M. J. Fischer
% N. Immerman
%T Interpreting Logics of Knowledge in Propositional Dynamic Logic with Converse
%J Information Processing Letters
%P 175-182
%K AI10
%V 25
%N 3
%A N. A. Alexandridis
%A P. D. Tsanakas
%T An Encoding Scheme for the Efficient Representation of Hierarchical Image
Structures
%J Information Processing Letters
%V 25
%N 3
%D MAY 29, 1987
%P 199-206
%K AI06 O06
%A J. H. Boose
%A J. M. Bradshaw
%T Expertise Transfer and Complex Problems: Using Aquinas as a Knowledge-
Acquisition Workbench for Knowledge-Based Systems
%J MAG140
%P 3-28
%K AI01
%A J. Diederich
%A I. Ruhmann
%A M. May
%T KRITION: A Knowledge-Acquisition Tool for Expert Systems
%J MAG140
%P 29-40
%K AI01
%A L. Eshelman
%A D. Ehret
%A J. McDermott
%A M. Tan
%T MOLE: A Tenacious Knowledge-Acquisition Tool
%J MAG140
%P 41-54
%K AI01
%A W. A. Gale
%T Knowledge-Based Knowledge Acquisition for a Statistical Consulting System
%J MAG140
%P 55-64
%K AI01
%A G. Klinker
%A J. Bentolila
%A S. Genetet
%A M. Grimes
%A J. McDermott
%T Knack-Report Driven Knowledge Acquisition
%J MAG140
%P 65-80
%K AI01
%A D. C. Littman
%T Modeling Human Expertise in Knowledge Engineering
%J MAG140
%P 81-92
%K AI01 AI09
%A K. Morik
%T Acquiring Domain Models
%J MAG140
%P 93-104
%K AI01
%A M. A. Musen
%A L. M. Fagan
%A D. M. Combs
%A E. H. Shortliffe
%T Use of a Domain Model to Drive an Interactive Knowledge-Editing Tool
%J MAG140
%P 105
%K AI01
%A Feng-Cheng Chang
%T Power Series Unification and Reversion
%J Applied Mathematics and Computation
%V 23
%N 1
%D JULY 1987
%P 7-24
%K AI14
%A Suranjan De
%A ShuhShen Pan
%A Andrew Whinston
%T Temporal Semantics and Natural Language Processing in a Decision Support
System
%J Information Systems
%V 12
%N 1
%D 1987
%P 29-48
%A E. Granum
%A G. A. Shippey
%A R. J. H. Bayley
%A G. Hamilton
%A D. Rutovitz
%T Real Time Digital Thresholding of Data from Continuous Scanning Linear Arrays
%J Signal Processing
%V 12
%N 4
%P 349-362
%K AI06
%A L. Gupta
%A M. D. Srinath
%T Contour Sequence Moments for the classification of Closed Planar Shapes
%J MAG141
%P 273-272
%K AI06
%A Noboru Babaguchi
%A Tsunehiro Aibara
%T Curvedness of a Line Picture
%J MAG141
%P 273-280
%K AI06
%A C. H. Hayden
%A R. C. Gonzelez
%A Ploysongsang
%T A Tempral Edge-Based Image Segmentor
%J MAG141
%P 281-290
%K AI06
%A H. Lynn Beus
%A S. S. H. Tiu
%T An Improved Corner Detection Algorithm Based on Chain-coded Plain Curves
%J MAG141
%P 291-296
%K AI06
%A Satoshi Suzuki
%A Keiichi Abe
%T Binary Picture Thinning by an Iterative Parallel Two Subcycle Operation
%J MAG141
%P 297-308
%K AI06
%A J. C. Fiala
%A R. M. Haralick
%T Comparison of a Regular and an Irregular Decomposition of Regions and Volumes
%J MAG141
%P 309-320
%K AI06
%A Maylor K. Leung
%A Yee-Hong Yang
%T A Region Based Approach for Human Body Motion Analysis
%J MAG141
%P 321-340
%K AI06
%A C. G. Leedham
%A A. C. Downton
%T Automatic Recognition and Transcription of Pitman's Handwritten Shorthand--
An Approach to Shortforms
%J MAG141
%P 341-349
%K AI06 AA06
%A A. M. Wallace
%T An Informed Strategy for Matching Models to Images of Fabricated Objects
%J MAG141
%P 349-364
%K AI06 AI07
%A H. B. Bidasaria
%T Least Desirable Feature Elimination in a General Pattern Recognition Problem
%J MAG141
%P 365
%K AI06
%A Tery Caelli
%A Shyamala Nagendran
%T Fast Edge-Only Matching Techniques for Robot Pattern Recognition
%J MAG142
%P 131-143
%K AI06 AI07
%A M. Pilar Martinez-perez
%A Javier Jimenez
%A Jose L. Navolon
%T A Thinning Algorithm Based on Contours
%J MAG142
%P 186-201
%K AI06
%A S. A. Lloyd
%A E. R. Haddow
%A J. F. Boyce
%T A Parallel Binocular Stereo Algorithm Utilizing Dynamic Programming and
Relaxation Labelling
%J MAG142
%P 202-225
%K AI06
%A Federico Bumbaca
%A Kenneth C. Smith
%T Design and Implementation of a Colour Vision Model for Computer Vision
Applications
%J MAG142
%P 226-245
%K AI06
%A Joseph O'Rourke
%A Heather Booth
%A Richard Washington
%T Connect-the-Dots: A New Heuristic
%J MAG142
%P 258
%K AI06
%A R. Banares-Alcantara
%A A. W. Westerberg
%A E. I. Ko
%A M. D. Rychener
%T Decade - A Hybrid Expert System for Catalyst Selection - I Expert System
Considerations
%J Computers and Chemical Engineering
%V 11
%N 3
%D 1987
%P 265-278
%K AI01 AA05
%A D. Dubois
%A H. Prade
%T Twofold Fuzzy Sets and Rough Sets
Some Issues in Knowledge Representation
%J MAG147
%P 3-18
%K O04 AI16
%A B. Bouchon
%T Fuzzy-Inferences and Conditional Probability Distributions
%J MAG147
%P 33-42
%K O04 AI16
%A A. O. Arigoni
%T Heuristic Embodiment of Evidence - Evaluation of the Credibility of
Hypothesized Causes
%J MAG147
%P 43-54
%K O04
%A H. Shvaytser
%T On a Consistency measure for Object Labeling Problems
%J MAG147
%P 55-72
%K O04 AI06
%A D. Norris
%A B. W. Pilsworth
%A J. F. Baldwin
%T Medical Diagnosis from Patient Records - A Method Using Fuzzy
Discrimination and Connectivity Analyses
%J MAG147
%P 73-88
%K AA01 AI01 O04
%A J. Anderson
%A W. Bandler
%A L. J. Kohout
%A C. Trayner
%T A Route-Choosing Medical Diagnostic Technique
%J MAG147
%P 89-96
%K AA01 AI01 O04
%A T. P. Martin
%A J. F. Baldwin
%A B. W. Pilsworth
%T The Implementation of FPROLOG - A Fuzzy Prolog Interpreter
%J MAG147
%P 119-130
%K T01 O04
%A B. W. Pilsworth
%T Review of the Panel Discussion on Fuzzy Reasoning in Artificial
Intelligence and Operations Research
%J MAG147
%P 159
%K AA05 O04
%A Edward L. Fisher
%A Shimon Y. Nof
%T Knowledge-Based Economic Analysis of Manufacturing Systems
%J Journal of Manufacturing Systems
%V 6
%N 2
%D 1987
%P 137-150
%K AA05 AA06
%A R. Milne
%T Strategies for Diagnosis
%J MAG144
%P 333-339
%K AA21
%A P. K. Fink
%A J. C. Lusth
%T Expert Systems and Diagnostics Expertise in the Mechanical
and Electrical Domains
%J MAG144
%P 340-349
%K AA21 AA05
%A K. D. Forbus
%T Interpreting Observations of Physical Systems
%J MAG144
%P 350-359
%K AI16
%A E. A. Scarl
%A J. R. Jamieson
%A C. I. Delaune
%T Diagnosis and Sensor Validation Through Knowledge of Structure and Function
%J MAG144
%P 360-368
%K AA21 AI16
%A H. Nawab
%A Y. Lesser
%A E. Milios
%T Diagnosis Using the Formal Theory of a Signal Processing Systems
%J MAG144
%P 369-379
%K AA21 AA05
%A M. J. Pazzani
%T Failure Driven Learning of Fault Diagnosis Heuristics
%J MAG144
%P 380-394
%K AA21 AI04
%A Y. Peng
%A J. A. Reggia
%T A Probabilistic Causal Model for Diagnosistic Problem Solving - Part II:
Diagnostic Strategy
%J MAG144
%P 395-406
%K AA21 O04
------------------------------
End of AIList Digest
********************
∂19-Sep-87 0236 LAWS@KL.SRI.Com AIList Digest V5 #216
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 19 Sep 87 02:14:47 PDT
Date: Fri 18 Sep 1987 23:27-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #216
To: AIList@SRI.COM
AIList Digest Saturday, 19 Sep 1987 Volume 5 : Issue 216
Today's Topics:
Seminars - PRIDE: Knowledge-Based Design (SRI) &
Declarative Device Modeling (UPenn) &
Functional Languages and Temporal Logic (SRI),
Conference - AI in Minerals and Technology &
Logic and Databases (Switzerland) &
AIAA Computers in Aerospace VI &
RIAO '88 Content-Based Text and Image Handling
----------------------------------------------------------------------
Date: Wed, 16 Sep 87 18:15:21 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - PRIDE: Knowledge-Based Design (SRI)
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
PRIDE: A KNOWLEDGE-BASED FRAMEWORK FOR DESIGN
Sanjay Mittal (MITTAL@XEROX.COM)
Intelligent Systems Laboratory, Xerox PARC
11:00 AM, MONDAY, September 21
SRI International, Building E, Room EJ228
In this talk I will describe the Pride project at Xerox. The first
part of the talk will be about an expert system for the design of
paper transports inside copiers. A prototype version of the system has
been in field test for over a year and will be in regular use by
year-end. It has been successfully used on real copier projects inside
Xerox - both for designing and for checking designs produced by
engineers. From an applications point of view we have been motivated
by the following observations: knowledge is often distributed among
different experts; the process of generating designs is unnecessarily
separated from their analysis, leading to long design cycles; and
design is an evolutionary process, i.e., a process of exploration.
The second part of the talk will describe the framework in Pride for
representing design knowledge and using it to support the design
process. In this framework, called Describe, the process of designing
an artifact is viewed as knowledge guided search in a
multi-dimensional space of possible designs. The dimensions of such a
space are the design parameters of the artifact. In this view,
knowledge is used not only to search the space but also to define the
space. Domain knowledge is organized in terms of design plans, which
are organized around goals. Conceptually, goals decompose a problem
into sub-problems and are the units for structuring knowledge. Design
goals have design methods associated with them, which specify
alternate ways to make decisions about the design parameters of the
goal. The third major element of a plan are constraints on the design
parameters. The framework provides a problem solver for executing
these plans. The problem solver combines dependency-directed
backtracking ideas with an advice mechanism and a context mechanism
for simultaneously maintaining multiple partial designs. The Describe
framework has been successfully used to build a second expert system
called Cossack for configuring micro-computer systems.
If time permits, I will talk about some of the more recent ideas that
have come out of the Pride project: Knowledge compilation, Partial
choices in constraint reasoning, and constraint compilation.
------------------------------
Date: Mon, 14 Sep 87 17:38:54 EDT
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: Seminar - Declarative Device Modeling (UPenn)
From: Christian Overton <overt@omega.prc.unisys.com>
Seminar
Paoli Research Center
UNISYS
Paoli. PA
Coordinating the Use of
Qualitative and Quantitative Knowledge
in Declarative Device Modeling
Peter Karp
Knowledge Systems Laboratory
Computer Science Department
Stanford, CA 94305
We describe several new qualitative representations and reasoning
techniques. These techniques allow us to represent both state
variables and the interactions between them with varying degrees of
precision. This is desirable when we have only partial knowledge
about these entities or when we wish to express approximations to the
knowledge we do have. New reasoning strategies have been develped to
allow the propagation of the different types of values through the
differnt types of interactions.
Tuesday, Sept. 15, 1987
4:00 - 5:00
Cafeteria Conference Room, PRC
For further information contact Chris Overton at 648-7533.
------------------------------
Date: Tue, 8 Sep 87 15:29:12 PDT
From: Margaret Olender <olender@malibu.ai.sri.com>
Subject: Seminar - Functional Languages and Temporal Logic (SRI)
11:00am, WEDNESDAY, September 9, 1987
SRI International, Building E, Room EJ228
CONTROLLING THE BEHAVIOUR OF FUNCTIONAL LANGUAGE SYSTEMS
USING TEMPORAL LOGIC
Lyndon While
Imperial College
London
Functional programming languages, although possessing many advantages,
have certain limitations when they are applied to systems where control
over the program's behaviour is required.
We have developed a methodology that overcomes this limitation without
destroying the pure declrative nature of these languages. Temporal logic
is used to specify any behavioural aspect of the problem and this is
then transformed together with the (pure) functional language program
to produce a program that is guaranteed to satisfy the temporal requirements
however it is implemented.
We will describe the Tempoaral Logic specification language used
together with the transformation rules. This methodology has been
implemented as a completely automatic process and we will give some
examples of its use.
------------------------------
Date: Sun, 06 Sep 87 19:13:48 CDT
From: "Kevin O'Kane (205) 348 6363"
<OKANE%UA1VM.BITNET@wiscvm.wisc.edu>
Subject: Conference - AI in Minerals and Technology
Artificial Intelligence in Minerals
and Technology Conference
October 20-21, 1987
The University of Alabama
Ferguson Center
Tucaloosa, Alabama
Sponsored by:
United States Department of the Interior
Bureau of Mines
Co-Sponsors:
The University of Alabama, College of Continuing Studies
The University of Alabama, College of Engineering
University of Missouri, Rolla
Colorado School of Mines
For information contact:
Dr. Jack R. Woodyard
U.S. Bureau of Mines
Tuscaloosa Research Center
(205) 759-9422
or
Registration Services
College of Continuing Studies
P.O. Box 2967
Tuscaloosa, AL 35487
(205) 348-3000
Program Agenda:
1. Tutorial: Introduction to Neural Networks and Associa-
tive Memory (3.5 hours) Bart Kosko, Verac Corp.
2. Neural Networks Simulation for Welding Image Under-
standing.
3. Introduction to the University of Alabama Department of
Mechanical Engineering's Robotics Laboratory.
4. The Use of Expert Systems for Mineral Processing Appli-
cations.
5. Toward Fuzzy Expert Systems: An Example from Mineral
Identification.
6. Predicting Chemical Parameters with Prolog.
7. Experiences Gained form Using an Expert Systems
Approach in Process Management.
8. Knowledge Systems for Troubleshooting Production
Machines.
9. Use of Fuzzy Logic for Rule Based Control of Liquid
Level in Vessels.
10. The Goal of User Development and Maintenance of Expert
Systems.
11. Genetic Algorithm.
12. MICA - An Expert System.
13. Expert System for Material Selection.
14. Application of Re-Writing Techniques to Inference Tech-
niques.
15. Process Control with a General Purpose Fuzzy Expert
System.
16. Computer Architecture and Intelligent Systems for Real
Time Applications.
17. Role of AI in Analytical Instrumentation.
18. Application of Expert Systems Knowledge Refinement
Techniques in Material Technology.
19. Application of Artificial Intelligence to Alloy Design.
20. Use of Expert Systems in in Cast Metals Technology.
21. Prototyping of an Expert System for Troubleshooting of
Clinkers Grinding Mills.
22. CORDIAL: A PC Computer-based System for the Diagnosis
of Stress Corrosion Behavior in High Strength Aluminum
Alloy.
23. Artificial Intelligence in Automated Scrap Processing.
24. Applications of Expert Systems Technology at Bethlehem
Steel Corporation.
25. Panel Discussion, Summation and Conclusion.
For registration information, contact the Jack Woodyard or
Registration Services (given above) or OKANE at
UA1VM.BITNET.
------------------------------
Date: 10 Sep 87 23:59:31 GMT
From: mcvax!cui!shneider@uunet.UU.NET (SCHNEIDER Daniel)
Reply-to: mcvax!cui!shneider@uunet.UU.NET (SCHNEIDER Daniel)
Subject: Conference - Logic and Databases (Switzerland)
SGAICO (Swiss Group for Artificial Intelligence and Cognitive Science)
CONFERENCE AND TUTORIAL ON LOGIC AND DATABASES
HEC, University of Lausanne, Switzerland
(sorry for being late, but the deadlines are not so real ....)
CONFERENCE, Wednesday, October 7, 1987
Jean-Marie Nicolas (ECRC, Munich): On Deductive Databases
Shamim A. Naqvi (MCC, Austin): The Problem of Recursive Queries
in Knowledge Based Systems}
Laurent Vieille (ECRC, Munich): DEDGIN: A Deductive Query-Answering
Database System}
Eric Simon (INRIA, Paris): A Production Rule Based Approach
to Deductive Databases
Richard Paul Braegger (ETH,Zurich): Knowledge Based Tools
for the Design of Data Bases
Conference Fees SI or SVI/FSI Sfr. 120.-
non members Sfr. 200.-
students Sfr. 50.-
TUTORIAL, Tuesday, October 6, 1987
A one-day introduction to the subject will be offered both in French and in
German by Pierre Bonzon (HEC, Lausanne), Robert Marti and Alfred Ultsch (ETH,
Zurich). The number of participants will be limited to 30 per group. Familiarity
with DBMS concepts will be assumed and emphasis will be on logic concepts.
Tutorial Fees SI or SVI/FSI Sfr. 130.-
non members Sfr. 210.-
students Sfr. 20.-
Program Committee Pierre Bonzon (University of Lausanne), Jiri Kriz (BBC,Baden)
Daniel Schneider (University of Geneva), Alfred Ultsch (ETHZ)
Registration: Contact the SI secretariat: (+41 1) 481 73 90 (Ms. A.-M. Nicolet)
SI/SGAICO, P.O.Box 570, 8027 Zurich, Switzerland.
(Late registration for the conference is possible at the registration desk)
From: Daniel K.Schneider, ISSCO, University of Geneva, 54 route des Acacias,
1227 Carouge (Switzerland), Tel. (..41) (22) 20 93 33 ext. 2116
--> to EAN/X400/MHS (on Unix, (preferable :]) :
EAN/X400:shneider@cui.unige.chunet | if reply does
ARPA: shneider%cui.unige.chunet@csnet-relay.arpa | not work,
CSnet: shneider%cui.unige.chunet@csnet-relay.csnet | keep trying:
(or:....%relay.cs.net@relay.cs.net) | mailers are
JANET: shneider%cui.unige.chunet@cs.ucl.ac.uk | *great* fun!
uucp: mcvax!cernvax!cui!shneider | ;-( |+{ :=[
--> to BITNET (on VMS, the easy solution):
BITNET: SCHNEIDE@CGEUGE51 ARPA: SCHNEIDE%CGEUGE51.BITNET@WISCVM
== Warnings: (1) hitting the reply key may not work
(2) CHUNET will be renamed soon into CH
--
Daniel K.Schneider, ISSCO, University of Geneva, 54 route des Acacias,
1227 Carouge (Switzerland), Tel. (..41) (22) 20 93 33 ext. 2116
--> to EAN/X400/MHS (on Unix, (preferable :]) :
EAN/X400:shneider@cui.unige.chunet | if reply does
ARPA: shneider%cui.unige.chunet@csnet-relay.arpa | not work,
CSnet: shneider%cui.unige.chunet@csnet-relay.csnet | keep trying:
(or:....%relay.cs.net@relay.cs.net) | mailers are
JANET: shneider%cui.unige.chunet@cs.ucl.ac.uk | *great* fun!
uucp: mcvax!cernvax!cui!shneider | ;-( |+{ :=[
--> to BITNET (on VMS, the easy solution):
BITNET: SCHNEIDE@CGEUGE51 ARPA: SCHNEIDE%CGEUGE51.BITNET@WISCVM
------------------------------
Date: Fri, 11 Sep 87 06:03 PDT
From: nesliwa%nasamail@ames.arpa (NANCY E. SLIWA)
Subject: Conference - AIAA Computers in Aerospace VI
As a member of the AIAA Technical Committee on Computer Systems, I wanted
to share with you the program of our up-coming bi-annual conference,
Computers in Aerospace 6. The themes this year ar AI, Ada, and Advance
Architectures, all slanted to aerospace applications. I would appreciate
your sharing this information with anyone in your organization that you
think might be interested in it. I'm hapy to answer any questions:
FTS 928-3871, (804)865-3871
Nancy Sliwa
[I've cut this from the original 47,000 characters. If you
need the full text, contact the author. -- KIL]
Subj: Computers in Aerospace VI Program
American Institute of Aeronautics and Astronautics
Computers in Aerospace VI Conference
Hilton at Colonial
Wakefield, Massachusetts
October 7 - 9, 1987
Conference Committee
General Chairman
Malcolm Stiefel
MITRE Corp.
Technical Program Chairman
Lt. Colonel Ralph Gajewski
SDIO
Technical Program Co-Chairman
Wayne H. Bryant
NASA Langley Research Center
------------------------------
Date: Fri, 11-SEP-1987 18:28 EST
From: FOXEA%VTVAX3.BITNET@wiscvm.wisc.edu
Subject: Conference - RIAO '88 Content-Based Text and Image Handling
In V3 #20 the call for papers for RIAO '88 was published. I have heard that
there has been a disappointing response from US universities. Since some
of you may not have received #20, due to mail problems or summer trips,
I am sending out the call again.
Some may have noted that this conference is the same week as the
Office Information Systems Conference. Special arrangements will be
made to schedule people who want to attend both to speak on the 21st
or 22nd if they want to then go on to the OIS conference.
While it is desirable that systems being discussed be demonstrable,
it is understood that university systems are typically prototypes, so
people should not be scared off by that factor. - Ed
CALL FOR PAPERS
RIAO 88
USER-ORIENTED CONTENT-BASED
TEXT AND IMAGE HANDLING
Massachusetts Institute of Technology
Cambridge, MA
March 21-24, 1988
Conference
organized by:
Centre National de la Recherche Scientifique (CNRS)
Centre National de Recherche des Telecommunications (CNET)
Institut National de Recherche en Informatique
et Automatique (INRIA)
Ecole Nationale Superieure des Mines de Paris
Centre de Hautes Etudes Internationales d'Informatique
Documentaires (CID)
US participating organizations:
American Federation of Information Processing Societies
(AFIPS)
American Society for Information Science (ASIS)
Information Industry Association (IIA)
This conference is prepared under the direction of:
Professor Andre Lichnerowicz
de l'Academie des Sciences de Paris
and
Professor Jacques Arsac
correspondant de l'Academie des Sciences de Paris
RIAO: Recherche d'Informations Assistee par Ordinateur
A GENERAL INTRODUCTION:
RIAO 88 is being held to demonstrate the state of the art in
information retrieval, a domain that is in rapid evolution
because of developments in the technology for machine control of
full-text and image databases. This evolution is stimulated by
the demands of end-users generated by the recent availability of
CD-ROM full text publishing and general public access to
information data bases.
A group of French organizations has taken the initiative of
preparing this conference. Its wish in promoting this forum is
not only to stimulate and challenge researchers from all nations
but also to increase an awareness of European technology.
This "call for papers" is beeing distributed world-wide. We
want to reach individuals in the research communities throughout
the university and industrial sectors.
The conference will be held in Cambridge, MA. We hope that
it will encourage the exchange of European and American
viewpoints, and establish new links between research teams in
United-states and Europe.
CALL FOR PAPERS
General theme
Full-text and mixed media database systems are
characterized by the fact that the structure of the
information is not known a priori.
This prevents advance knowledge of the types of
questions that will be asked, unlike the situation found in
hierarchical and relational database management systems.
You are invited to submit a paper showing how the
situation can be dealt with. Special attention will be given to:
- techniques designed to reduce imprecision
in full-text database searching;
- data entry and control;
- "friendly" end-user interfaces.
- new media
A large number of specific subjects can be treated
within this general framework. Some suggestions are made in
the following section.
Specific themes
A) Linguistic processing and interrogation of full
text databases:
- automatic indexing,
- machine generated summaries,
- natural language queries,
- computer-aided translation,
- multilingual interfaces.
B) Automatic thesaurus construction,
C) Expert system techniques for retrieving information
in full-text and multimedia databases:
- expert systems reasoning on open-ended domains
- expert systems simulating librarians accessing
pertinent information.
D) Friendly user interfaces to classical information
retrieval systems.
E) Specialized machines and system architectures designed
for treating full-text data, including managing and accessing
widely distributed databases.
F) Automatic database construction scanning techniques,
optical character readers, output document preparation, etc...
G) New applications and perspectives suggested by
emerging new technologies:
- optical storage techniques (videodisk,
CD-ROM, CD-I, Digital Optical Disks);
- integrated text, sound and image retrieval
systems;
- electronic mail and document delivery based
on content;
- voice processing technologies for database
construction;
- production of intelligent tutoring
systems;
- hypertext, hypermedia.
Conditions for participation
The program committee is looking for communications
geared toward practical applications. Papers which have not been
validated by a working model, a prototype or a simulation, or for
which a realization of such a model seems currently unlikely, may
be refused.
Authors must submit a paper of about 10 pages doubled
spaced, and a 100 word abstract.
Four copies must be sent before October 30 to one of
these two addresses:
- RIAO 88, Conference Service Office, MIT, Bldg 7, Room 111
CAMBRIDGE, MA 02139
- RIAO 88, CID, 36 bis rue Ballu, 75009 PARIS FRANCE
Each presentation will last 20 minutes followed by 10
minutes of discussion and questions.
Arrangement have been made with the international
journal "Information Processing and Management" for publishing
expanded versions of some papers.
High quality audiovisual techniques should be used
when presenting the paper.
Separate demonstration sessions can be scheduled
if requested.
Particular attention will be paid to :
- the use of readily available equipment for
demonstrations (IBM PC, APPLE, network connec-
tions...);
- pre-recorded video or floppy disk displays.
Hardcopy printouts of results should be avoided if
possible.
English is the working language of the conference.
For further information call:
in North America : Karen Daifuku,
tel: (202) 944 62 52
in other countries: Secretariat General du CID in France,
tel: (1) 42 85 04 75
------------------------------
End of AIList Digest
********************
∂19-Sep-87 0419 LAWS@KL.SRI.Com AIList V5 #217 - Literature Duplication, Philosophy
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 19 Sep 87 04:16:24 PDT
Date: Fri 18 Sep 1987 23:35-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #217 - Literature Duplication, Philosophy
To: AIList@SRI.COM
AIList Digest Saturday, 19 Sep 1987 Volume 5 : Issue 217
Today's Topics:
Comment - Duplication of AI Literature Titles,
Philosophy - Boltzmann on Philosophy & Natural Kinds,
Computer Science - Discipline Nature & P = NP ?
----------------------------------------------------------------------
Date: Mon, 14 Sep 87 12:53:58 pdt
From: Eugene Miya N. <eugene@ames-pioneer.arpa>
Subject: Note on MP biblio update (WARNING!)
Please excuse cross-posting to so many newgroups, but I believe the
following to be important.
Recently, while updating bibliographic entries, I have noticed a
disturbing trend. I had to resolve in excess of 300 name conflicts
in 8,000. Most were updates in status from TRs to Journals or Books.
But a size percentage were papers publised in more than one location
(31 titles total), and papers/texts with the same title, but different
authors/contents, etc. (18, remember double each of these counts for a
lower bound). Increasing interest is creating a bigger headache
For example: popular titles include:
%T Distributed Operating Systems (one book, one article)
%T Elliptic Problem Solvers
%T Supercomputers (3 books this title)
%T Supercomputers in Theoretical and Experimental Science (one book, one
article)
%T A Framework for Distributed Problem Solving
%T Estimating Speedup in Parallel Parsing
%T Multi-grid solvers on parallel computers
One interesting name conflict seems to come from titles of SIMD processors
such as [SIMD titles]
%T The Distributed Array Processor
%T The Massively Parallel Processor
which occur in some cases 4-5 times. Will Connection Machine papers be
far behind?
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
Date: Mon, 14 Sep 87 11:51:26 EDT
From: mckee%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: Boltzmann on philosophy
and as long as we're collecting anti-philosophical quotes:
There is much that is appropriate and correct in the writings of
these philosophers. Their remarks, when they denounce other
philosophers, are appropriate and correct. But when it comes to
their own contributions, they are usually not so.
- Ludwig Boltzmann
Quoted in the preface to John Casti's "Connectivity, Complexity, and
Catastrophe in Large-Scale Systems" (1979). No citation for Boltzmann,
though...
------------------------------
Date: 14 Sep 87 15:03:19 GMT
From: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@seismo.CSS.GOV>
Reply-to: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@seismo.CSS.GOV>
Subject: Re: Natural kinds
In article <"870828113435.1.rjz@JASPER"@UBIK.Palladian.COM>
rjz%JASPER@LIVE-OAK.LCS.MIT.EDU writes:
>In McCarthy's message of Jul 10, he talks of the need for AI
>systems to be able to learn and use "natural kinds",
I'd like to continue the sociological perspective on this debate.
Rule number 1 in sociology is forget about "naturalness" - only
sociobiologists are really into "nature" now, and look at the foul
images of man that they've tried to pass off as science (e.g. Dworkin).
> McCarthy's original point is the more crucial: that people seem to be able
> to classify objects in the absence of precise information.
Psychologists cram a lot under the heading of "ability". The learner
is often assumed to have an active, conscious problem solving role.
When dealing with formal problems and knowledge, such a
characterisation seems valid. With social constructs such as informal
categories, "ability" is not the result of an active learning process.
Rather the ability follows automatically from cultural immersion.
>This is important if individuals are to "make sense" of their world,
>meaning they are able to induce any significant
>generalizations about how the world works.
Artifacts of civilization are only induced once. Thereafter, if they
fulfil social needs, they remain unchanged. Rather than induce what a
chair is, children learn what it is as part of their sociolinguistic
development. They come to know what a chair is without ever actively
and consciously inducing a formal definition.
>Perhaps we could call this expanded notion an "empirical kind".
"Empirical" is about as helpful as "natural" when it comes to reasoning
about social phenomena.
>Third: Such "kinds" are especially important for communicating with other
>individuals. Being based on individual experience, no two persons'
> conceptions of a given concept can be assumed to correspond _exactly_.
At last, some social reasoning :-)! However, surface differences in
statements about meaning do not imply deep differences over the real
concept. The problem is one of language, not thought. Note also that
where beliefs about a concept are heavily controlled within a society,
public expression about a concept can be almost identical. See under
ideology or theocracy.
Once again, the reason why so much AI research is just one big
turn-off is that much of it is a very amateur and jargon-ridden
sophomore attempt at formalising phenomena which are well understood
and much studied in other real disciplines. Anthropological studies of
the category systems of societies abound. Levi-Strauss for one has
explored the reoccurance of binary oppositions in many category
systems. The difference between the humanities and AI is mainly that
the former are happy to write, as elegantly as possible, in natural
language, whereas in the latter there is a fetish for writing in a
mixture of LISP, cut-down algebra and folk-psychology without an ounce
of scholarship. There is rigour no doubt, but without scholarship it
is worthless. Artificial ignorance is an apt characterisation.
The debate on natual kinds appears to have emerged from a discussion
of where AI needs to go next. Perhaps AI folk should drop the
hill-climbing and take their valuable techniques back into the
disciplines which can make use of them in a sensible and balanced way.
Then perhaps only programmes worth writing will be implemented and
this nonsense about tidying up poorly expressed ideas on a dumb
machine can be interred once and for all.
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
Date: 16 Sep 87 14:21:59 GMT
From: styx.rutgers.edu!schaffer@RUTGERS.EDU (Schaffer)
Subject: Patrick Hayes on AI & Science
Section 10 of Hayes's paper "The Second Naive Physics Manifesto" is
entitled "Is This Science?" The section is reproduced in full here:
The earlier manifesto ended on a note of exquisite methodological
nicety: whether this activity could really be considered *scientific*.
This second manifesto will end on a different note. Doing this job
is necessary, important, difficult and fun. Is it really scientific?
Who cares?
------------------------------
Date: Wed 16 Sep 87 17:06:07-PDT
From: Andy Freeman <ANDY@Sushi.Stanford.EDU>
Subject: Materials Science
appears to be a science. It is the exception that tests the rule
"Every field with `science' in its name isn't."
-andy
------------------------------
Date: 17 Sep 87 05:45:57 GMT
From: pioneer!eugene@ames.arpa (Eugene Miya N.)
Subject: Re: Is Computer Science Science?
Not a science yet, but as Mike Shafto pointed out. Denning will have
column in American Scientist on this (I am reviewing) Nov. maybe. I will have
two papers on this in ACM Software Engineering Notes (positive
suggestions for improvements), and I also suggest reading the paper
by Knuth in 1985 Amer. Math. Monthly on the differences between
Mathematical and Algorithmic thinking (Computation != math),
and oh yes, Simon's "Sciences of the Artificial" especially the
chapter on Empiricism (and his Turing award lecture).
Summary and concesses? It aspires, it's different from other sciences,
it can be improved. Need we say more?
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
Date: 16 Sep 87 22:12:41 GMT
From: ramesh@cvl.umd.edu (Ramesh Sitaraman)
Subject: Re: Is Computer Science Science?
In article <737@elmgate.UUCP> ram@elmgate.UUCP (Randy Martens) writes:
>I am of the firm opinion that there is NO such thing as
>computer science.
Unfortunately you are totally wrong!!! The scientific part of CS
deals with unravelling the nature of computation. This is the
object of study of theoretical areas such as Complexity theory,
recursive function theory, programming language semantics etc.
Computation is an abstract process but unlike other abstract
formalisms is immediately applicable and can be realised through
physical computers. Thus there has been such an overwhelming
growth in computer applications that the applicational aspects of CS are
more evident to an *outsider* than the theoretical core.
Note that computation existed long before computers. Neither Eratosthenes
or Galois knew anything about digital computers but they certainly
did know about computation. Therefore the development of computers,
though extremely beneficial, is only incidental to a theoretician.
>"Reality - What a Concept !" - R.Williams
Ramesh
--
-----------------------------------------------------------------
ARPA: ramesh@cvl.umd.edu | If I had had more time, I could
SPRINT:(301) 927 6831 | have written you a shorter letter.
UUCP: ramesh@cvl.uucp | -Blaise Pascal
------------------------------
Date: 17 Sep 87 13:31:08 GMT
From: sunybcs!bingvaxu!leah!uwmcsd1!uwm-cs!litow@rutgers.edu (Dr. B.
Litow)
Subject: Re: Is Computer Science Science?
In article <2474@cvl.umd.edu>, ramesh@cvl.umd.edu (Ramesh Sitaraman) writes:
> In article <737@elmgate.UUCP> ram@elmgate.UUCP (Randy Martens) writes:
> >I am of the firm opinion that there is NO such thing as
> >computer science.
>
> Unfortunately you are totally wrong!!! The scientific part of CS
> deals with unravelling the nature of computation. This is the
> object of study of theoretical areas such as Complexity theory,
> recursive function theory, programming language semantics etc.
> Computation is an abstract process but unlike other abstract
> formalisms is immediately applicable and can be realised through
> physical computers. Thus there has been such an overwhelming
> growth in computer applications that the applicational aspects of CS are
> more evident to an *outsider* than the theoretical core.
I agree with this poster. I fact I would go on to say that the design of
programming languages,systems and such things as network protocols,etc.
are also just applications. I earlier posted my belief that CS is an entirely
new branch of mathematics so that in a way
CS is indeed not a science in the sense that physics is a science. However,
there are profound issues at the border of CS and physics,for example which
I take as a sound indication of the depth of CS. The confounding of CS with
its applications can only impede progress especially in the matter of new
applications.
The failure to consider 'TCS' as real CS is becoming a serious matter and
I think that the current accreditation issue for CS in colleges must be
resolved in a manner that places sufficient emphasis on computation theory.
I close with an example. The emergence of NC and related parallel computing
models out of alternating Turing machine studies of the late 70's is
a clear indication of the power of good theory.
------------------------------
Date: Thu, 17 Sep 87 15:03:33 EDT
From: dml@NADC.ARPA (D. Loewenstern)
Subject: Re: Is Computer Science is Science?
>From: kodak!elmgate!ram@cs.rochester.edu (Randy Martens)
>I am of the firm opinion that there is NO such thing as
>computer science. To quote (and I have forgotten the attribution)
>"Computer Science bears the same relationship to Real Science, that
>plumbing bears to Hydrodynamics."
>There is, however, Computer Engineering. (and Software Engineering,
>and Systems Engineering etc.). Science is the discovery of the new.
>Engineering takes what the scientists have found, and finds ways
>to do useful things with it. The two are like Yin and Yang, closely
>interrelated, but not the same, and each dependant on the other.
I think that what Mr. Martens has said is:
1. a. Science is the discovery of the new.
b. There is no such thing as computer science.
=> There is no discovery of the new in the realm of computers.
2. a. Engineering takes what the scientists have found...
=> Computer Engineering takes what the Computer Scientists have found...
b. There is no such thing as computer science.
=> There are no computer scientists.
=> Nothing has been found by computer scientists.
=> Computer Engineering takes nothing and finds ways to do useful
things with it. (8v))
David Loewenstern
Naval Air Development Center
code 7013
Warminster, PA 18974-5000
<dml@nadc.arpa>
------------------------------
Date: 15 Sep 87 09:49:49 GMT
From: mcvax!hafro!krafla!snorri@seismo.css.gov (Snorri Agnarsson)
Subject: Re: P may indeed = NP !!
...
> "Dr. Swart's problem establishes that the Hamilton circuit problem can
> be solved in polynomial time by converting a mathematical programming
> formulation of the problem into a linear programming formulation and
> using existing polynomial time algorithms as established by Kachiyan
> and Karmarkar."
...
OK - let me take a guess as to what is wrong with this approach:
My guess is that Karmarkars polynomial time algorithms are only
polynomial time if calculations are performed using fixed accuracy
floating point arithmetic, and if infinite precision arithmetic is
used then the algorithms are no longer polynomial time.
Furthermore, I would guess that to solve the Hamiltonian circuit
problem you would need infinite precision arithmetic.
--
Snorri Agnarsson UUCP: snorri@rhi.edu
Science Istitute ...!mcvax!hafro!rhi!snorri
University of Iceland
------------------------------
Date: 17 Sep 87 03:02:38 GMT
From: linus!bs@husc6.harvard.edu (Robert D. Silverman)
Subject: Re: P may indeed = NP !!
In article <11@krafla.UUCP] snorri@krafla.UUCP (Snorri Agnarsson) writes:
]
]My guess is that Karmarkars polynomial time algorithms are only
]polynomial time if calculations are performed using fixed accuracy
]floating point arithmetic, and if infinite precision arithmetic is
]used then the algorithms are no longer polynomial time.
]Furthermore, I would guess that to solve the Hamiltonian circuit
]problem you would need infinite precision arithmetic.
]--
]Snorri Agnarsson UUCP: snorri@rhi.edu
]Science Istitute ...!mcvax!hafro!rhi!snorri
]University of Iceland
Sorry, your guess makes some sense but is incorrect. The arithmetic precision
required for Khachian's algorithm (and Karmarkar's) may be built into the
algorithm. Secondly, all linear programming problems with rational coefficients
may be solved using finite precision.
I'm getting tired of hearing about P=NP proofs. It reminds me too much of
the many crackpots from previous generations who tried to 'square the circle'
or 'trisect a general angle' with straightedge and compass. All of the P=NP
proofs reported so far have the same flaw: They try to formulate an NP problem
as a linear program but ALL wind up requiring an exponential number of
variables in the size of the problem instance.
Bob Silverman
------------------------------
End of AIList Digest
********************
∂21-Sep-87 2359 LAWS@KL.SRI.Com AIList V5 #218 - Prolog, Lisp Syntax, OPS5 for the PC
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 21 Sep 87 23:58:55 PDT
Date: Mon 21 Sep 1987 20:19-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #218 - Prolog, Lisp Syntax, OPS5 for the PC
To: AIList@SRI.COM
AIList Digest Tuesday, 22 Sep 1987 Volume 5 : Issue 218
Today's Topics:
Queries - Expert Systems on the Mac & KRL &
Publication Vehicles for AI & 'how' and 'why' in Prolog,
AI Tools - Object-Oriented Prolog & Procedures and Data &
Lisp Syntax & OPS5 for the PC,
Humor On the Kids Screaming Behind
----------------------------------------------------------------------
Date: 21 Sep 87 18:31:41 GMT
From: rochester!ritcv!waw@RUTGERS.EDU (Walter Wolf)
Subject: Expert Systems on the Mac
In the near future, I have to implement an expert
system on a Mac. I am aware of two tools:
1) Humble, a shell developed by Xerox which runs entirely
within a Smalltalk environment and
2) Some combination of ExperIntelligence products, such as
common OPS5, Common Lisp and the inerface builder.
An extensive graphic interface is a required part of the
system.
I would greatly appreciate hearing from anyone who knows
anything (pro or con) about these or other tools for the Mac.
Please e-mail to me -- I will summerize and post anything
of general interest.
Thanks in advance,
Walter Wolf
waw@rit
rochester!ritcv!waw
------------------------------
Date: 12 Sep 87 15:16:00 GMT
From: mcvax!unido!uklirb!spieker@seismo.css.gov
Subject: KRL-Information wanted - (nf)
Hi, there in netland!
I heard about the frame-oriented language KRL (Bobrow,Winograd). Looking
for further information about KRL since 1980 I found nothing. So I would
appreciate getting some more recent information.
Already found:
Bobrow, Winograd: An Overview of KRL, a Knowledge Representation Language
Lehnert, Wilks: A Critical Perspective on KRL
Bobrow, Winograd: KRL: Another Perspective
Thanks in advance
Peter Spieker
Universitaet Kaiserslautern
Fachbereich Informatik
P.O.Box 3049
D-6750 Kaiserslautern
West-Germany
E-mail(UUCP): spieker@uklirb.uucp (...mcvax!unido!uklirb!spieker)
------------------------------
Date: 16 Sep 87 20:54:07 GMT
From: linus!philabs!raca@husc6.harvard.edu (Rich Caruana)
Subject: Query about publication vehicles for AI
Quite a few months back I saw a posting here about the different forums
for AI publications and their citation frequencies. The posting stated
that in AI, unlike in most other fields, most publications and citations
were in conference proceedings (particularly IJCAI and AAAI). Other
fields cite journals much more heavily than conferences.
For reasons too complex and too boring to go into, I'd be very
interested in getting:
a) this original posting, or
b) a reference or source for this information, or
c) any other information regarding this subject.
E-mail or post as you see fit:
Usenet: philabs!raca
Arpanet: raca@philabs.philips.com
You can also call me at 914-945-6450 if that is easier.
Thanks ahead of time.
Richard A. Caruana
AI Department
Philips Labs
345 Scarborough Rd.
Briarcliff Manor, NY 10510
[The SIGART Newsletter had a survey of the online retrieval
services a few issues back. About half of the available AI
literature could be found in one of the common databases; half
of the remaining citations were in another. -- KIL]
------------------------------
Date: 17 Sep 87 10:43:40 GMT
From: mcvax!kddlab!icot!nttlab!gama!shako!mazda@seismo.css.gov
(N.Mazda)
Subject: 'how' and 'why' in prolog
Does anyone know how to program 'How' and 'Why' in Dec-10
Prolog? I am novice to both Expert Systems and Prolog.
Thank you in advance for your valuable info.
MAZDA, N. at ISEP, U. of Tsukuba, Japan.
------------------------------
Date: Wed, 16 Sep 87 18:25 EDT
From: Brad Miller <miller@DOUGHNUT.CS.ROCHESTER.EDU>
Reply-to: miller@cs.rochester.edu
Subject: Object oriented PROLOG
Date: Sun, 13 Sep 87 14:55:07 EDT
From: lakshman@ATHENA.MIT.EDU
Hi! Does anybody have a source code for creating objects with
inheritence capabilities and other standard stuff in PROLOG that
can be made available in the public domain ?
Jaideep Ganguly
Our HORNE system might do what you want, though it doesn't produce PROLOG, it
does produce horn clauses. HORNE is a prolog-like language, with a
sublanguage: REP that is pretty much like KL-1 but does certain things more
intelligently (in our opinion), like use e-unification to assign values to
slots which allows you to deal with the value of a slot that has not yet been
assigned better than if it were only a variable; types are supported on
objects and variables; variables can be constrained with arbitrary predicates,
etc. etc. REP objects have roles which are inherited in the type hierarchy.
(that is, if you define a type ACTION with role ACTOR and a subtype of ACTION
as, say, HIT, it will also have an ACTOR role since it's parent type does. TR
is available, send $2.50 to Gail Cassell, TR Secretary @ the phys address in
the header to this note if you want more info.
The code for HORNE/REP is written in CL using some ZL extensions, and runs on
the symbolics 7.1 or TI 2.1 systems (soon 3.0). Unfortunately, its also pretty
much unsupported: about a year ago we started to rewrite it from the ground up
to handle contextual reasoning, and provide other major enhancements, and the
result, RHET, will probably not be publically available until the spring. (on
the other hand, it may be worth waiting for: HORNE is pretty crufty being a
translation from franz and showing the stretch marks of an active research
tool of several years).
Neither are strictly in the public domain, but the non-commercial licence (for
HORNE/REP) is for a site and only $150. You are free to reuse the code as you
like. I'm not familiar with other legal details, you can ask Peg for a licence
agreement if you are interested or curious. Basically it's just something that
says we don't care what you do with it, but we are absolved of any
responsibility.
At any rate, if you were to get HORNE/REP; REP sits on top of HORNE and
produces horn clauses as I said; you may be able to play with the code and
have it produce PROLOG forms instead, though I think it does depend on being
able to create variables with types and/or constraints. (even that can be
modeled in pure PROLOG, it just might be more work than you are willing to
invest)...
Hope this helps,
Brad Miller
------
miller@cs.rochester.edu {...[allegra|seismo]!rochester!miller}
Brad Miller
University of Rochester Computer Science Department
------------------------------
Date: 16 Sep 87 20:15:17 GMT
From: nuchat!uhnix1!sugar!peter@uunet.uu.net (Peter da Silva)
Subject: Re: procedures and data
> [instead of]
>
> (+ a b)
>
> A program might look like
>
> + (2 2)
In the lisp 1.5 system on the 11/70 at Berkeley some years ago this was an
alternate input parser. You could switch to it using the ($mumble) special
function. I thought it ugly, but some people liked it. I think this was
called nlambda form, because it also deferred evaluation of the arguments
until you eval-ed them.
FORTH has a valid alternative syntax and semantics that captures some of the
flavor of lisp. You might want to look into it for ideas.
--
-- Peter da Silva `-_-' ...!hoptoad!academ!uhnix1!sugar!peter
-- 'U` ↑↑↑↑↑↑↑↑↑↑↑↑↑↑ Not seismo!soma (blush)
------------------------------
Date: Wed, 16 Sep 87 15:48:18 GMT
From: Christopher Dollin <kers%hplb.csnet@RELAY.CS.NET>
Subject: procedures and data
Hi
I am afraid that Eric Lee Green has become confused, mostly (I suspect) by
some of Lisp's more obscure design decisions.
Eric is correct in saying that evaluating a symbol with a procedure value (ie
a procedure as its value) should return the value of the data cell of the
symbol; indeed, in both Scheme and Vulgar Lisp, this is exactly what happens
(the difference is just in the way those values are obtained).
Eric then goes on to say:
But wait, how do we actually execute the procedure!
Lisp does this with hand-waving and head-nodding, by making programs
consist of lists, the first element of which is always assumed to be a
procedure which needs executing.
In other words, we are introducing "syntactic sugar" to work around
the problem of having to explicitly indicate what we wish to be
executed.
Well ... NO. Irrespective of language (by and large), we need some way of
indicating that a (procedure) value is to be APPLIED rather than just USED (eg
passed as an argument, delivered as a result). The Lisp convention is to
represent programs as lists (for the inconvenience of the user) and apply the
value found at the head of such a list be applied to the arguments which are
the values found in the rest of the list. This is NOT syntactic sugar;
syntactic sugar means constructs which are nice to write but can be
re-expressed within the language without the construct, and Lisp has precious
few of them.
It is true that
(defun urgh (junk foo) (blah1) (blah2))
and
(+ a b)
have the same form, although in the "defun" the arguments are literal data
and in the "+" they are expressions to be evaluated. That's because the
"defun" is SYNTAX; it defines the shape of the language, and is interpreted at
compile-time (loosely speaking) where the values being manipulated are
parse-trees. The fact that they look the same is a consequence of a Lisp
design decision that application (whether of a run-time procedure or a
syntactic processor) is indicated in the same way, viz, by the list notation.
So, to answer the questions ...
Can this dichotomy between value and execution be mended for
procedure-objects without hand-waving?
Yes. The distinction between syntactic processing (== compile-time ==
pre-process time) and execution (== evaluation == run-time) is not
hand-waving, and has little to do with procedure values.
Would requiring literal data to be quoted be too big an imposition upon
the programmer, and would it be worth the gain in expressiveness? (just
imagine macros without the mess).
Yes it would, and it wouldn't work; you can't express quote without drawing
the distinction between compile-time and run-time. No gain in expressiveness
would result. [It wouldn't make macros any less horrible, either].
The kludgy scheme doesn't help, either. For example, it requires the system to
know which symbols are procedure names in advance - the very thing that the
Lisp syntax avoids (although Vulgar Lisp persists in using the bizzare
two-value system for symbols).
In fact Scheme does NOT distinguish the evaluation of a procedure-valued
symbol from that of a non-procedure-valued object. What is DOES distinguish is
the use of an apparantly function-calling form, viz
(f x1 x2 ... xn)
where the symbol "f" is one of its built-in syntactic constructs (or a macro
in those Schemes with macros in them). And this, as I implied above, is
ESSENTIAL - in any language.
Hope this helps,
Regards,
Kers
PS Wow - a whole reply on this topic and I haven't said how much nicer Pop is
than Lisp!
(Using KMail 10-Apr-87 (Kers))
------------------------------
Date: Thu 17 Sep 87 10:40:44-PDT
From: Rich Alderson <ALDERSON@Score.Stanford.EDU>
Subject: Lisp Syntax
In AIList V5 #213, we find:
Date: 14 Sep 87 04:25:10 GMT
From: mtune!codas!killer!usl!elg@RUTGERS.EDU (Eric Lee Green)
Subject: procedures and data
...
When procedure symbols are encountered in the eval stream, they are called
with the next list in the eval stream as the parameter list. A special
prefix character is necessary to explicitly access the procedure-object,
to, for example, assign it to another variable.
A program might look like
+ (2 2)
print ( / (2 f))
Without commenting on the questions raised, I'd just like to point out that the
proposed syntax is "eval-quote" Lisp (as opposed to "eval" Lisp) extended to
non-top-level forms. An "eval-quote" Lisp, such as Lisp 1.5, is one in which
the top-level loop is defined in Lisp as
(defun top-level-loop ()
loop-top
(print (apply (read) (read)))
(go loop-top))
(NB: This is typical Lisp 1.5 programming style--"let" and friends didn't yet
exist.)
Rich Alderson
alderson@score.stanford.edu
------------------------------
Date: Thu, 17 Sep 87 10:15 EDT
From: Len%AIP1%TSD%atc.bendix.com@RELAY.CS.NET
Subject: OPS5 for the PC
Date: Thu, 17 Sep 87 10:05 EDT
From: Len Moskowitz <Len@HEART-OF-GOLD.ABATSD>
Subject: OPS5 for the PC
To: "3077::IN%\"AIList-Request@kl.sri.com\""@TSD1.ABATSD
Message-ID: <870917100518.5.LEN@HEART-OF-GOLD.ABATSD>
I reviewed TOPSI 2.0 (from Dynamic Master Systems of Atlanta, Georgia,
404-565-0771) in the August 1986 issue of BYTE. It was an incomplete, slow,
non-standard OPS5 but was reasonably priced (under $400) and useful for some
applications. A later release was supposed to include Rete but the beta
version I saw was still pretty buggy. By now though, it might be solid.
I reviewed OPS5+ (from Computer * Thought of Plano, Texas, 214-424-3511) on
Byte's BIX computer information service in June of 1987. OPS5+ is a very fast,
and complete OPS5 for the PC with useful extensions. It interfaces well with
external procedures written in C. It is also very expensive (around $1700).
You also have the option of running the Common Lisp version of Forgy's OPS5
under a PC Common Lisp, though it'll likely be slower than OPS5+.
By the way, anyone looking for a PC-based production system language should
seriously consider NASA's CLIPS, available from COSMIC (404-542-3265)for $200.
It is program number M87-11021. The documentation is an additional $17. It is
written in C and source is provided.
I'd be happy to send out copies of the reviews. Please send a large,
self-addressed, double-stamped envelope to:
Len Moskowitz
Bendix TSD
mc 4/8
Teterboro, NJ 07608
------------------------------
Date: Fri, 18 Sep 87 20:07:11 MDT
From: t05rrs%mpx1@LANL.GOV (Dick Silbar)
Subject: On the kids screaming behind
About two weeks ago someone posed the problem of the vacuum cleaner
salesman and the housewife; he was supposed to guess the ages of the
three kids knowing the sum of ages was 13 and the product equal to
the house number. Nice problem. However, Rajan Gupta points out to
me that any vacuum cleaner salesman worth his salt would have had
enough visual and audible clues from the kids screaming in the back-
ground to have given the answer right off. People on the AIList are,
I gather, not supposed to use plausible reasoning?
------------------------------
End of AIList Digest
********************
∂22-Sep-87 0202 LAWS@KL.SRI.Com AIList Digest V5 #219
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 22 Sep 87 02:02:38 PDT
Date: Mon 21 Sep 1987 20:39-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #219
To: AIList@SRI.COM
AIList Digest Tuesday, 22 Sep 1987 Volume 5 : Issue 219
Today's Topics:
Neural Nets - Shift Invariance & References,
Philosophy - Natural Kinds & Computer Science
----------------------------------------------------------------------
Date: 19 Sep 87 18:18:56 GMT
From: maiden@sdcsvax.ucsd.edu (VLSI Layout Project)
Subject: Re: Neural Net Literature, shifts in attention
Someone sent me mail about a citation for Fukushima's network that
handled "shifts in attention". I lost the address. If that person
receives this information through this channel, I'd appreciate a
e-mail letter.
"A Neural Network Model for Selective Attention in Visual Pattern
Recognition," K. Fukushima, _Biological Cybernetics_ 55: 5-15 (1986).
"A Hierarchical Neural Network Model for Associative Memory,"
K. Fukushima, _Biological Cybernetics_ 50: 105-113 (1984).
"Neocognitron: A Self-organizing Neural Network Model for a Mechanism
of Pattern Recognition Unaffected by Shift in Position,"
K. Fukushima, _Biological Cybernetics_ 36: 193-202 (1980).
The same person mentioned about vision-like systems, so here are some
interesting physiologically grounded network papers:
"A Self-Organizing Neural Network Sharing Features of the Mammalian
Visual System," H. Frohn, H. Geiger, and W. Singer, _Biological
Cybernetics_ 55: 333-343 (1987).
"Associative Recognition and Storage in a Model Network of
Physiological Neurons," J. Buhmann and K. Shulten, _Biological
Cybernetics_ 54: 319-335 (1986).
Concerning selection:
"Neural networks that learn temporal sequences by selection," S. Dehaene,
J. Changeux, and J. Nadal, _Proceeding of the National Academy of
Sciences, USA_ 84: 2727-2731 (1987).
I hope this of help. I apologize for the delay; my bibliography on
neural networks spans an entire file cabinet and is severely disorganized
after the last move.
Edward K. Y. Jung
------------------------------------------------------------------------
UUCP: {seismo|decwrl}!sdcsvax!maiden ARPA: maiden@sdcsvax.ucsd.edu
------------------------------
Date: 18 Sep 87 13:49:36 GMT
From: ihnp4!homxb!homxc!del@ucbvax.Berkeley.EDU (D.LEASURE)
Subject: Neural Net Literature
In article <598@artecon.artecon.UUCP>, donahue@artecon.artecon.UUCP
(Brian D. Donahue) writes:
> Does anyone know of a good introductory article/book to neural networks?
We're using Rumelhart and MCClelland's 2 (I've heard a rumor that a
third volume is out) volume set on the Parallel Distributed Processing
Project in a seminar at Rutgers. I've only 8 chapters of it, but it
covers a lot of ground in neuroscience, cognitive psychology
(though some would disagree that such models are really cog-psy),
and computing. I recommend it. It's only $25 for both volumes in
paperback.
--
David E. Leasure - AT&T Bell Laboratories - (201) 615-5307
------------------------------
Date: Fri, 18 Sep 87 12:00:12 GMT
From: Caroline Knight <cdfk%hplb.csnet@RELAY.CS.NET>
Subject: Is Computer Science Science? Or is it Art?
Randy Martens says:-
"There is, however, Computer Engineering. (and Software Engineering,
and Systems Engineering etc.). Science is the discovery of the new.
Engineering takes what the scientists have found, and finds ways
to do useful things with it."
If this is so, my first question is
Who are the relevant scientists and what have they discovered?
-*-
As an AI researcher I'm always discovering new things - although
possibly not interesting in the same way as Newton's laws of motion or
Einstein's theory of general relativity - they are still potentially
new knowledge. (Most people must be content to play with grains of
sand not pebbles!)
However I would defend an engineer's creativity and ability to
experiment - they too discover new things but with a different aim in
mind and a different form of reporting than the scientist.
However I believe that in software there is a better analogy with art
and illustration than engineering or science. I have noticed that this
is not welcomed by many people in computing but this might be because
they know so little of the thought processes and planning that go on
behind the development of, say, a still life or an advertising poster.
Like software art is frequently pliable and reworkable; like software
there are many different methods and philosophies (many not employed
explicitly by experts although there are procedures for producing
certain types of work), rules of thumb and conventions; there are
great practioners and many more humble industrious ones; there are
different schools of thought and also ferverent arguments about such
low level things as Acrylics or Oils, sable brushes or manmade fibre
(here ethical issues also creep in), the "rightness" of working from a
photograph, etc. In illustration and advertising the artist might be
given a very wide but constrained brief or a very tightly specified
mock-up to work from. A work of art or an ad are often the results of
a carefully executed plan (although the results are not always quite
was expected).
I have also watched both good artists and good software makers at work
and several similarities struck me: the light sketch with more work
put into some of the trickier areas, experimentation with different
compositions, throwing out or completely removing bits, putting
finisihing touches which change the whole although are little enough
in themselves.
What is useful that can come of this analogy? Here are some
suggetions:-
Training: An artist will frequently learn their own style through
meticulous study of previous greats (whose great software is there for
us to emmulate?).
At first working from nature is important although more freedom and
greater abstraction will come later. An artist must learn to see and
understand - this is something which many software workers could do
with applying.
Aids: An artist has sketch pads for roughs or capture of structure or
examples of detail. The organisation of these is often less than
perfect - in software we have a better chance of providing this
although currently our best attempts such as Lisp machines and
environments like POPLOG are still very much less than perfect too.
Aids for producing mockups - for instance cartoonists use sheets of
shading which can be cut to fit the required area - in software we
need some such things to allow us to prototype with hints at detail
without putting it all in.
Aids for throwing stuff away! How many novices or less than expert
programmers cling to the stuff they've written when it needs throwing
out and redesigning from scratch! This is like the advice given in
school not to use an eraser - of course eventually the artist knows
when it is worth using one but at first it is better to concentrate on
developing the ability to create smoothly and without fiddling.
Well I guess I've gone on long enough - I'd be pleased to reply to
anyone interested in this point of view - thanks for reading this
far!
Caroline Knight cdfk@lb.hp.co.uk
cdfk@hplb.csnet
Tel: (0272) 799910 x4040 Telex: (0270) 449206
Fax: (0272) 790076
HPLabs, Hewlett Packard Ltd, Filton Rd, Stoke Gifford, BRISTOL
BS16 1NY
Everything I write is from me personally and does not represent
Hewlett Packard in any way.
------------------------------
Date: Sat 19 Sep 87 16:03:18-EDT
From: Albert Boulanger <ABOULANGER@G.BBN.COM>
Subject: Generalization & Natural Kinds
To add some beef to much of this natural kinds discussion, I suggest
that those interested in the issue of natural kinds and generalization take
a look at a recent paper by Roger Shepard:
"Toward a Universal Law of Generalization for Psychological Science"
Science, 11 September 1987, 1317-1323
From the abstract:
A psychological space is established for any set of stimuli
by determining metric distances between the stimuli such
that the probability that a response learned to any stimulus
will generalize to any other is an invariant monotonic function
of the distance between them. To a good approximation, this
probability of generalization (i) decays exponentially with this
distance, and (ii) does so in accordance with one of two
metrics, depending on the relation between the dimensions along
which the stimuli vary. These empirical regularities are
mathematically derivable from universal principles of natural
kinds and probabilistic geometry that may, through evolutionary
internalization, tend to govern the behaviors of all sentient
organisms.
Albert Boulanger
BBN Labs
------------------------------
Date: 21 Sep 87 11:31:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: Natural kinds
Gilbert Cockton writes:
> I'd like to continue the sociological perspective on this debate.
> Rule number 1 in sociology is forget about "naturalness" - only
> sociobiologists are really into "nature" now, and look at the foul
> images of man that they've tried to pass off as science (e.g. Dworkin).
This seems a somewhat abrupt dismissal of natural kinds, which has
lately attracted some support by people such as Saul Kripke, who is
neither a computer scientist, dumb, nor politically unreliable
(although he IS a philosopher, and is thereby suspect, no doubt).
The (philosophically) serious question is to what extent our shared
concepts ("dog", "star", "electron", "chair", "penguin", "integer",
"prime number") are merely arbitrary social conventions, and to what
extent they reflect objective reality (the old nominalist-realist
debate). A sharper re-phrasing of the question might be:
To what extent would *any* recognizably rational being share our
conceptual framework, given exposure to the same physical environment?
(Eg, would Martians have a concept of "star"?).
I believe there have been anthropological studies, for instance,
showing that Indian classifications of animals and plants line
up reasonably well with the conventional Western taxonomy.
If there are natural kinds, their relevance to some AI work seems
obvious.
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: 21 Sep 87 17:40:08 GMT
From: Michael Shafto <aurora!shafto@ames.arpa>
Reply-to: shafto@aurora.UUCP (Michael Shafto)
Subject: Re: Materials Science
I would like an explanation of why Materials Science is
particularly "scientific" compared to other "<foo> Science"
disciplines. In particular, Materials Science doesn't seem
any more "scientific" (or less) than Computer Science.
Mike Shafto
------------------------------
Date: 21 Sep 87 17:52:53 GMT
From: shafto@AMES-AURORA.ARPA (Michael Shafto)
Subject: Re: Is Computer Science Science?
Alfred North Whitehead called mathematics the "science of
abstract forms." If that's too Platonic, then call it
"the science of abstract descriptions." I think if you
adopt the position that Real Science is about Nature, and
that mathematics is not Real Science, then you'll eventually
end up (with no further help from me) saying either
(a) mathematicians don't make discoveries, or (b) they
make discoveries about the properties of formal systems
or systems of abstract descriptions, and that THESE are
not part of Nature. If you follow (a), then you confine
yourself to a limited group of discussants who share your
idiosyncratic notion of 'discovery'; if you follow (b), then
you put the content of mathematics somewhere outside Nature.
Exactly where, I don't know.
Someone (perhaps Lakatos or Feyerabend) said that scientists
know about as much about science as fish know about
hydrology. This is well illustrated whenever scientists
quit DOING science and start talking about it.
Mike Shafto
------------------------------
Date: 21 Sep 87 19:00:13 GMT
From: pioneer!eugene@ames.arpa (Eugene Miya N.)
Subject: Re: Is Computer Science Science?
A couple of more recommended readings which came to me after a short
conversion with Denning:
"Cargo Cult Science" by Richard Feynman last chapter (1974 Comm. Addr.
at Caltech) in his Autobiography which I reread before bed last evening.
"An Empirical Study of FORTRAN Programs" Software -- Practice and
Experience by Don Knuth Feb. 1971, see intro and conclusions.
Knuth's paper in American Math. Monthly on the differences between
Algorithmic and Mathematical Thinking, around 1985.
These along with Simon, etc. mentioned earlier.
Unfortunately, I would say CS exhibits some cargo cult characteristics.
This does not have to be, we can change it.
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
Date: 21 Sep 87 22:49:56 GMT
From: pioneer!eugene@AMES.ARPA (Eugene Miya N.)
Subject: Re: Is Computer Science Science?
Oh yeah, one more reference thought on the way to lunch:
W. Daniel Hillis The Connection Machine, MIT Press, 1986,
Last Chapter entitled something like "Why Computer Science is No Good"
Says CS lacks scale, symmetry, and locality of effect.
--eugene
------------------------------
End of AIList Digest
********************
∂29-Sep-87 0143 LAWS@KL.SRI.Com AIList V5 #220 - Seminars, Conference on Uncertainty
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Sep 87 01:43:02 PDT
Date: Mon 28 Sep 1987 23:24-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #220 - Seminars, Conference on Uncertainty
To: AIList@SRI.COM
AIList Digest Tuesday, 29 Sep 1987 Volume 5 : Issue 220
Today's Topics:
Seminars - Class Hierarchies with Contradictions (AT&T) &
Knowledge-Based Software Development Tools (AT&T) &
The ENGINEOUS Project at GE (NASA Ames) &
Heuristic Functions for Task Scheduling (SMU) &
Autonomous Construction Robots (Lockheed),
Conference - 1988 Workshop on Uncertainty in AI
----------------------------------------------------------------------
Date: Mon 21 Sep 1987 09:13:21
From: dlm%allegra.att.com@RELAY.CS.NET
Subject: Seminar - Class Hierarchies with Contradictions (AT&T)
Time: Thursday, September 10, 1987 1:00pm.
Place: AT&T Bell Laboratories Murray Hill 3D-473
Speaker: Alex Borgida
Affiliation: Rutgers University
Title: Of Quakers and Republicans: A Syntax, Semantics,
and Type Theory for Class Hierarchies with Contradictions
Abstract:
Disparate fields such as Artificial Intelligence, Databases and
Programming Languages have discovered the joys of object-oriented
programming. One of the principal features of this paradigm is the
presence of classes of objects organized in subclass hierarchies,
which provide a form of polymorphism and the notion of inheritance.
The arguments in favour of these mechanisms are concerned with the
ease of developing and modifying programs, but we show that in several
circumstances the same kinds of arguments can be used to undermine the
usual strict interpretation of specialization: namely that a subclass
must be in every way a subtype of its superclass(es). We therefore
propose a syntax that allows the definition of subclasses appearing to
contradict their superclasses, albeit in an explicit and controlled
way. After demonstrating the proper semantics for this construct, we
examine the difficulties of writing correct programs when statements
made about the objects in some class may be contradicted for elements
belonging to a subclass. To solve these difficulties, we propose a
type theory which admits "exceptional subclasses", and consider the
problem of reasoning with these types.
Sponsor: Ron Brachman
------------------------------
Date: Mon 21 Sep 1987 09:13:21
From: dlm%allegra.att.com@RELAY.CS.NET
Subject: Seminar - Knowledge-Based Software Development Tools (AT&T)
Time: Monday Sept 14, 1987 1:30 P.M.
Place: Murray Hill 3D-473 (Lab 1125 conf. room)
Speaker: Douglas Smith
Affiliation: Kestrel Institute
Title: Knowledge-Based Software Development Tools
Abstract: Current research on knowledge-based software development
tools at Kestrel Institute is briefly surveyed. We then focus on
systems for automatically performing algorithm design, deductive
inference, finite differencing, and data structure selection. A
detailed case study shows how these systems could cooperate in
supporting the transformation of a formal specification of a
scheduling problem into efficient, executable code.
Sponsor: Van Kelly
------------------------------
Date: Fri, 25 Sep 87 13:33:41 PDT
From: JARED%PLU@ames-io.ARPA
Subject: Seminar - The ENGINEOUS Project at GE (NASA Ames)
NASA, Ames Research Center
Intelligent Systems Forum
Siu Shing Tong
General Electric
The ENGINEOUS Project at General Electric
Abstract:
The ENGINEOUS project was established in 1985 to address the problem of
designing complex hardware that utilizes a massive number of parameters
and analysis tools. For example, to design an aircraft engine,
approximately 10,000 Fortran programs may be iteratively applied from
conceptual design to final production. The number of relevant parameters
defining a typical engine is estimated to be 300,000. The human
intervention currently required to iterate these programs and parameters,
particularly between programs and disciplines, contributes significantly
to the 7 to 10 years lead time for the development of a new engine.
An experimental system to aid engine designers has been developed and is
being tested. ENGINEOUS makes use of artificial intelligent techniques
(i.e., object oriented programming, knowledge based systems, rapid
prototyping, etc.) to address problems too complex to be effectively
handled by conventional programming techniques. This presentation will
discuss the current status, initial user's experience, and the current
development effort to map ENGINEOUS into a heterogeneous,
distributed/parallel processing environment.
Date: Thursday, October 1, 1987
Time: 1:30PM
Location: Bldg. 258, rm. 127, the auditorium
Inquires: Alison Andrews, (415) 694-6741, andrews%ear@ames-io.ARPA, or
David Jared, (415) 694-6525, jared%plu@ames-io.ARPA
VISITORS ARE WELCOME: Register and obtain vehicle pass at Ames Visitor
Reception Building (N-253) or the Security Station near Gate 18. Do not
use the Navy Main Gate.
Non-citizens (except Permanent Residents) must have prior approval from the
Director's Office one week in advance. Submit requests to the point of
contact indicated above. Non-citizens must register at the Visitor
Reception Building. Permanent Residents are required to show Alien
Registration Card at the time of registration.
------------------------------
Date: Sat, 26 Sep 1987 22:55 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Seminar - Heuristic Functions for Task Scheduling (SMU)
Three Practical Heuristic Functions for Task Scheduling:
Descriptions and Analyses
SPEAKER: Mingfang Wang (mwang%smu@csnet-relay) LOCATION: 315 SIC
Southern Methodist University TIME: 1:30 pm
ABSTRACT
Generally, task scheduling in a multi-processing environment is an
NP-hard problem. Here, three task scheduling algorithms using different
heuristic functions are presented and analyzed. These algorithms fall into
the category of \fIpriority list\fR methods. The algorithms are analyzed
both analytically and through simulations. The trade-off is between the time
complexity of the task scheduling and the optimalily of the schedule. A fast
algorithm can have a time complexity of O(n * log n),
but the task schedule produced by the algorithm is not as good as those with
time complexity of O(n↑2).
------------------------------
Date: Mon, 28 Sep 87 13:28 CDT
From: SULLIVAN%lockheed.com@RELAY.CS.NET
Subject: Seminar - Autonomous Construction Robots (Lockheed)
FROM: JOSEPH W. SULLIVAN O/90-06 B/259 (415)354-5213
SUBJECT: AIC COLLOQUIUM
The Lockheed AI Center is pleased to announce a presentation by
Dr. Michael R. Genesereth of the Logic Group at Stanford
University. An abstract of the presentation is provided below.
Proposal for Ten Years of Research on
Autonomous Construction Robots
Michael R. Genesereth, Ph.D.
DATE: 14 October 1987
TIME: 3:30
PLACE: Lockheed Artificial Intelligence Center
Main Conference Room
2710 Sand Hill Rd. (Lockheed Bld. #259)
Menlo Park
One of the boldest promises of Artificial Intelligence is
the creation of an autonomous robot, one that is capable of
functioning appropriately in an arbitrary environment so as to
achieve an arbitrary goal. The environment and goal are
described in advance by the robot's client, in as much or as
little detail as he desires. Given this description, the robot
then acts autonomously, sensing and acting on its environment in
a manner appropriate to the client's goal.
Although there have been efforts in the past to build such
robots, these efforts have not met with great success due to
limitations on various technological fronts. In recent years,
however, there has been significant progress on these fronts;
and, in light of this progress, it appears likely that, with
additional research and a strong effort at integration, it should
be possible within ten years to achieve this goal.
This talk describes one particular research project aimed at
achieving this goal. The project is a collaborative venture of
the Logic Group and the Robot Reasoning Group of Stanford
University and is just getting underway.
In order to ground our research and development, we have chosen
to concentrate on autonomous robots that are experts at the
construction of electromechanical artifacts. Insofar as good
methodology involves verification of proper construction, our
robots will also need to be experts at the testing of artifacts,
the diagnosis of observed failures, and their repair.
We believe this project to be a good one for several reasons.
First of all, the robots produced are likely to be applicable to
many military and industrial applications, e.g. small-scale
manufacturing, space-station assembly, planetary exploration,
engineering behind enemy lines, and operations at radioactive and
toxic chemical sites. Secondly, we believe the project will be
beneficial for research in both Artificial Intelligence and
Robotics by forcing the integration of results from disciplines
that have over the years grown apart. Finally, we believe that
the project, given its university setting, will have educational
benefit by once again holding up for students the exciting goal
of creating autonomous robots.
------------------------------
Date: Thu, 24 Sep 87 06:58:41 PDT
From: Ross Shachter <SHACHTER@SUMEX-AIM.STANFORD.EDU>
Subject: Conference - 1988 Workshop on Uncertainty in AI
CALL FOR PARTICIPATION
Fourth Workshop on Uncertainty in Artificial Intelligence
Sponsored by AAAI
St. Paul, Minnesota, August 19-21, 1988
(preceding the AAAI Conference)
This is the fourth annual AAAI Workshop on Uncertainty in AI. The
first three workshops have been successful and productive, involving
many of the top researchers in the field. The first two workshop
proceedings have been published in the North-Holland Intelligence and
Pattern Recognition series, and the third proceedings is in press.
The general subject is automated or interactive reasoning under
uncertainty.
This year's emphasis is on the control of uncertain reasoning
processes and the issues of knowledge engineering in uncertain
domains. The most effective way to make points, compare approaches,
and clarify issues in these research areas is through demonstration in
applications, so these are especially encouraged, although more
theoretical research papers are also welcome. Many of the ideas
discussed at earlier workshops have been incorporated into prototype
and production software. This year we would especially like to
encourage the demonstration of some of these systems.
The key to the success of past workshops has been the ability to
interact with leading researchers in all aspects of the field. There
will be ample opportunity for informal discussions as well as panel
discussion to focus and debate the issues. In order to maintain this
interaction, all accepted papers will appear in the proceedings and be
presented in poster sessions. This format worked well at the 1987
workshop, and participants requested that it be done again.
Papers are invited on the following topics:
* Applications: results, implementation problems and experiences,
analyses of the experiences of end users
* Knowledge engineering under uncertainty: problem structuring,
corrections for bias, consensus among experts, man-machine interface
and human-in-the-loop systems
* Control of uncertain reasoning processes
* Different uncertainty calculi: theoretical and empirical
comparisons, transformations between representations, criteria for
decision making, axiomatic frameworks
* Revision of beliefs in an uncertain environment
* Robotics: uncertainty in perception and control
* Planning: generation of feasible plans under uncertainty
* Development of standard test cases
* Other uncertainty in AI issues
Papers will be carefully reviewed. Space is limited, so prospective
attendees are urged to submit a paper with the intention of active
participation in the workshop. Preference will be given to papers
that have demonstrated their approach in real applications.
Nonetheless, the underlying methodology should be supported by solid
theory to encourage discussion on a scientific basis. Again, all
accepted papers will be included in the proceedings and presented in
poster sessions.
Four copies of a paper should be sent to the program chairman by March
31, 1988. (No extended abstracts will be accepted.) Acceptances will
be sent by May 25, 1987. Final (camera ready) papers incorporating
the reviewers' comments must be received by July 15, 1988. There is
an eight page limit on the camera-ready copy. (A few extra pages are
available for a nominal fee.) Copies of the proceedings will be
available at the workshop.
General Chair: Program Chair:
Tod Levitt Ross Shachter
Advanced Decision Systems Center for Health Policy
201 San Antonio Circle 125 Old Chemistry Building
Suite 286 Duke University
Mountain View, CA 94040 Durham, NC 27706
(415) 941-3912 (919) 684-4424, 684-3023, 942-5852
levitt@ads.arpa shachter@sumex-aim.stanford.edu
Program Committee: P. Bonissone, P. Cheeseman, L. Kanal, J. Lemmer, T.
Levitt, R. Patil, J. Pearl, E. Ruspini, R. Shachter, G. Shafer
------------------------------
End of AIList Digest
********************
∂29-Sep-87 0358 LAWS@KL.SRI.Com AIList V5 #221 - Queries, Directions of AI
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Sep 87 03:58:18 PDT
Date: Mon 28 Sep 1987 23:31-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #221 - Queries, Directions of AI
To: AIList@SRI.COM
AIList Digest Tuesday, 29 Sep 1987 Volume 5 : Issue 221
Today's Topics:
Queries - Unification Benchmarks & Real-Time AI in Italy &
Reading List & J.F. Allen's Work on Time & Boltzmann Machine &
Vivarium Project & AAAI Speeches,
Neural Networks - ASSP Reference & Hinton's Recirculation Algorithm,
Comments - Goal of AI: Where Are We Going?
----------------------------------------------------------------------
Date: 22 Sep 87 14:12:12 GMT
From: unc!bts@mcnc.org (Bruce Smith)
Subject: Unification benchmarks?
Does anyone have a good set of unification problems? I want to run
simulations of unifications on an architecture being developed here
at UNC, and I'd like a set of "typical" problems. (And, I guess I'd
also like to be able to say I'm not the only one who claims they're
typical.)
A paper by Trum and Winterstein, referenced by Martelli & Montanari,
might have what I'm looking for. Can anyone supply a copy of
Trum P. and Winterstein,G. "Description, implementation and
practical comparison of unification algorithms," Internal Rep.
6/78, Fachbereich Informatik, Univ. of Kaiserlautern, Germany.
Other references on this topic are welcome, also. Thanks!
__________________________________
Bruce T. Smith, bts@unc.cs.unc.edu
Dept. of Computer Science
Sitterson Hall/ UNC-CH
Chapel Hill, NC 27514
------------------------------
Date: Thu, 24 Sep 87 09:42:10 edt
From: WRM%WPI.BITNET@wiscvm.wisc.edu
Subject: Looking for researchers
I have a colleague who is looking for current AI
research activity in Italy. In particular he is
interested in real-time AI systems. Does anyone
know of such activity? Thanks in advance.
Bill Michalson Bitnet wrm@wpi
Arpanet wrm%wpi.BITNET@wiscvm.ARPA
------------------------------
Date: 23 Sep 87 17:42:39 GMT
From: ihnp4!chinet!nucsrl!ragerj@ucbvax.Berkeley.EDU (John Rager)
Subject: Paper Request
I am going to teach a course called Applied AI. The student are generally
upperclass and graduate students in engineering fields (but not in
computer science). I am trying to gather a reading list for the course.
I would like suggestions for papers about applications in engineering,
manufacturing, management, etc. The papers should:
1. be well written
2. be about an attack on a (quasi-)real problem
3. be detailed enough to convey understanding of what was done
and how it was done (technical reports are fine).
Please send suggestions and I will summarize later.
Thank-you
John Rager
------------------------------
Date: 24 Sep 87 09:14:00 GMT
From: mcvax!unido!uklirb!noekel@uunet.uu.net
Subject: J.F.Allen's work on time - (nf)
Hi there,
in Communications of the ACM of November 1983 James F. Allen describes
several extensions to his well-known temporal logic, such as reference
intervals, a duration reasoner, and a date-line feature. I would like to know
if any of these extensions have actually been implemented and tested. Are
there subsequent papers on this line of research that I have missed? Ditto
for papers containing critical remarks by other people? Perhaps James Allen
is on the net himself?!?
Happy inferring
Klaus Noekel
Universitaet Kaiserslautern
Fachbereich Informatik
P.O.Box 3049
6750 Kaiserslautern
West Germany
UUCP: ...!mcvax!unido!uklirb!noekel
"Why should I worry about opinions? I'll stick to my prejudices!"
------------------------------
Date: Sun, 27 Sep 87 15:25:30 EDT
From: Ali Minai <amres%uvaee.ee.virginia.edu@RELAY.CS.NET>
Subject: Boltzmann Machine
While reading two different references about the Boltzmann Machine, I came
across something I did not quite understand. I am sure that there is a
perfectly reasonable explanation, and would be glad if someone could point
it out.
In chapter 7 of PARALLEL DISTRIBUTED PROCESSING (Vol 1), by Hinton and
Sejnowski, the authors define Pij+ as the probability of units i and j
being on when ALL visible units are being clamped, and Pij- as the
probability of i and j being on when NONE of the visible units are
being clamped (pp 294, 296). They then proceed to present the expression
for the gradient of G with respect to weights Wij as -1/T (Pij+ - Pij-).
However, in the paper entitled LEARNING SYMMETRY GROUPS WITH HIDDEN
UNITS: BEYOND THE PERCEPTRON, by Sejnowski, Keinker and Hinton, in
Physica 22D (1986), pp 260-275, it is explicitly stated that Pij+
is the probability when ALL visible units (input and output) are being
clamped, BUT Pij- is the probability of i and j being on when ONLY THE
INPUT UNITS ARE CLAMPED (pp 264). So there seems to be no concept of
FREE-RUNNING here.
Since the expression for dG/dWij is the same in both cases, the
definitions of Pij- must be equivalent. The only explanation I could
think of was that "clamping" the inputs ONLY was the same thing as letting
the environment have a free run of them, so the case being described is
the free-running one. If that is true, obviously there is no contradiction,
but the terminology sure is confusing. If that is not the case, will
someone please explain.
Also, can anyone point out any latest references to work on the Boltzmann
Machine?
Thanks,
Ali.
---------------------------------------------------------------------------
Ali Minai,
Department of Electrical Engg.
University of Virginia,
Charlottesville, Va 22901.
ARPANET: amres@uvaee.ee.Virginia.EDU
------------------------------
Date: Mon, 28 Sep 87 07:07:25 PDT
From: erickson@lbl-csam.arpa (Marvin Erickson [ams-pnl])
Subject: Vivarium Project
Does anyone know the status of Alan Kay's Vivarium Project? (Rumored or
officially published?) If Apple isn't giving out any info, how about the
MIT Media Lab? I've only hear a little in MacWeek articles and the like.
Also, MacWeek mentioned a related program called "BrainWorks" -- any MIT-ers
willing to offer a more detailed description than what the mag gave?
Mark A. Whiting
(c/o erickson@lbl-csam)
------------------------------
Date: Fri, 25 Sep 87 13:13:22 PDT
From: AAAI <AAAI-OFFICE@SUMEX-AIM.STANFORD.EDU>
Subject: help!
If anyone has made a tape of Pat Winston's Presidential Address from AAAI-87,
the AAAI would really appreciate a copy. Our copy got scrappled.
Two other AAAI Presidents, Marvin Minsky and Ed Feigenbaum, would also like
audio tapes of their Presidential Addresses if anyone has them.
Thanks,
Claudia Mazzetti
AAAI
445 Burgess Drive
Menlo Park, CA 94025
------------------------------
Date: 24 Sep 87 17:49:54 GMT
From: ur-tut!mkh1@cs.rochester.edu (Manoj Khare)
Subject: Re: Neural Networks & Unaligned fields
In article <1241@uccba.UUCP> finegan@uccba.UUCP (Mike Finegan) writes:
>In article <759@ucdavis.UUCP>, g451252772ea@ucdavis.UUCP (g451252772ea) writes:
>> > IEEE ASSP (Acoustics, Speech, and Signal Processing) April 1987,
>>
>> I found the 4/87 issue (and the rest of 1987) , but not this article.
>> Are you certain of this reference? Thanks...
>>
>I am not sure if it was April (I believe it was), but the whole journal is
>devoted to the subject of Neural Nets for that issue, and definitely exists.
> - Mike Finegan
> ...!{hal|pyramid}!uccba!finegan
The article "An Introduction to Computing with Neural Nets" by Richard P.
Lippmann appeared in IEEE ASSP magazine april 1987, pp 4-22.
Q. Does anybody have any idea if the book "Analog VLSI and Neural Systems" by
Carver A. Mead is published yet? OR Is there any way I could get his lecture
notes on the related course at CalTech? Thanks in advance.
..... Manoj Khare
------------------------------
Date: 27 Sep 87 06:43:56 GMT
From: deneb.ucdavis.edu!g451252772ea@ucdavis.ucdavis.edu
(0040;0000009606;0;327;142;)
Subject: references: IEEE ASSP and Hinton's recirculation algorithm
Thanks for the help with the IEEE ASSP reference; indeed I was looking
at the journal, not the 'magazine' (two shelves up, higher than me). It
appears worth the second trip.
Now: Geoffrey Hinton claims to have a new 'recirculation' algorith for
back-propagation, which is claimed to be 'more biologically realistic'
according to the Nature commentary reporting his claim (Nature, 7/9/87,
p. 107) (That's July, not Sept, for all you over-sea folk). But only
that commentary has appeared- I don't know where (if) Hinton has published
the algorithm itself. The commentary only mentions 'a packed audience at
the Society of Experimental Psychology', not even stating where the meeting
was.
Any ideas?
Thanks - Ron Goldthwaite, Psychology & Animal Behavior, U.Cal. Davis
'Economics is a branch of ethics pretending to be a science;
Ethology is a science, pretending relevance to ethics'
------------------------------
Date: 25 Sep 87 04:19:19 GMT
From: cbosgd!osu-cis!tut!dlee@ucbvax.Berkeley.EDU (Dik Lee)
Subject: Re: Neural Networks & Unaligned fields
In article <1241@uccba.UUCP> finegan@uccba.UUCP (Mike Finegan) writes:
>In article <759@ucdavis.UUCP>, g451252772ea@ucdavis.UUCP (g451252772ea) writes:
>> > IEEE ASSP (Acoustics, Speech, and Signal Processing) April 1987,
>>
>> I found the 4/87 issue (and the rest of 1987) , but not this article.
>> Are you certain of this reference? Thanks...
>>
>I am not sure if it was April (I believe it was), but the whole journal is
>devoted to the subject of Neural Nets for that issue, and definitely exists.
Yes, the paper appeared in IEEE ASSP magazine, Apr. 1987. Be sure you are
looking at ASSP magazine, not Journal of ASSP; they are two different
publications.
- Dik Lee Dept. CIS, Ohio State Univ.
------------------------------
Date: 25 Sep 87 10:04:22 GMT
From: ihnp4!homxb!mtuxo!mtune!codas!killer!usl!khl@ucbvax.Berkeley.EDU
(Calvin K. H. Leung)
Subject: Goal of AI: where are we going?
Should the ultimate goal of AI be the perfecting of human intel-
ligence, or the imitating of intelligence in human behavior?
We all admit that the human mind is not flawless. Bias decisions
can be made due to emotional problems, for instance. So there is
no point trying to imitate the human thinking process. Some
current research areas (neural networks, for example) use the
brain as the basic model. Should we also spend some time on the
investigation of some other models which could be more efficient
and reliable?
Provided that we have the necessary technology to build robots
that are highly intelligent; they are efficient and reliable and
they do not possess any "bad" characteristic that man has. Then
what will be the roles man plays in the society where his intel-
ligence can be viewed as comparatively "lower form"?
AI, where are we going?
------------------------------
Date: 27 Sep 87 17:47:22 GMT
From: su-russell!nakashim@labrea.stanford.edu (Hideyuki Nakashima)
Subject: Re: Goal of AI: where are we going?
In article <178@usl> khl@usl.usl.edu.UUCP (Calvin Kee-Hong Leung) writes:
>
>We all admit that the human mind is not flawless. Bias decisions
>can be made due to emotional problems, for instance. So there is
>no point trying to imitate the human thinking process.
I believe that those "bad" characteristics of human are necessary
evils to intelligence. For example, although we still don't understand
the function of emotion in human mind, a psychologist Toda saids that
it is a device for servival. When an urgent danger is approaching, you
don't have much time to think. You must PANIC! Emotion is a meta-
inference device to control your inference mode (mainly of recources).
If we ever make a really intelligent machine, I bet the machine
also has the "bad" characteristics. In summary, we have to study
why human has those characteristics to understand the mechanism of
intelligence.
Hideyuki Nakashima
nakashima@csli.stanford.edu
(or nakashima%etl.jp@relay.cs.net)
------------------------------
End of AIList Digest
********************
∂29-Sep-87 0635 LAWS@KL.SRI.Com AIList V5 #222 - Bindings, Spang Robinson, Neural Networks
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Sep 87 06:35:21 PDT
Date: Mon 28 Sep 1987 23:49-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #222 - Bindings, Spang Robinson, Neural Networks
To: AIList@SRI.COM
AIList Digest Tuesday, 29 Sep 1987 Volume 5 : Issue 222
Today's Topics:
Bindings - Gary Cottrell & Slava Prazdny,
Review - Spang Robinson #3/9,
Announcement - Second Chair in AI at Sussex University,
Neural Networks - Hamming Classification Network
----------------------------------------------------------------------
Date: Wed, 23 Sep 87 21:52:35 PST
From: gary@sdcsvax.ucsd.edu (Gary Cottrell)
Subject: binding
I am now at:
Gary Cottrell
Department of Computer Science and Engineering C-014
UC San Diego
La Jolla, Ca. 92093
gary@sdcsvax.ucsd.edu (ARPA)
{ucbvax,decvax,akgua,dcdwest}!sdcsvax!sdcsvax!gary (USENET)
619-534-6640
------------------------------
Date: Mon 28 Sep 87 19:47:21-PDT
From: Ken Laws <Laws@KL.SRI.Com>
Subject: Slava Prazdny
Date: Wed, 23 Sep 87 15:38:40 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: sad news
I thought I should let people know of a very unfortunate accident that
occurred this weekend. Slava Prazdny (formally at SPAR/FLAIR, most recently
at FMC) died this past Sunday in a hang-gliding accident. There will
be a memorial service October 7. I will let you know of more details
when I find out.
-Amy
------------------------------
Date: Mon, 28 Sep 1987 10:56 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Summary of Spang Robinson #3/9, 9/87 (Leff file bm788)
Summary of Spang Robinson Report, September 1987, Volume 3, No. 9
The lead article is on neural networks.
TRW's Mark III offeres 500K interconnections per second for an eight board
machine.
Price for the Mark III is $60,000 to $90,000.
Robert Hecht-Nielsen and Todd Gutschow formed HNC which produces
a board level neurocomputer and software costing $9500 to $19,500.
Science Applicatiosn Corporation system does 10M interconnections
per second called the Delta-1 costing $15,000.
Texas Instruments, Siemens, AT&T Bell Labs and Synaptics are developing
true analog neural network chips.
Martingale Research has a contract with Wright Aeronautical Labs to work with
biological networks in culture. It also sels a network simulator software
costing from $75.00 to $1275.00.
Meiko Incorporated has sold 100 of the The Computing Surface which
supports from 1-1024 processor nodes.
Nestor Incorporated sells a data entry system for handwriting input to
computers for $1595, a "Decision Learning System" and the Nestor Development
system. It had ~$400,000 revenue in FY 86.
Neuraltech sells Plato/Aristotle which is a system development kit costing
$2000.00 for "Beta version."
Neuralware sells a neural network prototyping and developing system for $495.00
They have a 200 order backlog.
+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_+_
Shorts
Symanetec is merging with Living Video Text (inventor of Think Tank, Ready
and More).
Borland bought Ansa, the maker of Paradox. Borland has sold 120,000
copies of Turbo Prolog.
Information Builders Inc., of Focus fame, acquired Level Research.
Intellicorp reported a net loss of about four million on revenues
of about twenty million for the fiscal year ending June 30, 1987.
Symbolics reported losses of about twenty-five million on revenues of
about 103 million. They have announced version four of their Prolog
system.
Integrated Inference Machines has placed one of its SM45000 symbolic
processing systems at NASA-Ames.
DEC has established an AI Lab at Palo Alto.
Natural Language Incorporated has ported Data Talker and the NLI connector
to Apollo work stations.
Texas Instruments has introduced its Explorer II Color System.
Advanced Decision Systems has been awarded a research
contractor to monitor seismic events resulting from nuclear tests.
James McGowan is now the president and CEO of Palladian Software.
GENSYM of Cambridge, MA has filed a lawsuit against GigaMos
systems, both of whom are offsprings of LMI. GENSYM claims
that GigaMOS is "interfering with Gensym's customers and prospects."
------------------------------
Date: Wed, 23 Sep 87 09:18:12 gmt
From: Aaron Sloman <aarons%cvaxa.sussex.ac.uk@NSS.Cs.Ucl.AC.UK>
Subject: Second Chair in AI at Sussex University
I'd be grateful if you are able to post this. Thanks.
Aaron Sloman
UNIVERSITY OF SUSSEX
S C H O O L O F C O G N I T I V E S C I E N C E S
CHAIR IN ARTIFICIAL INTELLIGENCE
================================
Sussex University, a major UK centre for research and teaching in AI,
intends to appoint a second Professor of Artificial Intelligence in the
newly established multidisciplinary School of Cognitive Sciences, which
includes AI, Linguistics, Philosophy and Psychology. Applications will
be welcomed from candidates with research interests in areas of AI
relevant to cognitive processes in natural or artificial systems.
The appointee will play a major role in the continued development of AI
and Computer Science within the new School, which has a large network
of computers and workstations for teaching and research (SUNs, HP
9000/300s, VAX, GEC-63, Orion-2 etc.) and many industrial connections.
Current research interests include language, vision, learning,
intelligent documentation tools, logics for AI, logic programming,
development of AI languages and tools (POPLOG development), computers
in Education, philosophical foundations of AI, AI and psychology,
computational linguistics.
The preferred start date is 1st October 1988, and applications should
be received by October 30th 1987, though later applications will be
considered.
For further information and application forms please apply to:
The Personnel Office
Sussex House
University of Sussex
Brighton
BN1 9RH, England
Phone: (+44) (0)273 - 606755
Aaron Sloman
Cognitive Sciences, Univ of Sussex, Brighton, BN1 9QN, England
Phone: University (44)-(0)273-678294
UUCP: ...mcvax!ukc!cvaxa!aarons
ARPANET : aarons%uk.ac.sussex.cvaxa@cs.ucl.ac.uk
JANET aarons@cvaxa.sussex.ac.uk
------------------------------
Date: 26 Sep 87 18:57:21 GMT
From: ihnp4!occrsh!erc3ba!erc3bb!cord!packard!edsel!granjon!io!mtunk!m
tune!whuts!homxb!homxc!del@ucbvax.Berkeley.EDU
Subject: Re: IEEE ASSP April 1987 on Neural Networks
I found the article very interesting and decided to code the hamming
classification neural network. I thought the comp.ai would be
interested. I think I found a bug in the article's description of the
routine (see code).
It should be portable to any C compiler.
_______________________cut here______________________
/* ham.c
* c version of the hamming net
* david leasure
* 9/25/87
*
* this routine is a hamming classification network
* described in IEEE ASSP April 1987 by Richard P. Lippmann pg. 9
* correcting for a presumed bug in the presented routine
* the bug is the value set for THETA by Lippmann. When THETA is
* N / 2 it so overwhelms the outputs from the lower net that only 0
* activation values are passed up from the threshold function.
* I have chosen to set epsilon to 1 / 2M and to not have an upper
* limit on the threshold function so no saturation occurs
*
* the program is somewhat inefficient because of the use of
* data storage for maxnet (t[k,l] in lippman's) and for output[t,M]
* but they could be useful in a simulator of this network which allowed
* things to be fiddled with.
* the code could be improved by not encoding the size and values
* of the node matrices directly, too, reading them instead from files
* and/or a user interface.
*
* if you improve the code, please send me the diff's
* david e. leasure
* ihnp4!homxc!del or del@homxc.att.com
*/
[Contact the author if you need the code. It's about
7000 characters. -- KIL]
--
David E. Leasure - AT&T Bell Laboratories - (201) 615-5307
------------------------------
End of AIList Digest
********************
∂29-Sep-87 0913 LAWS@KL.SRI.Com AIList V5 #223 - Philosophy of Science
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Sep 87 09:12:49 PDT
Date: Mon 28 Sep 1987 23:57-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #223 - Philosophy of Science
To: AIList@SRI.COM
AIList Digest Tuesday, 29 Sep 1987 Volume 5 : Issue 223
Today's Topics:
Philosophy - Is Computer Science Science? Or is it Art?
----------------------------------------------------------------------
Date: 22 Sep 87 14:18:24 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: Is Computer Science Science?
In article <1073@aurora.UUCP>, shafto@aurora.UUCP (Michael Shafto) writes:
> .... I think if you
> adopt the position that Real Science is about Nature, and
> that mathematics is not Real Science, then .... either
> (a) mathematicians don't make discoveries, or (b) they
> make discoveries about the properties of formal systems
> or systems of abstract descriptions, and that THESE are
> not part of Nature. If you follow (a), then you confine
> yourself to a limited group of discussants who share your
> idiosyncratic notion of 'discovery'; if you follow (b), then
> you put the content of mathematics somewhere outside Nature.
But formal systems are a product of the human mind, and the human mind
(as a feature of _Homo_sapiens_) is a part of Nature. Science,
mathematics, literature, and other intellectual activities are things
humans do because of our innate capacities and social norms.
> Someone (perhaps Lakatos or Feyerabend) said that scientists
> know about as much about science as fish know about
> hydrology. This is well illustrated whenever scientists
> quit DOING science and start talking about it.
There are scientific disciplines (mostly less formally developed than
other disciplines like physics) that deal with the study of human
activities. One example is anthropology. I think the question "Is
computer science a science?" belongs to one of those disciplines.
Our problem when we work with computers is less abstruse. All we have
to know is whether we can succesfully communicate if we use the term
'Computer Science'. Obviously we can. Nobody complained that the
title question ("Is Computer Science Science") is ambiguous. We all
understand that the word "science" in the phrase "computer science"
is not the same as the word "science" standing alone.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 23 Sep 87 03:41:06 GMT
From: jsnyder@june.cs.washington.edu (Hei Yu)
Subject: Re: Is Computer Science Science?
In article <2835@ames.arpa> eugene@pioneer.UUCP (Eugene Miya N.) writes:
>
>W. Daniel Hillis The Connection Machine, MIT Press, 1986,
>Last Chapter entitled something like "Why Computer Science is No Good"
>Says CS lacks scale, symmetry, and locality of effect.
As I recall, Ehud Shapiro's dissertation "Automatic Debugging" (MIT Press)
included some similar kind of grousing about CS having a "flat" structure
with lots of incomparable elements.
jsnyder@june.cs.washington.edu.arpa John R. Snyder
{ihnp4,decvax,ucbvax}!uw-beaver!jsnyder Dept. of Computer Science, FR-35
University of Washington
206/543-7798 Seattle, WA 98195
------------------------------
Date: 24 Sep 87 00:49:03 GMT
From: pioneer!eugene@ames.arpa (Eugene Miya N.)
Subject: A quote from fortune.dat on science
This appeared on logout:
Science is what happens when preconception meets verification.
strings /usr/games/lib/fort* | egrep Science
will get it.
------------------------------
Date: Thu, 24 Sep 87 10:50:38 PDT
From: Stuart Ferguson <shf@solar.stanford.edu>
Reply-to: shf@solar.UUCP (Stuart Ferguson)
Subject: Re: Is Computer Science Science? Or is it Art?
+-- cdfk@hplb.CSNET (Caroline Knight) writes:
| ... I believe that in software there is a better analogy with art
| and illustration than engineering or science. I have noticed that this
| is not welcomed by many people in computing but this might be because
| they know so little of the thought processes and planning that go on
| behind the development of, say, a still life or an advertising poster.
This line of thinking appeals to me alot (and I'm a "person in computing,"
having 10+ years programming experience). I can apreciate this article
because my own thinking has led me to somewhat the same place regarding
"Computer Science."
My own favorite art form that parallels programming is literature (and all
forms of writing or word-smithy). Like programming, writing has a
tremendous number of practical uses in our society, and only a handful of
writers call themselves "artists." Yet the person who writes as an artist
has a power of expression that a "hack" writer lacks.
| What is useful that can come of this analogy? Here are some
| suggetions:-
| Training: An artist will frequently learn their own style through
| meticulous study of previous greats (whose great software is there for
| us to emmulate?).
Computer Science educators could certainly learn to "cultivate the artistic
temperment." There are techniques and information to learn and study in
both art and programming, but no art teacher would ever think that learning
the techniques will make the student a great artist. The same is true for
programmers.
| At first working from nature is important although more freedom and
| greater abstraction will come later. ...
Excellent analogy. The first programs I wrote were simulations of physical
systems (lunar lander games, spacewar games, billiard ball atom simulations
and 3D graphics rendering of simulated worlds) or real-world problems (like
tic-tac-toe or the traveling salesman problem). Only after mastering these
did I move on to writing parsers, text editors and compilers -- the more
abstract end of the scale.
| Aids for producing mockups - for instance cartoonists use sheets of
| shading which can be cut to fit the required area - in software we
| need some such things to allow us to prototype with hints at detail
| without putting it all in.
Yes, and here is where programming diverges from the analogy of illustration.
Projects in illustration are typically small scale (although I'm not involved
in the art so I can't really say!) whereas programming projects can be
enormous requiring man-years of work and huge volumes of code and are often
created by teams rather than individual artists. I think the analogy of
an epic novel or some other writing effort is more appropriate.
| Aids for throwing stuff away! How many novices or less than expert
| programmers cling to the stuff they've written when it needs throwing
| out and redesigning from scratch! This is like the advice given in
| school not to use an eraser - of course eventually the artist knows
| when it is worth using one but at first it is better to concentrate on
| developing the ability to create smoothly and without fiddling.
Amen! Here again I think the writing analogy works well. Can you imagine
what a novel would sound like if the author never did any re-writing? Or
if the author had a few scenes that he had written and tried to work
them into one large story without re-writing any of the smaller scenes?
Rapid prototyping in programming is akin to a first draft in writing. It
allows the programmer to get ideas out on paper (so to speak) where he can
evaluate them objectivly and see what needs changing or re-thinking.
My writing improved immeasurably when I discovered that I could actaully
throw something that I had writen away and re-write it, and the lesson
was not lost on my programming. Often people don't have the courage to
throw something away that works, and it requires a certain ammount of
mastery of one's art to do the same thing and do it better.
| Caroline Knight cdfk@lb.hp.co.uk
| cdfk@hplb.csnet
------------------------------
Date: 24 Sep 87 12:53:54 GMT
From: uwslh!lishka@speedy.wisc.edu (Christopher Lishka)
Subject: Re: Is Computer Science Science?
In article <1318@houdi.UUCP> marty1@houdi.UUCP (M.BRILLIANT) writes:
>In article <1073@aurora.UUCP>, shafto@aurora.UUCP (Michael Shafto) writes:
>
>> Someone (perhaps Lakatos or Feyerabend) said that scientists
>> know about as much about science as fish know about
>> hydrology. This is well illustrated whenever scientists
>> quit DOING science and start talking about it.
>
>Our problem when we work with computers is less abstruse. All we have
>to know is whether we can succesfully communicate if we use the term
>'Computer Science'. Obviously we can. Nobody complained that the
>title question ("Is Computer Science Science") is ambiguous. We all
>understand that the word "science" in the phrase "computer science"
>is not the same as the word "science" standing alone.
>
I've only caught the tail-end of this discussion, but I'd like to
insert a few comments of my own here. This discussion about whether
or not Computer Science is *Science* or *Real*Science* reminds quite a
bit of a local (and not so local) phenomena in politics here in
Madison. A lot of liberals (hey, I like them better than
conservatives, generally) go around toting themselves as
*Politically*Correct*, and label those who do agree with their views
as not begin *Politically*Correct*. It seems to me that this is where
this kind of discussion leads. Someone will go up to a Comp. Sci.
person and say I'm a *Real*Scientist*, but your not!"
My comment is "why bother?" Why put labels on another person like
that? I like to think that research which I will do in the future
will be in the realms of science and scientific inquiry, and that my
friends and other C.S. people are also doing useful scientific work.
Granted, what I am doing now is not really scientific 'cause I'm just
programming for a living (to get through school), but you can find
that kind of work in any of the traditional *Sciences*.
A final note: I heartily agree with the two comments I've included
above. As long as the label "Computer Science" works and serves its
purpose, why not leave it alone. It would seem that time spent
bickering about this sort of thing was much better spent doing
research, or programmning, or whatever. I would suspect that the
people *really* doing scientific research (whatever that means) don't
care what you call them, but would rather work at the answers they are
trying to find to the unanswered questions around them.
Disclaimer: my thoughts are my own and noone else's, except maybe my
Cockatiels'.
-Chris
--
Chris Lishka /lishka@uwslh.uucp
Wisconsin State Lab of Hygiene <-lishka%uwslh.uucp@rsch.wisc.edu
\{seismo, harvard,topaz,...}!uwvax!uwslh!lishka
------------------------------
Date: 24 Sep 87 17:52:02 GMT
From: pioneer!eugene@ames.arpa (Eugene Miya N.)
Subject: Re: Is Computer Science Science? (Funding)
Status Quo? Hopefully a short note:
The reason why you have to make some clear distinctions care partially
be read in the latest CPSR [Computer Professionals for Social
Responsibility] Newsletter. It appears in the halls of places like
Ames, JPL, DOE Labs, the NAS (Natl. Acad. Sci), NSF, etc. Basically if
you are not a science, you don't get funding from those Science
Agencies.
This is a difference in Geography (seen as an art) and Geology.
I studied remote sensing for several years. The fact that it was in a
geography --->cartography -->graph --> "art" department was a big
minus. RS is pretty respectable in some circles, and like AI, disreputable
in other circles. (arrows for Mike Shafto ;-)
The level of funding CS in non-military work is dropping. This is okay
if you don't mind working on ALVs, Pilots Associates, etc. I believe
AI should be funded, but for it's improvement, not rediscoveries and
rehashes hashes of things done 20 years ago. You are more than welcome
to do AI-research/CS-research, so long as you have money.
P.S. I mentioned JPL because I took one noted scientist to a CS lab
(graphics) and he came away saying, "Nice pictures, but what's the use?"
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene
------------------------------
Date: 24 Sep 87 15:53:25 GMT
From: shafto@ames-aurora.arpa (Michael Shafto)
Subject: Re: A quote from fortune.dat on science
In article <2858@ames.arpa> eugene@nike.UUCP (Eugene Miya N.) writes:
>This appeared on logout:
>Science is what happens when preconception meets verification.
>
>strings /usr/games/lib/fort* | egrep Science
>will get it.
And always remember Dr. Science's line (Duck's Breath
Mystery Theater): "There is a thin line between ignorance
and arrogance. I have managed to erase that line."
------------------------------
End of AIList Digest
********************
∂29-Sep-87 1543 LAWS@KL.SRI.Com AIList Digest V5 #224
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Sep 87 15:43:14 PDT
Date: Tue 29 Sep 1987 00:02-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #224
To: AIList@SRI.COM
AIList Digest Tuesday, 29 Sep 1987 Volume 5 : Issue 224
Today's Topics:
Bibliography - Leff File a59AB
----------------------------------------------------------------------
Date: Mon, 21 Sep 1987 18:25 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Bibliography - Leff File a59AB
%T Expressiveness and tractability in knowledge representation and reasoning
%A Hector J. Levesque
%A Ronald J. Brachmand
%J Computational Intelligence
%V 3
%N 2
%D MAY 1987
%X A fundamental computational limit on automated reasoning and its effect on
knowledge representation is examined. Basically, the problem is that it can be
more difficult to reason correctly with one representational language than with
another and, moreover, that this difficulty increases dramatically as the
expressive power of the language increases. This leads to a tradeoff between
the expressiveness of a representational language and its computational
tractability. Here we show that this tradeoff can be seen to underlie the
differences among a number of existing representational formalisms, in addition
to motivating many of the current research issues in knowledge representation.
%T Go\*:del, Lucas, and mechanical models of the mind
%A Robert F. Hadley
%J Computational Intelligence
%V 3
%N 2
%D MAY 1987
%X In \fIMinds, Machines, and Go\*:del\fP, J.R. Lucas offers an argument, based
on
Go\*:del's incompleteness theorems, that the mind cannot be modeled by a
machine. This argument has generated a variety of alleged refutations, some of
which are incompatible with others. It is argued here that the incompatibility
of these `refutations' points to a central paradox which has not yet been
resolved. A solution to this paradox is presented, and a related paradox,
concerning the existence of consistent models for inconsistent humans, is
described and solved. An argument is presented to demonstrate that although
humans commonly produce inconsistent output, they can, in an important sense,
be modeled by \fIconsistent\fP formal systems, if their behavior is
deterministic. It is also shown that Go\*:del's results present no obstacle
to humans' proving the consistency of their own formal models.
%T Domain circumscription: A re-evaluation
%A David W. Etherington
%A Robert Mercer
%J Computational Intelligence
%V 3
%N 2
%D MAY 1987
%X Some time ago, McCarthy developed the domain circumscription formalism for
closed-world reasoning. Recently, attention has been directed towards other
circumscriptive formalisms. The best-known of these, predicate and formula
circumscription, cannot be used to produce domain-closure axioms; nor does it
appear likely that the other forms can. Since these axioms are important in
deductive database theory (and elsewhere), and since domain circumscription
often can conjecture these axioms, there is reason to resurrect domain
circumscription.
.sp
Davis presents an intuitively appealing semantics for domain circumscription,
based on minimal models. However, under certain conditions McCarthy's syntactic
realization of domain circumscription can induce inconsistencies in consistent
theories with minimal models. We present a simple, easily motivated change that
corrects this problem but retains the appealing semantics outlined by Davis.
We also explore some of the repercussions of this semantics, including
soundness and limited completeness results.
%T Defeat among arguments: A system of defeasible inference
%A R.P. Loui
%J Computational Intelligence
%V 3
%N 2
%D MAY 1987
%X This paper presents a system of non-monotonic reasoning with defeasible
rules.
The advantage of such a system is that many multiple extension problems can
be solved without additional explicit knowledge; ordering competing extensions
can be done in a natural and defensible way, via syntactic considerations.
The objectives closely resemble Poole's objectives, but the logic is different
from Poole's. The most important difference is that this system allows the kind
of chaining that many other non-monotonic systems allow. Also, the form in
which the inference system is presented is quite unusual. It mimics an
established system of inductive logic, and it treats defeat in the way of the
epistemologist-philosophers. The contributions are both of content and of form:
the kinds of defeat that are considered, and the way in which defeat is treated
in the rules of inference.
%T A hybrid, decidable, logic-based
knowledge representation system
%A Peter F. Patel-Schneider
%J Computational Intelligence
%V 3
%N 2
%D MAY 1987
%X The major problem with using standard first-order logic as a basis for
knowledge representation systems is its undecidability. A variant of
first-order tautological entailment, a simple version of relevance logic, has
been developed that has decidable inference and thus overcomes this problem.
However, this logic is too weak for knowledge representation and must be
strengthened. One way to strengthen the logic is create a hybrid logic by
adding a terminological reasoner. This must be done with care to retain the
decidability of the logic as well as its reasonable semantics. The result, a
stronger decidable logic, is used in the design of a hybrid, decidable,
logic-based knowledge representation system.
%T Patterns of interaction in
rule-based expert system programming
%A Stan Raatz
%A George Drastal
%J Computational Intelligence
%V 3
%N 2
%D MAY 1987
%X We study the effect of adding a rule to a rule-based heuristic classification
expert system, in particular, a rule which causes an unforeseen interaction
with rules already in the rule set. We show that it is possible for such an
interaction to occur between \fIsets\fP of rules, even when no interaction is
present between any \fIpair\fP of rules contained in these sets. A method is
presented that identifies interactions between sets of rules, and an analysis
is given which relates these interactions to rule-based programming practices
which help to maintain the integrity of the knowledge base. We argue that the
method is practical given some reasonable assumptions on the knowledge base.
%A Charles Babcock
%T IBM Expert Program Afforded Product Status
%J ComputerWorld
%P 118
%D JUL 13, 1987
%K AT02
%X IBM upgraded its expert system product from "introductory program to
"full-fledged" product. It also has the capability of accessing it's
"relational data base management systems." The complete system sells for
$42,500.
%T CAE software
%J Electronic News
%D July 6, 1987
%P 30
%V 33
%N 1662
%K AT02 AA05
%X Trimeter technologies has introduced a "knowledge-base"
system to optimize ASIC designs costing $30,000.
%T Kurzweil's Entry in Lowe-End Scanners
%J Electronics
%D JUN 11, 1987
%P 105
%V 60
%N 12
%K AT02 AI06
%X This $10,000 unit can read 60 characters/second, handle multiple type
styles on the same page. It has a learning mechanism and a 10 to 40 thousand
word lexicon.
%T Fingerprint Reader Restricts Access to Terminals and PC's
%J Electronics
%D JUN 11, 1987
%P 104
%V 60
%N 12
%K H01 AT02 AI06
%X ThumbScan costs %995.00.
.br
ThumbScan Inc. Two Mid America Plaza, Suite 800, Oake Brook Terrace, Ill. 60181,
312-954-2336
%T This System Integrates DSP and Image Processor
%J Electronics
%D JUN 11, 1987
%P 106
%V 60
%N 12
%K AT02 AI06
%X Dataube integrates a Digital Signal Processor based on Analog Devices ADSP
2100 chip. It also contains video signal to bit conversion software. It also
contains various hardware assists such as convolution.
%T A new Way to Speed Up Artificial-Vision Systems
%J Electronics
%D JUN 11, 1987
%P 89-90
%V 60
%N 12
%K AI06 AT02
%X International Robotmotion's new image
processing box contains multiple boards, each optimized for
specific vision processes such as correlation, pixel statistical
processor. It also has two on board array processors. The system
costs $150,000.
%A G. J. Holzmann
%T Automated Protocol Validation in Argos: Assertion Proving and
Scatter Searching
%J IEEE Transactions on Software Engineering
%D JUN 1987
%V SE-13
%N 6
%P 683-696
%K AA08
%A H. Gallaire
%A J. Minker
%A J. Nicolas
%T Logic and Databases: A Response
%J SIGPLAN Notices
%V 22
%N 6
%D JUN 1987
%P 20-24
%A R. A. Sosnowski
%T Prolog Dialects: A Deja Vu of BASICS
%J SIGPLAN Notices
%V 22
%N 6
%D JUN 1987
%P 39-48
%K T02
%X divides two Prolog styles into Edinburgh Prolog and
micro-Prolog. Shows examples for various differences between these Prologs.
Also discusses Turbo Prolog which he claims is still another dialect of
Prolog.
%A A. Cheese
%T Multi-Moded Relations in Parlog
%J SIGPLAN Notices
%V 22
%N 6
%D JUN 1987
%P 49-51
%K T02 H03
%T New Entries Mark AI Shift From Lab to Market
%J Electronic News
%D JUL 20, 1987
%V 33
%N 1664
%K AT02 Data General Neuron Data DEC Digital Equipment Corporation T03 T01
Gensym O03
%X Discusses the following new products that appeared at the AAAI show:
.br
DEC new version of VAX VMS Lisp
.br
Package to support interchange of applications between personal computers
and Data General MV models
.br
386 board for Symbolics machines
%T Ansa Brings Out Multi-User Version of Paradox DBMS
%J Electronic News
%V 33
%N 1661
%D JUN 29, 1987
%P 19
%K AA09 H01 AT02
%X Paradox 2.0 runs on various networks and supports complete record locking.
%J ComputerWorld
%D JUN 29, 1987
%V 21
%N 26
%P 20
%K AT12 AI01
%X response to Henry Eric Firdman's letter on how not to build
an expert system. This letter states that the Dipmeter Advisor cost
two million to build including costs associated with transferring
to field use.
%A Louis Fried
%T The Dangers of Dabbling in Expert Systems
%J ComputerWorld
%D JUN 29, 1987
%V 21
%N 26
%K AI01
%X The SRI survey indicates the cost of application development for
expert systems is $700 dollars per rule and this excludes hardware,
software tools and the time of domain experts. The average cost
is $260,000 per application. Goes on to discuss the importance
of feasibility studies prior to building an expert system.
Also discusses various characteristics of appropriate projects.
%A David A. Ludlum
%T Consortium set to Create Expert System Shell
%J ComputerWorld
%D JUN 29, 1987
%V 21
%N 26
%P 73
%K T02 AI02 Intellect AA09 AA06 AI01 AT16
%X Liberty Mutual Insurance Co., Southern California Edison, Transamerican
Insurance and one other will be joining together to develop an expert system
that can interface with mainframe DBMS and CICS. The system will use Intellect
to formulate English queries to either DBMS or the rules themselves.
%J ComputerWorld
%V 21
%N 24
%P 25
%D JUN 15, 1987
%K AT04
%X France, Italy, UK and West Germany spent eighty million on AI software
in 1986 and are expected to spend 825 million by 1991.
%J InfoWorld
%D JULY 6, 1987
%V 9
%N 27
%P 18
%K AT02 H01 T01
%X Star Saphire converts LISP to C. The resulting C code can be translated,
compiled, optimized or link with other USER applications. It costs $495.00.
%A Robert X. Cringeley
%T Do They Really Want to Be as Smart as AT&T
%J InfoWorld
%D JULY 6, 1987
%V 9
%N 27
%P 78
%K AA08
%X AT&T plans to add AI tool to its network manager sometime in 1988.
%T Canada Firm Set to Buy Lisp for $3.2M
%J Electronic News
%V 33
%N 1657
%D JUN 1, 1987
%P 12+
%K AT16
%X GigaMos Holdings has bought the assets of Lisp Machine Inc. (which
earlier went into bankruptcy). GigaMos is affiliated
with Lisp Canada.
%A Karen Fitzgerald
%A Paul Wallich
%T Next Generation Race Bogs Down
%J IEEE Spectrum
%V 24
%N 6
%P 34-39
%K GA01 GA02 GA03
%X An NSF Team to assess the Japanese Fifth Generation came bakc
with mixed conclusions: Japan is already ahead in certain area while
others said that the Fifth Generation Project is a national embarassment.
Marc Snir of the Hebrew University in Jerusalem said that there
were many there because they were sent by their companies and that there
was little questioning of efforts. An assessment of the ICOT Personel
Sequential Inference Machine said that the system is inferior to US
Lisp Workstations but has enormous physical memory (80 megabytes).
.sp
The article has a table of the various projects, Fifth Generation
Computers, Alvey, Esprit, MCC and Strategic Computing, their
goals, accomplishments and funding.
%A Douglas Barney
%T Microsoft in Link Pact
%J ComputerWorld
%V 21
%N 22
%D JUN 1, 1987
%P 8
%K AI02 H01 AT16
%X Microsoft licensed a natural language interface but no products
are planned immediately.
%T New Products
%J ComputerWorld
%V 21
%N 22
%D JUN 1, 1987
%P 34
%K Pyramid T01 AT02
%X Pyramid Announced a Pyrlisp system for $6000.00
%T New Products
%J ComputerWorld
%V 21
%N 22
%D JUN 1, 1987
%P 48
%K AI06 AT02
%X IBASE system reads documents and includes automatic form processing.
%T Nickels and Dimes
%J ComputerWorld
%V 21
%N 22
%D JUN 1, 1987
%P 108
%K H02
%X Symbolics third quarter revenues ending March 29 was 24.6 million.
%A E. Sacks
%T Qualitative Sketching of Parameterized Functions
%B Knowledge Based Expert Systems for Engineering: Classification, Education
and Control
%E D. Sriram
%E R. A. Edey
%I Computational Mechanics Institute
%C Boston, USA
%D 1987
%P 1-13
%K AA11 AA12 AA13 AI01 AI14 AA01 AA05
%X ISBN 0-931215-81-1 (Boston) ISBN 0-905451-92-9 (Southampton)
%X This system uses Macsyma and "Bounder," a system that computes
bounds from inequalities to do qualitative sketching of univariate
expressions. It finds interesting points such as inflections,
maxima, minima and discontinuities. QS has been tested on the
following sets of equations in the literature:
the four important probability distributions: uniform, exponential,
gamma and normal, 17 out of 18 cases from the examples and exercises
in Keeney and Raiffa's text on utility theory. Additional work
will be done to deal with phase diagrams.
%A J. Geller
%A M. R. Taie
%A S. C. Shapiro
%A S. N. Srihari
%T Device Representation and Graphics Interfaces of VMES
%B Knowledge Based Expert Systems for Engineering: Classification, Education
and Control
%E D. Sriram
%E R. A. Edey
%I Computational Mechanics Institute
%C Boston, USA
%D 1987
%P 15-28
%K AI01 AA21 AI16 AA04 AI02
%X ISBN 0-931215-81-1 (Boston) ISBN 0-905451-92-9 (Southampton)
%X Discusses representations of electronic systems to be maintained.
Issues are the representation between the logical structure of the
device and the physical entity of what is on a circuit board or
other module to be replaced, graphical representation and natural
language interface.
%A D. J. Cooper
%T An Expert Systems Approach to Process Identification and Adaptive
Control
%B Knowledge Based Expert Systems for Engineering: Classification, Education
and Control
%E D. Sriram
%E R. A. Edey
%I Computational Mechanics Institute
%C Boston, USA
%D 1987
%P 29-41
%K H01 AA20 AI01 T01
%X ISBN 0-931215-81-1 (Boston) ISBN 0-905451-92-9 (Southampton)
%X Discusses a rule based system for adaptive control. The implementation
has not been completed. They intend to write a Lisp-Fortran based system.
%A R. H. Allen
%A S. Haran
%A V. Sharma
%A J. Sorab
%T Engineering and Artificial Intelligence Applications for the Evaluation
and Management of Shoulder Dystocia
%B Knowledge Based Expert Systems for Engineering: Classification, Education
and Control
%E D. Sriram
%E R. A. Edey
%I Computational Mechanics Institute
%C Boston, USA
%D 1987
%P 44-53
%K AA01 obstetrics delivery
%X ISBN 0-931215-81-1 (Boston) ISBN 0-905451-92-9 (Southampton)
%X This is a system to assist in the delivery of infants where the
shoulder jams against the pelvic bone. A physical model, as well
as a finite element model have been
developed to assist in learning about the physical forces involved.
In addition, a tactile sensing system to be worn underneath the
physician's surgical glove was built for the purpose of measuring
important parameters. The expert systems built as part of this
effort include one to predict the possibility of this condition
and another to manage it when it occurs. It is hoped that the
other work on finite elements, tactile sensing and other modeling
will be integrated within the system. This is an example of
an expert system being build contemporaneously with the research
to acquire the data on which it will be based.
%T TAKING ISSUE:
%T A critique of pure reason
%J Computational Intelligence
%V 3
%N 3
%D AUG 1987
%A Drew McDermott
%X with peer commentary edited by Hector Levesque
.sp
The relevance of logic to AI has been hotly debated from the very
beginnings of the field. Just when the issue seemed to be finally cooling
down, Drew McDermott, a noted researcher and hitherto loyal advocate of logic,
wrote a paper explaining why, after a decade of research, he has changed his
mind about the use of logic. The special section of /Computational
Intelligence/ will examine this issue in detail. After a short introduction,
the section will contain McDermott's paper, together with commentaries on it
by a number of prominent AI researchers: James Allen and Henry Kautz, Danny
Bobrow and Mark Stefik, Ken Bowen, Ron Brachman, Eugene Charniak, Johan de
Kleer, Jon Doyle, Ken Forbus, Pat Hayes, Carl Hewitt, Robert Kowalski, Robert
Moore, Geoff Hinton, Jerry Hobbs, David Israel, John McCarthy and Vladimir
Lifschitz, Nils Nilsson, Sandy Pentland, David Poole, Ray Reiter, Stan
Rosenschein, Len Schubert, Brian Smith, Mark Stickel and Mabry Tyson, Richard
Waldinger, Terry Winograd, and Bill Woods. Finally, McDermott replies to his
critics.
%T Equivalent logic programs and
symmetric homogeneous forms of
logic programs with equality
%A Kwok-Hung Chan
%J Computational Intelligence
%V 3
%N 3
%D AUG 1987
%X This article introduces the notion of CAS-equivalent logic programs: logic
programs with identical Correct Answer Substitution. It is shown that the
notions CAS-equivalence, refutational equivalence, and logical equivalence do
not coincide in the case of definite clause logic programs. Least-model
criteria for refutational and CAS-equivalence are suggested and their
correctness is proved. The least-model approach is illustrated by two proofs
of CAS-equivalence. It is shown that the symmetric extension of a logic
program subsumes the symmetry axiom, and the symmetric homogeneous form of a
logic program with equality subsumes the symmetry, transitivity, and predicate
substitutivity axioms of equality. These results contribute towards the
goal of building equality into Standard Prolog without introducing additional
inference rules.
%T Pragmatic modeling:
Toward a robust natural language interface
%A M. Sandra Carberry
%J Computational Intelligence
%V 3
%N 3
%D AUG 1987
%X One of the most important ways in which an information-provider assimilates a
n
information-seeking dialogue is by inferring the underlying task-related plan
motivating the information-seeker's queries. This paper presents a strategy
for hypothesizing and tracking the changing task-level goals of an
information-seeker, and building a model of his task-related plan as the
dialogue progresses.
.sp
Naturally occurring utterances are often imperfect. The
information-provider often appears to use inferred knowledge about the
information-seeker's underlying task-related plan to remedy any of his faulty
utterances and enable the dialogue to continue without interruption. This
paper presents a strategy for understanding one kind of defective utterance.
Our approach relies on the information-seeker's inferred task-related plan as
the primary mechanism for suggesting how an utterance should be understood,
thereby considering only interpretations that are relevant to what the
information-seeker is trying to accomplish.
------------------------------
End of AIList Digest
********************
∂02-Oct-87 0207 LAWS@KL.SRI.Com AIList V5 #225 - CPSR, Time, Boltzmann Machines, Slava Prazdny
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 2 Oct 87 02:07:07 PDT
Date: Thu 1 Oct 1987 23:32-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #225 - CPSR, Time, Boltzmann Machines, Slava Prazdny
To: AIList@SRI.COM
AIList Digest Friday, 2 Oct 1987 Volume 5 : Issue 225
Today's Topics:
Queries - Expert/AI Work in Communication Networks &
Annual Review of Computer Science & Neural Hardware &
Using the ATMS to Scan Homeric Verse,
Bindings - CPSR,
Representation - Time,
Neural Networks - Boltzmann Machines,
Obituary - Slava Prazdny
----------------------------------------------------------------------
Date: 29 Sep 87 14:33:39 GMT
From: cbosgd!cblpf!dtm@ucbvax.Berkeley.EDU (Dattaram Mirvke)
Subject: Need references on Expert/AI work in Communication Networks.
Need references/pointers to work done in the Expert systems/AI in the
Network domain. I am specially interested in simulations/modeling/
behavior analysis and fault diagnosis.
Please e-mail the responses to me unless the information is of
general interest. If I get sufficient responses I will summarise to the
net.Thanks in advance.
- Datta Miruke
cbosgd!cblpf!dtm
cbosgd!ncpe!drm
------------------------------
Date: 30 Sep 87 19:51:42 GMT
From: wucs1!grs@uunet.UU.NET (Guillermo Ricardo Simari)
Subject: Annual Review of Computer Science
The book "Logical Foundations of Artificial Intelligence"
by M. R. Genesereth, N. J. Nilsson contains the following reference,
Levesque, H., "Knowledge Representation and Reasoning",
Annual Review of Computer Science, 1986
Can anyone give me information about the above journal? I cannot find it
anywhere.
Guillermo Simari Washington University, Department of Computer Science
St. Louis, MO, 63130, U.S.A.
UUCP: grs@wucs1.UUCP or ...!{ihnp4,uunet}!wucs1!grs
------------------------------
Date: 1 Oct 87 02:02:46 GMT
From: munnari!mulga.oz!jayen@uunet.UU.NET (Jayen Vaghani)
Subject: Want information on Neural Hardware in use
I am preparing a talk for one of my honours subjects and part of the talk
centres on comparing neural hardware to other architectures.
I need information on what neural hardware is in use (possibly commercially
available) and what it is being used for. I would also like to know why this
direction was chosen as against using a more general purpose parallel
architecture and modelling the neural network on that. Perhaps some feelings
about whether the approach has any future would also be nice and what problems
were encountered in using the system.
Responses can be to the net or mailed to me. If people are interested I will
summarise any personal responses to the net. Possibly someone else has already
asked this question so I would be happy to hear what responses they got.
Thanks in advance,
Jayen.
-------
UUCP: {seismo,ukc,ubc-vision,mcvax}!mulga.oz!jayen
ARPA: jayen%mulga.oz@seismo.css.gov
CSNET: jayen%mulga.oz@australia
------------------------------
Date: 29 Sep 87 15:18:35 GMT
From: eagle!icdoc!qmc-cs!flash@ucbvax.Berkeley.EDU (Flash Sheridan)
Subject: Using the ATMS to Scan Homeric Verse
As a toy demo, I'm trying to use Johan deKleer's Assumption Based
Truth Maintenance System to scan Homer. I'd appreciate comments.
I'd also appreciate it if somebody could email me a hundred or so
lines, so I don't have to type in any more.
------------------------------
Date: 1 Oct 87 22:58:08 GMT
From: acornrc!rbbb@ames.arpa (David Chase)
Subject: Re: Using the ATMS to Scan Homeric Verse
In article <297@sequent.cs.qmc.ac.uk>, flash@ee.qmc.ac.uk (Flash Sheridan)
writes:
> ... to scan Homer.
> I'd also appreciate it if somebody could email me a hundred or so
> lines, so I don't have to type in any more.
[this doesn't really belong on this list, but this is a mighty stale
pointer. I am hoping that this will jog the memory of someone else on the
list with more recent information.]
Sometime around about 1975 (in high school) I went to a seminar at the Nat.
Junior Classical League convention where someone from Dartmouth talked
about feeding the Aeneid to a computer program, doing the meter, counting
"et"s, etc. I was under the impression that they had other classics on
line or on tape.
By the way, how should I type in ancient Greek on my U.S.A. keyboard? I
can use ` and ' and ~ for accents, but what about the breath marks?
David Chase, Olivetti Research Center
------------------------------
Date: 29 Sep 87 22:10:56 GMT
From: sdcrdcf!ism780c!jimh@hplabs.hp.com (Jim Hori)
Subject: Re: Is Computer Science Science? (Funding)
In article <2868@ames.arpa> eugene@pioneer.UUCP (Eugene Miya N.) writes:
>be read in the latest CPSR [Computer Professionals for Social
>Responsibility] Newsletter. It appears in the halls of places like
can you, or anyone, post the address of this
newletter?
jimh ...yeah you right
........................
------------------------------
Date: 30 Sep 87 16:28:47 GMT
From: pioneer!eugene@ames.arpa (Eugene Miya N.)
Subject: Re: Is Computer Science Science? (Funding)
Computer Professionals for Social Responsibility (National Office)
646 Emerson St.
Palo Alto, CA 94301
------------------------------
Date: 1 Oct 87 12:31:56 GMT
From: ihnp4!homxb!homxc!del@ucbvax.Berkeley.EDU (D.LEASURE)
Subject: Re: Is Computer Science Science? (Funding)
In article <7397@ism780c.UUCP>, jimh@ism780c.UUCP (Jim Hori) writes:
> can you, or anyone, post the address of this
> newletter? [CPSR]
CPSR, Inc. PO Box 717, Palo Alto CA 94301 415/322-3778
$30/yr $10/yr for student
--
David E. Leasure - AT&T Bell Laboratories - (201) 615-5307
------------------------------
Date: Tue, 29 Sep 87 09:46:05 -0400
From: koomen@cs.rochester.edu
Subject: Representation of Time
>From: mcvax!unido!uklirb!noekel@uunet.uu.net
>Subject: J.F.Allen's work on time - (nf)
Reference intervals, automatic interval hierarchy structuring, duration
logic, etc, have indeed been implemented, in support of my PhD research
project. For a description, watch for a UofR Tech Report and my
dissertation, both expected to appear within the next year.
-- Hans
EMail: Koomen@CS.Rochester.Edu Paper: Johannes A. G. M. Koomen
Dept. of Computer Science
Phone: (716) 275-9499 [work] University of Rochester
(716) 442-4836 [home] Rochester, NY 14627
------------------------------
Date: Tue, 29 Sep 87 13:13:25 PDT
From: ladkin@kestrel.ARPA (Peter Ladkin)
Subject: Re: J.F. Allen's work on time
There has been much subsequent work done on this topic. I'll try to
summarise what I know about. James Allen's system can be formulated as
a relation algebra in the sense of Tarski, and also as a complete,
countably categorical first-order theory. The theory is thus
decidable, and admits of quantifier elimination. This means that
arbitrary first-order constraints expressed in the system are
computably equivalent to a set of constraints without quantifiers.
Such collections of Boolean constraints may be checked for consistency
either by an extension of Allen's method, or in other ways. Marc
Vilain and Henry Kautz showed that the general constraint satisfaction
problem for this system is NP-complete. Allen and Pat Hayes have
formulated an alternative theory of time intervals as a collection of
first-order axioms. They want to allow the collection of pairs of
integers as a model, and thus the axioms are weaker than the original
system. These axioms have as models exactly sets of pairs from an
unbounded linear order. Johan Van Benthem has investigated interval
theories in his book `The Logic of Time'. All the theories are
comparable, it turns out, since the collections of primitives are
interdefinable.
For a reading list, the AAAI-86, AAAI-87, IJCAI-85 and IJCAI-87
conference proceedings contain papers on interval systems for time
representation, Allen and Hayes have a technical report (University of
Rochester) due out any day, I have also technical reports not in the
above sources (Kestrel Institute), and Edward Tsang (University
of Essex) has some also. Tom Dean (Brown University) is using interval
representations in his planner, and has investigated the most commonly
occurring constraint satisfaction problems in detail. Richard Pelavin
has incorporated Allen's interval system into the design for a
planner, and Henry Kautz has also investigated the use of interval
specifications in general planning problems. (Both are former
students of James Allen). There is van Benthem's book, and a review
of it by Steven Kuhn in the September 1987 Journal of Symbolic Logic
(of the open problems mentioned by Kuhn, the first and last were
solved already, by Roger Maddux and I, and I'm sure some others). Joe
Halpern and Yoav Shoham formulated a modal logic of time with interval
modalities, in the First Logic in Computer Science conference (1986,
Proceedings published by IEEE). Klaus Schultz at Tubingen has a
technical report comparing Allen's approach with Kamp's event theory,
and Austin Tate and Colin Bell have investigated the use of interval
constraints in the O-Plan planner at Edinburgh (Bell is at the
University of Iowa). Other references may be found by taking the
transitive closure of the `references' relation on these sources.
There is very closely related work being done by Robert Kowalski's
group on event structures (Imperial College).
Apologies to those whose work I've missed or are unaware of (please
let me know). Things are progressing fast, so we all ought to be on
each other's mailing lists.
peter ladkin
ladkin@kestrel.arpa
------------------------------
Date: Tue, 29 Sep 1987 11:09 EDT
From: "Scott E. Fahlman" <Fahlman@C.CS.CMU.EDU>
Subject: Boltzmann Machines
To answer your question about Boltzmann machines:
In the original Boltzmann Machine formulation, a pattern (think of this
as both inputs and outputs) is clamped into the visible units during the
teaching phase; the network is allowed to free-run, with nothing
clamped, during the normalization phase. The update of each weight is a
function of the difference between co-occurrence statistics measured
across that connection during the two phases.
The result (if all goes well) is a trained network that has no concept
of input and output: clamp a partial pattern into the visible units, and
the network will try to complete it in a way that is consistent with the
training examples. Clamp nothing, and the network should settle into
states whose distribution approximates the distribution of examples in
the training set.
Later, someone (Geoff Hinton, I think), realized that if the network was
really being trained to produce a certain input-to-output mapping, it
was wasteful of links and training effort to train the network to
reproduce the distribution of input vectors; an input will always be
supplied when the network is performing. If the visible units are
divided into an input set and an output set, if the teaching phase is
done as before, and if the inputs (only) are clamped during the
normalization phase, the network will "concentrate" on learning to
produce the desired outputs, given the inputs, and will not develop the
capability of reproducing the input distribution.
Some papers refer to the "completion" model, others to the "Input/Ouput"
model. The distinction is not always emphasized. The learning
procedure is essentially the same in either case.
Note that, unlike Boltzmann, the back-propagation model is inherently an
I/O model, though it is possible to do completion tasks with some added
work. For example, one might train a backprop network to map each of a
set of patterns into itself, and then feed it partial patterns at the
inputs.
-- Scott Fahlman, CMU
------------------------------
Date: 30 Sep 87 21:21:50 GMT
From: giraffe..arpa!krulwich@uunet.uu.net (Bruce Krulwich)
Reply-to: yale.ARPA!krulwich@uunet.uu.net (Bruce Krulwich)
Subject: Re: Boltzmann Machine
> Since the expression for dG/dWij is the same in both cases, the
> definitions of Pij- must be equivalent. The only explanation I could
> think of was that "clamping" the inputs ONLY was the same thing as letting
> the environment have a free run of them, so the case being described is
> the free-running one.
The point is that for any given inputs learning is done by comparing
the desired outputs with the outputs computed by the machine. This
called monitored learning, and is similar in this sense to back
propogation learning. This is used for networks that perform a
computation based on some input being clamped in the input units.
When the output units are clamped, the P values are something like
what they "should" be, so comparing these to the P values for
unclamped output units lets you approximate the error between the
units in qestion and learn from it.
Bruce Krulwich
ARPA: krulwich@yale.arpa If you're right 95% of the time,
or krulwich@cs.yale.edu why worry about the other 3% ??
Bitnet: krulwich@yalecs.bitnet
UUCP: {harvard, seismo, ihnp4}!yale!krulwich
------------------------------
Date: 29 Sep 87 11:04:18 PDT (Tue)
From: baird@cel.fmc.com (Michael Baird)
Subject: Slava Prazdny (Bindings)
As many of you know by now, Slava Prazdny died Saturday, September 19th, in a
hang-gliding accident, high in the California mountains. He is survived by
his wife, Dagmar Dolan, their as yet unborn child, and his 15 year old
daughter Bronja Prazdny. Slava was 38. He was with FMC's Santa Clara AI
Center during the past two years, and before that at Schlumberger's Palo Alto
Research Center / Fairchild Laboratory for Artificial Intelligence Research.
Memorial Services will be held at 3:15 p.m., Wednesday October 7th, 1987,
outdoors in Foothills Park, operated by the City of Palo Alto, just a few
miles up Page Mill Road "west" of I-280. Flowers may be brought to the
memorial. Dagmar invites members of the AI community to attend.
It is suggested that you enter the park gate (it says for Palo Alto residents
only -- but tell the guard that you are attending the memorial) around 3 p.m.
From the parking area find the "Lee" grove (two large redwoods) beyond the
picnic tables. Services will be informal, as Slava would have wanted them to
be.
Slava had published over 60 refereed papers, and was recognized
internationally as an expert in many aspects of human and machine perception.
His latest works in stereo vision and adaptive "neural" networks were deemed
scientific breakthroughs.
A beautiful Redwood tree in Big Basin State Park will be dedicated in Slava's
name. This will be a pleasant place we can go to remember Slava. The family
has asked that donations be sent in his name to The Sempirvirens Fund, 2483
Old Middlefield Way, Mountain View, CA 94043.
Mike Baird
baird@cel.fmc.com
(408) 289-4932
------------------------------
End of AIList Digest
********************
∂02-Oct-87 0444 LAWS@KL.SRI.Com AIList V5 #226 - Philosophy of AI and Computer Science
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 2 Oct 87 04:44:22 PDT
Date: Thu 1 Oct 1987 23:41-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #226 - Philosophy of AI and Computer Science
To: AIList@SRI.COM
AIList Digest Friday, 2 Oct 1987 Volume 5 : Issue 226
Today's Topics:
Comments - Goal of AI & Nature of Computer Science
----------------------------------------------------------------------
Date: 28 Sep 87 14:36:36 GMT
From: nbires!isis!csm9a!bware@ucbvax.Berkeley.EDU (Bob Ware)
Subject: Re: Goal of AI: where are we going?
>We all admit that the human mind is not flawless. Bias decisions
>can be made due to emotional problems, for instance. ...
The above has been true for all of recorded history and remains true
for almost everyone today. While almost everyone's mind is flawed due
to emotional problems, new data is emerging that indicates the mind can
be "fixed" in that regard. To see what I am referring to, read L Ron
Hubbard's book on "Dianetics".
MAIL: Bob Ware, Colorado School of Mines, Golden, Co 80401, USA
PHONE: (303) 273-3987
UUCP: hplabs!hao!isis!csm9a!bware or ucbvax!nbires!udenva!csm9a!bware
------------------------------
Date: 29 Sep 87 17:25:55 GMT
From: eugene@pioneer.arpa (Eugene Miya N.)
Reply-to: eugene@pioneer.UUCP (Eugene Miya N.)
Subject: Re: Is Computer Science Science? Or is it Art? [sort of hope
not]
In article <8709290724.AA10633@ucbvax.Berkeley.EDU> solar!shf
(Stuart Ferguson) writes:
>+-- cdfk@hplb.CSNET (Caroline Knight) writes:
>| ... I believe that in software there is a better analogy with art
>| and illustration than engineering or science. I have noticed that this
>| is not welcomed by many people in computing but this might be because
>| they know so little of the thought processes and planning that go on
>| behind the development of, say, a still life or an advertising poster.
>
>This line of thinking appeals to me alot (and I'm a "person in computing,"
>having 10+ years programming experience). I can apreciate this article
>because my own thinking has led me to somewhat the same place regarding
>"Computer Science."
I'm glad I waited a bit on this. Two years ago, I met Nico Habermann of
CMU. At that time I suggest CS could learn more from cognitive sciences
(psychology). Habermann has an EE PhD. He didn't like this idea due to
the softness. I suggest others try this question on other hard
CS-types. I only ask that you avoid analogies to introspection.
While the art analogy to computing has a certain appeal, especially the
iterative and prototypical aspects, and it also has Knuth behind it,
it also has some problems. Rather than mentioned them, I suggest you
send mail to DEK and report back.
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix}!ames!aurora!eugene
------------------------------
Date: 29 Sep 87 17:59:04 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: Goal of AI: where are we going?
In article <178@usl>, khl@usl (Calvin K. H. Leung) writes:
> Should the ultimate goal of AI be the perfecting of human intel-
> ligence, or the imitating of intelligence in human behavior?
>
> We all admit that the human mind is not flawless... So there is
> no point trying to imitate the human thinking process. Some
> current research areas (neural networks, for example) use the
> brain as the basic model. Should we also spend some time on the
> investigation of some other models which could be more efficient
> and reliable?
I always thought there were several different currents going in AI.
One stream is trying to learn how the human mind works and imitate it.
Another stream is trying to fill in the gaps in the capabilities of the
human mind by using unique machine capabilities in combination with
imitations of the mind. Some people are working with research
objectives, some have application objectives.
We don't need a unique goal for AI. We contain multitudes.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 29 Sep 87 18:25:36 GMT
From: nysernic!rpicsb8!csv.rpi.edu!franklin@rutgers.edu (W. Randolph
Franklin ( WRF ))
Subject: Re: Is Computer Science Science? (Funding)
In article <2868@ames.arpa> eugene@pioneer.UUCP (Eugene Miya N.) writes:
>Status Quo? Hopefully a short note:
>The reason why you have to make some clear distinctions care partially
>be read in the latest CPSR [Computer Professionals for Social
>Responsibility] Newsletter. It appears in the halls of places like
>Ames, JPL, DOE Labs, the NAS (Natl. Acad. Sci), NSF, etc. Basically if
>you are not a science, you don't get funding from those Science
>Agencies.
>
>This is a difference in Geography (seen as an art) and Geology.
>I studied remote sensing for several years. The fact that it was in a
>geography --->cartography -->graph --> "art" department was a big
>minus. RS is pretty respectable in some circles, and like AI, disreputable
This may be improving. NSF is soliciting proposals to set up a center
for excellence in Geographic Information Systems.
Wm. Randolph Franklin
Preferred net address: Franklin@csv.rpi.edu
Alternate net: wrf@RPITSMTS.BITNET
Papermail: ECSE Dept, Rensselaer Polytechnic Institute,
Troy NY, 12180
Telephone: (518) 276-6077
Telex: 6716050 RPI TROU -- general RPI telex number.
Wm. Randolph Franklin, RPI, 6026 JEC, (518) 276-6077, Franklin@csv.rpi.edu
------------------------------
Date: 30 Sep 87 02:08:00 GMT
From: munnari!comp.vuw.ac.nz!lindsay@uunet.uu.net (Lindsay Groves)
Subject: Re: Is Computer Science Science?
In article <5068@jade.BERKELEY.EDU> ed298-ak@violet.berkeley.edu
(Edouard Lagache) writes:
>>>
>.... Does Computer Science have any laws?
>>>
>>"Anything that can go wrong will go wrong."
>> ...
>
> Hey those aren't laws from Computer Science, they are from the
> Science (Religion?) of Murphyology.!
>
> E.L.
The August issue of the Communications of the ACM contains an article by
C.A.R.Hoare and eight others, entitled "Laws of Programming". One of their
laws (4) is:
ABORT U P = ABORT
where ABORT (which they denote by an upside down T) is a statement that can
do anything ("It places no constraint on the executing machine, which may do
anything, or fail to do anything; in particular, it may fail to terminate"),
and U is nondeterministic choice.
The text explaining this law says:
"This law is sometimes known as Murphy's Law, which state, "If it can go
wrong it will"; the left-hand side describes a machine that CAN go wrong
(or can behave like P), whereas the right-hand side might be taken to
describe a machine that WILL go wrong. But the true meaning of the law
is actually worse than this: The program ABORT will not always go wrong --
only when it ismost disastrous for it to do so! THe abundance of empirical
evidence for law (4) suggests that it should be taken as the first law of
computer programming."
It seems that being part of "Murphyology" doesn't preclude something from
being a law of Computer Science -- this one is given a very precise
statement and interpretation as a law of programming, which must also count
as a law of Computer Science. Given that Computer Science draws heavily on
such fields as mathematics, logic, linguistics (Chomsky's hierarchy has far
more relevance to Computer Science than it does to lingusitics!), electrical
engineering etc., it is not surprising that laws in Computer Science should
bear similarity to laws in other areas.
Lindsay Groves
Logic programmers' theme song: "The first cut is the deepest"
------------------------------
Date: 30 Sep 87 17:42:21 GMT
From: uwslh!lishka@speedy.wisc.edu (Christopher Lishka)
Subject: Re: Goal of AI: where are we going?
***Warning: FLAME ON***
In article <549@csm9a.UUCP> bware@csm9a.UUCP (Bob Ware) writes:
>>We all admit that the human mind is not flawless. Bias decisions...
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
The expression "we all" does not apply to me, at very least. Some of
us (at least myself)like to believe that the human mind should not be
considered to be either flawed or flawless...it only "is." I feel
that making a judgement on whether or not everyone admits that the
human mind is flawed happens to be a biased decision on the above
net-reader's part. Realize that not everyone has the same views as
the above...
>>...can be made due to emotional problems, for instance. ...
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
Is this statement to be read as "emotional problems can cause bias
decisions, which are flaws in the human mind?" If it does, then I
heartily disagree, because I once again feel that emotional problems
and/or bias decisions are not indicative of flaws in the human
mind...see above for my reasons.
>
>The above has been true for all of recorded history and remains true
>for almost everyone today. While almost everyone's mind is flawed due
↑↑↑↑↑↑↑↑↑↑
>to emotional problems, new data is emerging that indicates the mind can...
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
Again, I don't feel that my mind is "flawed" by emotional problems.
To me that seems to be a very "Western" (and I am making a rather
stereotyped remark here) method of thinking. As I have grown up with
parents who have Buddhist values and beliefs, I think that making a
value judgement such as "human minds are flawed because of..." should
be indicated as such...there is no way to prove that sort of "fact."
For all I know or care, the human mind is neither perfect nor flawed;
it just "is," and I don't wish to make sweeping generalities such as
the above. There are many other views of the mind out there, and I
recommend looking into *all* Religious views as well as *all*
Scientific views before even attempting a statement like the above
(which would easily take more than a lifetime).
>...be "fixed" in that regard. To see what I am referring to, read L Ron
↑↑↑↑↑
>Hubbard's book on "Dianetics".
To me this seems to be one of many problems in A.I.: the assumption
that the human mind can be looked at as a machine, and can be analyzed
as having flaws or not, and subsequently be fixed or not. That sort
of thinking in my opinion belongs more in ones Personal Philosophy and
probably should not be used in a "Scientific" (ugghh, another
hard-to-pin-down word) argument, because it is damned hard to prove,
if it is able to be proven at all.
I feel that the mind just "is," and one cannot go around making value
judgements on another's thoughts. Who gives anyone else the right to
say a person's mind is "flawed?" To me that kind of judgement can
only be made by the person "owning" the mind (i.e. who is thinking and
communicating with it!), and others should leave well enough alone.
Now I realize that this brings up arguments in other fields (such as
Psychology), but I feel A.I. should try and move away from these sort
of value judgements.
A comment: why don't A.I. "people" use the human mind as a model, for
better or for worse, and not try to label it as "flawed" or "perfect?"
In the first place, it is like saying that something big (like the
U.S. Government) is "flawed;" this kind of thing can only be proven
under *certain*conditions*, and is unlikely to hold for all possible
"states" that the world can be in. In the second place, making that
kind of judgement would seem to be fruitless given all that we
*do*not* know about the human brain/mind/soul. It seems to me to be
like saying "hmmmm, those damned quarks are fundamentally flawed", or
"neuronal activity is primarily flawed in the lipid bilayer membrane."
I feel that we as humans just do not know diddley about the world
around us, and to say it is flawed is a naive statement. Why not just
look at the human mind/brain as something that has evolved and existed
over time, and therefore may be a good model for A.I. techniques UNDER
CERTAIN CIRCUMSTANCES? A lot less people would be offended...
***FLAME*OFF***
Sorry if the above offends anyone...but the previous remarks offended
me enough to send a followup message around the world. If one is
going to make remarks based on very personal opinions, try to indicate
that they are such, and please remember that not everyone thinks the
way you do.
Of course, pretty much everything I said above is a personal opinion,
and I don't presume that even one other person thinks the same way as
I do (but it would be nice to know that others think similarily ;-).
Disclaimer: the above views are my thoughts only, and do not reflect
the views of my employer, although there is eveidence that my
cockatiels are controlling my thoughts !!! ;-)
-Chris
--
Chris Lishka /lishka@uwslh.uucp
Wisconsin State Lab of Hygiene <-lishka%uwslh.uucp@rsch.wisc.edu
\{seismo, harvard,topaz,...}!uwvax!uwslh!lishka
------------------------------
Date: 30 Sep 87 22:09:09 GMT
From: topaz.rutgers.edu!josh@rutgers.edu (J Storrs Hall)
Subject: Re: Goal of AI: where are we going?
lishka@uwslh.UUCP (Christopher Lishka) writes:
In article <549@csm9a.UUCP> bware@csm9a.UUCP (Bob Ware) writes:
>>We all admit that the human mind is not flawless. Bias decisions...
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
The expression "we all" does not apply to me, at very least. Some of
us (at least myself)like to believe that the human mind should not be
considered to be either flawed or flawless...it only "is."
It seems to me that this simply means that you hold the words "flawed"
and "flawless" to be meaningless. It is as if Bob Ware were saying
that the human mind were not plegrontless. Only I don't see why I
would get so upset if I saw people saying that minds are plegronted
at best, even if I didn't understand what they meant by the term.
I would instead make an effort to comprehend the concepts being used.
>>...can be made due to emotional problems, for instance. ...
Is this statement to be read as "emotional problems can cause bias
decisions, which are flaws in the human mind?" If it does, then I
heartily disagree, because I once again feel that emotional problems
and/or bias decisions are not indicative of flaws in the human
mind...see above for my reasons.
I would say that an emotional *problem* is by definition a flaw.
If you believe that Manson and Hitler and Caligula were not flawed,
but that is just the "way they were", and there is no reason to
prefer Thomas Aquinas over Lyndon LaRouche, then your own reasoning
is distinctly flawed.
To me that seems to be a very "Western" (and I am making a rather
stereotyped remark here) method of thinking. As I have grown up with
parents who have Buddhist values and beliefs, I think that making a
value judgement such as "human minds are flawed because of..." should
be indicated as such...there is no way to prove that sort of "fact."
Can you say "evangelical fundamentalist mysticism"? Your Eastern
values seem to be flavored by a strong Western intellectual
aggressiveness, which seems contradictory. Twice the irony in a
pound of holy calves liver.
There are many other views of the mind out there, and I
recommend looking into *all* Religious views as well as *all*
Scientific views before even attempting a statement like the above
(which would easily take more than a lifetime).
What an easy way to sidestep doing any real thinking. Do you suggest
that we should read all the religious writings having to do with
angels before we attempt to build an airplane? Do you think that one
must be an expert on faith healing and the casting out of demons
before he is allowed to make a statement about this interesting mold
that seems to kill bacteria?
In Western thought it has been realized at long and arduous last that
the appeal to authority is fallacious. Experiment works; the real
world exists; objective standards can be applied. Even to people.
>...be "fixed" in that regard. To see what I am referring to, read L Ron
>Hubbard's book on "Dianetics".
Experiment (the church of scientology) shows that Hubbards ideas in
this regard are hogwash. Hubbard's phenomenon had much more to do
with the charismatic religious leaders of the past, than the rational
enlightenment of the future.
To me this seems to be one of many problems in A.I.: the assumption
that the human mind can be looked at as a machine, and can be analyzed
as having flaws or not, and subsequently be fixed or not.
Surely this is independent of the major thrust of AI, which is to
build a machine that exhibits behaviors which, in a human, would be
called intelligent. It is true that most AI researchers "believe that
the mind is a machine", but it seems that the alternative is to
suggest that human intelligence has a supernatural mechanism.
That sort
of thinking in my opinion belongs more in ones Personal Philosophy and
probably should not be used in a "Scientific" (ugghh, another
hard-to-pin-down word) argument, because it is damned hard to prove,
if it is able to be proven at all.
My personal philosophy *is* scientific, thank you, and it is an
objectively better one than yours is.
I feel that the mind just "is," and one cannot go around making value
judgements on another's thoughts. Who gives anyone else the right to
say a person's mind is "flawed?"
Who gives me the right to say that 2+2=4 when you feel that it should
be 5? If the Wisconsin State Legislature passed a law saying that it
was 5, they would be wrong; if everybody in the world believed it was
5, they would be wrong; if God Himself claimed it was 5, He would be
wrong.
A comment: why don't A.I. "people" use the human mind as a model, for
better or for worse, and not try to label it as "flawed" or "perfect?"
In the first place, it is like saying that something big (like the
U.S. Government) is "flawed;" this kind of thing can only be proven
under *certain*conditions*, and is unlikely to hold for all possible
"states" that the world can be in.
But the U.S. Government IS flawed...
In the second place, making that
kind of judgement would seem to be fruitless given all that we
*do*not* know about the human brain/mind/soul.
Back in the middle ages, we didn't know much about the Black Plague,
but it was obvious that someone who caught it became pretty flawed
pretty fast. Furthermore, this small understanding was considered
sufficient grounds to inflict the social snubs of not associating
with such a person.
It is incredibly arrogant to declare that we must not make any
judgements until we know everything. The whole point of having
a human mind rather than a rutabaga is that you *are* able to make
judgements in the absence of complete information. Brains evolving in
a natural setting have always had to make *life-and-death* decisions
on the spur of the moment with whatever information was available.
Is that large furry creature dangerous? You've never seen a grizzly
bear before. No time to consult the views of all the world's ancient
religions on the subject...
I feel that we as humans just do not know diddley about the world
around us, and to say it is flawed is a naive statement.
To say that it is not flawed is just simply idiotic. If you apply
enough sophistry you may manage to get the conversation to a level
where the original statement is meaningless. For example, there are
(or may be) no "flawed" atoms in a broken radio. But to change the
level of discussion as a rhetorical device is tantamount to lying.
To do it without realizing you are doing it is tantamount to
gibberish.
Sorry if the above offends anyone...
It offends me greatly. The anti-scientific mentality is an emotional
excuse used to avoid thinking clearly. It would be much more honest
to say "I don't want to think, it's too hard work." Can't you see the
contradiction involved in criticizing someone for exercising his
judgement?
The champions of irrationality, mysticism, and superstition have
emotional problems which bias their cognitive processes. Their minds
are flawed.
--JoSH
------------------------------
Date: 30 Sep 87 16:31:00 GMT
From: uxc.cso.uiuc.edu!osiris.cso.uiuc.edu!goldfain@a.cs.uiuc.edu
Subject: Re: Goal of AI: where are we going?
Bob Ware, of Colorado School of Mines, writes :
> ... While almost everyone's mind is flawed due to emotional problems, new
> data is emerging that indicates the mind can be "fixed" in that regard. To
> see what I am referring to, read L Ron Hubbard's book on "Dianetics".
I suppose that if someone feels they have emotional problems and turned to Mr.
Hubbard for help, there is some sense to that. He ought to know about them,
since reports have indicated over the years that he has more than his fair
share of them ... :-)
Alternatively, one could consult someone who actually has credentials in
psychology. "You pays your money and you takes yer choice."
- Mark Goldfain
(ARPA: goldfain@osiris.cso.uiuc.edu)
------------------------------
End of AIList Digest
********************
∂07-Oct-87 2330 LAWS@KL.SRI.Com AIList V5 #227 - Goal of AI
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 7 Oct 87 23:30:16 PDT
Date: Sun 4 Oct 1987 23:41-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #227 - Goal of AI
To: AIList@SRI.COM
AIList Digest Monday, 5 Oct 1987 Volume 5 : Issue 227
Today's Topics:
Philosophy - Goal of AI
----------------------------------------------------------------------
Date: Sun, 4 Oct 87 14:56:42 -0200
From: Jacob Levy <jaakov%wisdom.bitnet@jade.berkeley.edu>
Subject: Another Blooming Endless Argument
Please!
It seems we are getting ready for another deluge, this time under the title
of "Re: Goal of AI: where are we going?". While the subject line certainly
does justify its inclusion in AI-digest, it may easily get out of hand and
deteriorate into personal arguments. There are already first signs of super
heated discussions and personal attacks in V5 #226.
The question I am asking myself when reading these postings is "how much of
this material is AI-related, and how much is purely philosophical/psycholo-
gical or whatever?" I suggest that authors participating in this discussion
would benefit from application of the same criterion - how much is this an
ARTIFICIAL intelligence-related posting? The word ARTIFICIAL is crucial and
determines, for me at least, whether I want to read on.
Another Please!
Remember that this is my personal opinion, I am "a small egg" only, so no
flames or personal attacks. Educate, not eradicate, OK?
P.S. Is the discussion entitled "Nature of Computer Science" really appro-
priate for AIlist?
Rusty Red (AKA Jacob Levy)
BITNET: jaakov@wisdom
ARPA: jaakov%wisdom.bitnet@wiscvm.wisc.edu
CSNET: jaakov%wisdom.bitnet@relay.cs.net
------------------------------
Date: 1 Oct 87 18:36:20 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: Goal of AI: where are we going?
In article <270@uwslh.UUCP>, lishka@uwslh.UUCP (Christopher Lishka) writes:
> ***Warning: FLAME ON***
>
> In article <549@csm9a.UUCP> bware@csm9a.UUCP (Bob Ware) writes:
> >>We all admit that the human mind is not flawless. Bias decisions...
> ↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
>
> The expression "we all" does not apply to me, at very least. Some of
> us (at least myself)like to believe that the human mind should not be
> considered to be either flawed or flawless...it only "is." ....
Some interesting points here.
Point one, the human mind is in fact a phenomenon, and phenomena are
neither flawed nor perfect, they are the stuff that observation is made
of. Score one for Lishka.
Point two, we keep using the human mind as a tool, to solve problems.
As such, it is not merely a phenomenon, but a means to an end, and is
subject to judgments of its utility for that purpose. Now we can say
whether it is perfect or flawed. Obviously, it is not perfect, since
we often make mistakes when we use it. Score one for Ware.
Point three, when we try to make better tools, or tools to supplement
the human mind, all these improvements are created by the human mind.
In fact, the purposes of these tools are created by the human mind.
The human mind is thus the ultimate reasoning tool. Score one for the
human mind.
You might say the same of the human hand. As a phenomenon, it exists.
As a tool, it is imperfect. And it is the ultimate mechanical tool,
since all mechanical tools are directly or indirectly made by it.
It is from these multiple standpoints that we derive the multiple goals
of AI: to study the mind, to supplement the mind, and to serve the mind.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 1 Oct 87 13:22:00 GMT
From: uxc.cso.uiuc.edu!uxe.cso.uiuc.edu!morgan@a.cs.uiuc.edu
Subject: Re: Goal of AI: where are we going?
Maybe you should approach it as a scientist, rather than an engineer. Think
of the physicists: they aren't out to fix the universe, or construct an
imitation; they want to understand it. What AI really ought to be is a
science that studies intelligence, with the goal of understanding it by
rigorous theoretical work, and by empirical study of
systems that appear to have intelligence, whatever that is. The best work
in AI, in my opinion, has this scientific flavor. Then it's up to the
engineers (or society at large) to decide what to do with the knowledge
gained, in terms of constructing practical systems.
------------------------------
Date: 2 Oct 87 15:31:04 GMT
From: bloom-beacon!gatech!udel!montgome@husc6.harvard.edu (Kevin
Montgomery)
Subject: Re: Goal of AI: where are we going?
In article <259@tut.cis.ohio-state.edu>
tanner%tut.cis.ohio-state.edu@osu-eddie.UUCP (Mike Tanner) writes:
>If you want to say that what I'm doing is not AI, fine. I think it is, but if
>you'll give me a better name I'll take it and leave AI to the logicians. It
>is not psychology (my experiments involve building programs and generally
>thinking about computational issues, not torturing college freshmen). And I'm
>not really interested in duplicating the human mind, it's just that the human
>mind is the only intelligence I know.
Welcome to the fascinating world of Cognitive Modelling!
If AI is to be pure logic, more power to it. But the "real world"
usually doesn't let one work only with pure logic- the case of incomplete
information is an example. If you saw me driving towards work, and it
is around 9am, you may conclude that I'm going to work. However, from
a purely logical point of view, my direction of travel has little to do
with my end destination. Whatever. I think modelling's more fun anyway!
(no flames about AI handling the above situation and 'most-probable
scenario' stuff, please)
--
Kevin Montgomery
------------------------------
Date: 1 Oct 87 12:49:39 GMT
From: tanner@tut.cis.ohio-state.edu (Mike Tanner)
Reply-to: tanner%tut.cis.ohio-state.edu@osu-eddie.UUCP (Mike Tanner)
Subject: Re: Goal of AI: where are we going?
In article <270@uwslh.UUCP> lishka@uwslh.UUCP (Christopher Lishka) writes:
>In article <549@csm9a.UUCP> bware@csm9a.UUCP (Bob Ware) writes:
>>We all admit that the human mind is not flawless. Bias decisions...
> ↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
>
> [the underscored bit above indicates a number of faulty assumptions,
> e.g., that it makes sense to talk about "flaws" in the mind.]
>
I liked this reply. Whether the problem is "western" philosophy or not, I'm
not sure. It may be true for the casual AI dabbler. I.e., the average
intelligent person on first thinking or hearing of the topic of AI will often
say things like, "But people make mistakes, do you really want to build
human-like machines?"
Within AI itself this attitude manifests itself as rampant normativism.
Somebody adopts a model of so-called correct reasoning, e.g., Bayesian
decision theory, logic, etc., and then assumes that the abundant empirical
evidence that people are unable to reason this way shows human reasoning to be
flawed. These people want to build "correct" reasoning machines.
I say, OK, go ahead. But that's not what I want to do. I want to understand
thinking, intelligent information processing, problem-solving, etc. And I
think the empirical evidence is trying to tell us something important. I am
not sure just what. It seems clear that thinking is not logical (which is not
to say "flawed" or "incorrect", merely "not logical"). An interesting
question is, "why not?" People are able to use language, solve problems -- to
think -- but is that in spite of illogic or because of it or neither? I don't
think we're going to understand intelligence by adopting an a priori correct
model and trying to build machines that work that way (except by negative
results).
If you want to say that what I'm doing is not AI, fine. I think it is, but if
you'll give me a better name I'll take it and leave AI to the logicians. It
is not psychology (my experiments involve building programs and generally
thinking about computational issues, not torturing college freshmen). And I'm
not really interested in duplicating the human mind, it's just that the human
mind is the only intelligence I know.
-- mike tanner
Dept. of Computer and Info. Science tanner@ohio-state.arpa
Ohio State University ...cbosgd!osu-eddie!tanner
2036 Neil Ave Mall
Columbus, OH 43210
------------------------------
Date: 3 Oct 87 06:14:38 GMT
From: vax1!czhj@cu-arpa.cs.cornell.edu (Ted Inoue)
Subject: Re: Goal of AI: where are we going? (Where should we go...)
In article <46400008@uxe.cso.uiuc.edu> morgan@uxe.cso.uiuc.edu writes:
>
>Maybe you should approach it as a scientist, rather than an engineer. Think
>...
>What AI really ought to be is a
>science that studies intelligence, with the goal of understanding it by
>rigorous theoretical work, and by empirical study of
>systems that appear to have intelligence, whatever that is. The best work
>in AI, in my opinion, has this scientific flavor. Then it's up to the
>engineers (or society at large) to decide what to do with the knowledge
>gained, in terms of constructing practical systems.
I wholeheartedly support this idea. I'd go even further however, and say that
most "AI" research is a huge waste of time. I liken it to using trial and
error methods like those used by Edison which led him to try thousands of
possibilities before hitting one that made a good lightbulb. With AI, the
problem is infinitely more complicated, and the chance of finding a solution
by blind experimentation is nil.
On the other hand, if we take an educated approach to the problem, and study
'intelligent' systems, we have a much greater chance of solving the mysteries
of the mind.
Some of you may remember my postings from last year where I expounded on the
virtues of cognitive psychology. After investigating research in this field
in more detail, I came up very disillusioned. Here is a field of study in
which the soul purpose is to scientifically discover the nature of thought.
Even with some very bright people working on these problems, I found that the
research left me cold. Paper after paper describe isolated phenomena, then go
on to present some absurdly narrow minded theory of how such phenomena could
occur.
I've reached the conclusion that we cannot study the mind in isolated pieces
which we try to put together to form a whole. But rather we have to study
the interactions between the pieces in order to learn about the pieces
themselves. For example, take vision research. Many papers have been written
about edge detection algorithms, possible geometries, and similarly
reductionist algorithms for making sense of scenes. I assert that the
interplay between the senses and the experiential memory is huge. Further,
because of these interactions, no simple approach will ever work well. In
fact, what we need is to study the entire set of processes involved in seeing
before we can determine how we perceive objects in space.
This is but a single example of the complexity of studying such aspects of the
mind. I found that virtually every aspect of cognition has such problems.
That is, no aspect is isolated!
Because of this immensely complex set of interactions, I believe that the
connectionist theories are heading in the right direction. However, these
theories are somewhat too reductionistic for my tastes as well. I want to
understand how the mind works at a high level (if possible). The actual
implementation is the easy part. The understanding is the hard part.
---Ted Inoue
------------------------------
Date: 3 Oct 87 23:47:07 GMT
From: lishka@uwslh.UUCP (Christopher Lishka)
Reply-to: lishka@uwslh.UUCP (Christopher Lishka)
Subject: Re: Goal of AI: where are we going?
In article <46400008@uxe.cso.uiuc.edu> morgan@uxe.cso.uiuc.edu writes:
>
>Maybe you should approach it as a scientist, rather than an engineer. Think
>of the physicists: they aren't out to fix the universe, or construct an
>imitation; they want to understand it.
I think this is a good point. I have always thought that Science was
a method used to predict natural events with some accuracy (as opposed
to guessing). Whether this is understanding, well I guess that
depends on one's definition. I like this view because it (to me at
least) parallels the attempts by nearly all (if not all) religions to
do the same thing, and possibly provide some form of meaning to this
strange world we live in. It also opens the possibility of sharing
views between scientists and other people explaining the world they
see with their own methods.
>What AI really ought to be is a
>science that studies intelligence, with the goal of understanding it by
>rigorous theoretical work, and by empirical study of
>systems that appear to have intelligence, whatever that is. The best work
>in AI, in my opinion, has this scientific flavor. Then it's up to the
>engineers (or society at large) to decide what to do with the knowledge
>gained, in terms of constructing practical systems.
I like this view also, and feel that A.I. might go a little further in
studying other areas in conjunction with the human mind. Maybe this
isn't pure A.I., but I'm not sure what pure A.I. is. One interesting
note is that maybe the people who are implementing various Expert
Systems (which grew out of A.I. research) for real-world applications
are the "engineers" of which morgan@uxe speaks of. And more power to
both the "scientists" and "engineers" then, and those in the gray area
in between. It's good to be able to work together like this, and not
have the "scientists" only come up with research that cannot be
applied.
Disclaimer: I am sitting here typing this because my girfriends cat is
holding a gun at my head, and am in no way responsible for the content
;-)
[If anyone really wants to flame me, please mail me; if you really
think there is some benefit in posting the flame, go ahead. I reply
to all flames, but if my reply doesn't get to you, it is because I am
not able to find a reliable mail path (which is too damned often!)]
-Chris
--
Chris Lishka /lishka@uwslh.uucp
Wisconsin State Lab of Hygiene <-lishka%uwslh.uucp@rsch.wisc.edu
\{seismo, harvard,topaz,...}!uwvax!uwslh!lishka
------------------------------
Date: 1 Oct 87 09:11:37 GMT
From: mcvax!enea!kuling!waldau@uunet.uu.net (Mattias Waldau)
Subject: Re: Goal of AI: where are we going?
In article <178@usl> khl@usl.usl.edu.UUCP (Calvin Kee-Hong Leung) writes:
>Provided that we have the necessary technology to build robots
>that are highly intelligent; they are efficient and reliable and
>they do not possess any "bad" characteristic that man has. Then
>what will be the roles man plays in the society where his intel-
>ligence can be viewed as comparatively "lower form"?
>
One of the short stories in Asimov's "I, robot" is about the problem
mentioned in the previous paragraph. It is about a robot and two humans
on a space station near our own sun. I can not tell more, otherwise I
spoil your fun. It is very good!
------------------------------
Date: Sun, 4 Oct 87 20:54:01 -0200
From: Eyal mozes <eyal%wisdom.bitnet@jade.berkeley.edu>
Subject: Re: Goal of AI: Where are we Going?
> I believe that those "bad" characteristics of human are necessary
> evils to intelligence. For example, although we still don't understand
> the function of emotion in human mind, a psychologist Toda saids that
> it is a device for servival. When an urgent danger is approaching, you
> don't have much time to think. You must PANIC! Emotion is a meta-
> inference device to control your inference mode (mainly of recources).
>
> If we ever make a really intelligent machine, I bet the machine
> also has the "bad" characteristics. In summary, we have to study
> why human has those characteristics to understand the mechanism of
> intelligence.
I think what you mean by "the bad characteristics" is, simply, free
will. Free will includes the ability to fail to think about some
things, and even to actively evade thinking about them; this is the
source of biased decisions and of all other "flaws" of human thought.
Emotions, by themselves, are certainly not a problem; on the contrary,
they're a crucial function of the human mind, and their role is not
limited to emergencies. Emotions are the result of subconscious
evaluations, caused by identifications and value-judgments made
consciously in the past and then automatized; their role is not "to
control your inference mode", but to inform you of your subconscious
conclusions. Emotional problems are the result of the automatization of
wrong identifications and evaluations, which may have been reached
either because of insufficient information or because of volitional
failure to think.
A theory of emotions and of free will, explaining their role in the
human mind, was developed by Ayn Rand, and the theory of free will was
more recently expanded by David Kelley.
Basically, the survival value of free will, and the reason why the
process of evolution had to create it, is man's ability to deal with a
wide range of abstractions. A man can form concepts, gain abstract
knowledge, and plan actions on a scale that is in principle unlimited.
He needs some control on the amount of time and effort he will spend on
each area, concept or action. But because his range his unlimited, this
can't be controlled by built-in rules such as "always spend 1 hour
thinking about computers, 2 hours thinking about physics" etc.; man has
to be free to control it in each case by his own decision. And this
necessarily implies also freedom to fail to think and to evade.
It seems, therefore, that free will is inherent in intelligence. If we
ever manage to build an intelligent robot, we would have to either
narrowly limit the range of thoughts and actions possible to it (in
which case we could create built-in rules for controlling the amount of
time it spends on each area), or give it free will (which will clearly
require some great research breakthroughs, probably in hardware as well
as software); and in the later case, it will also have "the bad
characteristics" of human beings.
Eyal Mozes
BITNET: eyal@wisdom
CSNET and ARPA: eyal%wisdom.bitnet@wiscvm.wisc.edu
UUCP: ...!ihnp4!talcott!WISDOM!eyal
------------------------------
End of AIList Digest
********************
∂08-Oct-87 0216 LAWS@KL.SRI.Com AIList V5 #228 - Philosophy, Native American Languages
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 8 Oct 87 02:16:15 PDT
Date: Sun 4 Oct 1987 23:46-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #228 - Philosophy, Native American Languages
To: AIList@SRI.COM
AIList Digest Monday, 5 Oct 1987 Volume 5 : Issue 228
Today's Topics:
Queries - Connection Graphs & IEEE Neural Net Conference &
Expert Systems Company Advice & TI Explorer/Common Lisp/PCs &
Protocols,
Graphics - Summary Pending,
Philosophy - Flaws,
Linguistics - Natural Kinds and Indians
----------------------------------------------------------------------
Date: 2 Oct 87 11:53:46 GMT
From: mcvax!enea!kuling!nilsh@uunet.uu.net
Subject: Connection Graphs
I've recently heard that there has been quite a lot of
work done on Connection Graphs in West Germany the past
few years. I would like to get in touch with people who
has been involved in this, especially from Munchen,
Kaiserslauten and Karlsruhe. My main interest for the
moment is results concerning completeness for the Connec-
tion Graph Proof Procedure of Kowalski. Please contant
me on net-mail or "snail-mail".
Net-Mail: nilsh@kuling.UUCP
Snail-Mail: Nils Hagner
Dept. of Computing Science
Uppsala University
P.O. Box 520
751 20 Uppsala
SWEDEN
------------------------------
Date: 4 Oct 87 02:54:50 GMT
From: munnari!latcs1.oz.au!suter@uunet.UU.NET (David Suter)
Subject: IEEE conf. (Boulder)
re: "Neural Info. Proc. Systems - Natural and Synthetic" conf.
Boulder, Colorado - Nov. 8-12 1987.
I would like to contact the registration people quickly. My snail mail
to some of the organisers has either been mis-directed or lost. Thus
if anyone can supply a direct conference telephone number, or an e-mail
address for registration - I would be grateful.
---------------------
David Suter ISD: +61 3 479-2596
Department of Computer Science, STD: (03) 479-2596
La Trobe University, ACSnet: suter@latcs1.oz
Bundoora, CSnet: suter@latcs1.oz
Victoria, 3083, ARPA: suter%latcs1.oz@uunet.uu.net
Australia UUCP: ...!uunet!munnari!latcs1.oz!suter
TELEX: AA33143
FAX: 03 4785814
------------------------------
Date: 30 Sep 87 17:11:06 GMT
From: decvax!dartvax!waltervj@ucbvax.Berkeley.EDU (walter jeffries)
Subject: Expert Systems Company Financing...
I am in the process of starting a company to do expert systems developement
in the field of psychiatry. Principles include two top domain experts in
this field, an expert in data anlysis, and an MBA canidate with training in
marketing in the computer field. I am not the business end of things but
would appreciate any comments/experiences that people may have with getting
capital (sources, things to be careful of, etc.). [...]
Many thanx,
-Waltervj@dartvax
------------------------------
Date: Fri, 02 Oct 87 19:44:19 GMT
From: A385%EMDUCM11.BITNET@WISCVM.WISC.EDU
Subject: TI Explorer, Common Lisp & PC's
Date: 2 October 1987, 19:42:38 GMT
From: A385 at EMDUCM11
To: AILIST-REQUEST at SRI
Hello AI community from Spain!!
We are a group of absolute beginners using the TI EXPLORER machine.
Our problem is that we only have two 'explorers' for a lot of people and we'd
like to profite our PC's (AT's) in order to get experience using Common Lisp,
but two question arise:
1) Which is the best Common Lisp implementation (with flavors, packages....)
running on AT's??. Is it Golden Common Lisp?
2) Does anyone has any experience connecting PC's and TI Explorers to
transfer files? Is it posible ?
Thank you very much in advance for any help or suggestion.
Yours
Javier Lopez <A385 at EMDUCM11>
------------------------------
Date: Fri, 2 Oct 87 08:05:37 edt
From: steve@hubcap.clemson.edu ("Steve" Stevenson)
Subject: Query on protocols.
I am interested in determining what general principles apply to defining
any type (human,machine, etc) of communications protocol. As an example,
what would one have to do to establish that two protocols are the "same".
[i.e., message-passing vs shared memory/wait/signal].
Steve (really "D. E.") Stevenson steve@hubcap.clemson.edu
Department of Computer Science, (803)656-5880.mabell
Clemson University, Clemson, SC 29634-1906
------------------------------
Date: 30 Sep 87 21:59:17 GMT
From: mcvax!ukc!mupsy!mucs!arnold@uunet.uu.net (Toby Howard)
Subject: Thanks for AI/Graphics...
Some time ago I posted a plea asking for any refs people could give me
on connecting AI and Graphics, and I promised to summarise. This note is to
say I'm really grateful for all the help I've received, and I *really will*
summarise, and thank people individually. Just now I'm mega-busy---but
I haven't forgotten!
toby
[This is a shared account. Please ignore the From: field, and reply to the
following address. Thanks]
Toby Howard Computer Graphics Unit, Manchester University, UK.
janet: thoward@uk.ac.man.cs.cgu
internet: thoward%cgu.cs.man.ac.uk@nss.cs.ucl.ac.uk
------------------------------
Date: 02 Oct 87 20:26:00 EDT
From: Walter Roberson <WCSWR%CARLETON.BITNET@WISCVM.WISC.EDU>
Subject: flaws
In AILIST of October 2nd,
Christopher Lishka (uwslh!lishka@speedy.wisc.edu), and
J Storrs Hall (topaz.rutgers.edu!josh@rutgers.edu)
discuss whether human minds are inherently flawed. Chris proposes that
human minds just *are*, neither flawed nor unflawed; JoSh disagrees
strongly, and claims Chris's position to not be scientifically based.
Leaving aside for the moment the question of whether mathematics is a
science (at last notice, AILIST list hadn't resolved that one), I
believe that I can offer a mathematical basis for Chris's position.
Consider a set (possibly infinite) of objects, U, and at least two
single-place predicates over that set, P, and Q. Add n-ary predicates
and distinguished constants, if you like. Consider the following
first-order sentance over this language: "For all x in U, Px => Qx". Is
this sentance true? It depends on the relations P and Q. If Qx is
"false" for all x in U, and at least one Px is "true", then the sentance
is false -- for that P and Q. If Px is "false" for all x in U, then the
sentance is true -- again, for that P and Q. Thus, the truth of the
sentance depends upon the structure
(U, set(P, Q, etc), set(constants), set(n-ary functions))
in which it is evaluated. Now, as there is at least one such structure
in which this sentance is false, the sentance is NOT "logically implied"
by the language of its formulation. And, as there is also at least one
such structure in which the sentance is true, one can only talk about
the validity of the sentance in terms of its value in a particular
structure. Loosely speaking, the validity of the sentance varies with
the interpretation one gives to the relationships.
Consider now the above sentance, ("for all x in U, Px => Qx") with the
human intepretation that it denotes "all minds are flawed" -- that is,
Px being interpreted as the predicate "x is a human mind", and Qx being
intepreted as the predicate "x is flawed". Assigning the sentance a
human interpretation makes it no more true or false than before: the
difference is only in the emotional zing of the interpretation.
Assigning a validity to the sentance based on a religious set of values
corresponds to chosing a structure and evaluating the sentance within
that structure. The sentance may be valid or invalid within that
structure, but, in isolation, the sentance will still be neither true
nor false. Chris's position is that "human minds are flawed" is only
true within certain belief sets: that it is not a true statement because
it is not a logically implied statement. JoSH's position is that the
interpretations of the words "human minds", "are" and "flawed", are such
that the statement is implicitly true: that semantically, the statement
is automatically self-restricting to the class of structures in which it
is true.
Certainly the conventional wisdom is that "nobody's perfect". That has a
certain intuitive "rightness" to it which is very compelling. And if
nobody is perfect, then everyone is flawed, right? But what someone
saying, "Nobody's perfect" really means is, "There isn't anyone that
measures up to my standards of perfection". That, however, is more a
reflection of the utterer's standards of perfection than upon the
intrinsic qualities of any other given person. A lot of people have done
things which haven't pleased me, but that's a matter of my expectations,
rather than a question of whether they were "flawed" or not.
---
In part of his response, JoSH disapproves of Chris's position, based
upon operational grounds. Indeed, we do not -need- to study the
aerodynamics of angels in order to build an airplane. I don't believe,
though, that Chris implied that we needed to do so: rather, he favours a
position closer to the doctrine of necessity; that if X isn't necessary
in order to do Y, and Y is your goal, then don't do X. In this case, X
is "assign a definite truth value to 'human minds are flawed'", and Y is
"computationally model a human intelligence". Chris believes X to be
unnecessary (and impossible in finite time anyways). JoSH believes it to
be possible; I haven't been watching closely enough to determine whether
he believes it to be necessary.
---
Is 2+2=4 ? In the ring Z4, No: 2+2=0 instead. And since '=' is merely
the symbol for a binary operation, traditionally a certain well-known
predicate, then sometimes 2+2=5 afterall. Try, for example, reading '='
as denoting the binary predicate traditionally represented as '<'.
Is the broken radio flawed? Well, if it was hit by lightning while
playing "satanic rock music", and melted down into a representation of
"Jesus", I rather doubt people would call it "flawed" when they couldn't
get music out of it. Not much use in trying to decide whether an object
is "flawed" or "bad" or "evil" or whatever -- if it doesn't do what you
want it to, perhaps it'll make a dandy paperweight instead. Or bonfire
fuel, if you've found it particularily frustrating.
Is a dead person "flawed" because they are no longer living? I'm told
that death is a very natural process -- happens to everyone, they say.
But its not going to happen to me -- at least not during my lifetime!
(Thanks, Raymond!)
Walter Roberson <WCSWR%CARLETON.BITNET@WISCVM.WISC.EDU>
---
Reference: "A Mathematical Introduction to Logic", Herbert B. Enderton,
1972, Academic Press
------------------------------
Date: Sat, 3 Oct 87 10:30:14 EDT
From: Bruce Nevin <bnevin@cch.bbn.com>
Subject: natural kinds and Indians
> From: cugini@icst-ecf.arpa
> I believe there have been anthropological studies, for instance,
> showing that Indian classifications of animals and plants line
> up reasonably well with the conventional Western taxonomy.
I saw this go by in AIList, and here it comes again in NL-KR, and I just
can't let you get away with it, John.
Glib references to `Indian classifications of animals and plants' remind
one of titles in the 17th century like `The Indian Language Reduced to
Grammar'. `Indian classifications', indeed!
Which of the hundreds of Amerindian languages? Which of the half-dozen
or so linguistic families in North America alone? Linguistic families
in the Americas are as diverse from each other as the Indo-European
family is from the Sino-Tibetan family, and as Finno-Ugaritic is from
both: there is no demonstrated genetic relationship whatsoever.
If the claim is across all Amerindian languages, it seems preposterous
on the face of it.
In some languages, terms for animals and plants are composite, derived
from or related to predicative compounds of the type `water-strider'.
In a polysynthetic language, some of the elements underlying such a
compound might be classificatory morphemes that imply a rather different
taxonomy. Certain of these we might gloss e.g. `long, slender object'
or `spherical object' or `flexible object'. Examining our glosses for
words incorporating these elements as affixes or infixes, however, we
always see abundant grounds for doubting that we have captured the
Indian generalization in our English net. What do `both arms', `lips',
`encircle', `sew' have in common? `Soft opposed forces' is the gloss
given for Pomo bi-. How about `fire, heat, cold, light, emotions,
mind'? Pomo mu- is glossed `nonlong object through the air', and the
above are glosses for its contribution in just some of its occurrences.
In other languages, such terms are (synchronically at least) primitive,
of the type `cat'. What do `horse', `dog', and `slave' have in common?
All are translations of caH:o'm in Achumawi, which appears to refer to a
social role rather than anything like genus or species. Indeed, all
such terms in Achumawi seem to imply place in a kind of `social'
structure involving all beings, a mental system orthogonal to our
Realist presumptions about `objective' `external' reality. Theories of
animism begin to get at it, perhaps, and here you might begin to get at
some cultural/religious commonality among peoples in the Americas.
In Wappo and in Yana, the word for 'dog' and `horse' is again the same,
but is the Spanish loanword chucho (cu:cu' in Wappo, su:su [pronounced
something like shoo-shoo] in Yana). Why not the Spanish word for horse,
cavallo? I don't have any information on the Wappo and Yana words for
`slave', but suspect strongly that the same `taxonomy' has a role here.
Compare Wappo ka'wa:yu?+ne'w `horse-yellowjacket', perhaps on the
analogy of English `horsefly', where ?ne'w is `yellowjacket'.
Achumawi, Pomo, and Yana are all Northern Hokan languages, b.t.w.,
and are (or were) in fairly close proximity in Northern California,
whereas Wappo is an unrelated Yukian language a bit further south,
between the Pomo languages/dialects and San Francisco Bay.
The Achumawi word for `dog' optionally has a diminutive suffix
(caHo'mak!a, `little slave/captive/subordinate one'), and there is
another word ?a?la'?mugi? that means `dog' but not `horse' or `slave'.
Before you get too excited, let me tell you that this appears to be a
descriptive term for a dog whose ears hang down; similarly, Yana
cahtumal?gu `dog', lit. `hang-ears'. In an Achumawi Prometheus myth,
such a dog brings back fire concealed in his ear. A cognate term
`dog-ear' is used for a basketry design, so it is well embedded in the
culture. Utterly no basis for a taxonomy associating dogs with e.g.
foxes, wolves, or coyotes, or them with one another.
References, please. What were the claims, exactly? What was the
claimed basis for them? Was the investigator comparing native
taxonomies or translations thereof into English? With virtual
certainty, the latter. Is your reference to original sources in the
anthropological literature or to secondary or tertiary sources there, or
to n-ary sources in the philosophical literature?
This sort of philosophy strikes me as systematized ethnocentrism. Go
ahead and claim that the world must be thus and so because every
reasonable person you know sees it that way. But don't go dragging the
Indians into it. God knows, they've suffered indignities enough!
Bruce Nevin
bn@cch.bbn.com
(This is my own personal communication, and in no way expresses or
implies anything about the opinions of my employer, its clients, etc.)
------------------------------
End of AIList Digest
********************
∂08-Oct-87 0443 LAWS@KL.SRI.Com AIList V5 #229 - Seminar, Conferences
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 8 Oct 87 04:43:03 PDT
Date: Mon 5 Oct 1987 00:00-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #229 - Seminar, Conferences
To: AIList@SRI.COM
AIList Digest Monday, 5 Oct 1987 Volume 5 : Issue 229
Today's Topics:
Seminar - Constraint-Posting Planning (BBN)
Conferences - Fall Joint Computer Conference 87 &
3rd Applications of AI in Engineering &
ASME Computers in Engineering
----------------------------------------------------------------------
Date: Wed 30 Sep 87 14:11:26-EDT
From: Marc Vilain <MVILAIN@G.BBN.COM>
Subject: Seminar - Constraint-Posting Planning (BBN)
BBN Science Development Program
AI/Education Seminar Series
Dominance and Subsumption in Constraint-Posting Planning
Michael Wellman
MIT Artificial Intelligence Lab
(MPW@ZERMATT.LCS.MIT.EDU)
BBN Laboratories Inc.
10 Moulton Street
Large Conference Room, 2nd Floor
10:30 a.m., Friday, October 2nd 1987
Abstract: By integrating a dominance prover into the plan search
process, the traditional constraint-posting planning paradigm can be
generalized to permit partially satisfiable goals. In this approach,
the view of planning as theorem proving is retained, although the
emphasis is on deriving facts about the admissibility of classes of
candidate plans. Plan classes are generated by posting constraints at
various levels of abstraction, then classified within a plan
specialization graph that manages inheritance of properties and
dominance characteristics. Efficient computation of plan class
subsumption is essential for effective use of dominance results.
I illustrate this planning framework with examples from SUDO-Planner, an
application to medical therapy currently under implementation. Medical
therapy has been an unattractive domain for AI planning techniques
because of the omnipresence of uncertainty and partially satisfiable
objectives. SUDO-Planner's knowledge base contains descriptions of
therapy actions at multiple levels of abstraction, with effects
represented by qualitative probabilistic influences. The nature of the
dominance results derivable by SUDO-Planner suggest that many
"metaplanning" rules may be recast as dominance conditions at
sufficiently high levels of abstraction.
------------------------------
Date: Fri, 2 Oct 1987 15:28 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Conference - Fall Joint Computer Conference 87
List of AI related Papers in Fall Joint Computer Conference 87
October 25-29, 1987, Infomart
Tuesday, October 27 10AM - Noon
Expresss: Rapid Prototyping and Product Development Via Integrated,
Knowledge-Based, Executable Specifications
P. Topping, J. McInroy, Lockheed;
W. M. Lively, S. Sheppard, Texas A&M University
Tuesday October 27 2-3:30
Deriving Contingencies Among Diagnostic Tests with Prolog by Code
Examination
R. Denney, Schlumberger Well Systems
A concuncurrent Multi-Paradigm List Processor TAO/ELis
I. Takeuchi, H. G. Okuno, N. Ohsato, M. Kamino, K. Yamazaki, NT&T, Japan
Wednesday, October 28 10AM-Noon
An Approach to Integrating Expert System Components into Production Sotware
W. B. Frakes, C. J. Fox AT&T Bell Labs
A Variation of Conceptual Graphs: An Object Oriented Approach
T. R. Hines, E. A. Unger, Kansas State University
Software Reusability and Knowledge Engineering
M. M. Tanik, D. Y. Y. Yun, W. Yin, Southern Methodist University
T. J. Lee, A. G. Dale, the University of Texas at Austin
A Parallel Algorithm fo r Execution of Production Systems on HMESH
S. B. Tien, C. S. Raghavendra, University of Southern California
Wednesday, October 28 2-3:30 PM
The Intelligent Machines Project in China
Chengwei Wong, Beijing Institute of System Engineering, China
DFM: The Dataflow Machine for Highly Parallel Symbol Manipulation
K. Amamiya, M. Takesue, R. Gasegawa, H. Mikama, NT&T, Japan
Wednesday, October 28 3:45-5:15 PM
New Methods fo rReal-Time and Image Recognition
O. K. Ersoy, D. Y. Kim, Purdue University
Dynamic Elastic Interpretation for 3D Objects Reconstruction from Serial
X-Sectional Images
W. C. Lin, C. C. Liang, Northwestern University;
C. T. Chen, University of Chicago
Representation and Recognition of Objects From Depth Maps
J. K. Aggarwal, B. C. Vemuri, The University of Texas at Austin
Thursday, October 29 10:30AM - NOON
Frame Synthesis and Inheritance Systems
M. Kim, A. S. Maida, Pennsylvania State University
A Knowledge-Based Message Generation System for the Nonverbal Profoundly
Motor Disabled
B. K. Sy, J. R. Deller, Jr. Northeastern University
A Uniform Architecture for Rule-Based Meta Reasoning and Representation
A. S. Maida, Pennsylvania State University
Thursday, October 29 2-3:30 PM
A Knowledge-Based Approach to Multiple Query Processing in Distributed
Database Systems
T. J. Teorey, J. T. Park, The University of Michigan
Parallel Execution of Logic Programs in the Framework of OR-Forest
Y. G. Tzu, Changsha Institute of Technology, China
A Dietary Recommendation Expert System Using OPS5
C. Kao, C. J. Hwang, Purdue University
A Conceptual Model for Case Grammar Analysis
K. Efe, P. A. Ng, New Jersey Institute of Technology
An Analysis of the Knowledge Used for a Structured Selection Problem
P. K. Fin,k, F. A. Iddings, M. A. Overby, Southwest Research Institute
An Architecture for Adaptive Learningin Rule-Based Diagnostic Expert Systems
D. C. St. Clair, W. E. Bond, B. B. Flachsbart, A. G. Vigland, McDonnell
Aircraft Corporation
Wednesday, October 28 6-7:30PM
The Development of Expert Systems - Some Pragmatic Issues
Ms. Lorraine M. Duvall, Duvall Computer Technologies, Panel Chair
N. J. Martin, SoftPert Systems Inc.; C. J. Green
Structured Systems and Software Inc.
Thursday, October 29 3:45-5:15PM
A Knowledge-Based Aproach to Computer-Aided Design of Structures
H. Adeli, K. V. Balasubramanyam, Ohio State University
2 Piece Jig-Saw Puzzle Robot Assembly with Vision, Position and Force Feedback
G. C. Burdea, New York
Proteus-1: A General Accelerator for CAD
S. P. Smith, B. Wood, J. Little, P. Hunter, MCC
(Also Panel Discussion on AI and Software Engineering with Dr. David Yun,
Southernm Methodist University as Panel Chair and R. Balzer, Information
Sciences Institute, C. V. Ramamorthy, University of California at Berkeley,
W. W. Royce, Lockheed Software Technology Center, M. M. Tanik, Southern
Methodist University, W. Bledsoe, MCC, Roger Bates, Texas Instruments)
------------------------------
Date: Tue, 29 Sep 87 23:06:01 EDT
From: sriram@ATHENA.MIT.EDU
Subject: Conference - 3rd Applications of AI in Engineering
FIRST CALL FOR PAPERS
THIRD INTERNATIONAL CONFERENCE ON
APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN
ENGINEERING
AUGUST 8TH-12TH, 1988
STANFORD, CALIFORNIA, USA
INTRODUCTION
The Third International Conference on AI in Engineering will be held
during the second week of August, 1988 in Stanford, California. The
first and second international conferences stimulated significant
presentations on both the tools and techniques required for the
successful use of AI in engineering and many new applications. The
organising committee members anticipate that the third conference will
be even more successful and encourage papers which describe recent
work to be submitted.
OBJECTIVES
The purpose of this conference is to provide an international forum
for the presentation of work on the state-of-the-art in the
applications of artificial intelligence to engineering problems. It
also aims to encourage and enhance the development of this most
important area of research.
CONFERENCE THEMES
The following application areas and topics are suggested and other
related areas will be considered:
--------------------------------------------------------------
| |
| Application Areas Topics |
| Design Representation |
| Diagnosis/Evaluation Problem Solving |
| Process Control and Planning Constraint Reasoning |
| Robotics Learning |
| Tutoring Qualitative Models |
| Sensing and Interpretation Tools |
| User Interfaces |
| |
--------------------------------------------------------------
INVITED SPEAKERS
Keynote: Dr Raj Reddy, Director of the Robotics Institute, Carnegie
Mellon University and President, AAAI.
Invited Speakers: Dr. Rick Hayes-Roth, Chief Scientist, Teknowledge
Others will be announced shortly.
SUBMISSION REQUIREMENTS
Authors are invited to submit full papers, preferably not exceeding
8,000 words.Each paper should include an abstract and have sufficient
details, such as the type of knowledge representation, problem solving
strategies, and the implementation language used, to permit evaluation
by a committee consisting of renowned experts in the field. Each
paper should be accompanied by the following details on the first
page: author's name, address, affiliation, the name and address,
e-mail, telex and fax of the person to whom all correspondence should
be sent, and an indication of the application area and the topic(s).
To allow for blind refereeing, the second page should commence with
the paper title and abstract and not include any identifying material
from the first page. Final instructions on typing format will be
forwarded to authors of each accepted paper after refereeing.
Four copies of the paper should be submitted to:
Professor John Gero
Technical Chair, AIE88
Department of Architectural Science
The University of Sydney
NSW 2006 Australia
Tel: 61-2-692-2328 (International)
Tlx AA26169
Fax: 61-2-692-3031
Net Address:
ARPA: john%archsci.su.oz@uunet.uu.net
UUCP: uunet!munnari!archsci.su.oz!john
CSNet: john@archsci.su.oz
In addition, one copy of the paper should be sent to:
Dr R. Adey
Computational Mechanics Institute
25 Bridge Street
Billerica, MA 01821
Tel. No: 617-667-7582
All papers should be submitted before January 15, 1988.
Notification of acceptance will be sent before March 15, 1988.
Final copies of the papers are due on or before April 8, 1988.
REVIEW CRITERIA
All papers will be reviewed by at least two experts in the area.
Acceptance of the paper will be based on the quality of the work and
its presentation in the paper.
ORGANIZING COMMITTEE
General Chair Dr. R. Adey, Computational Mechanics Institute, USA
Technical Chair Prof. J. Gero, University of Sydney, Australia
ADVISORY BOARD
Consists of renowned researchers in the field.
------------------------------
Date: Tue, 29 Sep 87 10:28:07 EDT
From: decvax!cvbnet!cheetah!rverrill@decwrl.dec.com (Ralph Verrilli)
Subject: Conference - ASME Computers in Engineering
CALL FOR PAPERS
1988 ASME INTERNATIONAL COMPUTERS IN ENGINEERING
CONFERENCE AND EXHIBITION
SAN FRANCISCO HILTON
SAN FRANCISCO, CALIFORNIA
July 31 - August 3, 1988
REAL WORLD APPLICATIONS OF EXPERT SYSTEMS
AND ARTIFICIAL INTELLIGENCE
The theme for the 1988 ASME International Computers in Engineering
Conference will focus on the emerging applications of expert systems
and artificial intelligence.
This conference and exhibition provides a forum for engineers,
managers, researchers, vendors, and users to discuss relevant
issues, and to present ideas on computer technology and its impact
on the engineering workplace. Over 80 papers and panel sessions are
planned covering a broad spectrum of technical computing and
computers in the engineering community. The topics covered will
encompass: computer aided design and manufacturing, computer
simulation, robotics, interactive graphics, finite element
techniques, microprocessors, computers in educations, expert
systems, and artificial intelligence.
Papers are solicited in all areas related to the application,
development, research, and education with computers in mechanical
engineering. Contributions in the form of full-length papers or
extended abstracts are solicited. Accepted papers will be published
in the bound Conference Proceedings. Full length papers of special
note will be reviewed after the conference for publication in the
Society's magazine "Computers in Mechanical Engineering (CIME)".
The annual event is sponsored by the Computers in Engineering
Division of the American Society of Mechanical Engineers (ASME).
San Francisco is the site of this years conference.
DEADLINES :
Submission of three copies of draft contributions
(paper or extended abstract) November 30, 1987
Notification of acceptance to authors February 15, 1988
Submission of author-prepared mats April 1, 1988
For the following technical areas please send papers to the
respective program chairmen :
{
Computer Aided Manufacturing, Computer Simulation, Turnkey CAD/CAM,
Integration of CAD and CAM, Computer Aided Testing, Computer Aided
Design, Interactive Graphics :
Dr. Donald Riley
Dept. of Mechanical Engineering
University of Minnesota
111 Church Street
Minneapolis, MN 55455
612-625-0591/1809 }
{
Artificial Intelligence, Knowledge Based Systems :
Mr. M.F. Kinoglu
AI and Expert Systems Group
Control Data Corporation
1450 Energy Park Drive
Saint Paul, MN 55108
612-642-3817 }
{
Microprocessors, Robotics, Special Purpose Computers, Man-Machine
Interfaces :
Mr. David W. Bennett
Battelle Pacific Northwest Labs
P.O. Box 999
Richland, WA 99352
509-375-2159 }
{
Robotics in Education, Teaching CAD in Higher Education, University
- Industry Collaboration, Microcomputers in the Classroom,
Computer-Aided Learning :
Dr. Gary Kinzel
Ohio State University
Dept. of Mechanical Engineering
206 West 18th Street
Columbus, Ohio 43210
614-292-6884 }
{
Finite Element Techniques, Software Standards, Computational
Geometry :
Dr. Kumar K. Tamma
Dept of Mechanical Engineering and Aerospace Engineering
West Virginia University
Morgantown, West Virginia
304-293-4111 }
{
Computers in Energy Systems, Computational Fluid Dynamics,
Computational Heat Transfer, Combustion Modelling, Process Control :
Dr. Ahmed A. Busaina
Dept. of Mechanical Engineering
Clarkson University
Potsdam, New York
315-268-6574 }
Topics not in the above categories contact Technical Program
Chairman :
Mr. Edward M. Patton
US Army Ballistic Research Lab
Aberdeen Proving Grounds, MD 21005
301-278-6805
------------------------------
End of AIList Digest
********************
∂08-Oct-87 0728 LAWS@KL.SRI.Com AIList V5 #230 - Speech Databases, Temporal Representation
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 8 Oct 87 07:28:11 PDT
Date: Wed 7 Oct 1987 23:08-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #230 - Speech Databases, Temporal Representation
To: AIList@SRI.COM
AIList Digest Thursday, 8 Oct 1987 Volume 5 : Issue 230
Today's Topics:
Queries - Structural Design and Fabrication &
500K Interconnections Per Second,
Literature - Annual Review of Computer Science,
Databases - Speech Databases,
Representation - Time,
Bibliography - Temporal Representation and Reasoning
----------------------------------------------------------------------
Date: Thu, 1 Oct 87 01:39 EDT
From: UKJWERK@VAX1.CC.LEHIGH.EDU
Subject: Project - Structural Design and Fabrication
From: "Keith J. Werkman (KJW1 @ LEHIGH) ATLSS Project B1" <KJW1@LEHIGH>
I would like to be added to your mailing list. I am interested in
Expert Systems related to the Engineering field....Civil Engineering
to be exact. My PhD research area is in the Design and Fabrication of
Steel Structures. The project, sponsored by NSF, is part of Lehigh
University's Engineering Research Center called ATLSS for Advanced
Technology in Large Structural Systems. My assigned project is called
the Designer/Fabricator Interface or interpreter (DFI). We are
looking into developing a system to help structural steel designers
better understand the steel fabricator's points of view and, at the
same time, allow the fabricator better understand how/why the designer
has ordered the specific fabrication in his drawings.
Thus, the system needs to present points of view. Current approach
includes a frame based system in Quintus Prolog on a Sun 3/160C. The
system includes such things as graphics (sunGKS) for input and display
of shop drawings in an effort to better describe events as preceived
by various parties involved.
Hopefully, the result will be a system that will help the mom-and-pop
design and fabrication firms throughout our country, hence (and this
is the NSF main point) make the US construction industry more
competative in the US marketplace. Thus, an interesting topic area
with some real potential goals.
If you know of any net messages/listing/notices/wispers of ES areas
any AI/ES related to CE, structural design, fabrication, welding,
erection, connection design, I would be most interested. Since I am
the only CS grad student currently involved with network SIGS in the
ATLSS center, I feel that any info I can get on current ES in CE might
be useful to others research projects such as connection design ,
material research, business related topics to ES in CE, etc...
Keith J Werkman
Lehigh University
CSEE Department
Packard Laboratory, #19
Bethlehem, PA 18015
(215)785-4508
BITNET: KJW1%LEHIGH.BITNET@WISCVM.WISC.EDU
Nets: ihnp4!c11ux!lehi3b15!scarecrow!keithw
kjw1@lehigh.BITNET
keith@lehigh.EDU
------------------------------
Date: 5 Oct 87 06:17:13 GMT
From: munnari!mulga.oz!jayen@uunet.UU.NET (Jayen Vaghani)
Subject: 500K interconnections - what does that mean?
In the Spang Robinson report, there was mention of neural chips handling 500K
interconnections per second? What does this actually mean? How do these chips
actually work (basically)?
Thanks, Jayen.
------------------------------
Date: 4 Oct 87 23:47:54 GMT
From: Walter Maner<psuvax1!pitt!bgsuvax!maner@RUTGERS.EDU>
Subject: Re: Annual Review of Computer Science
>
> The book "Logical Foundations of Artificial Intelligence"
> by M. R. Genesereth, N. J. Nilsson contains the following reference,
> Levesque, H., "Knowledge Representation and Reasoning",
> Annual Review of Computer Science, 1986
> Can anyone give me information about the above journal? I cannot find it
> anywhere.
This is not a journal but a book published each year by Annual Reviews, Inc.,
4139 El Camino Way, Post Office Box 10139, Palo Alto, CA 94303. The ISBN #
of the volume you want is 0-8243-3201-6. The same nonprofit company
publishes annual reviews of twenty-six other sciences. The 1986 review
of computer science was their first volume in this new series. Your article
begins on page 255.
--
CSNet : maner@research1.bgsu.edu | CS Dept 419/372-2337
UUCP : {cbatt,cbosgd}!osu-cis!bgsuvax!maner | BGSU
Generic : maner%research1.bgsu.edu@relay.cs.net | Bowling Green, OH 43403
Opinion : If you are married, you deserve a MARRIAGE ENCOUNTER weekend!
------------------------------
Date: Mon, 05 Oct 87 10:28:58 -0400
From: "Steven J. Nowlan" <nowlan%ai.toronto.edu@RELAY.CS.NET>
Subject: Speech Databases
A while back I posted a request for information on publically available
speech databases. A number of people sent me requests for this information
so I am posting a summary.
The best source of these databases in North America is the National
Bureau of Standards (NBS). The person to speak to is David Pallett
whose phone number is (301) 975-2935. However he is extremely busy.
The NBS maintains copies of several speech databases for isolated word
or connected digit recognition. They make copies of these databases
available on various media so that interested parties can copy the
database for their own uses. However, the waiting lists for most of
these databases are very long!
Here is a brief summary of what is available:
1. TI Isolated Word Database - digits, 10 control words, alpha-set
Multi-speaker, isolated word
2. VERBEX Database - eleven digits, multi-speaker, isolated word
3. FAA Database - 68 word vocab., multi-speaker, isolated word, phone lines
4. TI Connected Digits Database - variable length digit strings, multi-speaker
multi-dialect
Access to the above is obtained by contacting David Pallett.
5. AFTI/F-16 - 70 word vocab., multi-speaker, high-noise
Contact: Dr. Thomas J. Moore, Biological Acoustics Branch
Air Force Aerospace Medical Research Lab, Wright-Patterson
AFB, OH 45433.
6. MIT ICE CREAM database - connected sentences (1000 different sentences)
multi-speaker. Contact: David Pallett (Available end 87)
7. DARPA "Spelling Bee" Database - sentences of form "word spelling", 600
word vocab., multi-speaker, Contact: David Pallett (Avail 87?)
There are also a couple of DARPA databases available to the DARPA contractor
community, which are not yet public access, but may be in the near future.
Thanks to everyone who provided me with information, and I hope others
may find the above information useful.
Steve Nowlan
Arpanet: nowlan%ai.toronto.edu@relay.cs.net
CSNet,Bitnet: nowlan@ai.toronto.edu
EAN,X.400: nowlan@ai.toronto.cdn
UUCP: {uunet,watmath}!ai.toronto.edu!nowlan
------------------------------
Date: Mon, 5 Oct 87 12:08:38 EDT
From: rapaport@cs.Buffalo.EDU (William J. Rapaport)
Subject: representation of time
Another representation of time, inspired by Allen's work, but differing
in significant ways, is in:
Michael J. Almeida, "Reasoning about the Temporal Structure of
Narratives," Tech. Report 87-10 (Buffalo: SUNY Buffalo Dept. of
Computeer Science, 1987).
Copies may be had by contacting: library@cs.buffalo.edu
William J. Rapaport
Assistant Professor
Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260
(716) 636-3193, 3180
uucp: ..!{ames,boulder,decvax,rutgers}!sunybcs!rapaport
csnet: rapaport@buffalo.csnet
internet: rapaport@cs.buffalo.edu
[if that fails, try: rapaport%cs.buffalo.edu@relay.cs.net
or: rapaport%cs.buffalo.edu@csnet-relay. ]
bitnet: rapaport@sunybcs.bitnet
------------------------------
Date: Fri, 2 Oct 87 17:03:00 PDT
From: rshu@ADS.ARPA (Richard Shu)
Subject: Bibliography on Temporal Representation and Reasoning
Ken,
I've been reading up on temporal representation and reasoning
recently and have compiled the following bibliography. Please
distribute it to ailist if appropriate.
Richard Shu
@TechReport{allen81a,
key"allen81a",
author "ALLEN, J.F.",
title "Maintaining Knowledge About Temporal Intervals, TR 86",
institution "University of Rochester, Department of Computer Science",
year "1981"}
@TechReport{allen81b,
key"allen81b",
author "ALLEN, J.F.",
title "A general model of action and time, TR 97",
institution "University of Rochester, Department of Computer Science",
year "1981"}
@InProceedings{allen81c,
key "allen81c",
author "ALLEN, J.F.",
title "An Interval-Based Representation of Temporal Knowledge",
booktitle "Proceedings of 7th IJCAI",
organization "IJCAI",
pages"221-226",
month "August",
year "1981"}
@Article{allen83a,
key "allen83a",
author "ALLEN, J.F.",
title "Maintaining Knowledge About Temporal Intervals",
journal "Communications of the ACM",
volume "26(11)",
pages "832-843",
year "1983"}
@InProceedings{allen83b,
key "allen83b",
author "ALLEN, J.F. & KOOMEN, J.A.",
title "Planning using a temporal world model",
booktitle "Proceedings of 8th IJCAI 1983",
organization "IJCAI",
year "1983"}
@Article{allen84,
key "allen84",
author "ALLEN, J.F.",
title "Towards a general theory of action and time",
journal "Artificial Intelligence",
volume "23(2)",
pages "123-154",
year "1984"}
@TechReport{allen85a,
key"allen85a",
author "ALLEN, J.F. and HAYES, P.J.",
title "A Commonsense Theory of Time: The Longer Paper",
institution "University of Rochester, Department of Computer Science",
year "1985"}
@InProceedings{allen85b,
key "allen85b",
author "ALLEN, J.F. and HAYES, P.J.",
title "A Commonsense Theory of Time",
booktitle "Proceedings of IJCAI 1985",
organization "IJCAI",
pages"528-531",
year "1985"}
@Article{bruce72,
key "bruce72",
author "BRUCE, B.",
title "A Model for Temporal References and
its Application in a Question Answering Program",
journal "Artificial Intelligence",
volume "4",
pages "1-25",
year "1972"}
@TechReport{cheeseman83,
key"cheeseman83",
author "Cheeseman, P.",
title "A Representation of Time for Planning, Technical Note 278",
institution "SRI Artificial Intelligence Center",
year "1983"}
@InProceedings{cheeseman84,
key "cheeseman84",
author "Cheeseman, P.",
title "A Representation of Time for Automatic Planning",
booktitle "Proceedings of IEEE International Conference on Robotics",
organization "IEEE",
year "1984"}
@InProceedings{chun86,
key "chun86",
author "Chun Hon Wai",
title "A Representation for Temporal Sequence and Duration
in Massively Parallel Networks: Exploiting Link Interactions",
booktitle "Proceedings of AAAI-86, Philadelphia, Pa.",
organization "AAAI",
month "August",
pages"372-376",
year "1986"}
@TechReport{dean83,
key"dean83",
author "DEAN, T.L.",
title "Time Map Maintenance",
institution "Yale University Computer Science Department",
year "1983"}
@InProceedings{dean84a,
key"dean84a",
author "DEAN, T.L.",
title "Planning and Temporal Reasoning Under Uncertainty",
booktitle "Proceedings of IEEE Workshop on Principles of
Knowledge-Based Systems",
organization "IEEE",
month "December",
year "1984"}
@InProceedings{dean84b,
key"dean84b",
author "DEAN, T.L.",
title "Managing Time Maps",
booktitle "Proceedings of CSCSI 84.
Canadian Society for Computational Studies of Intelligence",
organization "CSCSI",
year "1984"}
@TechReport{dean84c,
key"dean84c",
author "DEAN, T.L.",
title "A TNMS User's Manual",
institution "Yale University Computer Science Department",
year "1984"}
@TechReport{dean85,
key"dean85",
author "DEAN, T.L.",
title"Temporal imagery: an approach to reasoning about time for planning
and problem solving",
institution "Yale University Computer Science Department",
year "1985"}
@InProceedings{dean85,
key "dean85",
author "DEAN, T.L.",
title "Temporal Reasoning Involving Counterfactuals and Disjunctions",
booktitle "Proceedings of 9th IJCAI 1985",
organization "IJCAI",
pages "1060-1062",
month "August",
year "1985"}
@InProceedings{dean86,
key "dean86",
author "DEAN, T.L.",
title "Intractability and time dependent planning",
booktitle "Proceedings of the Workshop on Planning and Reasoning About Action",
organization "AAAI",
month "July",
pages"143-164",
year "1986"}
@TechReport{fagan80,
key "fagan80",
author "FAGAN, J.J.",
title "Representing Time-Dependent Relations in a Medical Setting",
type "Ph.D. thesis",
institution "Stanford University",
year "1980"}
@TechReport{Hanks85,
key"Hanks85",
author "HANKS, S. and MCDERMOTT, D.",
title "Temporal Reasoning and Default Logics",
institution "Yale University Department of Computer Science",
year "1985"}
@Article{hendrix73,
key "hendrix73",
author "HENDRIX, G.G",
title "Modeling Simultaneous Actions and Continuous Processes",
journal "Artificial Intelligence",
volume "4",
pages "145-180",
year "1973"}
@InProceedings{hirschman81,
key "hirschman81",
author "HIRSCHMAN, L.",
title "Representing implicit and explicit time relations in narrative",
booktitle "Proceedings of 7th IJCAI",
organization "IJCAI",
pages "289-295",
month "August",
year "1981"}
@Article{kahn77,
key "kahn77",
author "KAHN, K. and GORRY, G.A.",
title "Mechanizing Temporal Knowledge",
journal "Artificial Intelligence",
volume "9",
pages "87-108",
year "1977"}
@InProceedings{kandrashina83,
key "kandrashina83",
author "Kandrashina, E.Y.",
title "Representation of Temporal Knowledge",
booktitle "Proceedings of 8th IJCAI 1983",
organization "IJCAI",
pages "343-345",
year "1983"}
@InProceedings{ladkin85,
key "ladkin85",
author "LADKIN, P.B.",
title "Comments on the Representation of Time",
booktitle "Proceedings of the 1985
Distributed Artificial Intelligence Workshop",
year "1985"}
@InProceedings{ladkin86a,
key "ladkin86a",
author "LADKIN, P.",
title "Primitives and Units for Time Specification",
booktitle "Proceedings of AAAI-86, Philadelphia, Pa.",
organization "AAAI",
month "July",
pages"354-359",
year "1986"}
@InProceedings{ladkin86b,
key "ladkin86b",
author "LADKIN, P.",
title "Time Representation: A Taxonomy of Interval Relations",
booktitle "Proceedings of AAAI-86, Philadelphia, Pa.",
organization "AAAI",
month "August",
pages"360-366",
year "1986"}
@InProceedings{leban86,
key "leban86",
author "LEBAN, B., MCDONALD, D and FORSTER, D.",
title "A Representation for Collections of Temporal Intervals",
booktitle "Proceedings of AAAI-86, Philadelphia, Pa.",
organization "AAAI",
month "August",
pages"367-371",
year "1986"}
@InProceedings{long83b,
key "long83b",
author "LONG, W. and RUSS, T.",
title "A Control Structure for Time Dependent Reasoning",
booktitle "Proceedings of 8th IJCAI 1983",
pages "230-232",
organization "IJCAI",
month "August",
year "1983"}
@InProceedings{malik83,
key "malik83",
author "MALIK, J. and Binford T.O.",
title "Reasoning in Time and Space",
booktitle "Proceedings of 8th IJCAI 1983",
organization "IJCAI",
pages "343-345",
year "1983"}
@InProceedings{masui83b,
key "masui83b",
author "MASUI, S., MCDERMOTT, J. and SOBEL, A.",
title "Decision-Making in Time-Critical Situations",
booktitle "Proceedings of 8th IJCAI 1983",
pages "233-235",
organization "IJCAI",
month "August",
year "1983"}
@InProceedings{miller85,
key "miller85",
author "Miller, D., Firby, J. and Dean, T.",
title "Deadlines, Travel Time and Robot Problem Solving",
booktitle "Proceedings of 9th IJCAI 1985",
organization "IJCAI",
pages "1052-1054",
year "1985"}
@Article{mourelatos78,
key "mourelatos78",
author "MOURELATOS, A.P.D.",
title "Events, processes and states",
journal "Linguistics and Philosophy",
volume "2",
pages "415-434",
year "1978"}
@TechReport{McDermott81,
key"McDermott81",
author "MCDERMOTT, D.",
title "A Temporal Logic for Reasoning about Processes and Plans",
institution "Yale University Department of Computer Science",
year "1981"}
@Article{mcdermott82,
key "mcdermott82",
author "MCDERMOTT, D.",
title "A Temporal Logic for Reasoning about Processes and Plans",
journal "Cognitive Science",
volume "6",
pages "101-155",
year "1982"}
@TechReport{Moore80,
key "Moore80",
author "Moore, R.",
title "Reasoning about knowledge and action (Technical Report 191)",
institution "SRI AI Center",
year "1980"}
@Book(rescher,
key "rescher",
author "RESCHER, N.",
title "Temporal Logic",
publisher "Springer-Verlag",
address "New York",
year "1971" )
@InProceedings{rit86,
key "rit86",
author "Rit, J.",
title "Propagating temporal constraints for scheduling",
booktitle "Proceedings of AAAI-86, Philadelphia, Pa.",
organization "AAAI",
month "August",
pages "383-388",
year "1986"}
@TechReport{shoham86,
key "shoham86",
author "SHOHAM, Y.",
title "Reasoning About Change:
Time and Causation from the Standpoint of Artificial Intelligens",
type "Ph.D. thesis",
year "1986"}
@InProceedings{shoham86,
key "shoham86",
author "Shoham, Y.",
title "Reified Temporal Logics: Semantical and Ontological Considerations",
booktitle "Proceedings of 7th ECAI, Brighton, U.K.",
organization "ECAI",
month "July",
year "1986"}
@InProceedings{shoham86,
key "shoham86",
author "Shoham, Y.",
title "Chronological Ignorance:
Time, Nonmonotonicity, Necessity and Causal Theories",
booktitle "Proceedings of AAAI-86, Philadelphia, Pa.",
organization "AAAI",
month "August",
pages "389-393",
year "1986"}
@TechReport{Smith83,
key "Smith83",
author "Smith, S.F.",
title "Exploiting Temporal Knowledge to Organize Constraints,
Technical Report CMJU-RI-TR-83-12",
institution "CMU Robotics Institute",
year "1983"}
@TechReport{Vere81,
key "Vere81",
author "Vere, S.A.",
title "Planning in Time: Windows and Durations for Activities and Goals",
institution "California Institute of Technology Jet Propulsion Laboratory",
year "1981"}
@TechReport{Vere84,
key "Vere84",
author "Vere, S.A.",
title "Temporal Scope of Assertions and Window Cutoff",
institution "California Institute of Technology Jet Propulsion Laboratory",
year "1984"}
@InProceedings{vere85,
key "vere85",
author "Vere, S.",
title "Temporal Scope of Assertions and Window Cutoff",
booktitle "Proceedings of 9th IJCAI 1985",
organization "IJCAI",
pages "1055-1059",
year "1985"}
@InProceedings{vilain82,
key "vilain82",
author "VILAIN, M.",
title "A System for Reasoning About Time",
booktitle "Proceedings of AAAI-82, Pittsburgh, Pa.",
organization "AAAI",
month "August",
year "1982"}
@InProceedings{vilain86,
key "vilain86",
author "VILAIN, M. and KAUTZ, H.",
title "Constraint Propagation Algorithms for Temporal Reasoning",
booktitle "Proceedings of AAAI-86, Philadelphia, Pa.",
organization "AAAI",
month "August",
year "1986"}
------------------------------
End of AIList Digest
********************
∂12-Oct-87 0020 LAWS@KL.SRI.Com AIList V5 #231 - Neural Networks, Common Lisp
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 Oct 87 00:20:15 PDT
Date: Sun 11 Oct 1987 22:04-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #231 - Neural Networks, Common Lisp
To: AIList@SRI.COM
AIList Digest Monday, 12 Oct 1987 Volume 5 : Issue 231
Today's Topics:
Queries - Beginning Text for AI and LISP &
Beta Sites for Lucid Common Lisp for the Sun 4 &
Planning Knowledge and Representation &
Public Domain PROLOG via FTP & Common Loops &
Scheme on the SUN & Commercial Uses for Neural Nets &
Neural Network Texts,
Neural Networks - 500K Connections per Second,
AI Tools - CMU Common Lisp Distribution
----------------------------------------------------------------------
Date: 8 Oct 87 09:53:05 GMT
From: marshek@ngp.utexas.edu (MAt)
Subject: Re: A good beginning text for AI & LISP
Hi there,
***PLEASE E-MAIL RESPONSES TO ME***
I would like to know about a good introductory text for AI and
the LISP language. I have a background in C, fortran but I presume that
does not help much, does it?
Thanx in advance
MAt
------------------------------
Date: Thu, 8 Oct 87 09:47:47 PDT
From: edsel!sears@labrea.stanford.edu (Steve Sears)
Subject: Looking for beta-sites to test Lucid Common Lisp for the Sun
4.
Lucid Common Lisp for the Sun 4 will soon be here. We are
interested in locating sites that can provide good feedback by
exercising our Sun 4 beta-test version. If you are interested, or know
someone that may be, please reply. You can also reach me by phone at
Lucid, (415) 329-8400.
Thanks in advance...
Steve Sears
------------------------------
Date: 9 Oct 87 02:26:39 GMT
From: lukose@aragorn.cm.deakin.OZ (Dickson Lukose)
Reply-to: lukose@aragorn.OZ (Dickson Lukose)
Subject: Planning Knowledge & Representation Survey
G'Day Colleagues,
I'm a newcomer to the planning paradigm and AI in general. My
research interest is in planning heuristics. I'm currently doing
a survey on:-
(1) "planning knowledge",
(2) "knowledge representation for planning" and
(3) "process of planning"
used by various types (eg. nonhierarchical, hierarchical, script-based
and opportunistic) of planning systems.
(1) Is there anyone who have done the above survey or knows someone who
have done so?
(2) Is anyone aware of any survey publications related to the above
mentioned areas?
(3) Has anyone got any bibliography related to the above subject areas?
I'm most interested in communicating with researchers currently
involved in R&D of "planning systems".
Any suggestions or pointers to the above request will be much
appreciated.
If enough interest shown, I will transmit(e-mail) the results of survey.
------------------------------------------------------------------
Dickson Lukose | UUCP: ...!seismo!munnari!aragorn.oz!lukose
Div. Comp. & Maths | ....!decvax!mulga!aragorn.oz!lukose
Deakin University |
Victoria, 3217 | ARPA: munnari!aragorn.oz!lukose@SEISMO.ARPA
Australia | ACSNET: lukose@aragorn
------------------------------
Date: 8 Oct 87 17:47:44 GMT
From: aplcen!jhunix!ins_akml@mimsy.umd.edu (Katherine Martha Lai)
Subject: Public domain PROLOG available via ftp?
Can anyone tell me where there is a public domain PROLOG that I
could get via ftp? I would be running it on a Sun 3/160 under
UNIX. Thanks!!
I am posting this for a friend, so it probably would be best to
reply to him directly (Marty Hall) at "hall@hopkins-eecs-bravo.arpa".
------------------------------
Date: Fri, 9 Oct 87 14:59 EST
From: STREIFF%HARTFORD.BITNET@WISCVM.WISC.EDU
Subject: Common Loops Request
Hi,
Im looking for a copy of Common Loops. Does any one have a
copy or know where i can get one? Were running Lucid V1.2 on Sun3/75's.
Thank you.
+------------------------------+----------------------------------------+
| S. David Streiff | BitNet : STREIFF@HARTFORD.BITNET |
| CE-CIM-EE | SlowNet : Box 2590 200 Bloomfield Ave |
| Combustion Engineering | West Hartford, CT. 06117 |
| Windsor CT. | MaBell : (203) 726-9117 |
-------------------------------+----------------------------------------+
DisClaimer : My employer is not responsible for anything that i say.
They will even deny my existance if given a chance.
------------------------------
Date: 8 OCT 87 15:08-N
From: U00124%HASARA5.BITNET@WISCVM.WISC.EDU
Subject: Request: Scheme on the SUN?
Hello Scheme users!
Within short we hope to have a Sun 3/60 system considting of 4 units
backed by two 141 MB disks and a 60 MB tape streamer. The system comes
fully furnished: C, Fortran 77, Pascal and Modula-2 (and UNIFY).
We are interested in running Lisp, preferably Scheme because we use it
in different courses and we like the IBM-PC implementation!.
The question is: is there a implementation of Scheme for the SUN? and if
so: Where to get it, how much it costs, etc..?
Any other info concerning Lisp and Prolog on the Suns will be apreciated.
Dr. Oscar Estevez
Chairman Study Programme
Medical Informatics, Univ. of Amsterdam.
------------------------------
Date: 4 Oct 87 23:59:33 GMT
From: imagen!atari!portal!cup.portal.com!barry_night-person_stevens@uc
bvax.Berkeley.EDU
Subject: commercial uses for neural nets -- have, also need, info
I am working on a study of commercial uses for neural nets. So far, these
include processing commercial loan applications, insurance underwriting,
insurance claims processing, signature verification, face and/or voice
identification for security, financial optimization.
I am interested in swapping applications with those who know of others.
These applications are using both hardware (such as the Hecht-Nielsen ANZA
board) and software systems.
Please contact me by phone at 619-755-7231
or in writing:
Barry A Stevens
Applied AI Systems, Inc.
PO Box 2747
Del Mar, CA 92014
------------------------------
Date: 7 Oct 87 09:50:45 GMT
From: plx!titn!jordan@sun.com (Jordan Bortz)
Subject: Neural Networks - Pointers to good texts?
Hello;
I'm looking for some good texts and/or articles on neural networks,
in English, and preferably focusing on real life algorithms/implementations
rather than obscure mathematics.
If you know of any, please let me know by mail, and I'll summarize
to the net; as this topic seems to be generating more interest.
I know some articles were mentioned earlier, but what about others?
Jordan
--
=============================================================================
Jordan Bortz Higher Level Software 1085 Warfield Ave Piedmont, CA 94611
(415) 268-8948 UUCP: (decvax|ucbvax|ihnp4)!decwrl!sun!plx!titn!jordan
=============================================================================
------------------------------
Date: Thu 8 Oct 87 14:28:06-EDT
From: Dave.Touretzky@C.CS.CMU.EDU
Subject: 500K connections per second
The inner loop (and most expensive part) of neural net simulations computes for
all j the net input to unit j, which is the sum for all i of the output of unit
i times the weight Wji on the connection from i to j. This is just a multiply
and accumulate loop. In fact, if you choose the right data structures, it's a
matrix-vector multiplication. So when someone advertises that their
"neurocmputer" does 500K connections per second, they mean it does five hundred
fetch-multiply-accumulate operations per second. This is a useful performance
measure because it is independent of the number of units and connections in the
model being simulated.
There is, unfortunately, no such thing as a commercially available
neurocomputer. Presumably, a neurocomputer would either be a computer made out
of neurons, or a computer whose physical structure in some way resembled that
of the nervous system. No product available today meets either of those tests.
What people are selling today as "neurocomputers" are just regular old
computers with some neural net simulation software. For example, Hecht-Nielsen
NeuroComputer Corporation, the outfit that's been running those full-page
four-color ads in AI Magazine, sells their ANZA "neurocomputer" for $15,000.
The ANZA system is an off-the-shelf IBM PC/AT with an add-on board containing a
Motorola 68020 with floating point co-processor and 4Meg of memory. For
roughly the same price you could buy a Sun III (same 68020 processor) and run
Unix and X-windows instead of PC-DOS. In fact, Hecht-Nielsen will be
announcing a version of their simulation software for the Sun in the near
future. That doesn't make the Sun III a neurocomputer, but then again, neither
is the ANZA.
The TRW Mark III is also a coprocessor build out of conventional components,
but it attaches to a Vax rather than an IBM PC. The Science Applications
Corporation Sigma-1 is a high speed number cruncher based on a Harvard
architecture (the single processor has separate data and instruction paths); it
is not a neurocomputer. Science Applications recently acquired a Connection
Machine which they plan to use for really heavy duty simulations. (Connection
machines aren't neurocomputers either; they're much more general purpose than
that. See the article by Blelloch and Rosenberg in IJCAI-87 for a report on
using a CM2 to simulate learning in neural nets.)
The TI Oddyssey DSP (Digital Signal Processor) is another board that does fast
matrix-vector multiplies. Like the other products I mentioned, it is a
conventional architecture, basically a handful of TMS 98020(?) hardware
multiplier chips. I have a special fondness for Texas Instruments because even
though they do some interesting neural net research, they never use the
misleading term "neurocomputer" in their ads for the Oddyssey.
Will there ever be real neurocomputers? Perhaps some day:
Some people are building VLSI circuits whose structure is based on an abstract
description of neural circuitry. For example, a group at BELLCORE led by
Joshua Alspector and Robert Allen has designed a 54-unit "Boltzmann Machine"
chip. The 54 neurons are physically implemented as separate processors on the
chip, and their N*(N-1)/2 weighted connections are also implemented by separate
pieces of circuitry, giving a fully parallel implementation. This is terrific
work, but it will be quite a while before it has any commercial impact, because
it's hard to put a lot of neurons on one chip, and expensive to communicate
across multiple chips. It is possible to cram several hundred neurons on a
chip if you go for fixed weights (resistors) rather than variable ones, but
then the network can't learn.
Carver Mead and Mass Silviotti at Caltech have built a "silicon retina" low
level vision chip using analog (!) VLSI circuitry. The chip's architecture was
inspired by the way real retinas do computation.
There is also work on optical implementations of neural networks, using lasers,
two-dimensional or volume holograms, and various mirrors and photosensors. Two
of the big names in this area are Dmitri Psaltis (Caltech) and Nabil Farhat
(Penn). It will probably take longer for this technology to reach the
marketplace than for VLSI-based technologies, as it is in a much earlier stage
of development.
A group at Bell Labs has been growing real neurons on a special substrate with
embedded electrodes, so they can have an electronic interface to a living
neural circuit. This is a neat way to study how neural circuitry works, but
they only deal with a handful of neurons at a time. I doubt whether it will
ever be practical to design special-purpose computers from living neurons.
A good place to learn more about neuromorphic computer architectures (a more
decorous term than "neurocomputer", in my opinion) is the proceedings of neural
net conferences. There's the proceedings of the 1986 Snowbird Meeting on
Neural Networks for Computing, published by the American Institute of Physics
in New York. There's also the IEEE First International Conference on Neural
Networks, which was held in San Diego this past June. And there's the IEEE
Conference on Neural Information Processing Systems - Natural and Synthetic,
which will be held in Denver, at the Sheraton Denver Tech Center, on November
8-12. This conference was originally to take place in Boulder, but
registration has been so heavy it had to move to larger quarters at the last
minute. The conference chairman is Yaser Abu-Mostafa at Caltech.
Sorry, I don't have information on how to order proceedings from the IEEE
conferences. Contact the IEEE.
-- Dave Touretzky
------------------------------
Date: Mon, 05 Oct 87 11:41:30 PDT
From: Vicki L. Gordon <vgordon@venera.isi.edu>
Subject: CMU Common Lisp Distribution
With DARPA funding, the University of Southern California's Information
Sciences Institute (USC/ISI) is serving as a distribution center for
public-domain Common Lisp software packages. The first of these packages
includes the source files for CMU Common Lisp (formerly known as "Spice
Lisp"). The package also includes an unsupported public-domain version
of the OPS5 language that is written in Common Lisp.
If there is sufficient interest, and if funding allows, we will later expand
the distribution program to include additional software packages from other
sources.
CMU Common Lisp is a full implementation of Common Lisp, developed as part of
the Spice project at Carnegie-Mellon University (CMU). This system runs only
on the IBM RT PC, and only under CMU's Mach operating system (superficially
similar to 4.3bsd Unix, but with a different internal organization). Since
the IBM RT version of Mach is not currently supported outside of CMU, it
follows that CMU Common Lisp is *NOT* a system that anyone can obtain and
run as is. We are making the sources for this system available because a
number of groups have found it to be a useful starting point for their own
Common Lisp implementations. Typically, it takes a man-year of effort to port
this system to a new machine and operating system (more if the target
environment is unusual). Individuals and small research groups who want a
Common Lisp for their own use are advised to use one of the commercially
available products.
This source code is in the public domain and, once you have them, there
is no restriction on how you may use them. They are made available as a public
service, with no warranty of any sort by the authors, CMU, or USC/ISI, and
with no promise of future support. CMU Common Lisp has been heavily used at
CMU, but it has not been extensively tested in any systematic way. Questions
about the distribution procedure may be directed via electronic mail to
ACTION@ISI.EDU, or you may call (213) 822-5511. Bug reports and questions
about the code itself should also be directed to SCOTT.FAHLMAN@CS.CMU.EDU.
This distribution package contains approximately 7 megabytes of ASCII source
files. It can be obtained over the Arpanet/Milnet by establishing an FTP
connection to VENERA.ISI.EDU and logging in as "anonymous" (any password can be
used). For optimal response time, please conduct your file transfer during
our non-primetime hours (1800 to 0800 PDT). The source files are kept in the
following directories:
/common-lisp/implementation/cmu/code
(Runtime system and interpreter for CMU Common Lisp on IBM RT PC under Mach)
/common-lisp/implementation/cmu/clc
(Compiler from Common Lisp to native code for RT/Mach. Mostly written in
Common Lisp itself.)
/common-lisp/implementation/cmu/hemlock
(Sources for the Hemlock text editor. This editor is similar at user level to
Emacs. Written in Common Lisp, but contains some Mach-specific system calls
and display code. Uses either X windows or standard termcap terminals.)
/common-lisp/implementation/cmu/OPS5
(Portable Common Lisp version of the OPS5 production-system language.
A quick and dirty port of the public domain version that was developed
originally in Franz Lisp. No support whatsoever is provided.)
/common-lisp/implementation/cmu/miscops
(Low level support routines for the IBM PC RT: garbage collection, generic
arithmetic, etc. Totally machine-specific. Provided as an example of what
needs to be done in order to port this lisp to another machine.)
/common-lisp/implementation/cmu/icode
(Lisp functions implementing the interface between Mach and CMU Common Lisp.
Very system-specific. Provided only as an example.)
/common-lisp/implementation/cmu/lib
(Cursor definition file and spelling dictionary used by the Lisp runtime
system).
If you would like to order a tape, we will first send you a release form
which you are required to sign prior to receiving the tape. When you return
the signed release, include a check made payable to USC/Information Sciences
Institute for $100.00 to cover the production and mailing costs. Please
remember to include a complete return address.
The default tape format will be tar 1600 bpi, unless otherwise specified.
Currently ISI is only prepared to distribute tapes containing the CMU
Common Lisp code to individuals or companies within the United States.
We are currently negotiating with the Department of Commerce and CMU
to obtain authorization to distribute the code to countries outside of
the United States; however, we do not expect approval in the immediate
future.
The following hardcopy documentation produced by CMU is also available
to all recipients at a cost of $20.00 per package (payable to USC/
Information Sciences Institute). The package includes:
- "Internal Design of Common Lisp on the IBM RT PC"
- "CMU Common Lisp User's Manual, Mach/IBM RT PC Edition"
- "Hemlock User's Manual"
- "Hemlock Command Implementor's Manual"
Please send your request for a tape and/or documentation to ACTION@ISI.EDU,
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------------------------------
End of AIList Digest
********************
∂12-Oct-87 0242 LAWS@KL.SRI.Com AIList V5 #232 - Time, Financing, Othello, Philosophy
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 Oct 87 02:42:19 PDT
Date: Sun 11 Oct 1987 22:15-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #232 - Time, Financing, Othello, Philosophy
To: AIList@SRI.COM
AIList Digest Monday, 12 Oct 1987 Volume 5 : Issue 232
Today's Topics:
Representation - Time Bibliography,
Business - Expert Systems Company Financing,
Games - International Computer-Othello Match,
Philosophy - Goal of AI & Flawed Minds
----------------------------------------------------------------------
Date: Thu, 8 Oct 87 15:23:36 PDT
From: ladkin@kestrel.ARPA (Peter Ladkin)
Subject: time bibliography
ailist readers might like to note that richard shu's bibliography
misses halpern and shoham's paper in LICS 1986, pelavin and allen's
paper in the Proceedings of the IEEE for October 1986, and also papers
published in AAAI-87 and IJCAI-87. Additionally, there is a large
literature on points and periods in philosophy since Rescher and
Urquhardt, to which one can get pointers from Kuhn's review of van
Benthem that I referenced. In a complete list of temporal reasoning,
one should also include the huge amount of literature from program
semantics, especially the semantics of concurrency. It was
interesting to note that Shu's bibliography and mine were almost
disjoint ............
peter ladkin
ladkin@kestrel.arpa
------------------------------
Date: 9 Oct 87 14:12:15 GMT
From: amdcad!sun!sundc!potomac!grover@ames.arpa (Mark D. Grover)
Subject: Re: Bibliography on Temporal Representation and Reasoning
I had a relevant article in AAAI 82:
Grover, M.D. "A Synthetic Approach to Temporal Information
Processing", AAAI-82, pg. 91-4.
Based on my PhD dissertation, the work addresses the use of Montague
Grammar-based temporal representations of complex English verb tense.
- MDG -
--
--> Our site is in transition. Please use one of the addresses below. <--
Mark D. Grover (grover@ads.ARPA) UUCP: ames!amdcad!sun!sundc!potomac!grover
Advanced Decision Systems 1500 Wilson Blvd #512; Arlington, VA 22209
Future address: grover@dc.ads.com "I've been ionized... but I'm okay now."
------------------------------
Date: 6 Oct 87 02:21:35 GMT
From: oliveb!intelca!mipos3!omepd!chedley@ames.arpa (CHEDLEY)
Subject: Re: Expert Systems Company Financing...
In article <7260@dartvax.UUCP> waltervj@dartvax.UUCP (walter jeffries) writes:
>
>I am not the business end of things but
>would appreciate any comments/experiences that people may have with getting
>capital (sources, things to be careful of, etc.). Of course, if you want to
>invest money as well as advice that would be appreciated too :-).
>
There are three major sources of money for start-up financing:
1) Money from the owners/starters of the company: In this case it is your and
your partners' own savings and personal loans (credit cards, Home equity loans,
personal unsecured bank loans,..)
MONEY FROM THIS SOURCE IS TYPICALLY INSUFFICIENT TO GET THE BUSINESS ROLLING
2) Venture Capital: This money belongs to funds(*), companies or private
individuals who are looking to invest in start-up businesses. In return they
require the "ownership" of a portion of the business, along with some other
conditions (oversight on the books of the company, a say in management
appointments, options on the share of the company if and when it goes
public,...etc)
MONEY FROM THIS SOURCE IS RELATIVELY AVAILABLE.
3) Govrmt Money (State/Federal) : This is typically an easy conditions loan
(low interest rate, long grace period, easy payment schedule..) provided by
some state or federal agencies to promote small and start companies.
Try to tap this source to the max. And you do not have to be a woman or a
member of a minority group to qualify for this cheap source of financing.
GOVRNMT MONEY IS THE CHEAPEST SOURCE OF FINANCING START UPS
Due to the constraints of the venture capitalist's money, it is advantageous
to leverage it as much as possible with the other sources's money. That is,
for each dollar from source 1 or 3, get the maximum venture capital you can
reach for.
(*): There are even a few venture capital mutual funds out there.
..CHEDLEY..
------------------------------
Date: 7 Oct 87 18:20:12 GMT
From: amdahl!oliveb!epimass!epiwrl!shore@ames.arpa (John Shore)
Subject: Re: Expert Systems Company Financing...
In article <7260@dartvax.UUCP> waltervj@dartvax.UUCP (walter jeffries) writes:
>
>I am in the process of starting a company to do expert systems developement
>in the field of psychiatry....
>...(sources, things to be careful of, etc.)....
Things to be careful of? Expert systems and AI.
js
------------------------------
Date: 6 Oct 87 01:17:50 GMT
From: mcvax!nikhefk!kvr@uunet.uu.net (kees van rijn)
Subject: intercontinental computer - othello match
INTERCONTINENTAL COMPUTER - OTHELLO MATCH
Last saturday there was a computer-othello match of
MY TURN in The Netherlands with
BILL in the USA.
MY TURN has been written by Cas Wilders and won the
preceding local mini-tournament in Amsterdam with
REV87 (by Joost Buys),
MAST87 (by Ron Kroonenberg) and
BADIA1.2 (by Marcel van Tien).
BILL is vice-champion of the USA since last US' tournament,
some years ago.
BILL has been written by Kai-Fu Lee and Sanjoy Mahajan.
Communication between Pittsburgh USA
and Amsterdam NL took place via EARN / BITNET.
After this match, there were also games of
REV87 and MAST87 with BILL via this communication channel.
All games were won by BILL.
In the first match MY TURN got low mobility because of
a wrong move in the beginning. It was hopeless to continue
and Cas resigned. For the other two games, the level of the
participants was probably near equal, though initially REV87
had also problems with mobility, but it recovered.
For non-experts in othello, like me, it is however very difficult
to estimate the real value of a position.
All of us agreed that it is a very hard job to improve
strength of the programs further with known techniques.
According to Kai-Fu, faster machines lead only to marginal
improvement, and better search algorithm is too hard.
We think that most improvement of last years is from implementation
of specific othello knowledge into the programs.
However, probably the level of present programs is so
high, that in a tournament of best computer programs with
best human players, computers will win more than 80% of
the games.
Technically, the communication channel was good, though exact
time checking was impossible because of a delay of
about 5 seconds before a move arrived. This time is not
garanteed, and it is also not yet possible for the participants
to check the time that a message was sent.
Another problem was that backspaces from Amsterdam were not
executed, but turned into periods, so that careful typing was
required. We were later told that delete probably would
have been effective.
And sometimes, messages from other people were disturbing
clear communication.
Generally speaking however, the match passed off very successfully.
kees van rijn
(organizer)
------------------------------
Date: 6 Oct 87 21:04:05 GMT
From: PT!speech2.cs.cmu.edu!kfl@cs.rochester.edu (Fu Lee)
Subject: Re: intercontinental computer - othello match
In article <248@nikhefk.UUCP>, kvr@nikhefk.UUCP (kees van rijn) writes:
>
> INTERCONTINENTAL COMPUTER - OTHELLO MATCH
>
> Last saturday there was a computer-othello match of
> MY TURN in The Netherlands with
> BILL in the USA.
> ....
Thanks to Kees for organizing this match, and for this accurate
commentary. There were, however, a few misunderstandings which
I hope to clarify.
> All of us agreed that it is a very hard job to improve
> strength of the programs further with known techniques.
> According to Kai-Fu, faster machines lead only to marginal
> improvement, and better search algorithm is too hard.
Actually, I believe faster machines will lead to substantial improvement,
as they did for chess. However, making othello hardware is not as
fruitful since current programs already outplay humans, and since there
are no incentives. I think an improved search algorithm is both
more effective and intellectually satisfying. However, our attempts
in the past year have not been encouraging.
>We think that most improvement of last years is from implementation
>of specific othello knowledge into the programs.
Actually, the two major contributions from BILL are: (1) encoding all
Othello knowledge into tables for fast evaluation, and (2) Bayesian
learning of how to combine evaluation features.
> kees van rijn
> (organizer)
Kai-Fu Lee
------------------------------
Date: 4 Oct 87 18:23:43 GMT
From: ihnp4!homxb!mtuxo!mtune!codas!usfvax2!pdn!alan@ucbvax.Berkeley.E
DU (Alan Lovejoy)
Subject: Re: Goal of AI: where are we going?
In article <46400008@uxe.cso.uiuc.edu> morgan@uxe.cso.uiuc.edu writes:
/Maybe you should approach it as a scientist, rather than an engineer. Think
/of the physicists: they aren't out to fix the universe, or construct an
/imitation; they want to understand it. What AI really ought to be is a
/science that studies intelligence, with the goal of understanding it by
/rigorous theoretical work, and by empirical study of
/systems that appear to have intelligence, whatever that is. The best work
/in AI, in my opinion, has this scientific flavor. Then it's up to the
/engineers (or society at large) to decide what to do with the knowledge
/gained, in terms of constructing practical systems.
The word "artificial" implies either an imitation or synthetic object,
or the general/abstract laws governing an entire class of such objects.
The question is, does "artifical intelligence" mean "synthetic and/or
imitation intelligence" (most computer programs currently fall into this
category :-) ) or "real intelligence exhibited by artifical systems"?
Is AI mostly concerned with the *faking* of intelligence, with intelligence
per se or with intelligence as exhibited by artificial systems?
Given the current state of the art, perhaps it should be called
"Real Stupidity". (Only half :-) ).
The "scientific" study of intelligence would involve such subfields as
cognition, semantics, linguistics, semiotics, psychology, mathematics,
cybernetics and a host of other disciplines I can't think of right now,
some of which probably don't exist yet. Creating an intelligent
"artifact" (artificial intelligence) is only a "scientific" endeavor to
the extent it serves as experimental proof (or refutation) of some
*scientific* theory, or else as the raw data from which a theory is induced.
If the purpose of AI is to build a computer just as smart as a human
being because that would be a useful tool, then it's engineering.
If the purpose is to prove or induce theories about intelligence, then it's
scientific. It appears that both cases probably apply.
It is disturbing how often "science" is confused with "technology"
and/or "engineering". People also tend to forget that science involves
both the formulating of theories AND experiments. Experiments often
require a great deal of mundane (and sometimes not so mundane)
engineering work. AI came about because computers opened up a whole
new way to experimentally test theories about intelligence.
Physicists might very well try to construct an "artificial" universe,
if it would help to prove or induce a physical theory (the "Big Bang",
for instance). They'd probably require a lot of help from the engineers,
though (and probably a permit from the EPA :-) ).
--alan@pdn
------------------------------
Date: 5 Oct 87 23:11:11 GMT
From: PT!isl1.ri.cmu.edu!cycy@cs.rochester.edu (Christopher Young)
Subject: Re: Goal of AI: where are we going?
In article <1330@houdi.UUCP>, marty1@houdi.UUCP (M.BRILLIANT) writes:
> Point two, we keep using the human mind as a tool, to solve problems.
> As such, it is not merely a phenomenon, but a means to an end, and is
> subject to judgments of its utility for that purpose. Now we can say
> whether it is perfect or flawed. Obviously, it is not perfect, since
> we often make mistakes when we use it. Score one for Ware.
This is true. However, this is not the only use for the human mind. The
human mind is also used to imagine fanciful dreams, to love and hate and
otherwise feel emotion, and to make value judgement even when there is no
real logical reason for choosing option one over option two. So perhaps it
can be flawed in one way, but not in others (since it is difficult to say
what is flawed in some of these instances).
--
-- Chris. (cycy@isl1.ri.cmu.edu)
I know you believe you understand what you think I said, but I am not sure
you realise that what you heard is not what I meant.
------------------------------
Date: 5 Oct 87 22:58:34 GMT
From: PT!isl1.ri.cmu.edu!cycy@cs.rochester.edu (Christopher Young)
Subject: Re: Goal of AI: where are we going?
In article <270@uwslh.UUCP>, lishka@uwslh.UUCP (Christopher Lishka) writes:
> To me this seems to be one of many problems in A.I.: the assumption
> that the human mind can be looked at as a machine, and can be analyzed
> as having flaws or not, and subsequently be fixed or not.
>
> A comment: why don't A.I. "people" use the human mind as a model, for
> better or for worse, and not try to label it as "flawed" or "perfect?"
I guess I basically agree, though I certainly feel that there are some
people whose reasoning is either flawed or barely existent, and it is true
in fact that physiological parameters can affect thought, and that these
parameters can be adjusted in certain ways to cause depression, and to recover
from depression (etc). So in that way, one might say that human minds may
become flawed, I suppose.
On the other hand, since we pretty much define "mind" based on human ones,
it's hard to say that they are flawed. If there was something "perfect"
(whatever that might be", then it might very well not be a mind.
I do believe that there is some mechanism to minds (or perhaps a variety of
them). One reason why I am interested in AI (perhaps this is very Cog. Sci.
of me, actually) is because I think perhaps it will help elucidate the ways
in which the human mind works, and thus increase our understanding of human
behaviour. I don't know; perhaps I am naive in that respect. At anyrate,
I do try to use the human mind as a model in at least some of what I am doing.
Just thought I'd throw in my two cents.
--
-- Chris. (cycy@isl1.ri.cmu.edu)
I know you believe you understand what you think I said, but I am not sure
you realise that what you heard is not what I meant.
------------------------------
Date: 4 Oct 87 20:19:03 GMT
From: wcalvin@well.UUCP (William Calvin)
Reply-to: wcalvin@well.UUCP (William Calvin)
Subject: Re: Goal of AI: where are we going?
Making AI a real science suffers from the attitude of many of its founders:
they'd rather re-invent the wheel than "cheat" by looking at brain research.
While Minsky's SOCIETY OF MIND is very interesting, one gets the impression
that he hasn't looked at neurophysiology since the 1950s. Contrast that to
Braitenberg's little book VEHICLES (MIT Press 1984), which summarizes a lot
of ideas kicking around neurobiology at the simple circuit level.
The other thing strikingly missing, besides a working knowledge of
neurobiology beyond the Hubel-Wiesel level, is a knowledge of evolutionary
biology beyond the "survival of the fittest" level. Emergent properties are
a big aspect of complex systems, but one seldom hears much talk about them
in AI.
William H. Calvin
University of Washington NJ-15, Seattle WA 98195
------------------------------
Date: 6 Oct 87 18:23:31 GMT
From: bbn!uwmcsd1!uwm-cs!litow@cs.rochester.edu (Dr. B. Litow)
Subject: Re: Goal of AI: where are we going? (Where should we go...)
>
> The principal difficulty in cognitive science is that it is in its
> infancy. I think that psychology is today where physics was in
> Newton's time. And a LOT of "narrow minded" theories came and went in
> Newton's time. Including Newton's theories.
>
> Steve Frysinger
Newton's primary contribution in Principia is a method. The method has NOT
been modified at its core in the elapsed three centuries. It is still at
the basis of all western physical science. Newton understood its importance
as V.Arnold has pointed out in his book Geometric Methods in the Theory of
Ordinary Differential Equations (Springer). The method is very simple to
state: pose and solve differential equations for the phenomena. Prior to
anything else in western physics there is this method. In this respect all
of quantum mechanics is only a conservative (almost in the sense of logic)
extension of rational mechanics. Incidentally rational mechanics was not
developed explicitly by Newton. It is a product of the Enlightenment
researchers,e.g. the Bernoullis and especially Euler. Underlying the method
is something nameless which when it is finally investigated (the time is
approaching) will be a decisive element in actually showing what is really
conveyed by the adjective "western".
------------------------------
Date: 5 Oct 87 15:04:54 GMT
From: spf@moss.ATT.COM
Reply-to: spf@moss.UUCP (Steve Frysinger)
Subject: Re: Goal of AI: where are we going? (Where should we go...)
In article <493@vax1.UUCP> czhj@vax1.UUCP (Ted Inoue) writes:
}Some of you may remember my postings from last year where I expounded on the
}virtues of cognitive psychology. After investigating research in this field
}in more detail, I came up very disillusioned. Here is a field of study in
}which the soul purpose is to scientifically discover the nature of thought.
}Even with some very bright people working on these problems, I found that the
}research left me cold. Paper after paper describe isolated phenomena, then go
}on to present some absurdly narrow minded theory of how such phenomena could
}occur.
Perhaps you're right; there is not doubt that the system in question
is highly complex and interconnected.
However, the same claim can be made about the domain of physics. And
(in the west at least) research and progress in physics has been built
upon small pieces of the problem, complete with small theories (which
usually seemed incredibily naive when disproved). Now another
approach to physics is possible (see Kapra's "Tao of Physics"). It
would probably not be observational (which I require of any science)
but introspective instead. Me? I like both. When I do science, I
build up from measurable components, creating and discarding petty
theories along the way. When I do zen, it's another matter entirely
(no pun intended).
The principal difficulty in cognitive science is that it is in its
infancy. I think that psychology is today where physics was in
Newton's time. And a LOT of "narrow minded" theories came and went in
Newton's time. Including Newton's theories.
Steve Frysinger
------------------------------
End of AIList Digest
********************
∂12-Oct-87 0431 LAWS@KL.SRI.Com AIList V5 #233 - Philosophy
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 Oct 87 04:31:06 PDT
Date: Sun 11 Oct 1987 22:21-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #233 - Philosophy
To: AIList@SRI.COM
AIList Digest Monday, 12 Oct 1987 Volume 5 : Issue 233
Today's Topics:
Philosophy - Goals of AI & Flawed Minds
----------------------------------------------------------------------
Date: 5 Oct 87 15:41:48 GMT
From: merlyn@starfire.UUCP (Brian Westley)
Subject: Re: (Where should we go...) How to get there?
Ted Inoue writes:
> In article <46400008@uxe.cso.uiuc.edu> morgan@uxe.cso.uiuc.edu writes:
> >What AI really ought to be is a
> >science that studies intelligence, with the goal of understanding it by
> >rigorous theoretical work, and by empirical study of
> >systems that appear to have intelligence, whatever that is.
> ....
> On the other hand, if we take an educated approach to the problem, and study
> 'intelligent' systems, we have a much greater chance of solving the mysteries
> of the mind...
>
> ---Ted Inoue
This might work, but I would compare your method (understand the human mind
first, then mimic it via computer) to be similar to early heavier-than-air
experiments. Birds were the only working model, but we never got off the
ground until we stopped building airplanes that flapped their wings.
Intelligent computers will probably be as different from the human mind as
747's are from hummingbirds. They will both 'think', but in radically
different ways.
Of course, I could be wrong, so both methods should be explored.
Merlyn LeRoy
------------------------------
Date: 8 Oct 87 10:06:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: flawed minds
I'm sure I'm gonna regret getting into this (stop me before I
philosophize again), but here goes.
Put me down as a "yes" vote on the question if all (the vast
majority of ?) human minds are flawed.
First, to clear away some underbrush: of course the truth of the
statement is relative to the meaning of the words used.
"grass is green" is false if the referent of "grass" is zebras, ho hum.
To "play fair", it seems to me we should attempt to take the most
plausible interpretation of what is after all a pithy statement,
and contend with that.
It seems to me that "mind" normally means "that which enables the
owner of the mind to think" - eg if a Martian had a glarp instead
of a brain, but could still play a mean game of chess, and discuss
the NFL strike, etc, we surely would agree s/he had a mind.
Since it is an *essential* feature of a mind that it enables one to think
(positivistic formulation: mind IS the ability to think), it seems
fair to say that to the extent one thinks imperfectly, one's mind is
flawed. I am blithely assuming that "correct thinking" implies at
least the ability to formulate accurate descriptions of the world,
and manipulate them so as to draw correct conclusions.
I don't claim that a mind is nothing but an implementation of logic,
but it at least ought to be logically correct as far as it goes.
Insofar as the human mind implements unsound logic, it is flawed
(lots of people, eg, fall into the fallacy of the converse,
multiply incorrectly, etc.)
"the human mind is flawed" thus seems to me the same kind of
statement as "XYZ cars don't work well". Of course, considered
qua phenomenon, an XYZ car is neither good, bad, nor ugly.
But insofar as one accepts the bland (?) assumption that the
essential purpose of a car, qua car, is to transport you from
A to B, via roadway, then the question is merely whether XYZ
cars in fact usually succeed or not in this task.
The essential purpose of a mind, qua mind, is, among many other
things, to draw conclusions correctly from a given set of facts.
To the extent it fails to do so, it is flawed.
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: Thu 08 Oct 1987 08:33 CDT
From: UUCJEFF%ECNCDC.BITNET@WISCVM.WISC.EDU
Subject: THE MIND
I read some of the MIND theories espoused in the Oct 2 list, and am
frankly disappointed. All those debates are based on the Science vs
Mysticism debates that were going on 10 years ago when I was an undergrad.
I have since discarded both arguments into the /dev/null file. Nonetheless
I would like to make a few comments.
1) It is wrong to assume emotion is a flaw of the mind, or even bring up
Manson and Hitler. I would say absence of emotion is a flaw of the mind.
You want to talk about genius where mind and emotion are equal partners,
look at Ornette Coleman or John Coltrane. Anyone who downgrades emotion
(or i should say "emotional intelligence") is committing suicide.
2) Even if you say a mind is flawed because it can't be "objective",
( I know some cyberneticians who were saying that we soon won't be
talking in terms of "objective" vs "subjective". Those words will be
obsolete) let me ask a question. Does anyone believe that as two
people become more informed about any subject, as their knowledge and
information increases that they will become in agreement? I think the
answer is no, and not because the mind is flawed.
3) Some of you seem to be making science in general and AI in particular
a religion. Especially with pie-in-the-sky projects of making computers
AI identical to human intelligence. That strikes me as another immortality
project. Let us say for the sake of argument that you could ( sometime in
the year 2525). In that case the product will be necessarily flawed since
the human mind is flawed by your arguments. So what have your gained.
4) In the area of art, I prefer so-called irrationality and surrealism.
it is more interesting.
5) AI should concern itself with solving problems, discovering new ways to
solve and conceptialize problems. It is not as glamorous as making artificial
souls, but more practical and fruitfull.
Jeff "FREE" Beer, PAN recording artist
------------------------------
Date: 7 Oct 87 14:56:14 GMT
From: umn-d-ub!umn-cs!ramarao@rutgers.edu (Bindu Rama Rao)
Subject: Re: Goal of AI: where are we going?
Is the Human mind flawed?
Can we pass such a judgement without knowing anything about the human mind?
Do we really understand how the mind works?
Aren't we trying to model the mind because we are in awe of all the
power the mind posesses?
Is the mind flawed just because humans make decisions based on
their emotional involvement? Isn't the mind used for analysis only
while emotions play a major part in formulating the final decision?
Let's not hastily dismiss the human mind as flawed.
-bindu rama rao.
------------------------------
Date: 9 Oct 87 15:32:59 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: Goal of AI: where are we going?
In article <2281@umn-cs.UUCP>, ramarao@umn-cs.UUCP (Bindu Rama Rao) writes:
>
> Is the Human mind flawed?
>
> Can we pass such a judgement without knowing anything about the human mind?
>
> Do we really understand how the mind works?
Let's draw an analogy. You are driving an X-Brand car from Pittsburgh to
Atlanta and halfway there it bursts into flame. Without knowing how the
car works you can conclude it was flawed.
Mr X. goes to an employment interview and gets angry or flustered and
says something that causes him to be rejected. Without knowing how his
mind works you can conclude it was flawed.
> Aren't we trying to model the mind because we are in awe of all the
> power the mind posesses?
Of course we are. But saying the mind is enormously powerful is not
contradicted by saying it's not perfect. A car with a big engine is
enormously powerful and almost certainly not perfect.
> Is the mind flawed just because humans make decisions based on
> their emotional involvement? Isn't the mind used for analysis only
> while emotions play a major part in formulating the final decision?
Factually, we know the mind is flawed because we observe that it does
not do what we expect of it. As a hypothesis, we can test the idea
that it is flawed because of the action of what we call emotions. As
a further hypothesis, we can also test the idea that emotions motivate
all human activity. Personally, I like both those hypotheses.
Question of definition here: do we agree that emotion, reason,
consciousness, will, etc., are all functions of the mind?
> Let's not hastily dismiss the human mind as flawed.
Who's dismissing it? I know my car is flawed, but I can't afford to
dismiss it. I'm not dismissing my mind either. How could I? :-)
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 10 Oct 87 11:24:28 GMT
From: k.cc.purdue.edu!l.cc.purdue.edu!cik@j.cc.purdue.edu (Herman
Rubin)
Subject: Re: Goal of AI: where are we going?
In article <1368@houdi.UUCP>, marty1@houdi.UUCP (M.BRILLIANT) writes:
> In article <2281@umn-cs.UUCP>, ramarao@umn-cs.UUCP (Bindu Rama Rao) writes:
> >
> > Is the Human mind flawed?
> >
> > Can we pass such a judgement without knowing anything about the human mind?
> >
> > Do we really understand how the mind works?
>
The human mind is definitely flawed, very fortunately. I do not see how an
intelligent entity can fail to be flawed if it has only the computing power
of the universe available.
I define intelligence as the ability to deal with a _totally unforeseen
situation_. It is easy to give examples in which the amount of information
needed to effect a logical decision would require more memory than the size
of the universe permits. Therefore, dealing with such a situation _requires_
that such extralogical procedures as intuition, judgment, somewhat instinctive
reactions, etc., must be involved. That is not to say that one cannot find out
that certain factors are of lesser importance. But the decision that these
less important factors can or should be ignored is still a matter of judgment.
Therefore, an intelligent treatment of a problem of even moderate complexity
requires that nonrational procedures must be used. These cannot be correct;
at most we can determine in _some_ cases that they are not too bad. In other
cases, we can only hope that we are not too far off.
There is no "rational" intelligent entity for moderately difficult problems!
--
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907
Phone: (317)494-6054
hrubin@l.cc.purdue.edu (ARPA or UUCP) or hrubin@purccvm.bitnet
------------------------------
Date: 10 Oct 87 17:01:55 GMT
From: udel!montgome@cs.rochester.edu (Kevin Montgomery)
Subject: Re: Goal of AI: where are we going?
>> In article <2281@umn-cs.UUCP>, ramarao@umn-cs.UUCP (Bindu Rama Rao) writes:
>> > Is the Human mind flawed?
C'mon guys, lighten up for a sec. Flawed implies a defect from it's
design. Therefore, if someone's mind doesn't do what it's designed
to do (namely help keep the organism alive, etc), THEN it's flawed
(ex: schizos, manics, etc). A "normal" person does NOT have a flawed
mind, just an illogical one. What do you expect when the old brain
(producing emotions, feelings and the like) is still in the design?
So the $64K answer is: no, the mind is not (usually) flawed, but it
is illogical. Is having an illogical mind a problem? Hell no! It's
what keeps organisms going- drives for self-preservation, procreation,
etc. While striving to be logical IS (i feel) a noble aspiration,
there's no way to totally shut out something like emotions so deeply
ingrained into the mental architecture. (one may even argue that
if we were to consider all things logically, then civilization would
die out rather quickly, but i'm not gonna touch that one) At any rate,
if you want to do some neato cognitive modelling stuff, then you've
got to (eventually) incorporate the functions of the old brain (illogic)
with the logical processes we normally consider. If you're gonna
do some neato expert system stuff involving pure logic, then don't worry
about it. `kay? `kay.
--
Kevin Desperately-trying-to-get-into-Stanford Montgomery
------------------------------
Date: 11 Oct 87 18:34:10 GMT
From: yale!krulwich@husc6.harvard.edu (Bruce Krulwich)
Subject: Re: Goal of AI: where are we going?
In article <1368@houdi.UUCP> marty1@houdi.UUCP (M.BRILLIANT) writes:
>Factually, we know the mind is flawed because we observe that it does
>not do what we expect of it.
If I expect my car to take me to the moon and it doesn't, is it
flawed?? No, rather my expectation of it is wrong. Similarly, we
shouldn't say that the mind is flawed until we're sure that our
definition of "intelligence" is perfect.
> As a hypothesis, we can test the idea
>that it is flawed because of the action of what we call emotions.
Why do you assume that emotions are a flaw?? Just maybe emotions are
at the core of intellegence, and logic is just a side issue.
>As
>a further hypothesis, we can also test the idea that emotions motivate
>all human activity. Personally, I like both those hypotheses.
If you think that emotions motivate all human activity, why do you
dismiss emotions as a flaw in the mind?? It seems to me that human
activity is a lot more "intelligent" than any AI system as of yet.
>Question of definition here: do we agree that emotion, reason,
>consciousness, will, etc., are all functions of the mind?
Yes, and not necessarily "flawed" ones.
Bruce Krulwich
ARPA: krulwich@yale.arpa Being true heros,
or krulwich@cs.yale.edu they lept into action.
Bitnet: krulwich@yalecs.bitnet (Bullwinkle)
UUCP: {harvard, seismo, ihnp4}!yale!krulwich (Any B-CC'ers out there??)
------------------------------
Date: 12 Oct 87 00:45:58 GMT
From: topaz.rutgers.edu!josh@rutgers.edu (J Storrs Hall)
Subject: Re: Goal of AI: where are we going?
krulwich@yale.ARPA (Bruce Krulwich):
If I expect my car to take me to the moon and it doesn't, is it
flawed??
If you expect your car to take you to the moon, then I would say
your mind *is* flawed...
--JoSH
:↑)
------------------------------
Date: 11 Oct 87 16:55:37 GMT
From: psuvax1!vu-vlsi!swatsun!scott@husc6.harvard.edu (Jay Scott)
Subject: Is the human mind flawed?
Here's how I think about it:
"Flawed" I take to mean "not-good in some particular respect." And "good"
does not have a fixed, absolute meaning. If you ask, "Is this rock good?"
I have to reply, "What for?" It may be good used as a piece of gravel but
bad used as a gemstone!
So in the same way, you may ask "Is the human mind flawed?" I answer
"Depends. Is there something you wanted to use one for?" If you think
minds just are, then "flawed" doesn't apply (neither does "perfect").
But if you want to use a mind to, say, do math, you're likely to be annoyed
at its tendency to make mistakes--a flaw, for your purposes.
--
Your opinion may vary. I can only define words as I use them, not as you may.
Jay Scott
...bpa!swatsun!scott
------------------------------
End of AIList Digest
********************
∂12-Oct-87 0610 LAWS@KL.SRI.Com AIList V5 #234 - Seminars, Statistics Conference
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 12 Oct 87 06:10:03 PDT
Date: Sun 11 Oct 1987 22:34-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #234 - Seminars, Statistics Conference
To: AIList@SRI.COM
AIList Digest Monday, 12 Oct 1987 Volume 5 : Issue 234
Today's Topics:
Seminar - Systems with Multiple Expertise (BBN) &
Very Large Traveling Salesman Problems (Stanford) &
AI in Manufacturing (SU) &
Pengi: An Implementation of a Theory of Activity (SU) &
Persistence, Intention, and Commitment (AT&T),
Conference - AI and Statistics at JSM
----------------------------------------------------------------------
Date: Mon, 28 Sep 1987 10:34 EDT
From: Marc Vilain <MVILAIN at G.BBN.COM>
Subject: Seminar - Systems with Multiple Expertise (BBN)
[Forwarded from the IRList Digest.]
BBN Science Development Program
AI/Education Seminar Series
SYSTEMS WITH MULTIPLE EXPERTISE
Alexander Makarovitsch
Computer Science Department, West Catholic University
(Angiers, France)
BBN Laboratories Inc.
10 Moulton Street
Large Conference Room, 2nd Floor
10:30 a.m., Tuesday, September 29, 1987
Abstract: By a system with multiple expertise, we mean one containing
two or more expert systems, all working on a common information domain.
Three such systems under current development will be briefly reviewed.
(1) Syclope, a system being developed for the French Board of
Electricity for aiding agents working under risky conditions to
improve their task behavior;
(2) Sonar, a system being developed for the Bull Computer Group for
aiding in the design, operation, and maintenance of computer
networks;
(3) Link, a system being developed for the Bull Group for aiding
decision makers in the networked computer area in the processes of
product planning.
The review will focus on the difficulties encountered in key aspects of
the development process: the acquisition of expertise, knowledge
representation, man/machine interface, and interactions amopng the
system and multiple users and experts.
------------------------------
Date: Fri 2 Oct 87 15:50:59-PDT
From: Anil R. Gangolli <GANGOLLI@Sushi.Stanford.EDU>
Subject: Seminar - Very Large Traveling Salesman Problems (Stanford)
15-October-87: David Johnson (AT&T Bell Labs)
Near-Optimal Solutions to
Very Large Traveling Salesman Problems
Most experimental studies of algorithms for the Travel-
ing Salesman Problem (TSP) have concentrated on relatively
small test cases, instances with 100 cities or less. In
practice, however, much larger instances are frequently
encountered, both in engineering and scientific applica-
tions. This talk begins by surveying complexity results
about the TSP and the status of algorithms for finding
optimal solutions to small instances. It then goes on to
report the results of experiments with standard TSP heuris-
tics on large instances, from 500 cities to 100,000, examin-
ing the trade-offs obtainable between running time and qual-
ity of solution. Most of the standard heuristics will be
compared, including such new approaches as ``simulated
annealing,'' but particular emphasis will be placed on the
acknowledged ``champion,'' the sophisticated Lin-Kernighan
algorithm. Using various programming tricks, we have imple-
mented a version of this heuristic for the Euclidean case
that remains feasible even for 10,000 city instances (8
hours on a minicomputer), and continues to find tours that
are within 2% of optimal. For 20,000 or more cities, we
could still obtain tours that were within 5% of optimal
using Lin-Kernighan as a subroutine in a partitioning scheme
suggested by Karp. If one is willing to settle for slightly
worse tours, an approximate version of the Christofides
heuristic seems to stay within 20% of optimal and has quite
acceptable running times even for 100,000 cities.
------------------------------
Date: Fri, 9 Oct 1987 15:16 PDT
From: Marty Tenenbaum <TENENBAUM@SPAR-20.ARPA>
Subject: Seminar - AI in Manufacturing (SU)
FIRST-CUT: A Knowledge-based CAD/CAM System
for Concurrent Product and Process Design
Prof. Mark Cutkosky (ME)
Friday, Oct. 16 at 3:30 pm.
Terman 556
Abstract: FIRST-CUT is a novel CAD/CAM system for rapid prototyping of
mechanical parts. Parts are designed interactively by graphically
composing a high-level plan for producing them. A plan consists of
abstract machining operations, such as "make hole" or "make pocket".
As each operation is added, expert systems check feasibility and fill
in details (e.g., whether a hole should be drilled, milled, or bored.)
Also, a solid modeler incrementally simulates the plan to detect
geometric interference problems and to enable the designer to
visualize the part taking shape. Completed plans are compiled into
NC-code and run on a table-top milling machine to physically
instantiate the design.
A second part of the project is concerned with monitoring the actual
execution of process plans on specially instrumented machine tools,
and using the results to refine the knowledge base and produce better
plans.
A live demonstration will follow the talk.
Students seeking an exciting real-world domain for AI research (in
areas such as planning, spatial reasoning, knowledge-acquisition and
learning, intelligent agents, signal understanding and man-machine
communication) are especially invited.
------------------------------
Date: Fri 9 Oct 87 15:47:14-PDT
From: Anne Richardson <RICHARDSON@Score.Stanford.EDU>
Subject: Seminar - Pengi: An Implementation of a Theory of Activity
(SU)
Daniel Weise is hosting Phil Agre here at Stanford on Tuesday, October 27
who will be giving the following talk in Bldg. 200, Rm. 303 at 4:15:
***For any questions, please contact Daniel@mojave.***
Pengi: An implementation of a theory of activity
Phil Agre
MIT Artificial Intelligence Laboratory
AI has typically sought to understand the organized nature of human activity
in terms of the making and execution of plans. There can be no doubt that
people use plans. But before and beneath any plan-use is a continual
process of moment-to-moment improvisation. An improvising agent might use a
plan as one of its resources, just as it might use a map, the materials on a
kitchen counter, or a string tied round its finger. David Chapman and I
have been studying the organization of the most common sort of activity, the
everyday, ordinary, routine, familiar, practiced, unproblematic activity
typified by activities like making breakfast, driving to work, and stuffing
envelopes. Our theory describes the central role of improvisation and the
inherent orderliness, coherence, and laws of change of improvised activity.
The organization of everyday routine activity makes strong suggestions about
the organization of the human cognitive architecture. In particular, one can
get along remarkably well with a peripheral system much as described by Marr
and Ullman and a central system made of combinational logic. Chapman has
built a system with such an architecture. Called Pengi, it plays a
commercial video game called Pengo, in which a player controls a penguin to
defend itself against ornery and unpredictable bees. The game requires both
moderately complex tactics and constant attention to opportunities and
contingencies. I will outline our theory of activity, describe the Pengi
program, and indicate the directions of ongoing further research.
------------------------------
Date: Thu 8 Oct 1987 12:40:14
From: dlm@allegra.att.com
Subject: Seminar - Persistence, Intention, and Commitment (AT&T)
Title: Persistence, Intention, and Commitment
Speaker: Philip R. Cohen
Affiliation: SRI International Menlo Park, CA
Place: AT&T Bell Laboratories Murray Hill 3D-473
Date: October 8, 1987 1:30 PM.
(work done jointly with Hector Levesque)
Abstract:
This talk explores principles governing the rational balance among an
agent's beliefs, goals, actions, and intentions. Such principles provide
specifications for artificial agents, and approximate a theory of human
action (as philosophers use the term). By making explicit the conditions
under which an agent can drop his goals, i.e., by specifying how the
agent is _committed_ to his goals, the formalism captures a number of
important properties of intention. Specifically, the formalism provides
analyses for Bratman's three characteristic functional roles played
by intentions, and shows how agents can avoid intending all the foreseen
side-effects of what they actually intend. Finally, the analysis shows
how intentions can be adopted relative to a background of relevant beliefs
and other intentions or goals. By relativizing one agent's intentions in
terms of beliefs about another agent's intentions (or beliefs), we
derive a preliminary account of interpersonal commitments.
------------------------------
Date: 7 Oct 87 12:26:16 GMT
From: ihnp4!erc3bb!may@ucbvax.Berkeley.EDU (M.A.Yousry)
Subject: Conference - AI and Statistics at JSM
At the August 22-25, 1988 Joint Statistical Meetings (American
Statistical Association, Biometric Society, Institute of Mathematical
Statistics) in New Orleans, I'll be chairing an invited session, titled
"Bridging the Gap, Artificial Intelligence and Statistics," on solving
problems using combinations of AI and statistical techniques.
Both applied and theoretically oriented papers will be considered.
Potential areas might include fault diagnosis, process control,
reasoning with uncertainty, ... If you are interested in giving a talk,
please send a short abstract to:
...!{ihnp4, allegra}!erc780!may
or
Mona Yousry, (609) 639-2405
AT&T - ERC
PO Box 900
Princeton, NJ 08540
------------------------------
End of AIList Digest
********************
∂15-Oct-87 0150 LAWS@KL.SRI.Com AIList V5 #235 - Business and Marketing, Neuromorphic Terminology
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Oct 87 01:50:45 PDT
Date: Wed 14 Oct 1987 23:14-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #235 - Business and Marketing, Neuromorphic Terminology
To: AIList@SRI.COM
AIList Digest Thursday, 15 Oct 1987 Volume 5 : Issue 235
Today's Topics:
Queries - Italian AI & NExpert & Scheme as a First Lisp &
Engineer/Scientist Expert Systems &
Connection Machine Applications to Vision &
AI Workstations & Learning Software & Prolog Shopping,
Business - Expert Systems Company Financing & AI Marketing,
Neuromorphic Systems - Terminology
----------------------------------------------------------------------
Date: 12 Oct 87 07:26:23 GMT
From: imagen!atari!portal!cup.portal.com!tony_mak_makonnen@ucbvax.Berk
eley.EDU
Subject: european connection
I would like to E-mail to people in Italy interested in the kind of things we
discuss here . i know there is a connection thru Amsterdam and Turin . Any
pointers on how to do it and who to contact first are appreaciated . I
speak and write italian fluently and will gladly accept messages in that
language
------------------------------
Date: Mon, 12 Oct 87 13:16 MET
From: SYS_MS@bmc1.uu.se
Subject: NExpert
Neuron Data's NExpert system shell should soon be available for the Macintosh.
Have anyone out there used it for real development. What is the performance
compared to the VAX implementation. Pro's and con's of NExpert?
Mats
------------------------------
Date: Mon, 12 Oct 87 09:47:42 -0400
From: howell%community-chest.mitre.org@gateway.mitre.org
Subject: Scheme as a first lisp?
I'm interested in learning lisp "in my spare time", and I'd
prefer to do it on my Sun 3/75. For that reason, I'm thinking
about bringing GNU C Scheme up on the Sun. Before I do, I have a few
questions (of obvious neophyte level!). Thanks in advance for
any responses (please respond directly, I'm not on this list).
1) How solid is GNU Scheme? I'm using GNU EMACS and GNU
BISON (== YACC), and I've been really happy with both, so
I imagine GNU Scheme is fairly bug-free...
2) How different is Scheme from Common Lisp and Franz?
3) Is it a good idea/bad idea/neutral idea for someone intending
to learn lisp to start with Scheme?
4) If I go with Scheme, are there other recomended books/articles
in addition to "Structure and Interpretation of Computer
Programs" by Abelson and Sussman(s) [Sussmen? sorry...]
Thanks for any help.
Chuck Howell
the MITRE Corporation, Mail Stop Z645
7525 Colshire Drive, McLean, VA 22102
(703) 883-6080
ARPA: howell@mitre.arpa
------------------------------
Date: 14 Oct 87 11:23:00 PDT
From: "SEF::BROWER" <brower%sef.decnet@nwc-143b.arpa>
Reply-to: "SEF::BROWER" <brower%sef.decnet@nwc-143b.arpa>
Subject: Engineer/Scientist Expert System info
We are looking into the possibility of creating an expert system to
capture the expertise of engineers/scientists and would appreciate any
information anyone has on existing systems of this nature or systems being
developed of this nature.
My address is: Brower@NWC-143B.ARPA until 19 Oct. 87.
After Oct. 19 my address changes to: Brower@NWC.ARPA.
Thank you in advance. Roger Brower
------------------------------
Date: 14 Oct 87 05:19:37 GMT
From: jason@locus.ucla.edu
Subject: Looking for connection machine applications to vision
I am currently beginning to look into the area of vision research
applied to the connection machine, or other connectionist architectures.
I would appreciate any good references and input in this area.
Jason Rosenberg
jason@CS.UCLA.EDU
------------------------------
Date: Wed, 14 Oct 87 19:40 N
From: KOLB%HTIKUB5.BITNET@wiscvm.wisc.edu
Subject: help! (ai-workstations)
hi out there,
we are a (for Holland) pretty old and matured AI&NLP research group, but
so is our hardware equipment, which we share with the rest of the university.
Now we seem to have the chance of getting some stuff such as workstations
on our own. Any recommendations (or - even more useful - warnings)?
what we're looking for is an integrated environment with good PROLOG-, LISP-
and maybe some object-oriented facilities, but also capable of managing
old-fashioned languages such as pascal and C. Good graphics facilities would
help, too.
Please, reply directly to me. I'm gonna summarize the results for the net,
if wanted.
Thanx, hap kolb
Address: EMAIL: kolb@htikub5.bitnet
SNAILMAIL: hap kolb
Tilburg University - SLE
Postbus 90153
NL-5000 LE Tilburg
The Netherlands
------------------------------
Date: Tue, 13 Oct 87 10:12:40 GMT
From: Richard White <rw%aiva.edinburgh.ac.uk@NSS.Cs.Ucl.AC.UK>
Subject: Query - Learning software
The Edinburgh Computing and Social Responsibility (CSR) group
are looking for software which may beused or adapted for use
in an AI teaching module which will (hopefully!) be offered to
Scottish school children in 1988, at least on a trial basis.
The module, aimed at 16-18 year olds, is concerned with the
study of learning in both human and machines. Areas of
interest include induction, discovery and analogy based learning.
What we are short of are sample programs which can be used to
illustrate some of the problems involved in the study and simulation
of these processes. By necessity these have to be simple and relatively
small, the target machines being Nimbus's (British IBM-compatible PC).
Prolog would be the preferable language, but then we can't be too choosy!
Software should be public domain as we are running on a **very** small
budget.
If anyone knows of anything which might be suitable we would be very
grateful to hear about it. Could you Email any replies DIRECT to me.
Thanks in anticipation,
Richard White (on behalf of CSR group)
JANET: R.White@uk.ac.edinburgh
ARPA: R.White%uk.ac.ed@nss.ucl.ac.uk
UUCP: ...!ukc!ed.ac.uk!R.White
------------------------------
Date: 14 Oct 87 13:46:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: Prolog shopping
I'm doing some serious shopping for an industrial strength Prolog
to run under VAX/VMS. The only vendors of which I am aware are:
1. Quintus
2. IF/Prolog (Munich Germany)
3. Prolog-1 from Expert Systems International
Desirable features include:
1. nice environment/editor for changing and testing
2. external DB - preferably based on SQL
3. ability to call external languages, eg FORTRAN routines.
I'd be happy to hear about any new products, assessments, suggestions, etc.
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: 13 Oct 87 16:09:18 GMT
From: jbn@glacier.stanford.edu (John B. Nagle)
Subject: Re: Expert Systems Company Financing...
Right now, the venture capital community has had it with expert systems.
Hambrecht of Hambrecht and Quist, one of the more influential venture
capitalists, has been quoted as saying "Artificial intelligence is the most
effective means yet invented for separating investors from their money".
There are no AI startup success stories yet, remember; nothing comparable
to SUN or Lotus has happened. A few companies made it to IPO, but the
stocks never took off. Of the companies that received a lot of public
attention, the score is as follows.
Annual Annual Yesterday P/E
High Low
Intellicorp 11 1/8 4 1/8 5 3/4 29
Teknowledge 21 5/8 8 13 1/4 loss
Symbolics 6 1/8 3 3 1/4 loss
Lisp Machines (bankrupt)
So forget an expert system startup using the venture capital route until
somebody makes it.
But venture capital is a fad-driven industry. Neural nets are hot
this month.
John Nagle
[John tells me there's a downbeat article on AI in the latest
Forbes. (I hope I got that right.) -- KIL]
------------------------------
Date: 14 Oct 87 16:11:57 GMT
From: iscuva!randyg@uunet.uu.net (Randy Gordon)
Subject: Re: Expert Systems Company Financing...
But...
That really doesn't reflect on AI's success. There have been quite a number
of wildly sucessful AI projects that I know of, but they are usually buried
deep in companies that do other things, and noone talks about them, so
they won't lose competitive advantage.
None of the pure AI companies really had a chance. All they sold were tools
to solve problems, and consulting services. But one tool generates many
end products, and theres only so much training you can do before your customer
knows as much as you do.
Companies that sell end products that use AI techniques(such as Syntelligence,
or the thousand and one genetic engineering companies) are doing quite well.
So are the ones that use AI as part of a tool to increase productivity or
spread expertise, like Dec.
If any of those pure AI companies had ANYONE with decent marketing(not sales!)
experience, they would have started generating applications, (with tools as a
sideline). Theres a HUGE vein of expertise out there to be mined. Many
industries lack the will, expertise, or political situation to make use of the
knowledge that exists and the AI techniques necessary to utilize it.
AI techniques can fulfill needs that are difficult to answer with other
technologies. In combination with more ordinary programming techniques, you
can provide a demonstratably superior product in many areas. But you have
to be answering needs!
AI companies don't have problems because they are AI, they have problems
because noone in them really understands how to succeed as a business,
rather than as a glorified consulting firm.
Randy Gordon
------------------------------
Date: Wed 14 Oct 87 22:16:47-PDT
From: Ken Laws <Laws@KL.SRI.Com>
Reply-to: AIList-Request@SRI.COM
Subject: AI Marketing
Part of what we are seeing in AI is the evolution from horizontal to
vertical marketing. Vertical integration (i.e., applications) had to
wait for the horizontal suppliers to develop their machines and software
-- with the exception of a few early systems such as Dendral and R1/XCON.
The horizontal market has saturated, though, partly because it is much
easier to develop a general-purpose system than it is to really understand
a customer's applications and needs (in addition to developing an AI
system capable of handling previously unsolved problems). Unless some
new market opens up -- business, military, educational, or consumer --
the horizontal companies have now sold to everyone interested in buying.
The companies that will survive are the ones cultivating vertical markets
such as warehousing or the printing industry. In some cases these companies
are now offering higher priced software with reduced functionality, but
with vocabulary and customer support aimed at a specific industry. In
other cases the applied systems have not yet become visible simply because
it takes a long time to turn a general tool into a useful tool. Expert
systems are not dead; the successful ones are just going through another
development cycle. The resulting proprietary systems will be hyped in
the trade journals rather than the research journals, and will be part
of the commercial woodwork from now on.
-- Ken
------------------------------
Date: 11 Oct 87 03:32:10 GMT
From: wcalvin@well.UUCP (William Calvin)
Reply-to: wcalvin@well.UUCP (William Calvin)
Subject: Re: Neural Networks - Pointers to good texts?
Best book on neural networks is THE CRUSTACEAN STOMATOGASTRIC GANGLION by
Selverston and Moulins (Springer 1987). If you mean neural-like networks,
try the Rumelhart et al PARALLEL DISTRIBUTED PROCESSING (MIT Press 1986).
We brain researchers sure get tired of hearing neural-like networks
referred to as "neural networks", an established subject for 25 years since
the days of Limulus lateral inhibition. Calling silicon networks "neural" is
about like the hype in the early days when every digital computer was
called a "brain" by the media.
William H. Calvin
University of Washington NJ-15, Seattle WA 98195
wcalvin@well.uucp wcalvin@uwalocke.bitnet
------------------------------
Date: 13 Oct 87 03:30:21 GMT
From: sabbath.rutgers.edu!leasure@rutgers.edu (David E. Leasure)
Subject: Re: Neural Networks - Pointers to good texts?
wcalvin@well.UUCP (William Calvin) writes:
> We brain researchers sure get tired of hearing neural-like networks
>referred to as "neural networks", an established subject for 25 years since
>the days of Limulus lateral inhibition. Calling silicon networks "neural" is
>about like the hype in the early days when every digital computer was
>called a "brain" by the media.
Maybe we could all agree on a more faithful/less ingratiating term?
Maybe connectionist processing models or neuromorphic (after
Touretzky), or fine-grained parallel processing? (even Rumelhart's
Parallel Distributed Processing?)
David E. Leasure
Rutgers/AT&T
[Connectionism is a subset of the neuromorphic approach that uses
coarse -- or distributed -- coding instead of single nodes to
represent concepts. It's like representing all entities by feature
vectors instead of by symbol or name. Fine-grained parallel processing
includes new architectures such as the Connection Machine that are
not related to neural networks (beyond being ideal simulation
substrates). I don't know how PDP differs from any other distributed
processing, but the latter includes contract nets and inferential
databases. I'm willing to use "neuromorphic", although I'm not sure
that any one term can adequately describe this diverse field. The
name that sticks, though, will be the one that is most effective in
prying money from the military and governmental fuding agencies -- and
I suspect that "neural networks" will win precisely because of its
misleading connotations. -- KIL]
------------------------------
Date: 12 Oct 87 13:35:59 GMT
From: ssc-vax!dickey@beaver.cs.washington.edu (Frederick J Dickey)
Subject: Re: Neural Networks - Pointers to good texts?
In article <4191@well.UUCP>, wcalvin@well.UUCP (William Calvin) writes:
> We brain researchers sure get tired of hearing neural-like networks
> referred to as "neural networks", an established subject for 25 years since
> the days of Limulus lateral inhibition.
I think the above says that "biological" neural nets have been studied as a
formal discipline for 25 years and that this great ancestry gives biology
prior claim to the term "neural nets". Assuming that this is a correct
interpretation, let me make the following observation. In 1943, McCulloch
and Pitts published a paper entitled "A logical calculus of the ideas
immanent in neural nets". Minsky and Papert (Perceptrons) state that this
paper presents the "prototypes of the linear threshold functions". This paper
stikes me as clearly being in the "neural net-like" tradition. Now
1987-1943 = 44. Also note that 44 > 25. Therefore, it apears that the
"neural net-like" guys have prior claim to the term "neural net". :-).
------------------------------
End of AIList Digest
********************
∂16-Oct-87 0027 LAWS@KL.SRI.Com AIList V5 #236 - Semantics of Flawed Minds
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Oct 87 00:27:01 PDT
Date: Thu 15 Oct 1987 22:23-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #236 - Semantics of Flawed Minds
To: AIList@SRI.COM
AIList Digest Friday, 16 Oct 1987 Volume 5 : Issue 236
Today's Topics:
Semantics - Is the Human Mind Flawed?
----------------------------------------------------------------------
Date: Mon, 12 Oct 87 10:35 EST
From: "Linda G. Means" <MEANS@gmr.com>
Subject: ailist discussion of "flawed minds"
In AIList V5 #233,
ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
writes:
>Factually, we know the mind is flawed because we observe that
>it does not do what we expect of it.
Okay, let's take as given that the human mind is flawed.
If that judgment is the result of reasoning by a human mind
(i.e. a flawed mind), how can we take the judgment to be true?
Seems not unlike the paradox which arises from the statement,
"Everything I say is a lie".
Linda G. Means
GM Research Laboratories
means%gmr.com@relay.cs.net
[Ah, but that's a far cry from "Some things I say are lies." -- KIL]
------------------------------
Date: 12 Oct 87 17:12:39 GMT
From: ucsdhub!jack!man!sdsu!caasi@sdcsvax.ucsd.edu (Richard Caasi)
Subject: Re: Is the human mind flawed?
If the human mind was flawless we wouldn't be debating this issue.
To determine how flawed the human mind is we need to first define the
characteristics of a flawless or perfect mind. Any suggestions?
It certainly shouldn't have the limitations of Turing machines, that
is, it should be able to "solve" non-computable functions non-
algorithmically. Given perfect information as input, its output
should be likewise perfect, right? Or perhaps its output should
always be perfect regardless of how imperfect or incomplete its
inputs are. (Whcih violates the CS law of Garbage In Garbage Out)
Drawing an analogy with ideal operational amplifiers
in electronics, the perfect mind can be characterized by infinite
memory, zero learning time, zero search and recall time, sensory
perception with infinite bandwidth (flat frequency response from
negative infinity to positive infinity), zero computation time, and
knowledge of future inputs, etc., etc. (What do we have - God?)
Question: Does such a mind exist or is nothing perfect in the real
world?
------------------------------
Date: 12 Oct 87 20:12:26 GMT
From: pioneer!eugene@ames.arpa (Eugene Miya N.)
Subject: Re: Goal of AI: where are we going?
In article <578@louie.udel.EDU> montgome@udel.EDU (Kevin Montgomery) writes:
>>> In article <2281@umn-cs.UUCP>, ramarao@umn-cs.UUCP (Bindu Rama Rao) writes:
>>> > Is the Human mind flawed?
>C'mon guys, lighten up for a sec. Flawed implies a defect from it's
>design. Therefore, if someone's mind doesn't do what it's designed
Having read the postings which followed this, consider that the human eye
has many blind spots, the largest where the optic nerve is and many
smaller ones. The ear isn't perfect either. Also consider how we can
be fooled by Necker illusions, visual, verbal, auditory, etc. Flawed
many be too strong a word. Is the greater "mind" be flawed if it's
components and inputs are "flawed?" I prefer the "Just is" hypothesis.
On emotions: you may have something there, but AI people are not the people
to answer that question. A fellow I corresponded with on AI-Digest a
while noted he had a difficult time writing a Social Worker expert
system. Harder to dish out artificial compassion than artificial
Discrimination.
From the Rock of Ages Home for Retired Hackers:
--eugene miya
NASA Ames Research Center
eugene@ames-aurora.ARPA
"You trust the `reply' command with all those different mailers out there?"
"Send mail, avoid follow-ups. If enough, I'll summarize."
{hplabs,hao,ihnp4,decwrl,allegra,tektronix}!ames!aurora!eugene
------------------------------
Date: 12 Oct 87 20:23:46 GMT
From: gatech!pyr!kludge@rutgers.edu (Scott Dorsey)
Subject: Re: Is the human mind flawed?
If a thing is not perfect, it is flawed def. flaw
The human mind is a thing if it weren't, we wouldn't
talk about it
Nothing is perfect My mother said this
-------------------------------------------------------------------------------
The human mind is flawed
QED.
--
Scott Dorsey Kaptain_Kludge
SnailMail: ICS Programming Lab, Georgia Tech, Box 36681, Atlanta, Georgia 30332
Internet: kludge@pyr.gatech.edu
uucp: ...!{decvax,hplabs,ihnp4,linus,rutgers,seismo}!gatech!gitpyr!kludge
------------------------------
Date: 12 Oct 87 15:11:38 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Is the human mind flawed?
In article <17489@yale-celray.yale.UUCP>, krulwich@gator..arpa
(Bruce Krulwich) writes:
> In article <1368@houdi.UUCP> marty1@houdi.UUCP (M.BRILLIANT) writes:
> >Factually, we know the mind is flawed because we observe that it does
> >not do what we expect of it.
>
> If I expect my car to take me to the moon and it doesn't, is it
> flawed?? No, rather my expectation of it is wrong. Similarly, we
> shouldn't say that the mind is flawed until we're sure that our
> definition of "intelligence" is perfect.
There's a subtlety here. Your car is obviously not designed to go to
the moon; it won't come near trying. But I suggested that your car
should take you "from Pittsburgh to Atlanta" without bursting into
flame. That's not an unreasonable expectation, because, though it
probably wasn't designed for those particular roads, cars like it
usually do it successfully. Similarly, if I usually go through
interviews without "bursting into flame," I expect to be able to do it
regularly, and if once I screw up, I have to conclude that there is a
flaw somewhere.
> > As a hypothesis, we can test the idea
> >that it is flawed because of the action of what we call emotions.
>
> Why do you assume that emotions are a flaw?? Just maybe emotions are
> at the core of intellegence, and logic is just a side issue.
Note, please. I did not "assume that emotions are a flaw." First, I
argued that there was a flaw, and though that argument was challenged,
my reliance on that argument is obviously "why" I went on to the next
step. Second, I obviously did not "assume" anything about emotions; I
offered a hypothesis about emotions. "Why" I offered that hypothesis
is that it was suggested by an article I quoted:
== > Is the mind flawed just because humans make decisions based on
== > their emotional involvement? ....
> If you think that emotions motivate all human activity, why do you
> dismiss emotions as a flaw in the mind?? It seems to me that human
> activity is a lot more "intelligent" than any AI system as of yet.
Clearly I did not dismiss anything. Quoting again from my article:
== > Let's not hastily dismiss the human mind as flawed.
==
== Who's dismissing it? I know my car is flawed, but I can't afford to
== dismiss it. I'm not dismissing my mind either. How could I? :-)
Without trying to embarrass anybody, I would like to ask whether Mr.
Krulwich thought he was answering logically, and, if so, whether his
expectation that he could do so was any more reasonable than the
hypothetical expectation that his car could take him to the moon. I
think we try to do things with our minds that they can not successfully
do. Even if the flaw is in the expectation, the expectation is created
by the mind, so to argue that the flaw is not in the mind requires
great subtlety. (I am sure many readers will find my argument flawed.)
I might suggest that Mr. Krulwich answered more emotionally than
logically, but that statement would not only introduce "emotion" as an
undefined term, but also invite us to "dismiss" what seem to be some
vital mental processes. Just as physicians accept the human body for
what it is, without embarrassment, so should we accept the human mind.
Physically, all human bodies are different, and none are perfect. Why
then should anyone insist that the mind is unflawed?
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 13 Oct 87 12:47:26 GMT
From: PT.CS.CMU.EDU!SPICE.CS.CMU.EDU!spe@cs.rochester.edu (Sean
Engelson)
Subject: What the hell does flawed mean, anyway?
Could someone please define flawed, as it applies (or may apply) to
the mind? Flawed with respect to the performance of what action?
Formal logic? Aristotelian logic? Type theory? NP-complete
computations? Getting emotional? You need referents! I think that
most people are just talking past each other, as they are using
different referents. I am not getting involved yet, as I don't think
that I know what referents are appropriate---if anyone thinks they
know: What are they???
-Sean-
------------------------------
Date: 10 Oct 87 10:27:50 GMT
From: ihnp4!homxb!mtuxo!mtune!codas!killer!usl!khl@ucbvax.Berkeley.EDU
(Calvin K. H. Leung)
Subject: Re: Goal of AI: where are we going? (the right way?)
In article <1270@isl1.ri.cmu.edu> cycy@isl1.ri.cmu.edu (Christopher Young)
writes:
> I do believe that there is some mechanism to minds (or perhaps a variety of
> them). One reason why I am interested in AI (perhaps this is very Cog. Sci.
> of me, actually) is because I think perhaps it will help elucidate the ways
> in which the human mind works, and thus increase our understanding of human
> behaviour.
I agree with the idea that there must be some mechanisms that our
minds are using. But the different reasoning methods (proba-
bilistic reasoning, for instance) that we are studying in the
area of AI are not the way one reasons: we never use the Bayes'
Theorem in our thinking process. The use of those reasoning
methods, in my point of view, will never help increase our under-
standing of human behavior. Because our minds just don't work
that way.
Calvin K H Leung
--
Calvin K. H. Leung USL P.O. Box 41821
Lafayette, LA 70504
khl@usl.usl.edu.csnet 318-237-7128
------------------------------
Date: 14 Oct 87 15:47:09 GMT
From: ihnp4!homxb!genesis!odyssey!gls@ucbvax.Berkeley.EDU
(g.l.sicherman)
Subject: Re: Flawed human minds
> Let's draw an analogy. You are driving an X-Brand car from Pittsburgh to
> Atlanta and halfway there it bursts into flame. Without knowing how the
> car works you can conclude it was flawed.
>
> Mr X. goes to an employment interview and gets angry or flustered and
> says something that causes him to be rejected. Without knowing how his
> mind works you can conclude it was flawed.
And you could be wrong. Most likely Mr. X. didn't want the job after
all. He only wanted you to think he wanted the job. Give him credit
for some intelligence!
Of course Mr. X. is flawed from the company's point of view. But he's
flawed from his own point of view only if he can get what he wants and
doesn't. When this happens, the problem is not emotions but habits.
> Factually, we know the mind is flawed because we observe that it does
> not do what we expect of it.
By this criterion, we are all flawed. It brings to mind the one and only
law in J. B. Cabell's land of Philistia: "Do what seems to be expected of
you."
--
Col. G. L. Sicherman
...!ihnp4!odyssey!gls
------------------------------
Date: Wed 14 Oct 87 21:36:57-PDT
From: Ken Laws <Laws@KL.SRI.Com>
Reply-to: AIList-Request@SRI.COM
Subject: Re: Flawed human minds
I haven't read Cabell, but I find the quote interesting. I've been
saying something similar to family and friends for several years now --
people (esp. children) do what is expected of them, not what is demanded
of them. If teachers understood this they could get far more out of
their students. Expectation sets up a feedback loop in which the teacher
does whatever is necessary to elicit the desired behavior, whereas requests,
demands, etc., are events rather than processes. Similar feedback loops
are operative in the "lead" of a good dancer or the "ki" of a martial
artist.
-- Ken
------------------------------
Date: 14 Oct 87 00:19:54 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: What the hell does flawed mean, anyway?
In article <160@PT.CS.CMU.EDU>, spe@SPICE.CS.CMU.EDU (Sean Engelson) writes:
>
> Could someone please define flawed, as it applies (or may apply) to
> the mind? Flawed with respect to the performance of what action?
> Formal logic? Aristotelian logic? Type theory? NP-complete
> computations? Getting emotional? ....
All of the above.
> ... You need referents! I think that
> most people are just talking past each other, as they are using
> different referents. I am not getting involved yet, as I don't think
> that I know what referents are appropriate---if anyone thinks they
> know: What are they???
I claim that with respect to any referent the mind is flawed.
If any reader can define any referent with respect to which the
mind is perfect, I will admit my argument is flawed.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 15 Oct 87 00:35:32 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: Flawed human minds
In article <331@odyssey.ATT.COM>, gls@odyssey.ATT.COM (g.l.sicherman)
writes (quoting from something I wrote):
> > Let's draw an analogy. You are driving an X-Brand car from Pittsburgh to
> > Atlanta and halfway there it bursts into flame. Without knowing how the
> > car works you can conclude it was flawed.
> >
> > Mr X. goes to an employment interview and gets angry or flustered and
> > says something that causes him to be rejected. Without knowing how his
> > mind works you can conclude it was flawed.
>
> And you could be wrong. Most likely Mr. X. didn't want the job after
> all. He only wanted you to think he wanted the job. Give him credit
> for some intelligence!
>
> Of course Mr. X. is flawed from the company's point of view. But he's
> flawed from his own point of view only if he can get what he wants and
> doesn't. When this happens, the problem is not emotions but habits.
Also flawed from Mr. X's point of view. Sicherman argues that X only
seemed to get angry or flustered, in order to make sure the company
didn't make him an offer, because during the interview he decided he
didn't want a job with them. If I attributed Mr. X's actions to
intelligence I would expect him to conclude gracefully, let them make
an offer, and reject the offer, without making a bad impression on
somebody who later might be in a position to offer him a job in another
company. And I don't care whether you blame emotions or habits.
> > Factually, we know the mind is flawed because we observe that it does
> > not do what we expect of it.
>
> By this criterion, we are all flawed....
That's exactly what I meant.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
End of AIList Digest
********************
∂16-Oct-87 0251 LAWS@KL.SRI.Com AIList V5 #237 - Seminars, Connectionist Course, Conference
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Oct 87 02:51:36 PDT
Date: Thu 15 Oct 1987 22:54-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #237 - Seminars, Connectionist Course, Conference
To: AIList@SRI.COM
AIList Digest Friday, 16 Oct 1987 Volume 5 : Issue 237
Today's Topics:
Seminars - The Logical Foundations of Evidential Reasoning (SRI) &
The Matrix of Biological Knowledge (BBN) &
PROLOG and AI Applications - A European Perspective (UNISYS) &
Non-Deterministic Lisp (SRI) &
OB1: A Prolog-Based Object-Oriented Database (UNYSIS),
Course - Connectionist Summer School,
Conference - Computers in Engineering
----------------------------------------------------------------------
Date: Wed, 14 Oct 87 16:10:01 PDT
From: seminars@csl.sri.com (contact lunt@csl.sri.com)
Subject: Seminar - The Logical Foundations of Evidential Reasoning (SRI)
SRI COMPUTER SCIENCE LAB SEMINAR ANNOUNCEMENT:
THE LOGICAL FOUNDATIONS OF EVIDENTIAL REASONING
Enrique H. Ruspini
Artificial Intelligence Center
SRI International
Monday, October 19 at 4:00 pm
SRI International, Computer Science Laboratory, Room IS109
The approach proposed by Carnap for the development of logical bases
for probability theory is applied to formal structures that are based
on epistemic logics. Epistemic logics are modal logics introduced to
deal with issues that are relevant to the state of knowledge that
rational agents have about the real world. The use of epistemic
logics in problems of analysis of evidence is justified by the need to
distinguish among such notions as the state of a real system, the
state of knowledge possessed by rational agents, and the impact of
information on that knowledge.
Carnap's method for generating a universe of possible worlds is
followed using an enhanced notion of possible world that encompasses
descriptions of knowledge states. Within such generalized or
epistemic universes, several classes of sets are identified in terms
of the truth-values of propositions that describe either the state of
the world or the state of knowledge that rational agents have about it.
Probabilities defined over certain subsets of the epistemic universe
are then shown to have the properties of the belief and basic
probability assignment functions of the Dempster-Shafer calculus of
evidence.
Furthermore, extensions of a probability function defined over
epistemic subsets (representing different states of knowledge) to
truth-sets (representing true states of the real world) must satisfy
the interval probability bounds derived from the Dempster-Shafer
theory. These bounds correspond to the classical notions of lower and
upper probability and are the best possible, given a specific state of
knowledge.
Finally, the problem of combining the knowledge state of several
rational agents is also treated by consideration of epistemic
structures. The result of this analysis is a general formula for the
integration of evidence. From this formula and certain probabilistic
independence assumptions, the rule of combination of Dempster is
easily derived. The meaning of these independence assumptions is made
explicit through the insight provided by the formal structures that
are used to represent knowledge and truth.
NOTE FOR VISITORS TO SRI:
Please arrive at least 10 minutes early in order to sign in and
be shown to the conference room.
SRI is located at 333 Ravenswood Avenue in Menlo Park. Visitors
may park in the visitors lot in front of Building A (red brick
building at 333 Ravenswood Ave) or in the conference parking area
at the corner of Ravenswood and Middlefield. The seminar room is in
the International Building -- the white concrete structure on Ravenswood
to the East (left) of Building A. Visitors should sign in at the
International Building reception --- up the steps into the courtyard and
on the left.
IMPORTANT: Visitors from Communist Bloc countries should make the
necessary arrangements with Fran Leonard (415-859-4124) in SRI Security
as soon as possible.
------------------------------
Date: Tue 13 Oct 87 15:27:56-EDT
From: Marc Vilain <MVILAIN@G.BBN.COM>
Subject: Seminar - The Matrix of Biological Knowledge (BBN)
BBN Science Development Program
Joint Biotech and AI Seminar Series Lecture
"The Matrix of Biological Knowledge"
Kimberle Koile
BBN Labs
(KKOILE@G.BBN.COM)
BBN Labs
10 Moulton Street
2nd floor large conference room
10:30 am, Thursday October 15th
The body of experimental data in the biological sciences is immense and
growing rapidly. Its volume is so extensive that computer methods,
possibly straining the limits of current technology will be necessary to
organize the data. Moreover, it seems highly likely that there are a
significant number of as yet undiscovered ordering relations, new laws,
and predictive models embedded in the mass of existing information. To
employ this body of information productively, it will be useful to
create an extensive data/knowledge base, "the matrix of biological
knowledge," structured to provide a conceptual framework by the laws,
models, empirical generalizations, and physical foundations of the
modern biological sciences.
--- from a Santa Fe Institute press release
This talk will describe preliminary efforts to define and prototype parts of
the Matrix. These efforts took place at a summer workshop that was organized
as a result of a National Academy of Sciences report published in 1985,
"Models for Biomedical Research: A New Perspective." The workshop, sponsored
by the Santa Fe Institute with support from NIH, DOE, and several commercial
companies, was attended by fifty scientists from a variety of biology and
computer subdisciplines.
Note: A related talk on the Matrix will be given Friday morning
(announcement forthcoming) by Prof. Harold Morowitz of the
Department of Biophysics and Biochemistry at Yale University.
Prof. Morowitz chaired the Committee on Models for Biomedical
Research, which produced the above mentioned report, and
co-chaired the Workshop on the Matrix of Biological Knowledge.
------------------------------
Date: Wed, 14 Oct 87 15:50:48 EDT
From: finin@bigburd.PRC.Unisys.COM (Tim Finin)
Subject: Seminar - PROLOG and AI Applications - A European
Perspective (UNISYS)
AI Seminar
UNISYS Knowledge Systems
Paoli Research Center
Paoli PA
PROLOG AND AI APPLICATIONS - A EUROPEAN PERSPECTIVE
Raf Venken
BIM Prolog
Raf Venken, manager for BIM Prolog Research and Development, will be
visiting Logic Based Systems on Monday, October 19th. BIM is a high
performance Prolog which runs on UNIX-based SUN workstations as well
as VAXES under VMS, UNIX 4.2, and ULTRIX. BIM is involved in joint
research efforts with various universities throughout Europe and is a
member of ESPRIT (the "European MCC"). BIM has also contributed to
LOQUI, a large natural language project.
BIM claims to be the fastest general purpose Prolog system currently
available on the market. BIM includes "the first successful attempt
to include more intelligent debugging aids into the [Prolog] system"
and a "PARTIAL EVALUATION system which optimizes Prolog programs by
source-to-source transformations." BIM has also "extended the Prolog
language with the concept of MODULES to allow the easy development of
very large systems."
The talk will cover the philosophy and strategy behind BIM Prolog,
discuss current ESPRIT projects including a large NLP system, and
speculate about the future.
11:00am, Monday, October 19th
Cafeteria Conference Room
- if you are interested in attending, please send -
- mail to finin@prc.unisys.com or call 215-648-7446 -
------------------------------
Date: Wed, 14 Oct 87 11:54:41 PDT
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Non-Deterministic Lisp (SRI)
DEPENDENCY-DIRECTED BACKTRACKING IN NON-DETERMINISTIC LISP
Ramin Zabih (RDZ@SUSHI.STANFORD.EDU)
Computer Science Department
Stanford University
11:00 AM, MONDAY, October 19
SRI International, Building E, Room EJ228
Dependency-directed backtracking is a strategy for solving
generate-and-test search problems. Pure Lisp extended with McCarthy's
non-deterministic operator AMB is an elegant language for expressing
such problems. I will describe how to automatically provide
dependency-directed backtracking in SCHEMER, a non-deterministic Lisp
dialect.
It is also possible for SCHEMER to automatically provide other search
strategies than dependency-directed backtracking. In fact, SCHEMER
can support a large class of solution methods. I will show that
SCHEMER programs can make use of any algorithm for determining the
satisfiability of a propositional formula in Conjunctive Normal Form.
This is joint work with David McAllester.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Thu, 15 Oct 87 15:12:54 EDT
From: finin@bigburd.PRC.Unisys.COM (Tim Finin)
Subject: Seminar - OB1: A Prolog-Based Object-Oriented Database
(UNYSIS)
AI Seminar
UNISYS Knowledge Systems
Paoli Research Center
Paoli PA
OB1: A PROLOG-BASED OBJECT-ORIENTED DATABASE
Benjamin Cohen
SRI International
David Sarnoff Research Center
Princeton NJ 8540
In this talk I describe OB1, an object-oriented database facility. OB1
is a hybrid query language that incorporates most of the features of
relational query languages plus "view/objects" that allow sets as
values and recursive views. OB1 is implemented in Quintus Prolog and
includes server facilities that allow C & Fortran clients to query an
OB1 server over a SUN network. OB1 also has a graphics
Entity/Relationship data modeling editor used to design OB1 databases.
Ben will be here friday, October 23, from lunch time till 5 - I suppose
the talk would start around 1:30 or 2:00
2:00pm Friday, October 23
Cafeteria Conference Room
- if you are interested in attending, please send -
- mail to finin@prc.unisys.com or call 215-648-7446 -
------------------------------
Date: Wed 14 Oct 87 03:18:33-EDT
From: Dave.Touretzky@C.CS.CMU.EDU
Subject: Course - Connectionist Summer School
THE 1988 CONNECTIONIST MODELS SUMMER SCHOOL
ORGANIZER: David Touretzky
ADVISORY COMMITTEE: Geoffrey Hinton, Terrence Sejnowski
SPONSORS: The Sloan Foundation; AAAI; others to be announced.
DATES: June 17-26, 1988
PLACE: Carnegie Mellon University, Pittsburgh, Pennsylvania
PROGRAM: The summer school program is designed to introduce young neural
network researchers to the latest developments in the field. There will be
sessions on learning, theoretical analysis, connectionist symbol processing,
speech recognition, language understanding, brain structure, and neuromorphic
computer architectures. Students will have the opportunity to informally
present their own research and to interact closely with some of the leaders of
the field.
PARTIAL LIST OF FACULTY:
Yaser Abu-Mostafa (Caltech) James McClelland (Carnegie Mellon)
Dana Ballard (Rochester) David Rumelhart (Stanford)
Andrew Barto (U. Mass.) Terrence Sejnowski (Johns Hopkins)
Gail Carpenter (Boston U.) Paul Smolensky (UC Boulder)
Scott Fahlman (Carnegie Mellon) David Tank (AT&T Bell Labs)
Geoffrey Hinton (Toronto) David Touretzky (Carnegie Mellon)
George Lakoff (Berkeley) Alex Waibel (ATR International)
Yann Le Cun (Toronto) others to be announced
EXPENSES: Students are responsible for their meals and travel expenses,
although some travel assistance may be available. Free dormitory space will be
provided. There is no tuition charge.
WHO SHOULD APPLY: The summer school's goal is to assist young researchers who
have chosen to work in the area of neural computation. Participation is
limited to graduate students (masters or doctoral level) who are actively
involved in some aspect of neural network research. Persons who have already
completed the Ph.D. are not eligible. Applicants who are not full time
students will still be considered, provided that they are enrolled in a
doctoral degree program. A total of 50 students will be accepted.
HOW TO APPLY: By March 1, 1988, send your curriculum vitae and a copy of one
relevant paper, technical report, or research proposal to: Dr. David Touretzky,
Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, 15213.
Applicants will be notified of acceptance by April 15, 1988.
------------------------------
Date: Mon, 12 Oct 87 09:10:58 EDT
From: decvax!cvbnet!cheetah!rverrill@decwrl.dec.com (Ralph Verrilli)
Subject: Conference - Computers in Engineering
CALL FOR PAPERS
1988 ASME INTERNATIONAL COMPUTERS IN ENGINEERING
CONFERENCE AND EXHIBITION
SAN FRANCISCO HILTON
SAN FRANCISCO, CALIFORNIA
July 31 - August 3, 1988
REAL WORLD APPLICATIONS OF EXPERT SYSTEMS
AND ARTIFICIAL INTELLIGENCE
The theme for the 1988 ASME International Computers in Engineering
Conference will focus on the emerging applications of expert systems
and artificial intelligence.
This conference and exhibition provides a forum for engineers,
managers, researchers, vendors, and users to discuss relevant
issues, and to present ideas on computer technology and its impact
on the engineering workplace. Over 80 papers and panel sessions are
planned covering a broad spectrum of technical computing and
computers in the engineering community. The topics covered will
encompass: computer aided design and manufacturing, computer
simulation, robotics, interactive graphics, finite element
techniques, microprocessors, computers in educations, expert
systems, and artificial intelligence.
Papers are solicited in all areas related to the application,
development, research, and education with computers in mechanical
engineering. Contributions in the form of full-length papers or
extended abstracts are solicited. Accepted papers will be published
in the bound Conference Proceedings. Full length papers of special
note will be reviewed after the conference for publication in the
Society's magazine "Computers in Mechanical Engineering (CIME)".
The annual event is sponsored by the Computers in Engineering
Division of the American Society of Mechanical Engineers (ASME).
San Francisco is the site of this years conference.
DEADLINES :
Submission of three copies of draft contributions
(paper or extended abstract) November 30, 1987
Notification of acceptance to authors February 15, 1988
Submission of author-prepared mats April 1, 1988
For the following technical areas please send papers to the
respective program chairmen :
{
Computer Aided Manufacturing, Computer Simulation, Turnkey CAD/CAM,
Integration of CAD and CAM, Computer Aided Testing, Computer Aided
Design, Interactive Graphics :
Dr. Donald Riley
Dept. of Mechanical Engineering
University of Minnesota
111 Church Street
Minneapolis, MN 55455
612-625-0591/1809 }
{
Artificial Intelligence, Knowledge Based Systems :
Mr. M.F. Kinoglu
AI and Expert Systems Group
Control Data Corporation
1450 Energy Park Drive
Saint Paul, MN 55108
612-642-3817 }
{
Microprocessors, Robotics, Special Purpose Computers, Man-Machine
Interfaces :
Mr. David W. Bennett
Battelle Pacific Northwest Labs
P.O. Box 999
Richland, WA 99352
509-375-2159 }
{
Robotics in Education, Teaching CAD in Higher Education, University
- Industry Collaboration, Microcomputers in the Classroom,
Computer-Aided Learning :
Dr. Gary Kinzel
Ohio State University
Dept. of Mechanical Engineering
206 West 18th Street
Columbus, Ohio 43210
614-292-6884 }
{
Finite Element Techniques, Software Standards, Computational
Geometry :
Dr. Kumar K. Tamma
Dept of Mechanical Engineering and Aerospace Engineering
West Virginia University
Morgantown, West Virginia
304-293-4111 }
{
Computers in Energy Systems, Computational Fluid Dynamics,
Computational Heat Transfer, Combustion Modelling, Process Control :
Dr. Ahmed A. Busaina
Dept. of Mechanical Engineering
Clarkson University
Potsdam, New York
315-268-6574 }
Topics not in the above categories contact Technical Program
Chairman :
Mr. Edward M. Patton
US Army Ballistic Research Lab
Aberdeen Proving Grounds, MD 21005
301-278-6805
------------------------------
End of AIList Digest
********************
∂19-Oct-87 0133 LAWS@KL.SRI.Com AIList V5 #238 - Fault Diagnosis, Financing, AI Successes
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 19 Oct 87 01:32:48 PDT
Date: Sun 18 Oct 1987 23:14-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #238 - Fault Diagnosis, Financing, AI Successes
To: AIList@SRI.COM
AIList Digest Monday, 19 Oct 1987 Volume 5 : Issue 238
Today's Topics:
Queries - Fire, Women, and Dangerous Things & RB5X Robot &
Introductory Books on Lisp & "Eliza-Like" People Stories &
Net Mail to UK,
Application - Expert Systems for Fault Diagnosis,
Humor - "Eliza-Like" People Stories,
Education - Learning-Software Reference,
Business - Expert Systems Company Financing,
Opinion - The Success of AI
----------------------------------------------------------------------
Date: 13 Oct 87 08:27:52 GMT
From: cunyvm!unknown%psuvm.bitnet@ucbvax.Berkeley.EDU
Subject: Fire, Women, and Dangerous Things
I finally located a copy of George Lakoff's "Women, Fire, and
Dangerous Things: What Categories Reveal about the Mind" and
a quick look through the chapters seems to indicate that it
is an interesting synthesis.
Anyone out there read it already? I am interested in what
those with more experience in AI than I have think of Lakoff's
approach to categorization.
John M. Ford fordjm@byuvax
"The thing I hate about psychologists is that they are always
*classifying* everyone..."
------------------------------
Date: Fri 16 Oct 87 15:01:26-PDT
From: Matt Heffron <BEC.HEFFRON@ECLA.USC.EDU>
Subject: Query: "Not quite a toy" Robot
For lack of any more obvious place to ask this...
I have been given "custody" of a very sick "Not quite a toy" robot. (The R2D2
sort-of clone that is often seen attracting attention to vendors at trade
shows.) The robot was given to the principal of a small private school who
gave it to me in the hope that I can repair it, so they can use it at their
fund raising events. The problem is that although it has a manufacturer's
name, city and model/serial number, the manufacturer (RB Robot Corporation of
Golden, Colorado model RB5x) doesn't exist (according to the phone company).
Does anyone know someone who might have another of RB's robots (and have
schematics, or any documentation at all)? I'd rather fix what's there if I
can, instead of rebuilding the complete electronics sub-system from scratch.
Thanks in advance,
Matt Heffron BEC.HEFFRON@ECLA.USC.EDU
PS. I know that this is sort of a shot in the dark, but "netlanders" are
sufficiently knowledgeable that if anyone would know how to get some info
for this, they would. Thanks. MH
------------------------------
Date: Fri, 16 Oct 87 11:03:46 PDT
From: glasgow@marlin.nosc.mil (Michael G. Glasgow)
Subject: Introductory books on Lisp
I am new to AIList and AI programming and want to learn Lisp.
I have been looking through Steele's book, Common Lisp", and
have discovered that this is more of a reference manual than a
beginners guide. What I am wondering is if anyone can give me
the names of some good introductory Lisp books to get me started.
Thanks in Advance,
michael
Net: glasgow@marlin.nosc.mil
Reallife: NOSC - Code 423
271 Catalina Blvd.
San Diego, CA 92152-5000
------------------------------
Date: 16-OCT-1987 17:09:17
From: HANCOXPJ@MAIL.ASTON.AC.UK
Date: 16-Oct-1987 16:56 BST
Subject: Request for information
From: Dr P J Hancox <HANCOXPJ@uk.ac.aston>
Dept: Computer Science
Tel No: 021 359 3611 X4652
TO: Remote Addressee ( _POST IKBSBB@RL.VD )
TO: Remote Addressee ( _POST AILIST-REQUEST%COM.SRI.STRIPE@
CC: Remote Addressee ( _KIRK::WOONIMA )
I'm constructing a qualitative model for financial analysis and planning
for my PhD which I should finish in late 1988. I intend to supplement this
model with quantitative data held in a Financial Modelling
system(FPS/EPS2), to handle ambuiguous situations. I am therefore interested
in any work on:
qualitative models for financial analysis
automated interfacing between expert systems and financial
modelling systems.
Is there anyone out there doing or interested in similar work?
Irene Woon
JANET: woonimy@uk.ac.aston.kirk
uucp: ...seismo!mcvax!ukc!astonk!woonimy
phone: + 44 21 359 3611 extn 4272
Snailmail: Department of Computer Science and Applied Mathematics
Aston University
Birmingham. B4 7ET
United Kingdom
------------------------------
Date: 15 Oct 87 18:18:12 GMT
From: topaz.rutgers.edu!josh@rutgers.edu (J Storrs Hall)
Subject: "Eliza-like" people stories
I'm doing a paper on the relation of human conscious processes to
those of AI programs. I'm looking for stories which illustrate the
extent to which apparent human intelligence may actually consist of
Eliza-like verisimilitude. Example:
Customer: I'd like to return this pair of shoes. They're
both left shoes and one is two sizes smaller than
the other.
Clerk: We don't take returns. How do we know you haven't
worn them?
[from Reader's Digest]
Please send stories to me rather than the net...
--JoSH
------------------------------
Date: Fri, 16 Oct 87 14:04:55 MDT
From: yorick%nmsu.csnet@RELAY.CS.NET
Subject: Net mail to UK
Can any informed person out there tell me what is going on with
e-mail to the UK? There seems to have been some radical change
in the last month or so completely independent of the general
change in destination formats in the US (e.g. com, edu, gov, cs.net
and all that). The standard final component @ucl-cs.arpa no
longer seems to work as it has for a decade or so. A new
format is occuring in UK originating messages, in this list and elsewhere,
namely @nss.cs.ucl.ac.uk but that doesnt seem to
work as a destination from the US, moreover it is highly confusing
as it seems to import the internal UK JANET symbols (ac.uk)
into the arpanet address. Since it doesnt work maybe it doesnt matter.
There doesnt seem must use asking UK people as they dont know why
they can get out as usual but people aree having more trouble
reaching them. Another thing is that the preceding part of
the UK addresses (e.g. essex.ac.uk) in bloggs%essex.ac.uk@nss.whatever
is now being quoted randomly in orogianting headers in both orders
e.g. essex.ac.uk and uk.ac.essex. It always used to be the former.
Maybe someone in the UK knows what is going on there as it seems
that it must be UK rather that US stupidity. I'd be really
grateful for any wizard who can tell me either what's going
on, or, better still, how to get back to standard reliable
transatlantic e-mail.
Yorick Wilks.
[NSS.CS.UCL.AK.UC seems to have dropped out of the host
table at the moment. There is an entry for NS2..., but
the socket number differs from [128.41.9.3] and so must
be something other than a typo. UCL also has entries for
VTEST, TUNNEL, SAM, and TIGER, but not for UCL-CS. As for
the problems of the last month, I am beginning to get some
leads. The new Arpanet system insists that addresses contain
only official host names, and Arpanet hosts will convert
aliases to socket numbers if they can't determine the official
names. Many Unix systems, though, are still willing to send
and receive host aliases, but will reject mail to socket
numbers (since such mail in the past has been associated with
mailer loops). Mail from an Arpanet host to a Unix host may
therefore fail if the Arpanet host tables are not set up
exactly right. Many Unix postmasters are not aware of this
glitch, or perhaps do not know how to verify and correct the
Arpanet host tables. I presume that this has been the case
with UCL, although I don't know the nature of their system.
I will attempt to get things straightened out if I can get
a message through to UCL. -- KIL]
------------------------------
Date: 16 Oct 87 15:09:58 GMT
From: moss!erc3bb!may@RUTGERS.EDU (M.A.Yousry)
Subject: Re: Engineer/Scientist Expert System info
In article <8710150650.AA02610@ucbvax.Berkeley.EDU>,
brower%sef.DECnet@NWC-143B.ARPA.UUCP writes:
>
> We are looking into the possibility of creating an expert system to
> capture the expertise of engineers/scientists and would appreciate any
> information anyone has on existing systems of this nature or systems being
> developed of this nature.
>
We are working on an expert system to find root causes of fault
in a manufacturing process. We are using a statistical system to
filter the observations coming from the process, such as defects, or
analog measurments..then a rule based system is triggered by the statistical
output, uses the engineering knowledge and expertise to find root
causes of faults in the process.
Bob Parry ihnp4!erc780!bep
Mona Yousry ihnp4!erc780!may
------------------------------
Date: 16 Oct 87 14:00:48 GMT
From: ihnp4!homxb!vertigo!roller@ucbvax.Berkeley.EDU (P.MICHAELIS)
Subject: Re: "Eliza-like" people stories
> I'm doing a paper on the relation of human conscious processes to
> those of AI programs. I'm looking for stories which illustrate the
> extent to which apparent human intelligence may actually consist of
> Eliza-like verisimilitude.
I know this looks like a portion of a "M*A*S*H" script, but it really
did happen this way:
YOUNG, OVERWORKED DOCTOR: Why have you come to the hospital?
RECENTLY WOUNDED SOLDIER: Shrapnel wounds, sir.
YOUNG, OVERWORKED DOCTOR: How long have you been noticing these symptoms?
-- Paul Michaelis {AT&T Spine}!vertigo!roller
------------------------------
Date: Thu, 15 Oct 87 13:59:30 EDT
From: rapaport@cs.Buffalo.EDU (William J. Rapaport)
Subject: induction
>From: rw@aiva.edinburgh.ac.UK (Richard White)
Subject: Query - Learning software
The Edinburgh Computing and Social Responsibility (CSR) group
are looking for software which may be used or adapted for use
in an AI teaching module ...
Take a look at:
Robert L. Causey, "Simulations and Experiments in Philosophy of Science,"
[IBM] Perspectives in Computing, Vol. 7, No. 1 (Spring 1987), pp. 23-33.
William J. Rapaport
Assistant Professor
Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260
(716) 636-3193, 3181
uucp: ..!{ames,boulder,decvax,rutgers}!sunybcs!rapaport
internet: rapaport@cs.buffalo.edu
[if that fails, try: rapaport%cs.buffalo.edu@relay.cs.net
or: rapaport@buffalo.csnet ]
bitnet: rapaport@sunybcs.bitnet
------------------------------
Date: 16 Oct 87 18:08:44 GMT
From: faline!sabre!gamma!pyuxp!pyuxv!sr@bellcore.bellcore.com (S
Radtke)
Subject: Re: Expert Systems Company Financing...
In article <810@iscuva.ISCS.COM> randyg@iscuva.UUCP (Randy Gordon) writes:
>
>That really doesn't reflect on AI's success. There have been quite a number
>of wildly sucessful AI projects that I know of, but they are usually buried
>deep in companies that do other things, and noone talks about them, so
>they won't lose competitive advantage.
Come on, Randy, let's hear what the wildly successful AI projects were.
Most success stories I've heard had to be discounted considerably. They
tend to be stories about developments that are full of promise, rather
than systems that pay dividends or work for a living. The reports from
DEC about Xcon, for instance, did not include bottom line calculations
that include system development cost retrieval and maintenance cost, though
such support systems are part of the infrastructure and are hard to show as
profit centers.
Steve Radtke
pyuxv!sr
------------------------------
Date: 17 Oct 87 18:26:55 GMT
From: imagen!atari!portal!cup.portal.com!barry_night-person_stevens@uc
bvax.Berkeley.EDU
Subject: you CAN get funding for expert systems activities
It's true that the companies started around the large, LISP-based AI machines
have not done well.
I have recently finished a survey of 179 companies buying and using expert s
system tools. Also studied - several vendor companies for expert system
products. In short, the big machines aren't what they want -- that's why
the companies didn't do well.
Computer science-y things arent what they want, either. They are using
systems most that are:
simple to use, and in English (not in PROLOG)
easy to use to access databases, both in PCs and in mainframes
easy to interconnect, and to integrate with their corporate data, pgms
The smaller, simpler systems are doing well.
Also, venture capital firms are cautious about startups. Most prefer to let
someone else take the big risks. A few firms, such as Crosspoint and
The Sprout Group, will deal with seed.
To get funding from a professional source, you need more than a top drawer
product idea. You need a quality management team, or the knowledge that one
needs to be built; you need a good marketing study, PROVING that a demand
for your product exists, and sizing that demand. These, at a minimum.
If you also have a good handle on how your venture will work operationally,
you are just that much better off. Most of all, you'll need a good estimate
of what needs to be done to get your idea into production, and how much it
will cost. You also need a top-quality professional technical team to
do it with.
It may help to realize that you're fighting significant odds. In researching
a book I just completed (How to Write A Successful Business Plan, AMACOM)
we surveyed 900 venture capital firm and compiled some statistics.
only 1 in 2,500 plans that arrive "over the transom" at a VC firm
are ever funded.
if plans arrive through a trusted associate, 1 in 50 of those plans
are funded.
Getting funded then becomes a process: put together a top-quality, unique
product idea; get a quality, experienced management and professional
team together; PROVE THAT YOUR PRODUCT WILL SELL, preferably by actual
sales; put a set of thorough financial projections for revenue and
... you get the picture by now. Most people who put together a business plan
and try and get funding will probably not get funding.
Those companies that have followed the steps I've hinted at DO have a shot
at funding. There is a fund being set up just for the funding of companies
in the AI area, and that would be a logical place to start.
Yes, some of the big-machine companies have failed. Yes, investors have been
burned, and most of them are staying away. Yes, there has been too much
"smoke and mirrors" about AI. But... investments are STILL being made in
expert systems companies. But to get YOUR shot, you have to BUILD a venture
that IS AN ATTRACTIVE INVESTMENT.
Ca or write -- I'll help if I can. Barry Stevens, PO Box 2747, Del Mar,
CA 92014. 619-755-7231
------------------------------
Date: 18 Oct 87 22:34:36 GMT
From: violet.berkeley.edu!ed298-ak@jade.Berkeley.EDU (Edouard
Lagache)
Subject: Re: The Success of AI (Analysis of AI lack of progress).
Anyone interested in the question of A.I. success (or lack of it)
should have a look at Hubert Dreyfus's work. He has written two
books which are critical of present A.I. methodologies, and make
a purswasive argument for why present approaches to A.I. won't
work.
The books are:
What Computers Can't Do; the Limits of Artificial Intelligence
(Harper & Row, 1979)
Mind over Machine; The Power of Human Intuition and Expertise
in the Era of the Computer
(co-authored with Stuart Dreyfus and Tom Athanasiou, The
Free Press, 1986).
It perhaps goes without saying that Hubert Dreyfus is one of the
most disliked persons of A.I. researchers. However, no one in this
field can really afford to not be aware of Dreyfus's concerns.
Edouard Lagache
School of Education
U.C. Berkeley
lagache@violet.berkeley.edu
------------------------------
Date: 17 Oct 87 22:09:05 GMT
From: cbmvax!snark!eric@rutgers.edu (Eric S. Raymond)
Subject: Re: The Success of AI
In article <1922@gryphon.CTS.COM>, tsmith@gryphon.CTS.COM (Tim Smith) writes:
> Computers do not process natural language very well, they cannot
> translate between languages with acceptable accuracy, they
> cannot prove significant, original mathematics theorems.
I am in strong agreement with nearly everything else you say in this article,
especially your emphasis on a need for a new paradigm of mind. But you are,
I think, a little too dismissive of some real accomplishments of AI in at
least one of these difficult areas.
Doug Lenat's Amateur Mathematician program was a theorem prover equipped with
a bunch of heuristics about what is 'mathematically interesting', essentially
methods for grinding out interesting generalizations and combinations of known
theorems. Lenat fed it the Zermelo-Frankel set theory axioms and let it run.
After n hours of chugging through a lot of nontrivial but already-known
mathematics, it 'conjectured' and then proved a bunch of new results on the
number-theoretic properties of Pythagorean triples (3-tuples of integers of
the form <x, y, sqrt(x**2 + y**2)>).
I was a theoretical mathematician at the time I saw the AM paper. It was
*fascinating*. The program could probably have done a lot more, but it
eventually choked on the size of its own LISP data structures.
So at least one of your negative assertions is incorrect.
I never heard of this line of research being followed up by anyone but
Doug Lenat himself, and I've never been able to figure out why. He later
wrote a program called EURISKO that (among other things) won that year's
Trillion-Credit Squadron tournament (this is a space wargame related to
the _Traveller_ role-playing game) and designed an ingenious fundamental
component for VLSI logic. I think all this was in '82.
> I believe the great success of AI has been in showing that
> the old dualistic separation of mind and body is totally
> inadequate to serve as a basis for an understanding of human
> intelligence.
Correct. But while recognizing this, let's not lose sight of the real
accomplishments of AI in the purely-symbolic domain (whatever happened to
Steve Harnad, anyhow?).
I think AI has the same negative-definition problem that "natural philosophy"
did when experimental science got off the ground -- that once people get a
handle on some "AI" problem (like, say, playing master-level chess or automated
proof of theorems) there's a tendency to say "oh, now we understand that; it's
*just* computation, it's not really AI" and write it out of the field (it would
be interesting to explore the hidden vitalist premises behind such thinking).
So at any given time the referents for AI in peoples' minds are failures and
unproved speculations, and the field goes through these manic-depressive cycles
as it regroups around a new theory, problem or technology, explores it enough
to make it useful for others, and then loses it to the rest of the world.
Case in point: in the 1950s, *compilers* were considered "AI". I'm not old
enough to remember that, but some of you may be. So, don't throw out the
ship with the bath water -- er, that is, don't give up the baby -- er, oh,
*you* know what I mean. AI is a useful category not in spite of all the
ambiguity and confusion and excitement that surrounds it, but *because* of
that.
--
Eric S. Raymond
UUCP: {{seismo,ihnp4,rutgers}!cbmvax,sdcrdcf!burdvax,vu-vlsi}!snark!eric
Post: 22 South Warren Avenue, Malvern, PA 19355 Phone: (215)-296-5718
------------------------------
End of AIList Digest
********************
∂19-Oct-87 0343 LAWS@KL.SRI.Com AIList V5 #239 - Neuromorphic Terminology, AI Successes, Logican Joke
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 19 Oct 87 03:43:35 PDT
Date: Sun 18 Oct 1987 23:29-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #239 - Neuromorphic Terminology, AI Successes, Logican Joke
To: AIList@SRI.COM
AIList Digest Monday, 19 Oct 1987 Volume 5 : Issue 239
Today's Topics:
Neuromorphic Systems - Terminology,
Opinion - The Success of AI,
Humor - Two Logician Jokes,
Philosophy - Flawed Human Minds
----------------------------------------------------------------------
Date: 15 Oct 87 14:16:55 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: Neural Networks - Pointers to good texts?
In article <1465@ssc-vax.UUCP> dickey@ssc-vax.UUCP (Frederick J Dickey) writes:
>In article <4191@well.UUCP>, wcalvin@well.UUCP (William Calvin) writes:
>> We brain researchers sure get tired of hearing neural-like networks
>> referred to as "neural networks", an established subject for 25 years since
>> the days of Limulus lateral inhibition.
>
>I think the above says that "biological" neural nets have been studied as a
>formal discipline for 25 years and that this great ancestry gives biology
>prior claim to the term "neural nets". Assuming that this is a correct
>interpretation, let me make the following observation. In 1943, McCulloch
>and Pitts published a paper entitled "A logical calculus of the ideas
>immanent in neural nets". Minsky and Papert (Perceptrons) state that this
>paper presents the "prototypes of the linear threshold functions". This paper
>stikes me as clearly being in the "neural net-like" tradition. Now
>1987-1943 = 44. Also note that 44 > 25. Therefore, it apears that the
>"neural net-like" guys have prior claim to the term "neural net". :-).
Well . . . this is all rather silly. The PUBLISHED title of the classic
paper by McCullogh and Pitts is "A Logigal Calculus of the Ideas Immanent
in Nervous Activity." They NEVER use "neural net" as a technical term
(or in any other capacity) in the paper. They ARE, however, concerned
with a net model based on the interconnection of elements which they call
neurons--appealing to properties of neurons which were known at the time
they wrote the paper. Personally, I think Calvin has a point. Investigators
who are searching the literature will probably benefit from cues which
distinguish papers about actual physiological properties from those about
computational models of those properties.
------------------------------
Date: 17 Oct 87 23:58:18 GMT
From: ptsfa!well!wcalvin@ames.arpa (William Calvin)
Subject: Re: Neural Networks - Pointers to good texts?
I thank you all for the suggestions regarding renaming non-neural "Neural
Networks" -- perhaps we can continue the discussion in the newsgroup
comp.ai.neural-nets rather than here in comp.ai as such.
William H. Calvin
University of Washington NJ-15, Seattle WA 98195
[There is also the neuron%ti-csl.csnet@relay.cs.net list. -- KIL]
------------------------------
Date: 16 Oct 87 06:07:47 GMT
From: ucsdhub!jack!man!crash!gryphon!tsmith@sdcsvax.ucsd.edu (Tim
Smith)
Subject: The Success of AI
There is one humbling sense in which the work in AI in the
past 20 or so years will help considerably in the ultimate
understanding of human intelligence. If you look at concepts
of the brain in the recent past, you see that whatever was
the most current technological marvel served as a metaphor
for the brain. In the early 20th century the brain was a
telephone exchange. After WWII, the systems organization
metaphor was often used (the brain was a large corporation,
with a CEO, VPs, directors, etc.).
It wasn't until computers came along that there was a
metaphor for the brain powerful enough to be taken seriously.
Once people started to try to imitate their brains on
computers, some limitations became apparent. Interestingly
enough, the limitations are not so much in the technological
metaphor as in the present concept of the brain, or of the mind
in general.
There is no reason, in principle, that a very powerful
digital computer cannot imitate a mind, *as long as a mind
is some kind of abstract logic machine*. What AI has
discovered (though it is very unwilling to admit it) is that
this Cartesian (or even Platonic) concept of the mind is
hopelessly inadequate as a basis for understanding human
intelligence!
To conceive of the human mind as a disembodied logic machine
seemed like a great breakthrough to scientists and
philosophers. If it was this, it could be studied and
understood. If it wasn't this, then any scientific study of
the mind (hence, of intelligence) appeared to be fruitless.
The success rate in AI research (as well as most of cognitive
science) in the past 20 years is not very encouraging.
Predictions, based on very optimistic views of the problem
domain, have not been met. A few successful spin-offs have
occurred (expert systems, better programming tools and
environments), but in general the history is one of failure.
Computers do not process natural language very well, they cannot
translate between languages with acceptable accuracy, they
cannot prove significant, original mathematics theorems.
What AI researchers and other cognitive scientists now have to
face is fairly clear evidence that simulations of human
intelligence, where human intelligence is modelled as a
disembodied logic machine, are doomed to fail. Better hardware
is not the solution. Connection machines or simple silicon
neural nets are not the answer. A better concept of "mind" is
what is needed now. This is not to say that AI research should
halt, or that computers are not useful in studying human
intelligence. (They are indispensable.) What I think it does
mean is that one or more really original theoretical paradigms
will have to be developed to begin to address the problems.
One possible source of a new way of thinking about the problems
of modelling human intelligence might be found in a revolution
that is beginning in the cognitive sciences. This revolution is
of course not accepted by most cognitive scientists; many are
not even aware of it. It is difficult to characterize the
revolution, but it essentially rejects the Cartesian dualism of
mind and body, and recognizes that an adequate description of
human intelligence must take into account aspects of human
physiology, experience, and belief that cannot *now* be modelled
by simple logic (e.g., programs). For one example of this new
way of thinking, see the recent book by the linguist George
Lakoff, entitled "Women, Fire, and Dangerous Things." (Neither
the book nor the title are frivolous.)
I believe the great success of AI has been in showing that
the old dualistic separation of mind and body is totally
inadequate to serve as a basis for an understanding of human
intelligence.
--
Tim Smith
INTERNET: tsmith@gryphon.CTS.COM
UUCP: {hplabs!hp-sdd, sdcsvax, ihnp4, ....}!crash!gryphon!tsmith
UUCP: {philabs, trwrb}!cadovax!gryphon!tsmith
------------------------------
Date: 18 Oct 87 01:39:46 GMT
From: PT.CS.CMU.EDU!SPICE.CS.CMU.EDU!spe@cs.rochester.edu (Sean
Engelson)
Subject: Re: The Success of AI
Given a sufficiently powerful computer, I could, in theory, simulate
the human body and brain to any desired degree of accuracy. This
gedanken-experiment is the one which put the lie to the biological
anti-functionalists, as, if I can simulate the body in a computer, the
computer is a sufficiently powerful model of computation to model the
mind. I know, for example, that serial computers are inherently as
powerful computationally as parallel computers, though not as
efficient, as I can simulate parallel processing on essentially serial
machines. So we see, that if the assumption that the mind is an
inherent property of the body is accepted, we must also accept that a
computer can have a mind, if only by the inefficient expedient of
simulating a body containing a mind.
-Sean-
--
Sean Philip Engelson I have no opinions.
Carnegie-Mellon University Therefore my employer is mine.
Computer Science Department
----------------------------------------------------------------------
ARPA: spe@spice.cs.cmu.edu
UUCP: {harvard | seismo | ucbvax}!spice.cs.cmu.edu!spe
------------------------------
Date: Thu 15 Oct 87 16:36:24-CDT
From: David Throop <AI.THROOP@R20.UTEXAS.EDU>
Subject: Two Logician Jokes
#G-120-97A
I was hanging out at the Logicians Union Hall the other day and the place
was full of logicians, poring over logician's manuals and exchanging
gossip. Well, every so often, one of them would call out a number, and all
of the others would laugh real hard. Then they'd all go back to whatever
they were doing.
This seemed real odd behavior for such logical people. So I asked Robert,
who's a logician friend of mine there, what was going on.
"Hey, this is a hall for logicians," he said. "A while back, we collected
all of the jokes that we could prove were funny and put them in a catalog.
Everybody here's read it. Now when somebody wants to tell a joke, they
just call out its serial number." And he showed me the logical joke
catalog.
I thumbed through it for a while. Found a joke I liked. And at an
opportune time, I called it out: "G-120-97B!"
Nobody laughed.
I turned to Robert and said "So how come they didn't laugh?"
He shrugged. "You didn't tell it right."
=============================================================================
G-120-97C
I was hanging out at the Logicians Union Hall the other day and the place
was full of logicians, poring over logician's manuals and exchanging
gossip. Well, every so often, one of them would call out a number, and all
of the others would laugh real hard. Then they'd all go back to whatever
they were doing.
This seemed real odd behavior for such logical people. So I asked Robert,
who's a logician friend of mine there, what was going on.
"Hey, this is a hall for logicians," he said. "A while back, we collected
all of the jokes that we could prove were funny and put them in a catalog.
Everybody here's read it. Now when somebody wants to tell a joke, they
just call out its serial number." And he showed me the logical joke
catalog.
I thumbed through it for a while. Found a joke I liked. Actually, THIS
was the joke. This joke I'm telling you right now, it's numbered
G-120-97C. And here's where it gets hard. Because if the joke is funny,
then the logicians laugh, and that spoils the punchline. And the joke
isn't funny any more. But if the logicians will laugh at any funny joke.
So if they don't laugh, it's because the joke isn't funny. But then the
punchline works and its funny again.
So I can't tell you whether or not the logicians laughed. Either way, it
spoils the punchline.
------------------------------
Date: 16 Oct 87 12:56:21 GMT
From: ihnp4!homxb!genesis!odyssey!gls@ucbvax.Berkeley.EDU
(g.l.sicherman)
Subject: Re: The Job Hunt
> > > Mr X. goes to an employment interview and gets angry or flustered and
> > > says something that causes him to be rejected. Without knowing how his
> > > mind works you can conclude it was flawed.
> >
> > And you could be wrong. Most likely Mr. X. didn't want the job after
> > all. He only wanted you to think he wanted the job. Give him credit
> > for some intelligence!
>
> Also flawed from Mr. X's point of view. Sicherman argues that X only
> seemed to get angry or flustered, in order to make sure the company
> didn't make him an offer, because during the interview he decided he
> didn't want a job with them. If I attributed Mr. X's actions to
> intelligence I would expect him to conclude gracefully, let them make
> an offer, and reject the offer, without making a bad impression on
> somebody who later might be in a position to offer him a job in another
> company. And I don't care whether you blame emotions or habits.
You misunderstood me. I suggested not that X *seemed* to get angry, but
that he genuinely got angry. Emotions are not some kind of side effect--
they serve a constructive purpose. Anger, in particular, drives away
or destroys things that threaten your well-being.
Most likely Mr. X wants to avoid getting a job, but wants people in
general or certain people in particular to think he wants a job. It
happens all the time! You're wasting your time when you pontificate
to Mr. X. He's not going to tell a back-seat driver like you what he
really wants.
> > By this criterion, we are all flawed.
> That's exactly what I meant.
Well, it's a useless and insulting criterion.
--
Col. G. L. Sicherman
...!ihnp4!odyssey!gls
------------------------------
Date: 16 Oct 87 17:07:02 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: The Job Hunt
In article <333@odyssey.ATT.COM>, gls@odyssey.ATT.COM (g.l.sicherman) writes:
>
> You misunderstood me. I suggested not that X *seemed* to get angry, but
> that he genuinely got angry. Emotions are not some kind of side effect--
> they serve a constructive purpose. Anger, in particular, drives away
> or destroys things that threaten your well-being.
>
> Most likely Mr. X wants to avoid getting a job, but wants people in
> general or certain people in particular to think he wants a job. It
> happens all the time! You're wasting your time when you pontificate
> to Mr. X. He's not going to tell a back-seat driver like you what he
> really wants.
Do we need a definition of anger? Anger, as I understand it, is an
emotion that catalyzes physical actions but interferes with reason.
I agree that Mr. X may rationalize his action, but I don't believe
it was his best choice.
> > > By this criterion, we are all flawed.
>
> > That's exactly what I meant.
>
> Well, it's a useless and insulting criterion.
Pardon me. I thought what we all needed was a little humility. If
Col. G. L. Sicherman thinks either that he is perfect, or that I am
perfect, I disagree. Tentatively.
In my simplistic view, the mind is a complex system that came to be
what it is through variation and natural selection. It has
functions that we don't understand, adaptations for purposes we
don't understand, and adaptations for purposes that no longer exist.
If it's perfect, that's a marvelous coincidence.
If the aim of artificial intelligence is to model the human mind,
Col. Sicherman and I seem to agree that it's not enough. To model
anger, for instance, we also need artificial emotion. But if the
aim of artificial intelligence is to create a purely intelligent
entity without maladaptive emotions, Col. Sicherman and I would
disagree. I believe that at least some emotional responses are
maladaptive and would not exist in a perfect intelligence, while he
apparently believes the human mind is perfect and cannot be improved
upon.
So let us agree to disagree, and, as I suggested in an earlier
article, let some AI researchers model the human mind, while others
build something better adapted to specific tasks.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 17 Oct 87 08:52:56 GMT
From: imagen!atari!portal!cup.portal.com!tony_mak_makonnen@ucbvax.Berk
eley.EDU
Subject: Re: Flawed human minds
There is strange and profound truth to the following statements
All the universe is the brain
All you know is the mind
The second statement is more daring than the first . It is necessitated
by the need to posit something that is more than the physical parts
of brain . Assume a completely isolated , closed system capable of
reflection . I submit that such a thinking thing could not posit a
essential flaw in its make up .We see here many individual manifestations
of mind talking about flaws that one can only assume must be attributed to the
brain .What is that which stands back and reflects
on the flawed function
of that very instrument without which it would be a "null"in this universe ?
Can we call it "I" or "mind" . But then some seem to posit other "I"s than can
stand back and look at the first "Iand so on . Very confusing once we leave
the safety of behavioral psych . What seems to the morale at this point ?
Accept the obvious fact that the brain is not very efficient at calculative
functions , and the equally true fact that it is capable of creating machines
That can do that much better . Forget about the other abstract stuff .
This mind knows the limts of some brain functions and compensates for
them . It has so far proved adequate for the primary directive "the
survival of the species and life " . I submit to the members of this
jury that we cannot yet say that it is flawed . However should we
reach the ultimate folly of self destruction then only the absence of
an audience and judge will prevent a definitive verdict .
------------------------------
End of AIList Digest
********************
∂22-Oct-87 0106 LAWS@KL.SRI.Com AIList V5 #240 - Net Mail to UK, Lisp Books, Logician Jokes
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 22 Oct 87 01:05:57 PDT
Date: Wed 21 Oct 1987 22:26-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #240 - Net Mail to UK, Lisp Books, Logician Jokes
To: AIList@SRI.COM
AIList Digest Thursday, 22 Oct 1987 Volume 5 : Issue 240
Today's Topics:
Queries - Neuromorphic Systems Sources & Cash Flow and Expert Systems &
LISP on the AMIGA & Explanations in XPS,
Bindings - Net Mail to the UK,
Reviews - Introductory Books on Lisp,
Humor - Another Numbered Joke Joke
----------------------------------------------------------------------
Date: Tue 20 Oct 87 21:07:39-EDT
From: John C. Akbari <AKBARI@CS.COLUMBIA.EDU>
Subject: neuro sources
anyone have the source code for either of the following?
kosko, bart. constructing an associative memory. _byte_ sept. 1987
jones, w.p. & hoskins, j. back-propagation. _byte_ oct. 1987.
any help would be appreciated.
John C. Akbari
PaperNet 380 Riverside Drive, No. 7D
New York, New York 10025 USA
SoundNet 212.662.2476 (EST)
ARPANET & Internet akbari@CS.COLUMBIA.EDU
BITnet akbari%CS.COLUMBIA.EDU@WISCVM.WISC.EDU
UUCP columbia!cs.columbia.edu!akbari
------------------------------
Date: Mon, 19 Oct 87 20:09:29 GMT
From: A385%EMDUCM11.BITNET@wiscvm.wisc.edu
Subject: Literature on Cash-flow & Expert Systems
Date: 19 October 1987, 20:07:13 GMT
From: Javier Lopez Torres Tf: (91) 7113887 A385 at EMDUCM11
C/ Mirlo 1. 28024 Madrid -Spain-
To: AILIST-R at SRI
Hello AI Community from Spain!!!
We have just begun to developpe an expert system for cash-flow in Common-Lisp,
but we'd like first to acquire some theoretical background on this subject.
So please, could anyone of you suggest any good text about expert systems and
cash-flow??.
Thank you very much in advance for any help or suggestion.
Yours
Javier Lopez
UNiversidad Complutense de Madrid <a385%EMDUCM11.Bitnet>
------------------------------
Date: 21 Oct 87 13:30:44 GMT
From: oliveb!amiga!cbmvax!phillip@ames.arpa (Phillip Lindsay GUEST)
Subject: LISP on the AMIGA.
[Eat|Me]
I would like to hear from people working on anything related to LISP and/or
AI on the Amiga. This is important since I am trying to solicit a port of
a LISP product. Any general interest also welcome. (the more bullets the better)
------------------------------
Date: 22 Oct 87 01:06:41 GMT
From: spieker@uklirb.UUCP
Subject: Explanations in XPS - (nf)
Article-I.D.: uklirb.40000002
Hi,
can anybody outthere send me an (extended) bibliography on the subjects of
- Explanation Generation in Expert Systems
- User Modelling
Thanks
Peter Spieker
Universitaet Kaiserslautern
Fachbereich Informatik
P.O.Box 3049
D-6750 Kaiserslautern
FRG
UUCP: ...mcvax!unido!uklirb!spieker
------------------------------
Date: Tue, 20 Oct 87 00:30:58 EDT
From: brant@linc.cis.upenn.edu (Brant Cheikes)
Subject: net mail to the UK
If you happen to know the Usenet name of a host in the UK, then as a
temporary solution, you can use "ukhost!ukuserid@uunet.uu.net". The
ARPAnet host uunet.uu.net is an (official?) arpa/usenet gateway and
knows how to route mail to all known uucp hosts, including those in
the UK. I, for example, have been corresponding with my advisor,
Bonnie Webber, who's on sabbatical at Edinburgh, by addressing mail to
"eusip!bonnie@uunet.uu.net". Unfortunately, I think this only works
for Unix hosts on usenet. Mail to people at ucl-cs can be sent to
"ucl-cs!user@uunet.uu.net". Hope that helps.
Brant
Brant Cheikes University of Pennsylvania
ARPA: brant@linc.cis.upenn.edu Computer and Information Science
------------------------------
Date: 19 Oct 87 11:56 PDT
From: hayes.pa@Xerox.COM
Subject: email to UK
Some news about UK email. The UCL gateway has recently introduced a
policy ( see official notice reproduced below ) which polices traffic
through the gateway to an alarming extent. I have talked ( well,
listened ) to some moderately senior UK administrators about this and
have been told that this is being forced on them by the US military, but
you know what politicians are. Anyway, the effect has been to have
hackers of unknown competence start fiddling with a working system,
with predictable results. There seems to be considerable confusion:
the UCL locals ( email to liaison@cs.ucl.ac.uk ) insist that mail into
the UK should go through regardless of source and that only outgoing
mail will be policed, but the official bulletin says otherwise.
In the interim there is even more confusion here: The new `correct'
address, say the UCL hackers, is nss.cs.ucl.ac.uk, but the host tables
as of a couple of weeks ago had it as synonymous with the old
cs.ucl.ac.uk. ( and, by the way, with UCL-CS ) . The UCL people were
horrified when I told them of this so maybe things have changed ( cf
KILs reply to Yorick ), but for a while the following hack, suggested by
Doug Faunt at Schlumberger, worked just fine: mail to
whoever%nss.cs.ucl.ac.uk@cs.ucl.ac.uk
This apparently made the ucl machine forward to itself and then believe
the nss prefix. I am testing this again now but dont have results yet.
The NS2 having a different socket number is very encouraging, I bet this
is the missing NSS with a typo: I am testing this as well.
Pat Hayes
PS. Let me suggest that all users of netmail to the UK send their
comments on the following to whoever they think might be inclined to
listen, such as a senator or M.P.
-----------------
From: liaison@NSS.Cs.Ucl.AC.UK
Subject: Authorisation Information
Sender: daemon@NSS.Cs.Ucl.AC.UK
To: Witty.pa
TO UNAUTHORISED USERS OF THE UCL GATEWAY SERVICE PROJECT:
Access control has been introduced to the UCL ARPA/Janet
Gateway, so that only authorised users of the Service may
send traffic through the Gateway. This is because of
restrictions imposed on the Service by its funding bodies.
If you wish to exchange mail with users on the other side of
the Gateway, an application must be made to gain authorisation.
It is most appropriate for the UK user to apply. Mail is
authorised by either sender or receiver, so that a US user
is able to send mail to an authorised UK mailbox. If you are a
US user, please contact your UK colleague by some other means,
to explain what is now happening - he/she may be unaware of
these developments.
This applies to all the Internet networks reached from UCL via
Arpanet (including Usenet mail to or from US hosts that is routed via
UCL), and to PSS in the UK.
The actual authorisation mechanism depends on the registration
of mailboxes belonging to the applicant - the program necessary
to do this is available when and if authorisation is given.
One application is made per project group, in the name of
the principal investigator of the project. The mailboxes of all
the members of the group can then be registered as being
associated with the authorised user.
________________________________________________________________
Further information can be obtained from auto-mailboxes.
1.
For an application form (for UK users) and Introductory document to
the Gateway Service send a message to the auto-mailbox:
application-form@ucl-cs
2.
Some JANET sites have a contact who is willing to assist with
mail registration problems. A list can be obtained from the
auto-mailbox:
local-help@ucl-cs
3.
A general bulletin board for users of the UCL Gateway can be
obtained similarly from the auto-mailbox:
netnews@ucl-cs.
4.
The 'mreg' program allows authorised users to register mailboxes
for which they are responsible. A guide to using the 'mreg' program
can be obtained from the auto-malbox:
mreg-help@ucl-cs
No text should be included with messages to auto-mailboxes.
------------------------------
Date: Mon, 19 Oct 87 08:58:36 EDT
From: rapaport@cs.Buffalo.EDU (William J. Rapaport)
Subject: lisp books
An excellent self-study book on Lisp is:
Shapiro, Stuart C., LISP: An Interactive Approach (Computer Science Press)
It's dialect-independent, and assumes that the reader is sitting in front
of a terminal running Lisp while reading the book.
William J. Rapaport
Assistant Professor
Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260
(716) 636-3193, 3181
uucp: ..!{ames,boulder,decvax,rutgers}!sunybcs!rapaport
internet: rapaport@cs.buffalo.edu
[if that fails, try: rapaport%cs.buffalo.edu@relay.cs.net
or: rapaport@buffalo.csnet ]
bitnet: rapaport@sunybcs.bitnet
------------------------------
Date: 19 Oct 87 10:54:01 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Introductory books on Lisp
Date: Fri, 16 Oct 87 11:03:46 PDT
From: glasgow@marlin.nosc.mil (Michael G. Glasgow)
I am new to AIList and AI programming and want to learn Lisp.
I have been looking through Steele's book, Common Lisp", and
have discovered that this is more of a reference manual than a
beginners guide. What I am wondering is if anyone can give me
the names of some good introductory Lisp books to get me started.
There are several. Here are two:
Winston, Horn, "LISP". Addison-Wesley (1984 I think). Teaches
you common lisp from the atoms on up.
Charniak, Riesbeck, McDermott "Artificial Intelligence
Programming" Lawrence Erlbaum (1980). What every AI programmer
should know, though unfortunately the lisp dialect is getting a
bit dated.
Two others I know of but have never had the opportunity to use:
Wilensky, "Common LISPcraft". Norton, 1984.
Brooks, "Programming in Common Lisp." MIT Press, 1985.
You will undoubtedly hear from the partisans of other books.
------------------------------
Date: 20 Oct 87 02:55:25 GMT
From: voder!apple!andyr@decwrl.dec.com (Andy Rundquist)
Subject: Re: Introductory books on Lisp
In article <8710161803.AA06962@marlin.nosc.mil>, glasgow@MARLIN.NOSC.MIL
(Michael G. Glasgow) writes:
>
>
> I am new to AIList and AI programming and want to learn Lisp.
> I have been looking through Steele's book, Common Lisp", and
> have discovered that this is more of a reference manual than a
> beginners guide. What I am wondering is if anyone can give me
> the names of some good introductory Lisp books to get me started.
>
> Thanks in Advance,
>
> michael
To me, the best (and most enjoyable) Lisp introduction can be found in:
_The Little Lisper_ by D. Freidman.
Andy
(Now CONS a piece of cake into your mouth)
------------------------------
Date: Tue, 20 Oct 87 11:27:25 PDT
From: Stephen Smoliar <smoliar@vaxa.isi.edu>
Subject: Re: Introductory books on Lisp
Back in the dark ages when I was teaching LISP, I used to rely heavily on
THE LITTLE LISPER by Daniel Friedman. I felt that the important thing about
learning LISP was getting comfortable with expressing yourself in a functional
style and using the format of recursive definitions. Friedman does an
excellent job of walking you through a broad variety of examples. You
emerge from this book with a good sense of the power of a "pure" applicative
style of LISP programming. Having done so, you are now ready for the "real
world" provided by the particular dialect of LISP you will actually be using.
------------------------------
Date: 20 Oct 87 12:45:48 GMT
From: kddlab!secisl.seclab.junet!tau@uunet.UU.NET ("Yatchan" TAUCHI)
Subject: Re: Introductory books on Lisp
In article <8710161803.AA06962@marlin.nosc.mil>, glasgow@MARLIN.NOSC.MIL
(Michael G. Glasgow) writes:
> I have been looking through Steele's book, Common Lisp", and
> have discovered that this is more of a reference manual than a
> beginners guide.
It's not a good text book to Lisp beginners, but just specification of COMMON-
LISP.
> What I am wondering is if anyone can give me
> the names of some good introductory Lisp books to get me started.
I think there are not many good books on CommonLisp yet. I recommend
"Common LISPcraft" by Robert Wilensky, Norton $26.95. His book, "LISPcraft"
was very good text book on FranzLisp. I think it's easy to understand how to
write CommonLisp program.
----
Yasuyuki TAUCHI, SECOM IS-Lab, Tokyo JAPAN
NET: tau%seclab.junet@uunet.UU.NET
UUCP: ...!seismo!kddlab!titcca!secisl!tau
------------------------------
Date: Mon 19 Oct 1987 08:47 CDT
From: UUCJEFF%ECNCDC.BITNET@wiscvm.wisc.edu
Subject: >Everybody here's read it. Now when somebody wants to tell
a joke, th
>just call out its serial number." And he showed me the logical joke
>catalog.
>I thumbed through it for a while. Found a joke I liked. And at an
>opportune time, I called it out: "G-120-97B!"
>Nobody laughed.
G-120-97B Thats an IBM manual right?
------------------------------
Date: Mon, 19 Oct 87 11:14:16 BST
From: Graham Higgins <gray%ghiggins.lb.hp.co.uk@RELAY.CS.NET>
Subject: Two Logician Jokes
That's a shame. Why does there have to be a concrete catalogue? It prohibits a
variation which is arguably funnier ... can I change it around bit ?? ....
I was hanging out at the Logicians Union Hall the other day and the place
was full of logicians, poring over logician's manuals and exchanging
gossip. Well, every so often, one of them would call out a number, and all
of the others would laugh real hard. Then they'd all go back to whatever
they were doing.
This seemed real odd behavior for such logical people. So I asked Robert,
who's a logician friend of mine there, what was going on.
"Hey, this is a hall for logicians," he said. "A while back, we collected
all of the jokes that we could prove were funny and allocated each one a
number. Everybody here knows them. Now when somebody wants to tell a joke,
they just call out its number."
I thought about this for a while. Then I asked Robert if I could tell a joke,
you know, try out the system. He said it would be OK by him, so I called out a
number: "1209!"
Nobody laughed.
I turned to Robert and said "So how come they didn't laugh?"
He shrugged. "You didn't tell it right."
I asked for another try. Once more, Robert said it would be OK by him. I called
out a different number: "83417!".
Everybody collapsed in fits of mirth.
I turned to Robert, feeling pleased. "Told _that_ one OK, didn't I?", I said.
Robert was nearly helpless with laughter. He gasped, in between guffaws,
"Haven't heard that one before".
------------------------------
Date: Tue, 20 Oct 87 11:22:42 PDT
From: Stephen Smoliar <smoliar@vaxa.isi.edu>
Subject: Another numbered joke joke.
[Same first three paragraphs.]
One of the logicians called out: "G-120-97D!"
Suddenly, one logician had a fit of uncontrollable laughter; and it took
some time before he calmed down.
I turned to Robert and asked, "What happened?"
He replied, "Probably that logician had never heard that joke before."
Post Script: I originally heard these jokes in the context of Hollywood
producers exchanging jokes at lunch (even before I moved out to the shadow
of Hollywood).
------------------------------
End of AIList Digest
********************
∂22-Oct-87 0247 LAWS@KL.SRI.Com AIList V5 #241 - Seminars, Course in Information Processing
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 22 Oct 87 02:47:10 PDT
Date: Wed 21 Oct 1987 22:46-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #241 - Seminars, Course in Information Processing
To: AIList@SRI.COM
AIList Digest Thursday, 22 Oct 1987 Volume 5 : Issue 241
Today's Topics:
Seminars - Crystallizing Theories out of Knowledge Soup (SU) &
Event-Based Reasoning for Multiagent Domains (Bendix & BBN) &
Computing in the Year 2001 (Aston) &
Restricted And-Parallelism for Logic Programs (SMU),
Course - Information Processing
----------------------------------------------------------------------
Date: Tue 20 Oct 87 17:47:25-PDT
From: Marcelo Hoffmann <HOFFMANN@KL.SRI.Com>
Subject: Seminar - Crystallizing Theories out of Knowledge Soup (SU)
John Sowa, a member of the IBM Systems Research Institute will be
giving a talk titled "Crystallizing Theories out of Knowledge Soup
(knowledge base)", on Thursday, October 22, at 7:00 PM in Room 380C
Mathematics Department, Stanford University (while facing the Quad
from Palm Drive, in the nearest, right hand corner of the Quad). The
talks is sponsored by the IEEE Computer Society.
Abstract:
"The most challenging problems for AI arise from the difficulty of
characterizing the knowledge soup, analyzing it, and codifying it in
formal symbolic terms. These problems appear in many different guises
in knowledge acquisition, machine learning, metaphor analysis,
nonmonotonic reasoning, and reasoning with uncertainty. No complete,
formal solutions are possible, but methods of conceptual analysis,
belief revision, and dynamic type hierarchies permit special-case
subtheories to be crystallized out of the knowledge soup as needed.
This talk will use conceptual graphs as the formalism for representing
the crystallized theories and show how they can be used with belief
revision systems and dynamically changing type hierarchies".
Attendance is free.
------------------------------
Date: Thu, 15 Oct 87 08:49 EDT
From: DON%atc.bendix.com@RELAY.CS.NET
Subject: Seminar - Event-Based Reasoning for Multiagent Domains
(Bendix & BBN)
Where: Allied-Bendix Aerospace Technology Center
9140 Old Annapolis Rd (MD 108)
Columbia, MD 21045
When: 28 October 1987, 1:30pm
Who: Amy L. Lansky
SRI International, Artificial Intelligence Center
What: Localized Event-Based Reasoning for Multiagent Domains
This talk will present GEM, a structured, event-based concurrency model,
and GEMPLAN, a multiagent planner based on this model. A key focus of
this work has been the development of localized techniques for domain
representation and reasoning. Such techniques partition domain
descriptions and reasoning tasks according to the regions of activity
within a domain. GEM's use of locality is beneficial for alleviating
the frame problem in multiagent domains. GEMPLAN is a planning
architecture based on localized planning search spaces. By explicitly
utilizing constraint and property localization, GEMPLAN can pinpoint and
rectify interactions among regional search spaces, thereby reducing the
burden of ``interaction analysis'' ubiquitous to most planning systems.
Directions and RSVP (optional but helpful for planning):
Roz Alme (301) 964-4106 or ROZ@ATC.BENDIX.COM.
Marc Vilain <MVILAIN@G.BBN.COM> reports that the same seminar will be
given at BBN:
10 Moulton Street
2nd floor large conference room
10:30 am, Monday October 26
------------------------------
Date: 16-OCT-1987 16:55:10
From: HANCOXPJ@MAIL.ASTON.AC.UK
Subject: Seminar - Computing in the Year 2001 (Aston)
From: Dr P J Hancox <HANCOXPJ@uk.ac.aston>
Dept: Computer Science
Tel No: 021 359 3611 X4652
Aston University
Department of Computer Science and Applied Mathematics
Seminar
Wednesday 28 October 1987 at 3.00 pm in Room 550, Main Building
Computing in the year 2001
Brian Oakley
Director, The Alvey Directorate, London
The key to the advance in computing over the last 20 years has been the
inexorable increase in the speed, power and memory capacity of the silicon
chip. Will this continue and, if so, for how long? The talk will consider
the performance of the integrated circuit in the year 2001, and the
resulting power of the processor on a chip. Well before the turn of the
century multi-processors will have become common place, so that system
power will far exceed the individual processor power. And what will this
power be used to do? The talk will end by considering the new applications,
particularly the spread of so-called AI applications such as Expert
Systems, Natural Language, Voice and Image Processing.
Chairman: Dr B Gay.
Enquiries:
JANET: compsci@uk.ac.aston.mail
uucp: seismo!mcvax!ukc!aston!compsci
Computer Science, Aston University, Birmingham, B4 7ET, United Kingdom
+ 44 21 359 3611 extn 5313
------------------------------
Date: Mon, 19 Oct 1987 00:32 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Seminar - Restricted And-Parallelism for Logic Programs (SMU)
Restricted And-Parallelism for Logic Programs
SPEAKER: Doug DeGroot LOCATION: 315 SIC Southern Methodist University
Texas Instruments Inc. TIME: 1:30 pm
ABSTRACT
A number of parallel execution models have been proposed for the
highly-parallel execution of logic programs. Most of these center on
various forms of and-parallelism and/or or-parallelism. While the
majority of work in Europe and Japan seems to have focused on
or-parallel models, research in the United States had focused more on
and-parallelism. Some of the reasons for this will be examined, and a
number of models for and-parallelism and related research will be
mentioned. Then a specific model, called Restricted And-Parallelism
(RAP) will be described in detail. The discussion will focus on the
model itself, techniques for the automatic compilation of Prolog
programs into RAP graph expressions, and the proper handling of
side-effects in a parallel execution environment, and global
data-dependency analysis for better program decomposition. An overview
of RAP-related research efforts in other parts of the world will also
be discussed. Finally, topics for future research will be discussed as
time permits.
------------------------------
Date: 16 Oct 87 10:52:40 GMT
From: mcvax!cernvax!cui!pun@uunet.uu.net (PUN Thierry)
Subject: Course - Information Processing
(I am forwarding the following annoucement; please enquire directly
to the address below. TP.)
The Swiss Federal Institute of Technology, Lausanne presents a graduated
program leading to a M.S. in information processing with applications to
systems signals and images.
The closing of registrations is November 15 1987.
This program starting in March 1988 consisting of two terms study (one year)
including lectures, exercices and workshops is based on the following themes :
A) Communication system theory (160 hours)
A1) Systems theory (30 hours)
A2) Information theory (70 hours)
A3) Detection and estimation (60 hours)
B) Digital signal and image processing
B1) Digital signal processing (80 hours)
B2) Digital image processing (90 hours)
C) Pattern recognition and scene analysis (150 hours)
C1) Pattern recognition (90 hours)
C2) Scene analysis (60 hours)
D) Real time information processing (145 hours)
D1) Speech processing (60 hours)
D2) Signal processing and VLSI architecture (85 hours)
These lectures, exercices and workshops will be followed by a research
project during 6 months in 1989.
The lecturers are : M. Kunt (course director), F. Ade, M. Bellanger, D.
Bonvin, J. Caelen, G. Caelen-Haumont, G. Coray, F. de Coulon, P. Dewilde,
O. Faugeras, W. Fichtner, G. Granlund, C. Gueguen, B. Guerin, M. Hasler,
J.P. Haton, H. Hugli, R. Ingold, O. Kubler, R. Longchamp, H. Nussbaumer and
Ch. Sorin.
To get more informations please contact the secretariat du Laboratoire de
traitement des signaux de l'EPFL, Departement d'electricite, EPFL Ecublens,
CH 1015 Lausanne, SWITZERLAND, Tel. (4121) 472624 or 472601,
Telex 454062 EPFVD CH, Telefax (4121) 474660
PUN CGEUGE51 10/14/87
THIERRY PUN cvnet@yorkvm1 10/14/87 For posting on the net (start
------------------------------
End of AIList Digest
********************
∂22-Oct-87 0602 LAWS@KL.SRI.Com AIList V5 #242 - Successes of AI, Automated Discovery
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 22 Oct 87 06:02:43 PDT
Date: Wed 21 Oct 1987 22:53-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #242 - Successes of AI, Automated Discovery
To: AIList@SRI.COM
AIList Digest Thursday, 22 Oct 1987 Volume 5 : Issue 242
Today's Topics:
Comments - The Success of AI
Representation - Lenat's AM Program
----------------------------------------------------------------------
Date: 19 Oct 87 09:54:22 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: The Success of AI
Date: 18 Oct 87 01:39:46 GMT
From: PT.CS.CMU.EDU!SPICE.CS.CMU.EDU!spe@cs.rochester.edu (Sean
Engelson)
Given a sufficiently powerful computer, I could, in theory, simulate
the human body and brain to any desired degree of accuracy. * * *
Don't forget to provide all the sensory input provided by being
in, moving around in, and affecting the world. Otherwise you'll
be simulating a catatonic.
Do the terminally catatonic have minds?
------------------------------
Date: 19 Oct 87 10:27:22 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: The Success of AI
Date: 17 Oct 87 22:09:05 GMT
From: cbmvax!snark!eric@rutgers.edu (Eric S. Raymond)
* * *
I never heard of this line of research being followed up by anyone but
Doug Lenat himself, and I've never been able to figure out why. He later
wrote a program called EURISKO that (among other things) won that year's
Trillion-Credit Squadron tournament (this is a space wargame related to
the _Traveller_ role-playing game) and designed an ingenious fundamental
component for VLSI logic. I think all this was in '82.
See Lenat & J.S. Brown in AI Journal volume 23 #3, 1984: "Why AM
and EURISKO Appear to Work". The punchline of the article
(briefly) is that AM seems to have succeeded in elementary set
theory because its own representation structures (i.e., lists),
were particularly well suited to reasoning about sets. It
started breaking down at exactly the places where its
representation was inadequate for the concepts. For example,
there was no obvious way to move from its representation of the
number n as a list of length n, to a positional representation
that would make it more likely to discover things like
logarithms. Furthermore, its operations on procedures involved
local modifications to procedures expressed as list structures,
and as long as the procedures were compact these "mutations"
were likely to produce interesting new behavior, but as the
procedures get more complex, arbitrary random local
modifications had a vanishingly low success ratio. Hence it
would seem that direction to go from this insight is to make
programs that can learn new representations. There are probably
not enough people working on that. But anyway this is getting
off the subject, which is whether AI has had any successes.
Whether you want to count AM as a success is half-empty /
half-full issue; the field surely learned something from it, but
it surely hasn't learned enough.
------------------------------
Date: 19 Oct 87 17:47:45 GMT
From: brian@sally.utexas.edu (Brian H. Powell)
Subject: Re: The Success of AI
In article <228@snark.UUCP>, eric@snark.UUCP (Eric S. Raymond) writes:
> Doug Lenat's Amateur Mathematician program was a theorem prover equipped with
> a bunch of heuristics about what is 'mathematically interesting',
> [...]
>
> After n hours of chugging through a lot of nontrivial but already-known
> mathematics, it 'conjectured' and then proved a bunch of new results on the
> [...]
I feel compelled to challenge this, but not necessarily the rest of your
article.
AM wasn't a theorem prover. From the July, 1976 dissertation:
7.2.2 Current Limitations
[...]
AM has no notion of proof, proof techniques, formal validity, heuristics for
finding counterexamples, etc. Thus it never really establishes any conjecture
formally.
---end of excerpt---
The dissertation goes on to briefly suggest ways of adding this
capability, but as I understand it, no one ever has. Lenat himself, as I
recall, thought it was more interesting to do more work towards heuristics
than proving. EURISKO was the result of that. (i.e., you might get more
power if you could spend part of your time conjecturing heuristics in addition
to conjecturing about particular problems.)
AM is a neat program, but by many views it's overrated. It's great that
it conjectures all these neat theorems, but my impression is that it does
quite a bit of floundering to find them. I think it also spends a lot of time
floundering without finding anything useful, also. (A program run isn't
guaranteed to think of something clever.) Finally, it's not clear that the
program is really intelligent enough to realize that it's just conjectured
something intelligent. (I would bet that there are a lot of things AM has
considered uninteresting that humans consider interesting, and vice-versa.)
A human can monitor AM and modify the priority of certain tasks if the
human feels AM is studying the wrong thing. A human is practically required
for this purpose if AM is to do something especially clever. This turns AM
more into a search tool than an autonomous program, and I don't think a tool
is what Lenat had in mind.
If you read the summaries of AM, you think it's powerful. Once you read
the entire dissertation, you realize it's not quite as great a program as you
had thought, but you still think it's good research.
Brian H. Powell
UUCP: ...!uunet!ut-sally!brian
ARPA: brian@sally.UTEXAS.EDU
------------------------------
Date: 20 Oct 87 06:30:06 GMT
From: mcvax!cernvax!ethz!srp@uunet.uu.net (Scott Presnell)
Subject: Re: The Success of AI
In article <193@PT.CS.CMU.EDU> spe@spice.cs.cmu.edu (Sean Engelson) writes:
>
>Given a sufficiently powerful computer, I could, in theory, simulate
>the human body and brain to any desired degree of accuracy. This
Horse shit. The problem is you don't even know exactly what you are
simulating! I suppose you could say it's all a problem of definition,
however even with your assumtion that the mind is a integral part of the
body I still claim that you don't know what you're simulating. For
instance, dreams, are they logical?, do they fall in a pattern?, a computer
has got to have them to be a real simulation of a body/mind, but you cannot
simulate what you cannot accurately describe.
Let's get down to a specific case:
I propose that given any amount of computing power, you could not presently,
and probably will never be able to simulate me: Scott R. Presnell.
My wife can be the judge.
This may sound reactionary, that's because that's the way I responded
internally to this first statement. I apologize if I've jumped into a
discussion too quickly, I don't have time to read the previous discussions
right now.
Scott Presnell Organic Chemistry
Swiss Federal Institute of Technology (ETH-Zentrum)
CH-8092 Zurich, Switzerland.
uucp:seismo!mcvax!cernvax!ethz!srp (srp@ethz.uucp); bitnet:Benner@CZHETH5A
------------------------------
Date: 21 Oct 87 05:30:58 GMT
From: ucsdhub!jack!man!crash!gryphon!tsmith@sdcsvax.ucsd.edu (Tim
Smith)
Subject: Re: The Success of AI
In article <193@PT.CS.CMU.EDU> spe@spice.cs.cmu.edu (Sean Engelson) writes:
+=====
| Given a sufficiently powerful computer, I could, in theory, simulate
| the human body and brain to any desired degree of accuracy. This
| gedanken-experiment is the one which put the lie to the biological
| anti-functionalists, as, if I can simulate the body in a computer, the
| computer is a sufficiently powerful model of computation to model the
| mind. I know, for example, that serial computers are inherently as
| powerful computationally as parallel computers, though not as
| efficient, as I can simulate parallel processing on essentially serial
| machines. So we see, that if the assumption that the mind is an
| inherent property of the body is accepted, we must also accept that a
| computer can have a mind, if only by the inefficient expedient of
| simulating a body containing a mind.
| -Sean-
+=====
My claim is, specifically, that you cannot simulate a human
being (body and mind) with a digital computer, either in theory
or practice. Not a few people with whom I am in basic agreement
would claim that, well, it just *might* be conceivable in
theory, but you could never do it in practice.
I'ts not clear what is meant by "in theory" here. It sounds like
an unacceptable hedge. You might, for example, claim that with a
very large number of computers, all just at the edge of the
speed boundaries dictated by the laws of physics in the most
advanced materials imaginable, you could simulate a human body
and mind--but not in real time. But the simulation would have to
be in real time, because humans live in real time, doing things
that are critically time dependent (perceiving speech, for
example).
Similarly, humans think the way they do partially because of
their size, because of the environment they live in, because of
the speed at which they move, live, and think.
One of the consistent failings of AI researchers is to vastly
underestimate the intricacy and complexity of the kinds of
things they are trying to model (of course most of the other
cognitive scientists in this century have also underestimated
these things). Playing chess is nothing compared with natural
language understanding. We take language understanding for
granted, because, after all, we all do it. Yet we consider a
chess grand master brilliant, because we cannot match his
skills. But in fact, becoming a chess grand master is not more
difficult than learning to speak and write English. It's easier.
We learn language because we start early, spend *lots* and
*lots* of time doing it, and it's fun (watch children playing
word games sometime). We recognize that it's learn to speak or
perish, in a sense. Many fewer people are motivated (at the
early age required) to learn to play chess at the GM level.
The trouble with the kind of naive (if you'll pardon the
expression) reductionism inherent in your position is that it
seems to assume that any set of physical interactions that can
be expressed mathematically can be scaled up to a full-scale
simulation, and that this simulation would be indistinguishable
from the original thing.
Leaving aside AI for a moment, consider weather simulations.
Metereologists have developed computerized simulations of
phenomena such as hurricanes. Based on lots of data from past
storms, they can predict, with some accuracy, how a developing
storm might behave. This is obviously an extremely useful
capability. But to claim that a computer simulation of a
hurricane is exactly the same as the real thing would probably
sound like a very poor joke to someone who has experienced a
hurricane first-hand.
It seems to me that any intelligent person would say "how could
you ever truly simulate a hurricane, and why would you want to?"
Well, I have the same reaction to those who say that they want
to simulate human intelligence, or even some essential part of
it such as natural language understanding. How, and for God's
sake, *why*? To study human intelligence, using computers and
any other tools available, is a fascinating thing to do. I have
spent a number of years doing so. But to say that we are
approaching an era when human intelligence will be simulated
seems to be just about like saying that from the puff of air
generated by the wave of a hand it is only a few short steps to
a full-scale realistic simulation of a hurricane.
Know what it is you are trying to simulate!
--
Tim Smith
INTERNET: tsmith@gryphon.CTS.COM
UUCP: {hplabs!hp-sdd, sdcsvax, ihnp4, ....}!crash!gryphon!tsmith
UUCP: {philabs, trwrb}!cadovax!gryphon!tsmith
------------------------------
Date: 21 Oct 87 05:35:49 GMT
From: ucsdhub!jack!man!crash!gryphon!tsmith@sdcsvax.ucsd.edu (Tim
Smith)
Subject: Re: The Success of AI
In article <228@snark.UUCP> eric@snark.UUCP (Eric S. Raymond) writes:
+====
| In article <1922@gryphon.CTS.COM>, tsmith@gryphon.CTS.COM (Tim Smith) writes:
| > Computers do not process natural language very well, they cannot
| > translate between languages with acceptable accuracy, they
| > cannot prove significant, original mathematics theorems.
|
| I am in strong agreement with nearly everything else you say in this article,
| especially your emphasis on a need for a new paradigm of mind. But you are,
| I think, a little too dismissive of some real accomplishments of AI in at
| least one of these difficult areas.
|
| Doug Lenat's Amateur Mathematician program was a theorem prover equipped with
| a bunch of heuristics about what is 'mathematically interesting', essentially
| methods for grinding out interesting generalizations and combinations of known
| theorems.
| [...]
|
| So at least one of your negative assertions is incorrect.
+=====
OK, I'll accept your word on this (I'm a linguist, not a
mathematician).
+=====
| I think AI has the same negative-definition problem that "natural
| philosophy" did when experimental science got off the ground -- that
| once people get a handle on some "AI" problem (like, say, playing
| master-level chess or automated proof of theorems) there's a tendency
| to say "oh, now we understand that; it's *just* computation, it's not
| really AI" and write it out of the field (it would be interesting to
| explore the hidden vitalist premises behind such thinking).
+=====
Well, scientific (and philosophical) fields do progress, and there is
a normal tendency to discard the old and no longer interesting. But
there is an interesting aspect to what you are saying, I believe. Let
me try to develop it a bit, using chess as an example.
Chess: I am at a disadvantage here in one sense--I don't play the
game very well. In my limited understanding of it, it is a very
difficult game to play at a high level. It requires years of study,
usually starting at a young age, to become a grand master. It
requires peculiar abilities of concentration and nervous resources to
play chess at a competetive level. Nevertheless, I don't think of
chess as being a particularly intellectual game. It seems much more like
tennis to me (and I don't play that either). This is not a put-down!
I think of chess as being a sedentary sport--a sport for the mind.
Now here's the interesting point. If you were to come to me and say--
"Smith, you have a year to develop an automaton that will play some
kind of major sport at a championship level, competing against humans.
Money is no object, and you can have access to all the world's
experts in AI and robotics, but you must design a robot that plays
championship X in a year's time. What is X?" I would say, without a
moment's hesistation, "tennis".
Why? Of all the sports, tennis is the most bounded. It is played within
a very restricted area (unlike golf or even baseball), it is a
one-against-one sport (unlike football or soccer), the playing surfaces
(aside from Wimbledon) are the truest of all the major sports, and it
is indubitably the most boring of all the sports to watch (if not to
play). A perfect candidate for automation.
Chess? It is tennis for the mind. And so a perfect candidate for
initial attempts at AI. But if computers have conquered chess (as
they seem about to), does this mean that "real" artificial
intelligence is not far behind? No, it just means that chess was
over-rated as an intellectual exercise! On a scale of 1 to 10, in
terms of intellectual effort involved in playing the game, chess
seems to rate at about .002. In terms of skill, concentration
ability, depth of understanding of the game, etc. it is difficult.
But then, so is multiplying two 37 digit numbers in your head
difficult. Unless you're an "idiot savant", or a computer!
--
Tim Smith
INTERNET: tsmith@gryphon.CTS.COM
UUCP: {hplabs!hp-sdd, sdcsvax, ihnp4, ....}!crash!gryphon!tsmith
UUCP: {philabs, trwrb}!cadovax!gryphon!tsmith
------------------------------
Date: Wed, 21 Oct 87 09:50:51 PDT
From: Tom Dietterich <tgd@orstcs.cs.orst.edu>
Subject: Lenat's AM program
The exact reasons for the success of AM (and for its eventual failure
to continue making new discoveries) have not been established. In
Lenat's dissertation, he speculated that the source of power was the
search heuristics, and that the eventual failure was caused by the
inability of the system to generate new heuristics.
Then, in a paper by Lenat and Brown, a different reason is given:
namely that the representation of concepts was the critical factor.
There is a close relationahip between mathematics concepts and lisp,
so that mathematical concepts can be represented very concisely as
lisp functions. Simple syntactic mutation operations, when applied to
these concise functions, yield other interesting mathematical
concepts. In new domains, such as those tackled by Eurisko, it was
necessary to engineer the concept representation so that the concepts
were concisely representable.
Finally, in a paper published this year by Lenat and Feigenbaum, yet
another explanation of AM's (and Eurisko's) success and failure is
given: "The ultimate limitation was not what we expected (cpu time),
or hoped for (the need to learn new representations), but rather
something at once surprising and daunting: the need to have a massive
fraction of consensus reality already in the machine."
The problem with all of these explanations is that they have not been
subjected to rigorous experimental and analytical tests, so at the
present time, we still (more than ten years after AM) do not
understand why AM worked!
I have my own pet hypothesis, which I am currently subjecting to an
experimental test. The hypothesis is this: AM succeeded because its
concept-creation operators generated a space that was dense in
interesting mathematical concepts. This hypothesis contradicts each
of the preceding ones. It claims that heuristics are not important
(i.e., a brute force search using the concept-creation operators would
be only polynomially--not exponentially--more expensive). It claims
that the internal representation of the concepts (as lisp functions)
was also unimportant (i.e., any other representation would work as
well, because mutation operators are very rarely used by AM).
Finally, it claims that additional world knowledge is irrelevant
(because it succeeds without such knowledge).
There is already some evidence in favor of this hypothesis. At CMU, a
student named Weimin Shen has developed a set of operators that can
rediscover many of AM's concepts. The operators are applied in brute
force fashion and they discover addition, doubling, halving,
subtraction, multiplication, squaring, square roots, exponentiation,
division, logarithms, and iterated exponentiation. All of these are
discovered without manipulating the internal representation of the
starting concepts.
AM is a "success" of AI in the sense that interesting and novel
behavior was exhibited. However, it is a methodological failure of
AI, because follow up studies were not conducted to understand causes
of the successes and failures of AM. AM is not unique in this regard.
Follow-up experimentation and analysis is critical to consolidating
our successes and extracting lessons for future research. Let's get
to work!
Tom Dietterich
Department of Computer Science
Oregon State University
Corvallis, OR 97331
tgd@cs.orst.edu
OR tgd%cs.orst.edu@relay.cs.net
References:
\item Lenat, D. B., (1980). AM: An artificial intelligence approach to
discovery in mathematics as heuristic search, In Davis, R., and Lenat,
D. B., {\it Knowledge-based systems in Artificial Intelligence}, 1980.
\item Lenat, D. B., and Brown, J. S. (1984). Why AM and EURISKO appear to work,
{\it Artificial Intelligence}, 23(3) 269--294.
\item Lenat, D. B., and Feigenbaum, E. A. (1987). On the thresholds of
knowledge. In {\it IJCAI87, The Proceedings of the Tenth
International Joint Conference on Artificial Intelligence}, Milan, Los
Altos, CA: Morgan-Kaufmann.
\item Shen, W. (1987). Functional transformations in AI discovery
systems. Technical Report CMU-CS-87-117, Carnegie-Mellon University,
Department of Computer Science.
------------------------------
End of AIList Digest
********************
∂24-Oct-87 0131 LAWS@KL.SRI.Com AIList V5 #243 - Lisp Text, Prolog, Design, Cash Flow, Neural Nets
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 24 Oct 87 01:31:41 PDT
Date: Fri 23 Oct 1987 21:56-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #243 - Lisp Text, Prolog, Design, Cash Flow, Neural Nets
To: AIList@SRI.COM
AIList Digest Saturday, 24 Oct 1987 Volume 5 : Issue 243
Today's Topics:
Query - Connection Machine Architecture &
Neural Info Process Conference &
Multiexpert/Multiagent Researches & Prolog for Course,
Education - Common Lisp Textbooks & Prolog,
Application - AI and Design Automation/Design Assistance & Cash Flow,
Neuromorphic Systems - Byte Sources & Cybernetics
----------------------------------------------------------------------
Date: 21 Oct 87 19:16:18 GMT
From: Mark Attisha <local!attisha@RELAY.CS.NET>
Subject: Info on Connection Machine Wanted
We are wondering if anyone can provide us with information specific to the
Connection Machine. We have found that Hillis' book to be lacking in such
areas as hardware description and network communications. In particular,
we are interested in obtaining a description of processing element to router
communication, host to processing element communication, chip control unit
to processing element communication, the role of shared memory, a description
of the buses between chips and between processing elements, and so forth.
Thanks in advance.
Please send information to the: Mark Attisha
Department of Computing & Information Science
Queen's University
Kingston, Ontario K7L 3N6
Canada
e-mail attisha@qucis.bitnet
------------------------------
Date: 23 Oct 87 01:49:55 GMT
From: deneb.ucdavis.edu!g451252772ea@ucdavis.ucdavis.edu
(0040;0000001585;0;327;142;)
Subject: Neural Info Process conf. at Denver 11/8-12
Having just been informed I have funds to attend this, it would
be gratifying to learn if it's still open (moving to Denver changed the
crowd capacity to infinity, yes?)
I'm also interested if anyone has ideas on lodgings less expensive
than the Sheraton ... or travel inexpensively from near the Bay Area to
Denver (Davis is closest to Sacramento physically, but to SF otherwise...)
--thanks!
Ron Goldthwaite / UC Davis, Psychology and Animal Behavior
'Economics is a branch of ethics, pretending to be a science;
ethology is a science, pretending relevance to ethics.'
(apologies if the signature appears 2x)
------------------------------
Date: 23 Oct 87 18:14:28 GMT
From: leey@russell.STANFORD.EDU (Chin Lee)
Reply-to: leey@russell.stanford.edu (Yi-Chin Lee)
Subject: Need pointers to multi expert -- multi agent researches
Is there anyone out there on the net can provide me with bibliographical
pointers to researches related to multi expert -- multi agent planning
and knowledge representation?
Thanks.
------------------------------
Date: 22 Oct 87 23:50:08 GMT
From: ucsdhub!hp-sdd!ncr-sd!ncrcae!hubcap!steve@sdcsvax.ucsd.edu
("Steve" Stevenson)
Subject: Suggestions for Course
I have to teach an AI course for folks with little or no
background. I'd like to use prolog, but want to have them
learn it as much on their own as possible. Any suggestions
for texts?
At this time, I think I would like to concentrate on theorem
proving with perhaps some non-traditional stuff (fuzzy?) included.
Any suggestions here?
--
Steve (really "D. E.") Stevenson steve@hubcap.clemson.edu
Department of Computer Science, (803)656-5880.mabell
Clemson University, Clemson, SC 29634-1906
------------------------------
Date: Thu, 22 Oct 87 10:50:40 EDT
From: Chris Riesbeck <riesbeck-chris@YALE.ARPA>
Subject: AI Programming Book
Date: 19 Oct 87 10:54:01 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Introductory books on Lisp
Charniak, Riesbeck, McDermott "Artificial Intelligence
Programming" Lawrence Erlbaum (1980). What every AI programmer
should know, though unfortunately the lisp dialect is getting a
bit dated.
The Second Edition is now available, in Common Lisp, substantially
revised, with old bugs and typos replaced by sparkling new ones.
Artificial Intelligence Programming, Second Edition (1987)
Charniak, Riesbeck, McDermott, and Meehan
Lawrence Erlbaum Assoc, Inc.
365 Broadway, Hillsdale, NJ 07642
------------------------------
Date: Thu, 22 Oct 87 08:21:00 PDT
From: Marie Bienkowski <bienk@spam.istc.sri.com>
Subject: Common Lisp Textbooks
Date: Fri, 16 Oct 87 11:03:46 PDT
From: glasgow@marlin.nosc.mil (Michael G. Glasgow)
I am new to AIList and AI programming and want to learn Lisp.
I have been looking through Steele's book, Common Lisp", and
have discovered that this is more of a reference manual than a
beginners guide. What I am wondering is if anyone can give me
the names of some good introductory Lisp books to get me started.
As several people mentioned in response to this query, there are
several good texts on Common Lisp. What surprises me is that no one
mentioned Deborah Tatar's book. First, let me say that I relied on
Winston and then Wilensky when teaching LISP, both are good books.
(with Wilensky's being better). But when I tried to learn Common Lisp
from Steele, then found it was impossible, I discovered Tatar's
excellent book. It's published by Digital Press, and is entitled "A
Programmer's Guide to Common Lisp." While I have not used her book
for teaching, I think the examples are good enough to warrant its use.
And it is the perfect companion to Steele (in fact, Steele, wrote
the foreward for it). It may be more difficult to get than, say,
Wilensky's, but I think it is worth it. (If you go for nice-looking
covers, on the other hand, get Wilensky's. It's great-looking!)
Marie Bienkowski
bienk@istc.sri.com
------------------------------
Date: 23 Oct 87 16:25:20 GMT
From: oltz@tcgould.tn.cornell.edu (Michael Oltz)
Reply-to: oltz@tcgould.tn.cornell.edu (Michael Oltz)
Subject: Re: Introductory books on Lisp
In article <8710191454.AA26556@ht.ai.mit.edu> hamscher@HT.AI.MIT.EDU
(Walter Hamscher) writes:
> Charniak, Riesbeck, McDermott "Artificial Intelligence
> Programming" Lawrence Erlbaum (1980). What every AI programmer
> should know, though unfortunately the lisp dialect is getting a
> bit dated.
At a talk McDermott gave at Cornell in September, it was announced that
the 2nd edition of this book would be coming out soon.
--
Mike Oltz oltz@tcgould.tn.cornell.UUCP (607)255-8312
Cornell Computer Services
215 Computing and Communications Center
Ithaca NY 14853
------------------------------
Date: 23 Oct 87 14:15:52 GMT
From: ucsdhub!hp-sdd!ncr-sd!ncrlnk!ncrcam!morley@sdcsvax.ucsd.edu
(/usr/acct/morley)
Subject: Re: Suggestions for Course
In article <587@hubcap.UUCP>, steve@hubcap.UUCP ("Steve" Stevenson) writes:
> I have to teach an AI course for folks with little or no
> background. I'd like to use prolog, but want to have them
> learn it as much on their own as possible. Any suggestions
> for texts?
How about Turbo Prolog? Some will argue that it is not "true" Prolog, but
it is very close to the real thing. The manual is in tutorial form, and is
easy to learn and use. Also, Borland International offers a discount to
students. The price is very reasonable.
> --
> Steve (really "D. E.") Stevenson steve@hubcap.clemson.edu
> Department of Computer Science, (803)656-5880.mabell
> Clemson University, Clemson, SC 29634-1906
------------------------------
Date: 23 Oct 87 19:13:51 GMT
From: bbn!gatech!hubcap!grimlok@husc6.harvard.edu (Mike Percy)
Subject: Re: Suggestions for Course
in article <321@ncrcam.Cambridge.NCR.COM>, morley@ncrcam.Cambridge.NCR.COM
(/usr/acct/morley) says:
> Xref: hubcap comp.lang.prolog:345 comp.ai:820
>
> In article <587@hubcap.UUCP>, steve@hubcap.UUCP ("Steve" Stevenson) writes:
>> I have to teach an AI course for folks with little or no
>> background. I'd like to use prolog, but want to have them
>> learn it as much on their own as possible. Any suggestions
>> for texts?
>
> How about Turbo Prolog? Some will argue that it is not "true" Prolog, but
> it is very close to the real thing. The manual is in tutorial form, and is
> easy to learn and use. Also, Borland International offers a discount to
> students. The price is very reasonable.
>
True about TProlog, it is almost Prolog, but not quite. In fact, at some
places it is downright divergent and unusable. But for the environment
Dr. Stevenson is in, nearly every one of his students has used at least
Turbo Pascal and possibly TurboC. They are familiar with the Borland
systems, and can concentrate on their programs rather than than their
compiler and how to use it. Also, the speed of testing is nice, the
debugging trace is helpful, and Clemson has plenty of PCs. In these
days, when the VAX machines are quickly becoming overloaded, any PC
implementation will be a plus.
So Dr. Stevenson, here is my vote for TProlog, with the proviso that you
declare to the poor students that TProlog is a mere shadow of the true
power of the language.
Mike Percy
Clemson University
------------------------------
Date: 22 Oct 87 17:14:00 EDT
From: "ETD1::WILSONJ" <wilsonj%etd1.decnet@afwal-aaa.arpa>
Reply-to: "ETD1::WILSONJ" <wilsonj%etd1.decnet@afwal-aaa.arpa>
Subject: AI & Design Automation, Design Assistance
I'm beginning a study on Applications of AI in Design Automation and Design
Assistance. My interests range from IC CAD (my area of expertise) to the design
of mechanical, aerodynamic, and propulsion systems; and beyond. I need to
explore today's design issues, where does AI fit in, what are the most critical
design needs. I'd greatly appreciate brief replys on who's doing what in AI &
Design, and issues that you believe should be persued, i.e. the most promising
of advances in design, where is research lacking, etc.
I presently work in an AI prototyping facility whose function is to rapidly
transition state of the art AI technology into Air Force weapon systems; and
serve as a showcase for state of the art AI applications research and the latest
AI hardware and software innovations.
My research will help direct training and technical efforts at a newly
established AI Applications Center at the Miami Valley Research Institute
(MVRI) in Dayton, OH. Aeronautical Systems Division/Air Force Systems Command
at Wright Patterson AFB, OH awarded a $10 million contract to MVRI last week.
MVRI is a consortium of the University of Dayton, Wright State University,
Central State University, and Sinclair Community College. Teknowledge Federal
Systems Division and the Ohio State University Laboratory for Artificial
Intelligence Research (LAIR) will serve as subcontractors.
Thank You, :-)
James B. Wilson
ARPANET: wilsonj%etd1.decnet@<afwal-aaa.arpa>
US Mail: AFWAL/AAI
Bldg 22, Area B
WPAFB, OH 45433
Phone: (513) 255-1491
------------------------------
Date: Thu, 22 Oct 87 11:01:28 EDT
From: Brady@UDEL.EDU
Subject: Lopez query
To respond to Javier Lopez' query:
1. a couple of years ago AI Magazine had an article specifically
on this subject. The author likened the flow of cash through
a company to the flow of water into, through, and out of a system
of pipes and valves. The discussion reminded me of systems
that model electrical circuitry.
2. Most intermediate accounting and finance texts treat the
cash flow concept well. Usually, the most vexatious
problem in predicting cash inflows is estimating revenues, so
a good market analysis text may also help.
3. IEEE Expert recently devoted an issue to financial applications.
There may be something there about your topic.
------------------------------
Date: Thu 22 Oct 87 13:58:44-PDT
From: Matt Heffron <BEC.HEFFRON@ECLA.USC.EDU>
Subject: Re: neuro files
For general Info:
The sources to programs from Byte magazine are available from the BYTEnet
bulletin board system: (617)861-9764 (set modem at: 8-1-N or 7-1-E; 300
or 1200 baud). This system supports several PC "ftp" protocols, including
xmodem (and "standard" variations...)
-Matt Heffron BEC.HEFFRON@ECLA.USC.EDU
------------------------------
Date: 21 Oct 87 13:59:56 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: Neural Networks - Pointers to good
In article <8300006@osiris.cso.uiuc.edu> goldfain@osiris.cso.uiuc.edu writes:
>
> On the other hand, whatever became of the term "cybernetics" that Norbert
>Weiner coined long ago? I thought its definition was quite suitable for
>denoting this research.
I do not profess to be an expert in either the history of cybernetics or the
usage of the term; but, with that qualification, let me try to address this
question. As I recall, Weiner's original concern was with the design of
analog devices which, by virtue of feedback circuits, were capable of control
of other devices and adaptive behavior (which may be regarded as self-control).
Through my encounters with the literature as an AI researcher, I have observed
that the term "cybernetics" appears with greater frequency in Europe
(particularly the Soviet Union and the United Kingdom) than it does in
the United States. There is definitely a tendency to recognize that
Weiner's original principles could be generalized from analog to digital
hardware. However, I have the distinct impression that cybernetics grew
from the belief that behavioral knowledge was something which would ultimately
be encoded in the feedback loops, rather than in an explicit device concerned
with memory or the storage of a knowledge base. I would appreciate any
reactions to these comments simply to get the historical record straight.
------------------------------
End of AIList Digest
********************
∂24-Oct-87 0359 LAWS@KL.SRI.Com AIList V5 #244 - Financing, Neuromorphic Terminology, Flawed Minds
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 24 Oct 87 03:59:43 PDT
Date: Fri 23 Oct 1987 22:15-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #244 - Financing, Neuromorphic Terminology, Flawed Minds
To: AIList@SRI.COM
AIList Digest Saturday, 24 Oct 1987 Volume 5 : Issue 244
Today's Topics:
Business - Expert Systems Company Financing,
Neuromorphic Systems - Terminology & Textbook,
Philosophy - Flawed Human Minds
----------------------------------------------------------------------
Date: 18 Oct 87 17:52:45 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: Expert Systems Company Financing...
In the early eighteenth century a man of intense religious fervour named
Johann Ernst Elias Bessler claimed that God had revealed to him the secret
of the perpetual motion machine. He would tour villages in the costume of
a magician and offer demonstrations of his devices. Ultimately, he
attracted the attention of Count Karl von Hessen-Cassel, who undertook
to serve as a sponsor. At Hessen-Cassel's expense, Bessler built one
of these machines based on a wheel which was twelve feet in diameter.
Hessen-Cassel then invited many of the leading scientific minds of his
time to evaluate the project. In the course of this evaluation, the
machine apparently ran without stopping for 54 days. Ultimately, Bessler
was exposed as a fraud; and several scientific reputations were destroyed
as a consequence.
While the historical record of this affair is fragmented, there are several
rather interesting points which I would claim are at least remotely related
to the current discussion about similar sponsorship of artificial intelligence.
1. The evaluating scientists were not allowed to inspect the
inner workings of Bessler's machine. Bessler claimed they would
be blinded by the divine revelation (or words to that effect).
Hessen-Cassel apparently did see the inner workings and was
not blinded. Nevertheless, the evaluating committee agreed
to accept this constraint.
2. For all the time that Hessen-Cassel possessed this machine,
he never tried to do anything practical with it. Bessler's
previous demonstrations with smaller-scale machines always
climaxed with the machine being used to lift some impressive
weight. While Hessen-Cassel was in possession of a potentially
significant labor-saving device, he seemed content to keep it
locked in a room of his castle.
3. Bessler was never exposed on the grounds of any scientific
argument. Willem Jakob Gravesande published a "proof" of why
the machine worked, and the flaw in this proof was
subsequently published by Jacque de Crousaz. However,
Bessler was undone when a servant girl confessed that
she was powering the machine from an adjoining room.
This was later discovered to be a false testimony, but
Bessler was distraught by the affair. Before anyone had
a chance to inspect its interior, he destroyed the machine.
I do not intend to imply that artificial intelligence is like perpetual
motion, at least to the extent that it is a theoretical impossibility.
However, I am struck by certain behavioral parallels between past and
present. My personal opinion is that Bessler was probably an extremely
skilled "hacker" (in mechanics) for his time, with his personal confidence
reinforced by his religious convictions. He probably pulled off a pretty
good piece of work even if his mind was entirely "in the bits" (so to
speak) and largely ignorant of prevailing theory. What is pathetic,
however, is that those who were asked to evaluate him were willing to
play the game by his own rules. Indeed, there is some indication that
their opinions may have been slanted by the promise of sharing in the
monetary gain which Bessler's invention might yield. Also, there is
this depressing observation that the evaluation never involved putting
the machine to work; they were content to just let it run on in a
locked chamber.
Current "success stories" about artificial intelligence are not quite
as contrived as that of Bessler's machine running in a locked room for
54 days; but they come closer than I would feel is comfortable. To a
great extent, the "field testing" of "applied" expert systems often takes
place in rather constrained circumstances. A less polite way of putting
this might be to say that the definition of "success" is in danger of
being modified POST HOC to accommodate the capabilities of the system
being evaluated. Thus, I feel that all reports of such stories should
be viewed with appropriate scientific scepticism.
On the other hand, there is a positive side of this historical retrospective.
Had Hessen-Cassel actually put Bessler's machine to work, it might have
been of considerable benefit to him . . . even if it did not run forever.
In other words, a machine capable of dissipating its energy slowly enough
to run for a very long time, while not being a true perpetual motion
machine, would still be a useful tool. By concentrating on a theoretical
goal, rather than a practical one, Hessen-Cassel lost an opportunity to
exploit a potentially valuable resource. Similarly, sponsorship of
artificial intelligence should probably pay more heed to advancement
along specific pragmatic fronts and less to whether or not machines
which exhibit that behavior deserve to be called "intelligent." If
we recognize what we have for what it is, we may get more out of it
than we might think.
ACKNOWLEDGEMENT: I would like to thank Jim Engelhardt for the extensive
research he has performed regarding the story of Bessler. He is in the
process of incorporating his research into a play which he is calling
THE PERPETUAL MOTION MAN. His research has been quite thorough, and
his insights are noteworthy.
------------------------------
Date: Mon, 19 Oct 87 09:29 EST
From: "William E. Hamilton, Jr."
Subject: RE: AIList V5 #239 - Neuromorphic Terminology, AI Successes,
Of course the human mind is flawed. The proof is quite straightforward.
1. The Bible asserts that the mind of man is wicked (or evil, depending on
which translation you use)
2. Now, assuming you believe the Bible is true and that an evil mind is a
flawed mind (if you don't agree that an evil mind is flawed, you can
still find a collection of assertions about human behavior in the Bible
that, taken together, would indicate that the minds responsible for
such behavior are flawed), the assertion is proven.
3. But suppose you do not regard the Bible as true. Then the Bible is
flawed. However, the Bible has been on the world's best-seller
list for many years, and those who buy a flawed book must have flawed
minds. Therefore, there are millions of flawed minds out there.
Bill Hamilton
GM Research Labs
------------------------------
Date: 19 Oct 87 07:27:00 GMT
From: uxc.cso.uiuc.edu!osiris.cso.uiuc.edu!goldfain@a.cs.uiuc.edu
Subject: Re: Neural Networks - Pointers to good
I agree with the respondent whose user-name was listed as "smoliar" that this
haggling about earliest references is "silly". In fact, I don't understand
the need for any territorial fight over terminology here.
Do physiologists actually use the two-word term "neural network" in their
literature? "Neuron", and "neural tissue", surely, but do they actually use
"neural network" ? If not, then there is no ambiguity. Sure there is some
danger of confusion, but no more than I think is usual in cases of "learned
borrowing". The term "neural network" as used by "connectionist/AI"
researchers caught on precisely because this model of computation is based on
the gross behavior of real, mammalian-brain neurons. It can be viewed in some
ways as a study of the human brain itself. Thus it is no greater an abuse of
terminology than, for example, "pipeline computers".
On the other hand, whatever became of the term "cybernetics" that Norbert
Weiner coined long ago? I thought its definition was quite suitable for
denoting this research. I doubt that "connectionist" is much help, in view of
the fact that the "connection machine" is more a project in pure parallelism
than intended as a neural model.
If I am wrong about any of this, please enlighten me.
------------------------------
Date: 21 Oct 87 15:49:02 GMT
From: ssc-vax!dickey@beaver.cs.washington.edu (Frederick J Dickey)
Subject: Re: Neural Networks - Pointers to good texts?
From postnews Wed Oct 21 07:49:49 1987
> >interpretation, let me make the following observation. In 1943, McCulloch
> >and Pitts published a paper entitled "A logical calculus of the ideas
> >immanent in neural nets". Minsky and Papert (Perceptrons) state that this
>
> Well . . . this is all rather silly. The PUBLISHED title of the classic
> paper by McCullogh and Pitts is "A Logigal Calculus of the Ideas Immanent
> in Nervous Activity." They NEVER use "neural net" as a technical term
Well, this is very interesting. When I read Calvin's original
posting I was struck by the claim that neural nets had been studied for
25 years. This surely seemed too small a figure to me. To check this
out without initiating a major research project, I grabbed a copy of
Minsky and Papert's "Perceptrons" which happened to be on my desk at the
time and opened to the bibliography. M&P give the title of the McCullough and
Pitts paper as "A logical calculus of the ideas immanent in neural nets".
I'm looking at it right now and that's what it says. Apparently, the citation
is wrong. Well, I stand corrected.
I might comment by the way that regardless of the merits of Calvin's claim
that artificial neural nets ought to be named something else, I think the
effort is doomed to failure. The reason being that we seem to have become
an excessively marketing-oriented society. Labels are attached to things to
stimulate desired responses in "consumers," not to clarify crtical
distinctions. The practical problem one faces in much of the industrial world
is attempting to gain support for one's "research." To do this, one presents
one's proposed program to a manager, i.e., one markets it. The noise level
in this process is so high that nothing less than hype makes it through.
My experience with managers leads me to believe that they may have heard
of neural nets. If I tried to start a "neuroid" project, they would say
"Isn't that the same thing as a neural net?" I can guarantee you that they
aren't interested in the distinctions between artifical and biological nets.
How can an aerospace company make a profit from biological nets? In other
words, to start a artifical neural net project, I have to call it a neural
net, show how it applies to some product, how it adds value to the product
(neural nets will make the product more powerful than a locomotive, faster
than a speeding bullet, and able to leap over tall buildings at a single
bound), and how all this can be done by next year at a half man-year level
of effort.
If I lived in an ivory tower (a not unpleasant domicile), I'd say that
Calvin is right on. Out here in the cinder block towers, he's out to lunch.
To summarize, I'm sympathic to his viewpoint, but my sympathy isn't going
to make much difference.
------------------------------
Date: 23 Oct 87 06:50:34 GMT
From: well!wcalvin@LLL-LCC.ARPA (William Calvin)
Subject: Why "neural nets" is a bad name
I admit that "nerve nets" and the variant "neural networks" are catchy
titles; we neurobiologists have used the terms quite a lot, though mostly
informally as in the annual meeting called the "Western Nerve Net". Each real
neural network tends to become its own subject name, as in "stomatogastric"
and "retina", with papers on properties that transcend particular anatomies
incorporated into sessions called "theoretical neurobiology" or some such (I'm
on the editorial board of the JOURNAL OF THEORETICAL NEUROBIOLOGY, often
concerned with networks).
A quarter-century ago was the era of the Perceptron, the first of the
network learning models. Various people were simulating network properties
using neuron-like "cells" and known anatomy; when I was a physics undergrad in
1959, I did an honors thesis on simulating the mammalian retina (using anatomy
based only on light-microscopy, using physiology of neurons borrowed from cat
spinal motorneurons, using sensory principles borrowed from horseshoe crab! A
far cry from the CRAY-1 simulations these days using modern retinal
neurobiology). And if you think that your simulations run slow: I did
overnight runs on an IBM 650, which had to fetch each instruction from a
rotating drum because it lacked core memory.
Now this was also the era when journalists called any digital computer a
"brain" -- and I've pointed out that calling any pseudo-neural network a
"neural network" is just as flaky as that 60s journalistic hype. Now brain
researchers were not seriously inconvenienced by the journalistic hype -- but
I think that blurring the lines is a bad idea now. Why?
Real neural networks will soon be a small part of a burgeoning field
which will have real applications, even consumer products. To identify those
with real brain research may seem innocuous to you now because of the frequent
overlap at present between pseudo-neural networks and simulations of real
neural circuitry. But these distributed networks of pseudo-neurons are going
to quickly develop a life of their own with an even more tenuous connection to
neuroscience. They need their own name, because borrowing is getting a bad
name. Let me briefly digress.
We are already seeing a lot of hype based on a truly nonexistent
connection to real neuroscience, such as those idiot "Half Brain or Whole
Brain" ads in the Wall Street Journal and New York Times, where "John-David,
Ph.D." describes himself as one of the "world's most recognized
neuroscientists" recently "recognized as a Fellow by the International
Institute of Neuroscience" (Nope, I've never heard of it either, and I was
a founding member of the Society for Neuroscience back in 1970). See James
Gorman's treatment in DISCOVER 11/87 p38. Is this just feel-good floatation-
tank pseudo-psychology dressed up to look like hard science, another scheme to
part half-brained fools from their money?
Scientists are going to start to get touchy about consumer products
borrowing an inferred plug from real science, just as the FDA has gotten
touchy about white coats in Carter's Little Liver Pills advertisements
attempting to convey medical approval. And you can bet that, if pseudo-neural
nets become as successful as I think they will, some advertising genius will
try to pass off a nonfunctional product as a neural network "resonating with
your brain", try to get some of that aura of real science and technology to
rub off on the sham. Do you really want your field trapped in the middle of
an FDA/FTC battle with the sham exploiters because it initiated the borrowing?
Borrowing a name for a technology from a basic science is not traditional:
civil engineers do not call themselves "physicists".
We neurobiologists are always having to distinguish the theoretical
possibilities, such as retrograde transport setting synaptic strengths, from
reality. Those theoretical possibilities may, of course, be excellent
shortcuts that Darwinian evolution never discovered. And so we'll see
distinctions having to be drawn: "backpropagation works in pseudo-neural
nets, but hasn't been seen so far in real neural nets." If you call the
technology by the same name as the basic science, you start confusing
students, journalists, and even experienced scientists trying to break into
the field -- just try reading that last quote with "pseudo" and "real" left
out.
William H. Calvin
University of Washington NJ-15
Seattle WA 98195
wcalvin@well.uucp wcalvin@uwalocke.bitnet
206/328-1192 206/543-1648
------------------------------
Date: 18 Oct 87 23:37:35 GMT
From: ctnews!pyramid!prls!philabs!gcm!dc@unix.sri.com (Dave Caswell)
Subject: Re: Flawed human minds
>> Factually, we know the mind is flawed because we observe that it does
>> not do what we expect of it.
>
Factually, the mind knows the mind is flawed because the mind observes the
mind not doing what the mind expects the mind to do.
------------------------------
Date: 20 Oct 87 17:43:26 GMT
From: ucsdhub!hp-sdd!ncr-sd!ncrlnk!ncrday!seradg!bryan@sdcsvax.ucsd.ed
u (Bryan Klopfenstein)
Subject: Re: Flawed human minds
In article <359@white.gcm> dc@white.UUCP (Dave Caswell) writes:
>>> Factually, we know the mind is flawed because we observe that it does
>>> not do what we expect of it.
>>
>Factually, the mind knows the mind is flawed because the mind observes the
>mind not doing what the mind expects the mind to do.
So, is the mind flawed because it expects the wrong thing, or is the mind
flawed because it observes incorrectly, or is the mind flawed because it does
not live up to its expectations? Or is this a ridiculous question and a flawed
mind does not have the capability to evaluate itself, thus making it unable to
determine whether or not is really is flawed?
--
Bryan Klopfenstein CSNET bryan@seradg.Dayton.NCR.COM
NCR Corporation ARPA bryan%seradg.Dayton.NCR.COM@relay.cs.net
VOICE (513) 865-8080
-- Standard Disclaimer Applies --
------------------------------
Date: 20 Oct 87 15:43:54 GMT
From: ihnp4!homxb!genesis!odyssey!gls@ucbvax.Berkeley.EDU
(g.l.sicherman)
Subject: Re: The Job Hunt
> Do we need a definition of anger? Anger, as I understand it, is an
> emotion that catalyzes physical actions but interferes with reason.
> I agree that Mr. X may rationalize his action, but I don't believe
> it was his best choice. ...
>
> ... I thought what we all needed was a little humility. If
> Col. G. L. Sicherman thinks either that he is perfect, or that I am
> perfect, I disagree. Tentatively.
If you go telling people what you think they all need, we may decide
that you're not very humble!
Arguing over whether people are "perfect" or "flawed" is like arguing
whether Eugene the Jeep is a rodent or a marsupial. Perfect for *what?*
And I agree that we need a definition of anger. "Catalyzes physical
actions?" The anger *produces* the actions. If you had no emotions,
you would never act.
> ... I believe that at least some emotional responses are
> maladaptive and would not exist in a perfect intelligence, while he
> apparently believes the human mind is perfect and cannot be improved
> upon.
Again, perfect for what? It sounds as if you regard emotions as a
part of intelligence. We don't agree on the basics yet.
"This rock, for instance, has an I.Q. of zero. Ouch!"
"What's the matter, Professor?"
"It bit me!"
--
Col. G. L. Sicherman
...!ihnp4!odyssey!gls
------------------------------
Date: Tue, 20 Oct 87 16:21:42 PDT
From: larry@VLSI.JPL.NASA.GOV
Subject: Flawed/Flawless
FLAWED/FLAWLESS: I can argue on both sides.
FLAWLESS: Quality can only be judged against some standard. Every person
has (perhaps only slightly) a different value system, as may even the same
person at different times. So what is a flaw to one may be a "feature" to
another. (Examples: a follower of Kali may consider torture, death, and
corruption holy; a worshipper of the Earth Mother may consider monogamy a
sin and infertility a crime.) The only objective standard is survival of
the largest number of one's species for the longest time, and even this
"standard" is hopelessly flawed(!) by human subjectivity.
FLAWED: Nevertheless, humans DO have standards, and not only for made
objects like automobiles, that are essential to our survival and happiness.
We want lovers who have compatible timing (social, sexual), sensitivity (at
least enough not to hog the blankets or too obviously eye the competition),
enough intelligence (so we can laugh at the same jokes) but not too much
(winning an occasional argument is necessary to our self-esteem), etc.
Notice that TOO MUCH intelligence may be considered as bad a flaw as too
little.
And more FLAWLESS: From an evolutionary standpoint what is a "virtue" in
one mileau may become deadly when the environment changes. Performing some
mental activity reliably may be of little use when chaos sweeps through our
lifeways. THEN divergent thinking--or even simple error--may be more likely
to solve problems. A perfect memory (popularly thought to accompany great
intelligence) can be a liability, holding one rigidly to standards or
knowledge no longer valid. It is also the enemy of abstract/general
thought, which depends on forgetting (or ignoring) inessentials. (Indeed,
differential forgetting may be one of those great ignored areas of fruitful
research.)
AI: What does all this have to do with artificial intelligence? Maybe
nothing, but I'll invent something. Say ... the relationship of emotions to
intelligence. First, sensations of pain and pleasure drive thought, in the
sense that they establish values for thinking and striving to achieve or
avoid some event or condition. Sensation triggers emotions and in turn
triggers sensations which may act as second-level motivators. They also may
trigger subsystems for readiness (or inhibition) of action. (Example:
hunger depletes blood sugar, triggering anger when a certain level of stress
is reached, which releases adrenalin which energizes the body. Anger also
may cause partly or fully random action, which is statistically better than
apathy for killing or harvesting something to eat.)
At least that's the more traditional outlook on emotions--though that
outlook may have changed in ten years or so since I did much reading in
psychology. Even if true, however, the above outlook doesn't establish a
necessary link of emotion with artificial thought; humans can supply the
goals and values for a Mars Rover, an activate command can trigger emergency
energy reserves. Some other more intimate association of emotion with
thought is needed.
Perhaps emotions affect thought in beneficial ways, say improving the
thinking mechanism itself. (The notion that it impedes correct thought is
too conventional and (worse) obvious to be interesting.) Or maybe emotion
IS thought in some way. It is, after all, only a conclusion based on
incomplete brain evidence that thought is electrical in nature. Suppose the
electrical action of the brain is secondary, that the biochemical action of
the brain is the primary mechanism of thought. This might square with the
observation that decision often happens in the subconscious, very rapidly,
and integrates several (or even dozens) of conflicting motives into a vector
sum. In other words, an analog computer may be a better model for human
thought than a digital one. (In the nature of things that answer is likely
too simple. Most likely, I'd guess, the brain is a hybrid of the two.)
Larry @ jpl-vlsi
------------------------------
End of AIList Digest
********************
∂24-Oct-87 0914 LAWS@KL.SRI.Com AIList V5 #245 - AM, Success of AI, Dreyfus's Philosophy
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 24 Oct 87 09:13:49 PDT
Date: Fri 23 Oct 1987 22:23-PDT
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #245 - AM, Success of AI, Dreyfus's Philosophy
To: AIList@SRI.COM
AIList Digest Saturday, 24 Oct 1987 Volume 5 : Issue 245
Today's Topics:
Comments - Lenat's AM & The Success of AI & Dreyfus's Philosophy
----------------------------------------------------------------------
Date: 20 Oct 87 16:14:48 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: The Success of AI
In article <9320@ut-sally.UUCP> brian@ut-sally.UUCP (Brian H. Powell) writes:
> If you read the summaries of AM, you think it's powerful. Once you read
>the entire dissertation, you realize it's not quite as great a program as you
>had thought, but you still think it's good research.
>
Actually, Lenat and John Seely Brown did something rather like this when they
wrote the paper "Why AM and Eurisko Appear to Work" for AAAI-83.
------------------------------
Date: Thu 22 Oct 87 08:35:35-PDT
From: Douglas Edwards <EDWARDS@WARBUCKS.AI.SRI.COM>
Subject: Reworking Lenat
The claim that Lenat's work has not been retested should not be
allowed to pass without being questioned. Not only should Weimin
Shen's work, already cited by Tom Dietterich, be taken into account,
but there is apparently another attempt to work with the same approach
going on at MIT. *Artificial Intelligence Abstracts* cites the MIT AI
Memo AIM-898, "Discovery Systems" by K. W. Haase Jr. (*AI Abstracts*,
volume 1 number 1, January 1987). I have not yet read (or even
obtained) this memo, but the abstract suggests that Haase has not only
reimplemented Lenat's work but also tried to discover a principled
explanation for why it works, and that Haase's explanation for AM's
success would be quite different from Dietterich's and Shen's. I look
forward to learning more about Haase's work. I don't know if Haase
reads AILIST; if he does, it would be interesting to hear his own
comments on the AM controversy.
--- Douglas D. Edwards
(edwards@ai.sri.com)
------------------------------
Date: 20 Oct 87 14:48:35 GMT
From: bpa!cbmvax!snark!eric@burdvax.prc.unisys.com (Eric S. Raymond)
Subject: Re: The Success of AI
In article <9320@ut-sally.UUCP>, brian@ut-sally.UUCP (Brian H. Powell) writes:
> I feel compelled to challenge this, but not necessarily the rest of your
> article.
> AM wasn't a theorem prover. From the July, 1976 dissertation:
Thanks for the correction, which I also received by email from another comp.ai
regular. I never saw Lenat's dissertation, just an expository paper in one of
journals. I guess maybe the reason I thought the sucker had a theorem prover
attached was that I was working on LISP support for a theorem prover at the
time, and my associative memory got a collision in its hash tables :-).
Nevertheless, I think my more general observations about AI's definitional
problem remain valid. Compilers are a 'success' of AI. So are heuristic-based
search-and-backtrack algorithms. So is the visual analysis preprocessing used
in seeing pick-and-place robots. So (most recently) are 'expert systems'.
In *each case*, these problem areas were defined out of the AI field as soon
as they spawned halfway-usable technologies and acquired their own research
communities.
I think the same thing is about to happen to neural nets, BTW...
--
Eric S. Raymond
UUCP: {{seismo,ihnp4,rutgers}!cbmvax,sdcrdcf!burdvax,vu-vlsi}!snark!eric
Post: 22 South Warren Avenue, Malvern, PA 19355 Phone: (215)-296-5718
------------------------------
Date: 21 Oct 87 23:33:18 GMT
From: psuvax1!vu-vlsi!swatsun!scott@rutgers.edu (Jay Scott)
Subject: Re: The Success of AI
> Nevertheless, I think my more general observations about AI's definitional
> problem remain valid. Compilers are a 'success' of AI. So are heuristic-based
> search-and-backtrack algorithms. So is the visual analysis preprocessing used
> in seeing pick-and-place robots. So (most recently) are 'expert systems'.
> In *each case*, these problem areas were defined out of the AI field as soon
> as they spawned halfway-usable technologies and acquired their own research
> communities.
I agree. And I want to understand better why it's so.
Here's one speculation: People see intelligence as mysterious, intrinsically
non-understandable. So anything understood can't be part of intelligence,
and can't be part of AI. I assume this was what Eric had in mind in a
previous article, when he mentioned "hidden vitalist premises".
Of course some people believe explicitly that intelligence is mystical,
and say so. But even AI people may implicitly feel that, oh, this algorithm
isn't clever enough, real intelligence has to be cleverer than that. And
so it goes.
Any other good ideas?
> Eric S. Raymond
> UUCP: {{seismo,ihnp4,rutgers}!cbmvax,sdcrdcf!burdvax,vu-vlsi}!snark!eric
> Post: 22 South Warren Avenue, Malvern, PA 19355 Phone: (215)-296-5718
Jay Scott
...bpa!swatsun!scott
------------------------------
Date: 20 Oct 87 16:04:07 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: The Success of AI (Analysis of AI lack of progress).
Those who would like a taste of the Dreyfus style before embarking upon one of
his books in its entirely would do well to consult the Summer 1986 issue of
IEEE EXPERT. The article "Why Expert Systems Do Not Exhibit Expertise,"
by Hubert and Stuart Dreyfus, is an excerpt from MIND OVER MACHINE: THE
POWER OF HUMAN INTUITION AND EXPERTISE IN THE ERA OF THE COMPUTER. While
there is definitely merit to deflating exaggerated claims about expert systems
which have been made in the name of salesmanship, Hubert Dreyfus approaches
this issue as a philosopher. Consequently, the technical baggage he carries
is often not particularly timely and often inadequate. Were he to wage his
campaign on the battelground of the philosophy of mind, he might come away
with some notable victories; but by descending to the level of technology,
he often falls into traps of misconception.
Here is a sample passage:
Humans often think by forming images and comparing them
holistically. This process is quite different from the
logical, step-by-step operations that logic machines
perform.
There are several things wrong here. First of all, a holistic theory of
memory or reasoning remains a HYPOTHESIS. Claiming it as an observation
is a gross misrepresentation of the surrent state of cognitive science.
Second, the term "logic machine" has been introduced to capture a particular
machine architecture which lacks what Dreyfus wants it to lack. He does
not admit of the possibility of an alternative architecture for the
mechanization of thought which could model the holistic hypothesis.
Fortunately, more productive cognitive scientists HAVE pursued this
line of reasoning.
In any event, the text continues in an attempt to elaborate upon this point:
For instance, human beings use images to predict how certain
events will turn out.
This is, again, hypothesis. It rests on a weaker hypothsis which is never
cited: that human beings use MODELS to predict how certain events will
turn out. This is the whole "mental models" approach to cognition, for
which there is both subtantial literature and experiments in mechanical
implementation.
The text continues:
Programming a computer to analyze a scene has turned out to
be very difficult. Such programs require a great deal of
computation, and they work only in special cases with objects
whose characteristics the computer has been programmed to
recognize in advance.
Nevertheless, such programs may work better than people in those special
cases and can be used in factories. That is why industrial robotics has
become as effective as it has. I regard this as an instance of the situation
I raised regarding perpetual motion machines in an earlier note. I raised
the point that had Bessler's machine actually been put to work and found
to run for significantly long periods of time without energy input, it
would have been an impressive contribution even if its energy dissapated
very slowly, rather than not at all. Similarly, we would do better to
study special cases of scene analysis which are successes rather than
belabor the obstacles to a more general approach to the task.
It gets better:
But that is just the beginning of the problem. Computers
currently can make inferences only from lists of facts.
It's as if to read a newspaper you had to spell out each
word, find its meaning in the dictionary and diagram every
sentence.
This strikes me as a gross misrepresentation of mechanical reasoning, and
I think the crux of this misrepresentation is a confusion between reasoning
and representation. Fortunately, there are other philosophers who appreciate
that these are distinct issues; but they don't seem to attract as much
attention as Dreyfus.
One last jab in parting:
However, a computer cannot recognize emotions such as anger
in facial expressions, because we know of no way to break
down anger into elementary symbols. Therefore, logic machines
cannot see the similarity between two faces that are angry.
Yet human beings can discern the similarly almost instantly.
This strikes me as another example of sloppy thinking. Are we talking
about a GEDANKEN experiment here? If so, how are we to define it?
Are we looking at faces out of context in an attempt to infer emotion?
If so, then I would claim that humans are nowhere near as good as is
claimed. Indeed, man has been notorious for misreading emotion. The
lack of this skill has probably perpetrated many major historical events.
Seymour Papert used to accuse Dreyfus of committing the "superhuman human"
fallacy by assuming that an artrificial intelligence would surpass a human
one. Here is a situation where Dreyfus hasd gone out on a limb which he
should have left alone. Our understanding of how PEOPLE exhibit and
perceive emotion is sufficiently weak that, for the most part, artificial
intelligence seems to have to good sense to leave it in peace.
------------------------------
Date: 22 Oct 87 14:21:54 GMT
From: PT.CS.CMU.EDU!SPICE.CS.CMU.EDU!spe@cs.rochester.edu (Sean
Engelson)
Subject: The success of AI (misunderstandings)
A couple of clarifications in response to recent posts:
(a) My name is Engelson---NOT Engleson.
(b) I did not state that we could simulate the human body and brain at
this point in time. However, we could at some point, presumably, get
to the point where we know precisely how the body is constructed, and
construct a simulation of the physical processes that occur. This is
reasonable because the human body is finite in extent, and thus there
is a finite amount of information to discover, thus it can be
discovered in finite (although possibly very large) time. This is why
I say that computers are not a less-powerful model of computation than
the human brain, as the one can simulate the other. By 'as powerful'
I mean that the same computations may be performed by both; in the
same sense that a serial computer is as powerful as a parallel one, as
the one can simulate the other, although with a great loss of efficiency.
(c) No, it would not be neccesary to simulate the physical world in
our hypothetical super-computer. We could simulate the actions of the
sensory inputs by filtering such things as movie-camera output,
tactile sensors, etc., through a simulation of human sensory organs.
We know that that is theoretically possible through the same line of
reasoning as above.
-Sean-
--
Sean Philip Engelson I have no opinions.
Carnegie-Mellon University Therefore my employer is mine.
Computer Science Department
----------------------------------------------------------------------
ARPA: spe@spice.cs.cmu.edu
UUCP: {harvard | seismo | ucbvax}!spice.cs.cmu.edu!spe
------------------------------
Date: 23 Oct 87 09:00:36 GMT
From: mcvax!varol@uunet.uu.net (Varol Akman)
Subject: Re: The success of AI (misunderstandings)
In article <213@PT.CS.CMU.EDU> spe@spice.cs.cmu.edu (Sean Engelson) writes:
>
> ....................
>
>discovered in finite (although possibly very large) time. This is why
>I say that computers are not a less-powerful model of computation than
>the human brain, as the one can simulate the other. By 'as powerful'
> ---------------------------------
Congratulations, when are you going to receive your Nobel prize
for discovering that?
Varol Akman, CWI, Amsterdam
What is an individual? A very good question. So good, in fact, that
we should not try to answer it. - DANA SCOTT
------------------------------
Date: 23 Oct 87 17:59:07 GMT
From: uwslh!lishka@speedy.wisc.edu (Christopher Lishka)
Subject: Re: The success of AI (misunderstandings)
In article <213@PT.CS.CMU.EDU> spe@spice.cs.cmu.edu (Sean Engelson) writes:
>
>A couple of clarifications in response to recent posts:
>
>(b) I did not state that we could simulate the human body and brain at
>this point in time. However, we could at some point, presumably, get
>to the point where we know precisely how the body is constructed, and
>construct a simulation of the physical processes that occur. This is
>reasonable because the human body is finite in extent, and thus there
>is a finite amount of information to discover, thus it can be
>discovered in finite (although possibly very large) time. This is why
>I say that computers are not a less-powerful model of computation than
>the human brain, as the one can simulate the other. By 'as powerful'
>I mean that the same computations may be performed by both; in the
>same sense that a serial computer is as powerful as a parallel one, as
>the one can simulate the other, although with a great loss of efficiency.
>
I have some questions of Mr. Engelson (forgive me is I misspelled your
name in my last posting), that others on the net might answer also:
How do we know that a computer and a human are "as powerful" as each
other? How do we know that the same computations can be performed on
each "entity?" Referring back to the biological sciences (esp.
Neurobiology), it would seem that there is so much that is *not* known
that coming to conclusions about abstract things such as how a human
body computes (especially billions of computations that we are not
aware of) is a bit naive at this point. It seems like so many
mistakes that were made in the past about the human body and mind: the
brain as complex plumbing, the brain as a rather large telphone
network, etc. Can the assumption that the two are equal in their
power to compute really be made based on what humans know (and do not
know) about their own functioning? Just a thought (maybe I am looking
at this the wrong way...).
By the same reasoning as above, is the analogy between serial and
parallel computers (and a computer and human body) really a good one?
The differences between any computer and a human body (based on the
little we do know) is staggering. In theory, things appear to be the
same. But computers do not have hormones, neurotransmitters, internal
messengers, complex channels, etc. for each of their "basic"
constituents (which I am assuming are cells). Now, theoretically they
may not be necessary. In constructing a model, it is easy to overlook
what can be implemented and what is easy to implement. But
practically the mechanisms may be necessary. I don't know. No one
else knows. But I do know that my Professor of Neurobiology (whom I
think is a good source) as well as the Grad. Students I have spoken
with *all* warn me to beware of these oversights, because the small
details are what do make the difference. If these messenger molecules
and different neurotransmitters and sodium/potassium/calcium channels
and electrical vs. chemical channels were totally useless, why have
they survived millions of years of evolution? Are we then only
super-parallel processors when compared to parallel-processing
computers, just as parallel-processing computers are to serial
computers?
>(c) No, it would not be neccesary to simulate the physical world in
>our hypothetical super-computer. We could simulate the actions of the
>sensory inputs by filtering such things as movie-camera output,
>tactile sensors, etc., through a simulation of human sensory organs.
>We know that that is theoretically possible through the same line of
>reasoning as above.
Is this reasonable? Could we raise a human being properly be hooking
his retinal receptors to wires, his aural receptors to wires, his
tongue connections to a computer simulation, etc.? Would we get a
*normal* person? Personally, I don't think so, but then I don't know;
noone knows. And until someone such as Hitler comes along, the
question will probably remain unanswered. Now, I feel this applies to
computers because we would, in effect, be doing the same thing (given
that we could artificially create a model of a human in a computer).
You would still need to simulate the real world in the images that you
gave the machine. The images would need to respond to the machine.
When the machine wanted to move, all of the images and artificial
senses would need to reflect that. When the machine tried wanted to
ask a question while standing on its head, twiddling it fingers,
chewing gum, and computing pi to the fourth power, could the images
and artificial senses fed to it effectively simulate that? (I know,
it probably wouldn't have a head or do those things, so just insert
any funny little thing that a "child" computer-modelled human would do
at once.) Again, no small feat. Is this really possible in the
future?
>Sean Philip Engelson I have no opinions.
Just some thoughts of mine (the above are NOT intended to be flames).
I feel is a very interesting discussion, but in the end hinges on
one's personal beliefs and philosophies (but then, what doesn't ;-)
The usual disclaimer applies (including the bit about the cockatiels).
-Chris
--
Chris Lishka /lishka@uwslh.uucp
Wisconsin State Lab of Hygiene <-lishka%uwslh.uucp@rsch.wisc.edu
"What, me, serious? Get real!" \{seismo, harvard,topaz,...}!uwvax!uwslh!lishka
------------------------------
Date: 23 Oct 87 16:32:24 GMT
From: violet.berkeley.edu!ed298-ak@jade.Berkeley.EDU (Edouard
Lagache)
Subject: Clarifying Dreyfus's work (Re: The Success of AI).
I would like to clarify some of the aspects of Hubert Dreyfus's
work that were overlooked by Stephen Smoliar in his note. I won't try
to defend Dreyfus, since I doubt that many people on this SIG is really
open-minded enough to consider the alternative Dreyfus proposes, but
for the sake of correctness:
Most of Mr. Smoliar points are in fact dealt with in his first
book. His second book was intended more for the general public, thus
it glosses over a number of important arguments that are in the first
book. As a matter of opinion, I like the first book better, although
it is probably important to read both books to understand his full
position. The first book is:
What Computers Can't Do, The Limits of Artificial
intelligence, Harper and Row, 1979.
One point where Mr. Smoliar misses Dreyfus completely is in his
assumption that Dreyfus is taking about models. Dreyfus is far more
radical than that. He believes that humans don't make models, rather
they carry a collection of specific cases (images?)
Anyone who is at all honest in this field has to admit that there
are a lot of failures to be accounted for. While I feel that Dreyfus
is too pessimistic in his outlook, I feel that there is value in
looking at his perspective. I would hope that by reflecting on (and
reacting against) such skepticism, A.I. researchers would be able to
sharpen their understanding of both human and Artificial Intelligence.
Edouard Lagache
lagache@violet.berkeley.edu
------------------------------
End of AIList Digest
********************
∂26-Oct-87 0042 LAWS@KL.SRI.Com AIList V5 #246 - Seminars, Conferences
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 26 Oct 87 00:42:18 PST
Date: Sun 25 Oct 1987 22:24-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #246 - Seminars, Conferences
To: AIList@SRI.COM
AIList Digest Monday, 26 Oct 1987 Volume 5 : Issue 246
Today's Topics:
Seminars - Genetic Algorithms and Pallet Loading (BBN) &
Applying AI to Instruction (San Diego SIGART) &
Implementing Theorem Provers in Logic (UPenn),
Conferences - Expert Systems in Business and Finance &
Expert Systems in Agriculture &
Distributed AI Workshop
----------------------------------------------------------------------
Date: Fri 23 Oct 87 16:01:14-EDT
From: DDAVIS@G.BBN.COM
Subject: Seminar - Genetic Algorithms and Pallet Loading (BBN)
BBN Science Development Program
AI/Education Seminar Series
"GENETIC ALGORITHMS AND PALLET LOADING"
Pat Prosser
Dept. of Computer Science
Univ. of Strathclyde
Glasgow G1 1XH
U.K.
BBN Laboratories Inc.
10 Moulton Street
Large Conference Room, 2nd Floor
10:30 a.m., Tuesday, November 10, 1987
Abstract: Genetic Algorithms (GA) are search techniques based on the
paradigm of population genetics. A highly constrained loading
problem, the loading of stacks of plates onto pallets, is used as
a vehicle for measuring the suitability of a GA approach to
solving sequencing problems.
In this seminar the following points will be addressed:
- A brief description of the generic GA
- A description of the pallet loading problem
and two approaches taken in solving the problem
- The genetic representation used
- The two genetic algorithmic solutions implemented
GA1 and GA2
- Implementation and Performance issues
------------------------------
Date: 22 Oct 87 11:40:00 EDT
From: "GAIL SLEMON 455-1330" <gslemon@afhrl>
Reply-to: "GAIL SLEMON 455-1330" <gslemon@afhrl>
Subject: Seminar - Applying AI to Instruction (San Diego SIGART)
The San Diego chapter of ACM SIGART is meeting on November 19, Thursday
evening at the University of California, San Diego, Peterson Hall,
Room 103, 6:30 - 8:30 pm. Everyone is invited to attend. Free admission.
APPLYING AI TO INSTRUCTION
Dr. Greg Kearsley of Park Row Software
This session will focus on the two major applications of Artificial
Intelligence techniques to instruction: intelligent tutoring systems
and expert systems. The major types of intelligent tutors will be
described, along wih a discussion of design and development methodology.
--
For more info on SDSIGART and the above, contact:
Gail Slemon at (619) 455-1330 or GSLEMON@afhrl.arpa
------------------------------
Date: Thu, 22 Oct 87 19:07:41 EDT
From: dale@linc.cis.upenn.edu (Dale Miller)
Subject: Seminar - Implementing Theorem Provers in Logic (UPenn)
Implementing Theorem Provers in Logic Programming
Dissertation Proposal
Amy Felty
(felty@linc.cis.upenn.edu)
Computer and Information Science
University of Pennsylvania
Logic programming languages have many characteristics that indicate
that they should serve as good implementation languages for theorem
provers. For example, they are based on search and unification which
are also fundamental to theorem proving. We show how an extended
logic programming language can be used to implement theorem provers
and other aspects of proof systems for a variety of logics. In this
language first-order terms are replaced with simply-typed
lambda-terms, and thus unification becomes higher-order unification.
Also, implication and universal quantification are allowed in goals.
We illustrate that inference rules can be very naturally specified,
and that the search operations based on this language correspond to
those needed for searching for proofs. We argue on several levels
that this extended logic programming language provides a very suitable
environment for implementing tactic style theorem provers. Such
theorem provers provide extensive capabilities for integrating
techniques for automated theorem proving into an interactive proof
environment. We are also concerned with representing proofs as
objects. We illustrate how such objects can be constructed and
manipulated in the logic programming setting. Finally, we propose
extensions to tactic style theorem provers in working toward the goal
of developing an interactive theorem proving environment that provides
a user with many tools and techniques for building and manipulating
proofs, and that integrates sophisticated capabilites for automated
proof discovery. Many of the theorem provers we present have been
implemented in the higher-order logic programming language Lambda
Prolog.
Date: Friday November 6, 1987
Location: 554 Moore
Time: 1:30 PM
Committee: Val Breazu-Tannen
Robert Constable
Jean Gallier (Chair)
Andre Scedrov
Advisor: Dale Miller
------------------------------
Date: Fri 23 Oct 87 10:07:43-EDT
From: John C. Akbari <AKBARI@CS.COLUMBIA.EDU>
Subject: Conference - Expert Systems in Business and Finance
the first annual conference on expert systems in business and finance
esib-87
[informal announcement]
what: applications-oriented conference on the use of AI and expert systems
in financial domains
where: penta hotel, new york city (7th avenue at 33rd st.)
when: 10 - 12 november 1987
how much: $525 after 9 october
paper sessions: trading with AI
expert systems: opportunities and issues
tools and techniques for financial epxert systems
financial applications
business applications I
business applications II
business applications III
strategic issues in AI development
knowledge engineering challenges
panel discussions:
business and finance: viewing expert systems applications
from the user's requirements perspectives
applying AI in the real world
corporate america: viewng AI technology and organizational
issues from the academic perspective
financial expert systems on PCs: strategies for successful
implementation & integration
expert systems in the business curriculum
views from the press
tutorials: building expert systems
desktop AI: productivity and power in finance
effective knowledge engineering
sponsor: _the international journal of knowledge engineering_
for further info: learned information
143 old marlton pike
medford new jersey 08055 USA
tele. 609.654.6266
personal comments:
looks like an interesting program covering a broad range of work
in the financial services industry. there are several papers by
groups working on the street on internal, proprietary systems.
there are also several papers by vendors (syntelligence, inference,
etc.) who have experience in building these systems. my opinion is
that there the ratio of academic types to "real world" types is still
too high, but is better than most of those expensive "conferences"
put on by the market research and consulting groups. this conference
should be less content-free than most. it will be interesting to see
the effects of this week's crash on future efforts!
------------------------------
Date: Sat, 24 Oct 87 15:15 EDT
From: Thieme@BCO-MULTICS.ARPA
Subject: Conference - Expert Systems in Agriculture
CALL FOR PAPERS
TITLE: Integration of Expert Systems with Conventional Problem Solving
Techniques in Agriculture
SPONSORED BY: AAAI Applied Workshop Series
DESCRIPTION:
Problem solving techniques such as modelling, simulation, optimization,
and network analysis have been used for several years to help agricultural
scientists and practitioners understand and work with biological problems.
By their nature, most of those problems are difficult to define quantita-
tively. In addition many of the models and simulations that have been
developed are not "user-friendly" enough to entice practitioners to use
them. As a result, several scientists are integrating expert system
technology with conventional problem solving techniques in order to increase
robustness of their systems as well to increase usability and to aid in
result interpretation. The goal of this workshop is to investigate the
similarities and differences of leading scientists' approaches and to
develop guidelines for similar work in the future.
CONDITIONS OF PARTICIPATION:
Primary authors (presumably primary investigators) of submitted
manuscripts will be invited to participate in the workshop if their
manuscript is selected. Manuscripts will be submitted in full six weeks
prior to the workshop. The manuscripts will be reviewed for originality and
clear presentation of the topic of integration by a committee appointed by
the coordinating committee. Only 40 participants will be selected in order
to maximize free exchange of ideas. The manuscripts will be distributed to
the participants prior to the workshop in order to help them prepare
questions for other authors. If there is interest, the proceedings will be
published.
LOCATION AND TIME:
April 13-15, 1987 at the Menger Hotel in San Antonio, TX
FOR MORE INFORMATION CONTACT:
Dr. A. Dale Whittaker (409) 845-8379
Agricultural Engineering Department
Texas A&M University WHITTAK at TAMAGEN.BITNET
College Station, TX 77843-2117
Dr. Ronald H. Thieme (617) 671-3772
Honeywell Bull, Inc.
300 Concord Road THIEME at BCO-MULTICS.ARPA
Mail Station 895A
Billerica, MA 01821
Dr. James McKinion (601) 323-2230
Crop Science Research Laboratory
Crop Simulation Research Unit
P.O. Box 5367
Mississippi State, MI 39762-5367
Earl Kline (409) 845-3693
Agricultural Engineering Department
Texas A&M University KLINE at TAMAGEN.BITNET
College Station, TX 77843-2117
------------------------------
Date: Wed, 21 Oct 87 23:19:02 PDT
From: gasser%pollux.usc.edu@oberon.USC.EDU (Les Gasser)
Subject: Conference - DAI Workshop Announcement
WORKSHOP ANNOUNCEMENT - CALL FOR PARTICIPATION
8th Workshop on Distributed Artificial Intelligence
Lake Arrowhead Conference Center
Lake Arrowhead, CA.
May 22-25, 1988
The 8th Distributed AI Workshop will address the problems of
coordinated action and problem-solving among reasonably sophisticated,
intelligent computational "agents." The focus will be be synthetic and
pragmatic, investigating how we can integrate theoretical and
experimental ideas about knowledge, planning, negotiation, action,
etc. in multi-agent domains, to build working interacting agents.
Participation is by invitation only. To participate, please submit an
extended abstract (5-7 double-spaced pages, hard copy only) describing
original work in DAI to the workshop organizer at the address below.
Preference will be given to work addressing basic research issues in
DAI such as those outlined below. A small number of "interested
observers" will also be invited. If you are interested in being an
observer, please submit a written request to attend (hard copy), with
some justification. Participation will be limited to approximately 35
people.
A number of submitted papers will be selected for full presentation,
critique, and discussion. Other participants will be able to make
brief presentations of their work in less formal sessions. There will
be ample time allowed for informal discussion. All participants should
plan to submit a full paper version in advance, for distribution at
the workshop.
Suggested topics include (but are not necessarily limited to):
Describing, decomposing, and allocating problems among a
collection of intelligent agents, including resource allocation,
setting up communication, dynamic allocation, etc.
Assuring coherent, coordinated interaction among intelligent agents,
including allocating control, determining coherence, organization
processes, the role of communication in coherence, plan
synchronization, etc.
Reasoning about other agents, the world, and the state of the
coordinated process, including plan recognition, prospective
reasoning, knowledge and belief models, representation techniques,
domain or situation specific examples, etc.
Recognizing and resolving disparities in viewpoints, representations,
knowledge, goals, etc. (including dealing with incomplete,
inconsistent, and representationally incompatible knowledge) using
techniques such as communication, negotiation, conflict resolution,
compromise, deal enforcement, specialization, credibility assessment,
etc.
Problems of language and communication, including interaction
languages and protocols, reasoning about communication acts
inter-agent dialogue coherence, etc.
Epistemological problems such as joint concept formation, mutual
knowledge, situation assessment with different frames of
reference, etc.
Practical architectures for and real experiences with building
interacting intelligent agents or distributed AI systems.
Appropriate methodologies, evaluation criteria, and techniques for
DAI research, including comparability of results, basic assumptions,
useful concepts, canonical problems, etc.
For this DAI workshop, we specifically discourage the submission of
papers on issues such as programming language level concurrency,
fine-grained parallelism, concurrent hardware architectures, or
low-level "connectionist" approaches.
Please direct inquiries to the workshop organizer at the address below.
----------------------------------------------------------------
DATES:
Deadline for submission of extended abstracts: February 15, 1988
Notification of acceptance: March 21, 1988
Full papers due (for distribution at the workshop): April 25, 1988
----------------------------------------------------------------
WORKSHOP ORGANIZER:
Les Gasser
Distributed AI Group
Computer Science Department
University of Southern California
Los Angeles, CA. 90089-0782
Telephone: (213) 743-7794
Internet: gasser@usc-cse.usc.edu
----------------------------------------------------------------
WORKSHOP PLANNING COMMITTEE:
Miro Benda (Boeing AI Center) Phil Cohen (SRI)
Lee Erman (Teknowledge) Michael Fehling (Rockwell)
Mike Genesereth (Stanford) Mike Georgeff (SRI)
Carl Hewitt (MIT) Mike Huhns (MCC)
Victor Lesser (UMASS) N.S. Sridharan (FMC Corp)
----------------------------------------------------------------
Support for this workshop and for partial subsidy of participants'
expenses has been provided by AAAI; other support is pending.
------------------------------
End of AIList Digest
********************
∂26-Oct-87 0230 LAWS@KL.SRI.Com AIList V5 #247 - Knowledge, Neural Terminology, Design, Linguistics
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 26 Oct 87 02:30:43 PST
Date: Sun 25 Oct 1987 22:30-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #247 - Knowledge, Neural Terminology, Design, Linguistics
To: AIList@SRI.COM
AIList Digest Monday, 26 Oct 1987 Volume 5 : Issue 247
Today's Topics:
Clarification - Knowledge Soup,
Neuromorphic Systems - Historical Terminology,
Bibliographies - Design Automation/Assistance & Computational Linguistics
----------------------------------------------------------------------
Date: 24 October 1987, 20:03:38 EDT
From: john Sowa <SOWA@ibm.com>
Subject: Knowledge Soup
An abstract of a recent talk I gave found its way to the AIList, V5 #241.
But along the way, the first five sentences were lost. Those sentences
made a distinction that was at least as important as the rest of the
abstract:
Much of the knowledge in people's heads is inconsistent. Some of it
may be represented in symbolic or propositional form, but a lot of it
or perhaps even most of it is stored in image-like forms. And some
knowledge is stored in vague "gut feel" or intuitive forms that are
almost never verbalized. The term "knowledge base" sounds too precise
and organized to reflect the enormous complexity of what people have
in their heads. A better term is "knowledge soup."
Whoever truncated the abstract also changed the title "Crystallizing
theories out of Knowledge Soup" by adding "(knowledge base)". That
parenthetical addition blurred the distinction between the informal,
disorganized knowledge in the head and the formalized knowledge bases
that are required by AI systems. Some of the most active research in
AI today is directed towards handling that soup and managing it within
the confines of digital systems: fuzzy logic, various forms of default
and nonmonotonic reasoning, truth maintenance systems, connectionism
and various statistical approaches, and Hewitt's due-process reasoning
between competing agents with different points of view.
Winograd and Flores' flight into phenomenology and hermeneutics is based
on a recognition of the complexity of the knowledge soup. But instead of
looking for ways of dealing with it in AI terms, they gave up. Although
I sympathize with their suggestion that we use computers to help people
communicate better with each other, I believe that variations of current
AI techniques can support semi-automated tools for knowledge acquisition
from the soup. More invention may be needed for fully automated systems
that can extract theories without human guidance. But there is no clear
evidence that the task is impossible.
------------------------------
Date: Sat, 24 Oct 1987 14:44 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList V5 #244 Neuromorphic Terminology
Terms like "neural networks" were in general use in the 1940's. To
see its various forms I suggest looking through the Bulletin of
Mathematical Biophysics in those years. For example, there is a 1943
paper by Landahl, McCulloch and Pitts called "A statistical
consequence of the logical calculus of Nervous Nets" and a 1945 paper
by McCulloch and Pitts called "A heterarchy of values determined by
the topology of Nervous Nets. It is true that Papert and I confused
this with the title of another McCulloch Pitts 1943 paper, which used
the term "nervous activity" instead. Both papers were published
together in the same journal issue. In any case, "neural networks"
and "nervous nets" were already in the current jargon.
In the original of my 1954 thesis, I called them "Neural-Analog
Networks, evidently being a little cautious. But in the same year I
retitled it for publication (for University Microfilms) as "Neural
Nets and the Brain Model Problem". My own copy has "Neural Netorks
and the ..." printed on its cover. My recollection is that we all
called them, simply, "neural nets". A paper of Leo Verbeek has
"neuronal nets" in its title; a paper of Grey Walter used "Networks of
Neurons"; Ashby had a 1950 paper about "randomly assembled nerve
networks. Farley and Clark wrote about "networks of neuron-like
elements". S.C.Kleene's great 1956 paper on regular expressions was
entitled "Representation of events in Nerve Nets and Finite Automata".
Should we continue to use the term? As Korzybski said, the map is not
the world. When a neurologist invents a theory of how brains learn,
and calls THAT a neural network, and complains that other theories are
not entitled to use that word, well, there is a problem. For even a
"correct" theory would apply only to some certain type of neural
network. Probably we shall eventually find that there are many
different kinds of biological neurons. Some of them, no doubt, will
behave functionally very much like AND gates and OR gates; others will
behave like McCulloch-Pitts linear threshold units; yet others will
work very much like Rosenblatt's simplest perceptrons; others will
participate in various other forms of back-propagated reinforcement,
e.g., Hebb synapses; and so forth. In any case we need a generic term
for all this. One might prefer one like "connectionist network" that
does not appear to assert that we know the final truth about neurons.
But I don't see that as an emergency, and "connectionist" seems too
cumbersome. (Incidentally, we used to call them "connectionistic" -
and that has condensed to "connectionist" for short.)
------------------------------
Date: Sat 24 Oct EDT 1987 05:46
From: frodo%research.att.com@RELAY.CS.NET
Subject: Re: AI & Design Automation, Design Assistance
A few references on AI and VLSI CAD
%author Kowalski, T. J.
%title An Artificial Intelligence Approach to VLSI Design
%publisher Kluwer
%address Boston, MA
%date 1985
%keyword DAA
%author Wolf, W. H.
%author Kowalski, T. J.
%author McFarland, M. C.
%title Knowledge Engineering Issues in VLSI Synthesis
%journal Proceedings of the National Conference on Artificial Intelligence
%pages 866-871
%date 1986
%author Kowalski, T. J.
%author Geiger, D. J.
%author Wolf, W. H.
%author Fichtner, W.
%title The VLSI Design Automation Assistant: From Algorithms To Silicon
%journal Design and Test of Computers
%volume 2
%number 4
%pages 33-43
%date August, 1985
%author McFarland, M. C. S.J.
%author Kowalski, T. J.
%title Assisting DAA: The Use of Global Analysis in an Expert System
%journal Proceedings of the IEEE International Conference on Computer Design
%pages 482-485
%publisher IEEE
%address New York, NY
%date October 6, 1986
%keyword DAA BUD
------------------------------
Date: 21 Oct 87 20:12:35 GMT
From: russell!goldberg@labrea.stanford.edu (Jeffrey Goldberg)
Subject: Computational Linguistics Bibliography by E-Mail (CLBIB)
It is possible to do a keyword search on a > 1700 entry
bibliography of work in computational linguistics published in
the 1980's. Here is how:
Computational Linguistics & Natural Language Processing Bibliography by Mail
There is a large (> 1700 items) bibliography of 1980s natural
language processing and computational linguistics sitting on a
Sun called Russell at CSLI. Anyone with a computer account can
now search this bibliography and get a listing of the result by
using electronic mail.
INSTRUCTIONS
The keywords used for the lookup are to be given in the subject line of
your mail message addressed to clbib@russell.stanford.edu (36.9.0.9).
The body of your message will be thrown away.
Here is an example:
% mail clbib@Russell.Stanford.EDU
Subject: Woods ATN 1980
.
EOT
Null message body; hope that's okay
%
Or more compactly:
% Mail -s "woods atn 1980" clbib@Russell.Stanford.EDU < /dev/null
And here is what you would receive in return:
>>> Date: Wed, 11 Jul 87 12:03:35 PST
>>> To: yourname
>>> Subject: CLBIB search: Woods ATN ...
%A T.P. Kehler
%A R.C. Woods
%T ATN grammar modeling in applied linguistics
%D 1980
%P 123-126
%J ACL Proceedings, 18th Annual Meeting
%A William A. Woods
%T Cascaded ATN grammars
%D 1980
%V 6
%N 1
%P 1-12
%J American Journal of Computational Linguistics
This example show one mailing from a Unix machine, but you can
mail CLBIB from any machine and get a result, provided you
remember to put your search keys in the "Subject:" field of the
message.
The entries you get are in standard Unix 'refer' format (see the man page).
You may put between one and eight keywords in the mail "Subject: "
field, and each keyword can be any string of characters (name,
date, topic, etc.) that you think likely to be found in the items
of interest (case is ignored). The list of keywords is interpreted
conjunctively: "Woods" gets you everything published by anyone
called "Woods" in the 1980s, whereas "Woods 1983" narrows that down
to just the 1983 papers (or papers whose first or last page number
is "1983") by persons named "Woods" (or whose title refers to "woods"),
and, of course, there may be no such items (so the reply would contain
nothing). Only the first six characters in a keyword are significant,
so "generation" is indistinguishable from "generalized", and "Anderson"
is indistinguishable from "Andersson". You should bear this in mind
when you consider the relevance of what you receive to your intended
request.
To take up less CPU at this end, please use as your first keyword the
one that will narrow selections down the most. The first key may not be
a year.
If the first key is "help", you will be sent this file.
BUGS
The system is no better than the mail connections.
This system is worse than the mail connections.
The return address is determined only from information in the "From" field.
"Reply-To:" should be checked but it is not.
The return parsing is stupid and doesn't know all there is to know about
RFC822 mail headers.
The "From" and "Subject" fields must have exactly the "F" and the "S"
in uppercase.
It is impossible to seach for only the item "help". (You get this file if
the first key on a subject line is "help")
It is impossible to get all of the entries for one year. [This is not a
bug. If you want the entire list you can follow the instructions about
such things below.]
The mail handling scripts were written by linguists, not by
programmers. The scripts are fragile and the system may be
taken down without notice at anytime.
THE BIBLIOGRAPHY
Some sense of the scope of the bibliography can be gathered from
the following summary information. Here are the authors who find
themselves with a dozen or more of their 1980s publications included:
25 Aravind K. Joshi
19 Bonnie Lynn Webber
18 Robert C. Berwick
18 Jaime G. Carbonell
17 David D. McDonald
15 Philip J. Hayes
15 Wendy G. Lehnert
15 Fernando C.N. Pereira
14 Kathleen R. McKeown
14 Karen Sparck-Jones
13 Eugene Charniak
13 Barbara J. Grosz
13 Jerry R. Hobbs
13 Martin Kay
13 Stuart M. Shieber
12 Douglas E. Appelt
12 Philip R. Cohen
12 C. Raymond Perrault
12 Graeme D. Ritchie
12 Ralph M. Weischedel
12 Yorick A. Wilks
And the papers included distribute across the years like this:
1980: 207
1981: 138
1982: 211
1983: 240
1984: 219
1985: 247
1986: 353
1987: 117
The 1987 figure includes the contents of this year's ACL Proceedings,
and the relevant papers in AAAI-87, but not those from the upcoming
IJCAI meeting in August nor the as-yet-unpublished 1987 European ACL
Proceedings.
Machine-readable copies of
the entire bibliography are available on standard MS-DOS 360K DS/DD disks.
Write to Ms Sheila Lee, CSRP Series, School of Cognitive Sciences,
University of Sussex, BRIGHTON BN1 9QN, UK, asking for a copy of
the CL-NLP8X.BIB bibliography disk, and enclose a check for $16.00 to
cover media, handling, packing and postage costs.
A hardcopy version
of the entire bibliography with a permuted index of titles and an index to
nonprimary authors is to be published by CSLI/Chicago University Press
in November 1987 - details below:
%A Gerald Gazdar
%A Alex Franz
%A Karen Osborne
%A Roger Evans
%D 1987 - in press
%T Natural Language Processing in the 1980's - A Bibliography
%C Stanford
%S CSLI Lecture Notes
%I Chicago University Press
If there is a problem with this program please send a note to:
clbib-request@Russell.stanford.edu
But only questions about the mailing system can be dealt with. Problems
with the content of the bibliography (typos, omissions, etc) are not
something that we are capable of coping with here.
SEE ALSO
refer(1) Mail(1) tib(local)
AUTHORS & ACKNOWLEDGEMENTS
The bibliography was compiled at the University of Sussex under the
direction of Gerald Gazdar by Gerald Gazdar, Alex Franz, Karen Osborne,
and Roger Evans. Initial c-shell scripts were written by Evans and
Gazdar at Sussex. They were overhauled by Jeff Goldberg at CSLI.
In addition to more standard Unix tools (awk(1), sed(1), Mail(1), etc),
refer(1) (available on most Unix distributions) and Tib (available on the
Unix TeX distribution) are employed.
Unix is a trade mark of AT&T.
SUMMARY
To search bibliography mail to clbib@Russell.stanford.edu with the keywords
for the search as your Subject line.
To get a help file send to clbib@Russell.stanford.edu with "help" as the first
keyword in your subject line.
To get in touch with real people, send to clbib-request@Russell.stanford.edu
Information about getting a hardcopy of the bibliography with indicies will
be forthcoming any day now.
--
Jeff Goldberg
ARPA goldberg@russell.stanford.edu
UUCP ...!ucbvax!russell.stanford.edu!goldberg
------------------------------
End of AIList Digest
********************
∂26-Oct-87 0431 LAWS@KL.SRI.Com AIList V5 #248 - OCR, Introductory Prolog, Flawed Minds
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 26 Oct 87 04:31:31 PST
Date: Sun 25 Oct 1987 22:41-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #248 - OCR, Introductory Prolog, Flawed Minds
To: AIList@SRI.COM
AIList Digest Monday, 26 Oct 1987 Volume 5 : Issue 248
Today's Topics:
Query - Character Recognition,
Tools - OCR & Character Recognition,
Education - Introductory Prolog,
Comments - Flawed Minds & Goal of AI
----------------------------------------------------------------------
Date: 16 Oct 87 12:47:55 GMT
From: mcvax!ukc!its63b!hwcs!zen!vic@uunet.uu.net (Victor Gavin)
Subject: Character recognition
I have been puttering about for the past few weeks with an HP ScanJet (one
of those 300dpi digitizers). I have been asked to write some software which
can (given an image produced by the scanner) reproduce the original text of
the paper in a machine readable form.
The text will normally be numbers and the image will initially be a bit
pattern.
If someone can point me to some introductory texts on character recognition
I would be grateful.
If someone has already tackled this problem, any help I can get will be much
appreciated.
vic
--
Victor Gavin Zengrange Limited
vic@zen.co.uk Greenfield Road
..!mcvax!ukc!zen.co.uk!vic Leeds LS9 8DB
+44 532 489048 England
------------------------------
Date: 24 Oct 87 21:14:14 GMT
From: phri!roy@NYU.EDU (Roy Smith)
Subject: Re: Character recognition
In article <641@zen.UUCP> vic@zen.UUCP (Victor Gavin) writes:
> I have been asked to write some software which can (given an image
> produced by the scanner) reproduce the original text of the paper in a
> machine readable form.
I don't know much about it, but a company called DEST markets a
300-dpi scanner for the Macintosh (and, I think, IBM-PC) for about $2k,
including character recognition software. Unless your application has some
special requirements, I would imagine getting one of these jobs would be a
lot more cost-effective than writing your own software.
I've added comp.sys.mac to the Newsgroups line to see if anybody
there has any experience with the DEST they could share. While I'm at it,
can somebody compare and contrast the O($2k) scanners with the el-cheapo
Thunderscan for me. What to the "real" scanners have going for them that I
can't do with a Thunderscan?
--
Roy Smith, {allegra,cmcl2,philabs}!phri!roy
System Administrator, Public Health Research Institute
455 First Avenue, New York, NY 10016
------------------------------
Date: 25 Oct 87 00:51:32 GMT
From: dewey.soe.berkeley.edu!oster@ucbvax.Berkeley.EDU (David
Phillip Oster)
Subject: Re: Character recognition
In article <2984@phri.UUCP> roy@phri.UUCP (Roy Smith) writes:
>In article <641@zen.UUCP> vic@zen.UUCP (Victor Gavin) writes:
>> from a scanner image reproduce the original text of the paper in a
>> machine readable form.
>can somebody compare and contrast the O($2k) scanners with the el-cheapo
>Thunderscan for me. What to the "real" scanners have going for them that I
>can't do with a Thunderscan?
Thunderscan offers very high quality scanning, at resolutions up to
300 dpi, and up to 5 bits per pixel. (32 grays.) It can handle
originals up to 15" wide (in a wide carriage imagewriter) and at least
32767 scan lines long. (I haven't actually tried anything longer than
11", but when it finishes, the "continue scan" button is still waiting
to be presssed.) However, it is slow, (5 to 40 minutes, depending on
resolution and size of original.) and only works on single sheet,
thin, bendable material. (The material has to fit in the imagewriter
printer.) That means you'd do well to have a xerographic copier handy.
The expensive scanners are flat bed, copier style machines, and do
their work faster (can't be too much faster, though. It takes
15minutes to send an 8"x10" page at 1-bit per pixel 300dpi, over a
9600 baud line if you do not use a compressing transfer protocol.)
Olduvai Software makes a line of software that parses scanned pages
back into text. Either the current issue of MacUser has a review, or I
saw it in a recent copy of MacWeek, but for < $200.00 you get a
software package to do syntactic pattern recognition of letter
features, to determine the ASCII for the scanned page.
It is still cheaper to hire a human typist, but soon the cost balance
will flip the other way. (I expect that copy shops will offer a
service: bring in your books and blank disks, and for a few cents a
page, get them digitized to ASCII. (And won't that boost our needs for
on-line storage (What, only 300Gigabytes! How do your get by with such
a small library?)))
(note, I've directed followups to just comp.misc. If people want to continue
this discussion, they can read it there.)
--- David Phillip Oster --A Sun 3/60 makes a poor Macintosh II.
Arpa: oster@dewey.soe.berkeley.edu --A Macintosh II makes a poor Sun 3/60.
Uucp: {uwvax,decvax,ihnp4}!ucbvax!oster%dewey.soe.berkeley.edu
------------------------------
Date: 24 Oct 87 16:42:23 GMT
From: unc!bts@mcnc.org (Bruce Smith)
Subject: Re: Suggestions for Course
Turbo Prolog for an AI course? Why not FORTRAN, for that matter?
Quoting (without permission) from Alan Bundy's Catalog of AI Tools:
FORTRAN is the programming language considered by many to
be the natural successor of LISP and Prolog for AI research.
Its advantages include
1. It is very efficient for numerical computation (many AI
programs rely heavily on number crunching techniques).
2. AI programs tend to be very poorly constructed, meaning
that control needs to move frequently from one part of a
program to another. FORTRAN provides a special mechanism
for achieving this, the so-called GOTO statement.
3. FORTRAN provides a very efficient data structure, the
array, which is particularly useful if, for example, one
wishes to process a collection of English sentences each
of which has the same length.
______________________
Bruce T. Smith, UNC-CH
bts@unc.edu
------------------------------
Date: 24 Oct 87 21:09:34 GMT
From: rocky!wagner@labrea.stanford.edu (Juergen Wagner)
Subject: Re: Suggestions for Course
Great! I believe, Bruce hit the right point. Teaching a programming
language whose conceptual structure is that different from what most
people think of programming languages, should not be done using almost a
counterexample of that paradigm. Some people are convinced that
TurboP#$@$ is a real Prolog (which might be true in their understanding
of AI languages), and there might be applications where sliding away
from PASCAL over TurboProlog to (REAL) Prolog (just to introduce changes
step by step), but it is definitively no good choice for teaching
typical AI programming techniques which (by their nature) require symbol
crunching rather than number crunching. And if I first have to write a
bundle of declarations before I find out that this highly nested and
flexible data structure I have in mind cannot be implemented that way,
this is not what I expect of such a programming language.
Sure, TurboP#$@$ is available on IBM/PCs. But there are also other nice
Prologs around, even a Public Domain one (SBProlog, mentioned in this
newsgroup some time ago). So, why not take a real Prolog even if it is
only line-oriented, and even if you have to write the main parts of your
programs outside Prolog with a conventional text editor? The idea of an
AI course should be to convey to basic principles and the special way of
thinking and reasoning about (so-called) AI problems. Exploring and
experimenting with programs gives a good impression of that.
Ok. No more flames about TurboP#$@$.
Juergen Wagner, (USENET) gandalf@portia.stanford.edu
Center for the Study of Language and Information (CSLI), Stanford CA
------------------------------
Date: 25 Oct 87 03:50:08 GMT
From: violet.berkeley.edu!ed298-ak@jade.Berkeley.EDU (Edouard
Lagache)
Subject: Re: Suggestions for Course (Getting a PROLOG cheap or free)
I think that PROLOG is a much better choice for an intro course
on A.I. (someday maybe I will write a paper on why). As to getting
a PROLOG to use on IBM PCs, there are a number of Public Domain
PROLOGs around. One that I think would be fine for this use is
put out by Automata Design Associates and can be found in
various software libraries or contact them at:
A.D.A.
1570 Arran Way
Dresher, PA, 19025
(215) 646-4894
I think they charge $10 for a copy of their PD PROLOG, but that
would be a one time investment.
Edouard Lagache
lagache@violet.berkeley.edu
------------------------------
Date: 25 Oct 87 15:44:48 GMT
From: duke!gleicher@mcnc.org (Michael Gleicher)
Subject: Re: Suggestions for Course
(Couldn't bear it any longer - I have to put my two cents in)
(I am not a teacher - I am a student who has gone through the courses in
question)
An excellent point has been brought up - What is the real reason for wanting
to teach Prolog in an AI course? (by the way, replace prolog with lisp in
most cases in this article)
1) Because you want to foster the belief that Prolog and AI go
together -
This is downright BAD and wrong!
2) Because in order to read much of the literature, you must
understand Lisp/Prolog because it gets refered to alot -
This one I agree with
3) Because it is the IN thing to do -
I'm not even going to comment
4) Because it allows rapid prototyping so a small system that really
solves problems can be built in a short amount of time -
If this is your real goal, be sure not to get sidetracked.
In the AI course that I took, we were taught prolog, and
wrote programs to solve non-ai problems. I neither learned
about how to write AI programs nor how to rapidly build
a system in Prolog. I did learn some bad Prolog habits
because I was trying to program prolog the same way that
I would have coded in C - because there wasn't enough time
for someone to show me to think otherwise.
On the upside, We did have an assignment with DCG's that
was interesting (only that had any notion of an
AI problem to solve (natural language) or that showed me
a place where I couldn't use conventional programming tactics)
What using AI in a class DID do for me was allow me to get a summer job where
I really learned prolog, doing things that were NOT AI.
The best part of my AI class was when we looked briefly at many areas of
interest in the current research (expert systems, natural language, planning,
connectionism, ...). Unfortunately, this was at the end of the course. Maybe a
more effective way to teach AI would be to show the applications and use them
to justify why you need to study logic and predicate calculus and frames and
...
Using Turbo prolog could only accomplish #1 and #3 on the list above, but
other people have already said this.
Again, I am not a teacher, just a student who has taken these courses, and is
still interested in the subject DESPITE the courses.
And -
PROLOG IS NOT JUST FOR ``AI''
Mike
------------------------------
Date: 25 Oct 87 02:50:37 GMT
From: kludge@pyr.gatech.edu (Scott Dorsey)
Reply-to: kludge@pyr.gatech.edu (Scott Dorsey)
Subject: Humor - Flawed Minds
In article <8710240608.AA19274@ucbvax.Berkeley.EDU>
RCSMPA::HAMILTON@gmr.COM ("William E. Hamilton, Jr.") writes:
>Of course the human mind is flawed. The proof is quite straightforward.
Fred the Football Player says, "I don't get no A's in none of my
classes. Dis is either cause da professirs what give de tests is
flawed, or cause I is flawed. If eider one of dese tings is true,
den I can state catigorikly dat dere is at least won person what
got a flawed mind. If one person got a flawed mind, then he isn't
no good at judgin' if udder people also got flawed minds. Den, since
no person can tell if deir mind is flawed (cause if you mind is
flawed, it might be flawed in way dat make you tink it aint flawed.
If it aint flawed, den you no it aint flawed, but eider way you tink
da same ting, so ya gotta assume dat it's flawed), dey gotta assume
dat it is, so dey aint able to be sure dat dey can tell if anyone
else got one flawed mind. Derefore ya gotta assume dat everybody got
a flawed mind."
--
Scott Dorsey Kaptain_Kludge
SnailMail: ICS Programming Lab, Georgia Tech, Box 36681, Atlanta, Georgia 30332
Internet: kludge@pyr.gatech.edu
uucp: ...!{decvax,hplabs,ihnp4,linus,rutgers,seismo}!gatech!gitpyr!kludge
------------------------------
Date: 22 Oct 87 16:29:25 GMT
From: mcvax!ukc!its63b!hwcs!hci!gilbert@uunet.uu.net (Gilbert
Cockton)
Subject: Re: What the hell does flawed mean, anyway?
In article <1373@houdi.UUCP> marty1@houdi.UUCP (M.BRILLIANT) writes:
>
>I claim that with respect to any referent the mind is flawed.
>If any reader can define any referent with respect to which the
>mind is perfect, I will admit my argument is flawed.
Imperfection?
Pointing to one's belly button
Making excuses
...
...
...
...
...
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
Date: 22 Oct 87 16:20:09 GMT
From: mcvax!ukc!its63b!hwcs!hci!gilbert@uunet.uu.net (Gilbert
Cockton)
Subject: Re: Goal of AI: where are we going?
In article <1368@houdi.UUCP> marty1@houdi.UUCP (M.BRILLIANT) writes:
>Factually, we know the mind is flawed because we observe that it does
>not do what we expect of it.
I expect my car to fetch my shoes
I observe that my car does not fetch my shoes
My car is flawed.
I expect my dog to not move from the fire when I come to put more coal on
I observe that my dog is moving when I come to put more coal on
My dog is flawed
I expect the word foliage to mean any "leaves" on trees shrubs
I observe that people in New England use the word to mean Autumn leaves
People in New England are flawed
Wow! This must be logic we're seeing :-)
Now for an argument based only on my understanding of what it is to
convince: We can expect nothing untoward from something we do not
fully understand at the level of a predictive model. I understand my
car, I do not understand dogs or New Englanders.
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
Date: 23 Oct 87 15:00:25 GMT
From: mcvax!ukc!stc!idec!camcon!ijd@uunet.uu.net (Ian Dickinson)
Subject: Re: Is the human mind flawed?
in article <2809@sdsu.UUCP>, caasi@sdsu.UUCP (Richard Caasi) says:
>
> If the human mind was flawless we wouldn't be debating this issue.
> To determine how flawed the human mind is we need to first define the
> characteristics of a flawless or perfect mind. Any suggestions?
My mind does exactly what I want it to do. I like to be emotive, to be
able to intuit, guess, make mistakes and learn from them, do silly
things to let off steam, laugh at obscure jokes etc. All of these
abilities could be regarded as flaws in a device which aspired to
mechanistic perfection. But I like my mind - for me it _is_ perfect
(although maybe not so to another person).
> Drawing an analogy with ideal operational amplifiers
> in electronics, ....
Hum. I can't think of a machine that I would like to use as an
analogy here. One problem is that we know that the individual components
of the brain (perhaps more analogous to an electronic device) have
pretty awful performance characteristics, but the *mind* as a whole
has characteristics that no machine in existence today can begin to
match. So, whilst I have no doubt that we can create technology
that does improve on the metrics listed in the posting (indeed I am
actively involved in helping to do so), I *do* doubt that this will
get us much nearer to a mindful machine.
> Question: Does such a mind exist or is nothing perfect in the real
> world?
Ultimately, reality is all we have. End of problem.
--
Ian Dickinson Cambridge Consultants Ltd, AI group (0223) 358855 [U.K.]
uucp: ...!seismo!mcvax!ukc!camcon!ijd or: ijd%camcon.uucp
>> Disclaimer: All opinions expressed are my own (surprise!). <<
>> To dance is to live, but the dance of life requires many strange steps <<
------------------------------
Date: 22 Oct 87 15:51:10 GMT
From: mcvax!ukc!its63b!hwcs!hci!gilbert@uunet.uu.net (Gilbert
Cockton)
Subject: Re: Goal of AI: where are we going?
In article <15196@topaz.rutgers.edu> josh@topaz.rutgers.edu
(J Storrs Hall) writes:
>In Western thought it has been realized at long and arduous last that
>the appeal to authority is fallacious.
Tell that to the judge. This understanding of Western social
practices seems weak given its confusion of intellectual idealism with
social reality. Authority counts for far more than rationality or science.
>Experiment works; the real world exists;
Not true all the time - scientific method is flawed, as any sophomore
who's studied epistemology can tell you. The modern command over nature
is due, not to a slavish and unimagintive application of statistical
inference and hypothetico-deductive reasoning, but to an engagement
which combines rigour, rationality (self-critical candour) and
imagination. This view of reality and experiment is very dated and it's
time some of us ignored the off-the-cuff dogma of our chemistry and
physics teachers (rarely real people :-) ) and caught up with modern
Western thinking (and eternal practice).
> objective standards can be applied. Even to people.
They must be proved objective first though, so this argument is empty.
What is an objective standard? I admit the value of the idea,
otherwise our concepts of morality would be weakened. But the term is
not to be used lightly. "flawed" is not an objective standard, though
it can be defined idiosyncratically and after the fact to correspond
to standards which are. Calling the human mind "flawed" in essence
could be being motivated by a lack of fit with an AI model - now
shouldn't this lack of fit suggest the model is flawed and not the
human mind? Note that at the end of the day, the unimaginative
application of any method is less important than the people who are
convinced, and remain convinced over the rest of their life. Science
and convincement are not one and the same, and it is the latter which
guides human life.
>It is true that most AI researchers "believe that
>the mind is a machine", but it seems that the alternative is to
>suggest that human intelligence has a supernatural mechanism.
No, Mind is extra/para-natural - we cannot observe it as we do nature,
and thus the values of science do not apply. More spiritual and
humanist approaches do. By the way, as a historan originally, I would
hold that humanist and spiritual views of human nature have dominated,
and continue to dominate, the public thinking on Man. Reductionist
mechanical scientists appear to be an ugly minority who have little
*respectful* social contact outside their own self-congratulating cliques.
>The anti-scientific mentality is an emotional
>excuse used to avoid thinking clearly. It would be much more honest
>to say "I don't want to think, it's too hard work."
There are other interpretations of this. I wouldn't use, for example,
predicate logic (and thus Frames, semantic nets, etc),
to describe the design process, not because it is too hard, but
because it becomes a cretinous tool when describing such a rich
human phenomenum. Thus I am not avoiding hard work; I am avoiding
*fruitless* work. Many workers in AI would do better if they stopped
trying to cram the world into an impoverished computational
representation and actually explored the rich range of non-computable
knowledge representations (e.g. the Novel, the painting, psalms, the
monographs of the liberal arts). If this is all too inaccessible to their
critical abilities, they could at least read some of the established
works of scholarship on semantics (e.g. Lyons' 2 volumes).
>The champions of irrationality, mysticism, and superstition have
>emotional problems which bias their cognitive processes. Their minds are flawed
This is very sad. I think the author is missing something, somewhere.
I cannot believe that those who share a same higher view of humanity
are misleading themselves. What does the author's friends think?
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
End of AIList Digest
********************
∂26-Oct-87 0728 LAWS@KL.SRI.Com AIList V5 #249 - Success of AI
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 26 Oct 87 07:28:30 PST
Date: Sun 25 Oct 1987 22:48-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #249 - Success of AI
To: AIList@SRI.COM
AIList Digest Monday, 26 Oct 1987 Volume 5 : Issue 249
Today's Topics:
Comments - The Success of AI
----------------------------------------------------------------------
Date: 23 Oct 87 13:23:05 GMT
From: cbmvax!snark!eric@rutgers.edu (Eric S. Raymond)
Subject: Re: The Success of AI
In article <1342@tulum.swatsun.UUCP>, scott@swatsun (Jay Scott) writes:
>[quoting me:]
>> In *each case*, these problem areas were defined out of the AI field as soon
>> as they spawned halfway-usable technologies and acquired their own research
>> communities.
>
> Here's one speculation: People see intelligence as mysterious, intrinsically
> non-understandable. So anything understood can't be part of intelligence,
> and can't be part of AI. I assume this was what Eric had in mind in a
> previous article, when he mentioned "hidden vitalist premises".
Yes, that is precisely what I intended.
> Any other good ideas?
Maybe :-). A friend once told me that she'd read that human institutions reach
a critical size at 250 people; that that is the largest social unit for which
a single member can keep a reasonable grasp on the capabilities and style of
everyone else in the group. This insight explains the allegedly remarkably
consistent size of pre-industrial villages in areas where enough settlement
land is available so that people can move elsewhere when they want.
There is supposedly one well-known company that has found that the productivity
gains from holding their work units down to this size more than justify the
diseconomies of scale from small plants.
This idea gets some confirmation from my experience of SF fandom, a totally
voluntarist subculture that has, historically, thrown off sub-communities
like yeast buds (SCA, Trek fandom, the Darkovans, the Dr. Who people, etc.
etc.). We even have a name for these 'buds'; they're called "fringe fandoms"
and the people in them "fringefen" (the correct plural of "SF fan" is, by
ancient tradition "SF fen").
In this context, the theory needs a little generalizing; what seems
to count for that magic 250 is not the number of self-described "Xites", but
rather the smaller number of *organizers* and *regulars*; the people that
maintain the subculture's communications networks and set its style.
Now: let's assume a parallel division in science between "stars" (the people
who do, or are seen to be doing, the important work) and "spear carriers"
(the people who fill in the corners, tie down the details, go after the
last decimal places, and get most of the grants ;-)). We then have:
RAYMOND'S HYPOTHESIS:
A scientific field with more than 250 "stars" will tend to fragment
into subspecialties more and more strongly as the size increases.
It would be interesting to look at other classes of voluntarist subcultures
(like, say, fringe political parties) to see if a similar pattern holds.
--
Eric S. Raymond
UUCP: {{seismo,ihnp4,rutgers}!cbmvax,sdcrdcf!burdvax,vu-vlsi}!snark!eric
Post: 22 South Warren Avenue, Malvern, PA 19355 Phone: (215)-296-5718
------------------------------
Date: 23 Oct 87 21:23:31 GMT
From: ihnp4!chinet!nucsrl!coray@ucbvax.Berkeley.EDU (Elizabeth)
Subject: Re: The success of AI (misunderstandings)
in reponse to: spe@SPICE.CS.CMU.EDU (Sean Engelson) / 9:21 am Oct 22, 1987 /
> This is reasonable because the human body is finite in extent,
> and thus there is a finite amount of information to discover,
> thus it can be discovered in finite (although possibly very large) time.
I am planning on gracefully failing my qualifiers in just two weeks, and
one of the questions I plan to fail will have to do with decidability.
Because now I know that I will blithely point out that language is finite in
extent and thus there is only a finite amount of information which it
can convey, so why worry about unprovable true theorems? We'll just
prove all the true ones (in possibly very large finite time?) and then
see if the theorem of interest is in this finite set.
Grade -2.
------------------------------
Date: Saturday, 24 October 1987, 18:41-EDT
From: nick@MC.LCS.MIT.EDU
Subject: The success of AI (misunderstandings)
In article <193@PT.CS.CMU.EDU> spe@spice.cs.cmu.edu (Sean Engelson) writes:
>Given a sufficiently powerful computer, I could, in theory, simulate
>the human body and brain to any desired degree of accuracy.
You are in good company. Laplace thought much the same thing
about the entire physical universe.
However, some results in chaos theory appear to imply that
complex real systems may not be predictable even in principle. In a
dynamic system with sufficiently 'sensitive dependence on intial
conditions' arbitrarily large separations can appear (in the state
space) between points that were initially arbitrarily close. No
conceivable system of measurement can get around the fact that the
behavior of the system itself 'systematically' erodes our information
about its state.
For a good intro to chaos theory, see the article by Farmer,
Packard, et. al. in Scientific American December 86..
------------------------------
Date: 24 Oct 87 20:41:29 GMT
From: ihnp4!homxb!whuts!mtune!codas!usfvax2!pdn!alan@ucbvax.Berkeley.E
DU (Alan Lovejoy)
Subject: Re: The Success of AI
In article <193@PT.CS.CMU.EDU> spe@spice.cs.cmu.edu (Sean Engelson) writes:
/Given a sufficiently powerful computer, I could, in theory, simulate
/the human body and brain to any desired degree of accuracy...
/...if I can simulate the body in a computer, the
/computer is a sufficiently powerful model of computation to model the
/human mind...
The ultimate in "machine emulation"!!!!
Why does this remind me of Chomsky's concept of 'weak' and 'strong'
equivalence between grammars? Hmmm...
--alan@pdn
------------------------------
Date: 24 Oct 87 20:52:32 GMT
From: ihnp4!homxb!whuts!mtune!codas!usfvax2!pdn!alan@ucbvax.Berkeley.E
DU (Alan Lovejoy)
Subject: Re: The Success of AI
In article <224@bernina.UUCP> srp@bernina.UUCP (Scott Presnell) writes:
/In article <193@PT.CS.CMU.EDU> spe@spice.cs.cmu.edu (Sean Engelson) writes:
/>Given a sufficiently powerful computer, I could, in theory, simulate
/>the human body and brain to any desired degree of accuracy.
/
/Horse shit. The problem is you don't even know exactly what you are
/simulating! ...
/For instance, dreams, are they logical?, do they fall in a pattern?, a computer
/has got to have them to be a real simulation of a body/mind, but you cannot
/simulate what you cannot accurately describe.
Simulated horse shit! I can write a simulator for the IBM-PC to run on
a Macintosh-II, without knowing or understanding all the IBM-PC programs
that will ever run on it. The same is in principle possible when the
machine being emulated is a human body.
/Let's get down to a specific case:
/I propose that given any amount of computing power, you could not presently,
/and probably will never be able to simulate me: Scott R. Presnell.
/My wife can be the judge.
Which wife? The one being simulated by the computer as part of the
simulated environment in which you are being simulated? How would you
or she know which "world" you belonged to?
--alan@pdn
------------------------------
Date: 24 Oct 87 21:08:27 GMT
From: ihnp4!homxb!whuts!mtune!codas!usfvax2!pdn!alan@ucbvax.Berkeley.E
DU (Alan Lovejoy)
Subject: Re: The Success of AI
In article <1993@gryphon.CTS.COM> tsmith@gryphon.CTS.COM (Tim Smith) writes:
/In article <193@PT.CS.CMU.EDU> spe@spice.cs.cmu.edu (Sean Engelson) writes:
/+=====
/| Given a sufficiently powerful computer, I could, in theory, simulate
/| the human body and brain to any desired degree of accuracy. This
/You might, for example, claim that with a
/very large number of computers, all just at the edge of the
/speed boundaries dictated by the laws of physics in the most
/advanced materials imaginable, you could simulate a human body
/and mind--but not in real time. But the simulation would have to
/be in real time, because humans live in real time, doing things
/that are critically time dependent (perceiving speech, for
/example).
You make the invalid assumption that "simulation" means that those of
us in the real universe can not distinguish the simulated object or
process from the real thing. It is just as valid to deal with
simulations that enable one to make accurate predictions about what
would happen in the real world in some well-specified scenario, even
if the simulation doesn't look anything like what is simulates in the
physical sense. What matters is the logical equivalence or similarity
in an abstract reality.
/Similarly, humans think the way they do partially because of
/their size, because of the environment they live in, because of
/the speed at which they move, live, and think.
If the environment of an object is simulated in addition to the object
itself, one need merely synchronize the object with the simulated
environment as to speed, size, etc.
--alan@pdn
------------------------------
Date: 23 Oct 87 16:22:45 GMT
From: mcvax!ukc!its63b!hwcs!hci!gilbert@uunet.uu.net (Gilbert
Cockton)
Subject: Re: The Success of AI
In article <193@PT.CS.CMU.EDU> spe@spice.cs.cmu.edu (Sean Engelson) writes:
>Given a sufficiently powerful computer, I could, in theory, simulate
>the human body and brain to any desired degree of accuracy. This
>gedanken-experiment
keinen gedanken mein Herr!
In **WHICH THEORY**? Cut out this use of theoretical to mean "given
arbitrary fantasies". Theories have real substance, and you are
obliged to elaborate on the theory before alluding to it.
Given a sufficiently powerful computer, could I, in theory, get
everyone on the net to like my postings? Rhetorical of course, so spare
me any abusive replies :-). The point again, is that I would have to
elaborate the theory and test it out to be sure. Furthermore, I could
not expect everyone to be convinced, that in the event of highly
unlikely (impossible I believe) universal acceptance of my postings,
that my theory really was the explanation. In short, even if one dropped
fantasy for science, people in general are not going to be convinced.
> if I can simulate the body in a computer, the computer is a
> sufficiently powerful model of computation to model the mind.
Of course. Now simulate it. And of course, you won't be slowed down by reading
up on all the unanswered objections to the **belief** that computable formalisms
can model mind. In short, this is no contribution to the argument.
>we must also accept that a computer can have a mind, if only by the
>inefficient expedient of simulating a body containing a mind.
Ahem. Socialisation.
AI people rarely have a handle on this at all. I take it that your
computer simulation of the body is going to go down to the park with
you to see the ducks, go down to playgroup, start primary school and
work through to a degree, mixing all the time with a wide range of
people, reading books, watching TV and visiting interesting places?
Look, people are people because they interact as people with people.
Now, who's going to want to interact with your computer as if it were
a person?
Need I go on?
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
Date: 23 Oct 87 13:13:59 GMT
From: mcvax!ukc!its63b!hwcs!hci!gilbert@uunet.uu.net (Gilbert
Cockton)
Subject: Re: The Success of AI
In article <1922@gryphon.CTS.COM> tsmith@gryphon.CTS.COM (Tim Smith) writes:
(the best posting on this issue I've seen)
>It wasn't until computers came along that there was a
>metaphor for the brain powerful enough to be taken seriously.
Hence the circularity in much AI appeal to cognitive psychology.
As the latter is now riddled with information processing concepts, the
impulsive observer will be quick to conclude from cog. psy. research
that cognition works like a computer. Wrong conclusion - many cognitive
psychologists talk about mind *as if it were* a computer. Likeness,
especially presumed likeness, is not the same as essence, assuming
noumenal objects exist of course.
>There is no reason, in principle, that a very powerful
>digital computer cannot imitate a mind
Apologies for picking up on this, given the writer's (deleted)
qualification and probable sarcasm about arguments of this form. This
may appear perverse, but what on earth are these arguments of the form
"nothing in principle prevents"? They are used much by the "pure" AI
misanthropes, but I can never find any substance in such arguments.
Which principles? How can we argue from these principles to
possibility/impossibility. After all, is there anything of any genuine
interest to non-logicians which is logically impossible, rather than
semantically contradictory (a married bachelor for example)?
Again, I pick this up because AI zealots reach for this argument all
the time, and it isn't an argument at all.
(PS - no flames on "misanthrope" or "zealot", one can be studying an
AI topic without losing one's humanism or one's sense of moderation.
I am only characterising those who are misanthropic zealots, a specialisation
and not a generalisation.)
>The success rate in AI research (as well as most of cognitive
>science) in the past 20 years is not very encouraging.
Despite all that taxpayers' money :-)
> A better concept of "mind" is what is needed now.
Well said. "Better" concepts related to mind than those found in cog. sci.
already exist. The starting point is the elaboration of the observable human
phenomena which we are attempting to unify within a study of mind. These
phenomena have been studied since the dawn of time. There are many
monumental works of schlarship which unify the phenomena grouped into
well-defined subfields. The only problem for AI workers surveying all
these masterpieces is that none of the authors are committed to
computational models. Indeed, they would no doubt laugh at anyone who
suggested that their work could be reduced to a Turing Machine compatible
notation.
> This is not to say that AI research should halt
But AI research could at least be disciplined to study the existing work
on the phenomena they seek to study. Exploratory, anarchic,
uninformed, self-indulgent research at public expense could be stopped.
(and not just in AI, although I've never seen such a lack of
discipline and scholarship anywhere else outside of popular history
and futorology, neither of which attract public funds).
> or that computers are not useful in studying human
> intelligence. (They are indispensable.)
Yes (no). They have proved useful in many areas of study. They have
never been used at all in others, beacuse they have not been able to
offer anything worthy of attention.
> For one example of this new way of thinking, see the recent book by the
> linguist George Lakoff, entitled "Women, Fire, and Dangerous Things."
Does he use computers?
>I believe the great success of AI has been in showing that
>the old dualistic separation of mind and body is totally
>inadequate to serve as a basis for an understanding of human intelligence.
How can you attribute the end of dualism to AI research. This is a
historical statement which should be backed up by references to
specific pieces of work in AI. I doubt that anything emerging from AI
(rather than the disciplines of Cognitive Science)
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
End of AIList Digest
********************
∂28-Oct-87 0031 LAWS@KL.SRI.Com AIList V5 #250 - Cybernetics, Education, Neuromorphic Simulators
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 28 Oct 87 00:31:28 PST
Date: Tue 27 Oct 1987 21:43-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #250 - Cybernetics, Education, Neuromorphic Simulators
To: AIList@SRI.COM
AIList Digest Wednesday, 28 Oct 1987 Volume 5 : Issue 250
Today's Topics:
Queries - NIL & Literature Classification &
Parallel Logic Programming and Architectures,
Definitions - Cybernetics,
Education - Introductory Lisps and Prologs,
Neuromorphic Systems - Simulator Sources,
References - Chaos Theory
----------------------------------------------------------------------
Date: Tue, 27 Oct 87 06:54:35 -0500
From: johnson <johnson@UDEL.EDU>
Subject: NIL (the lisp)
where can i get a copy (of the source code for) NIL (the lisp implementation)?
does anyone out there have a small (minimal) fast lisp in C with
free or at least royalty-free source code ?
thanks,
johnson@UDEL
------------------------------
Date: 26 Oct 87 15:53:00 GMT
From: mcvax!unido!uklirb!noekel@uunet.uu.net
Subject: Literature classification - (nf)
Hi everybody,
we're currently building a AI bibliography and are still searching for a
suitable classification/key word scheme. If there are any schemes that have
gained wide-spread use in the AI community I would be very interested to
learn about them. Obviously adopting such an existing scheme would be the
sensible thing to do since in this case it would be much easier to merge
our bibliography with others.
Hints and pointers are welcome. If I get buckets of answers, I'll summarize
to the net.
Thanks in advance
Klaus Noekel
Universitaet Kaiserslautern
Fachbereich Informatik
Postfach 3049
6750 Kaiserslautern
West Germany
UUCP: ...!mcvax!unido!uklirb!noekel
------------------------------
Date: 27 Oct 87 14:49:00 EST
From: Innes (I.A.) Ferguson <IAF%BNR.BITNET@wiscvm.wisc.edu>
Subject: Parallel logic programming and architectures
I am currently in the process of trying to track down which schools
are doing graduate research in the area of parallel logic programming
and/or related machine architectures, and have come up with about a
dozen so far. If anybody attends or knows of any graduate schools doing
work in this area, I would very much like to hear from them.
If I get enough response, I'll make up a list and post it on the net.
Thanks in advance.
Innes A. Ferguson,
BNR Ltd., Ottawa, Canada
tel.: (613) 727-2586
NETNORTH: iaf@bnr
------------------------------
Date: 26 Oct 87 09:56:26 GMT
From: speedy!honavar@speedy.wisc.edu (A Buggy AI Program)
Subject: Cybernetics, some definitions
In article <3861@venera.isi.edu> smoliar@vaxa.isi.edu.UUCP
(Stephen Smoliar) writes:
>In article <8300006@osiris.cso.uiuc.edu> goldfain@osiris.cso.uiuc.edu writes:
>> On the other hand, whatever became of the term "cybernetics" that Norbert
>>Weiner coined long ago? I thought its definition was quite suitable for
>>denoting this research. ...
Some definitions (From "Cybernetic Medley" by Pekelis, MIR Publishers,
Moscow, 1986 - which by the way, is an eminently readable book):
"study of control and communication in machines and human beings" -
-- Norbert Weiner, USA.
"a science concerned with the study of systems of any nature which are
capable of receiving, storing, and processing information so as to use
it for control"
-- Academician A. N. Kolmogorov, USSR.
"the art of securing efficient operation"
-- L. Couffignal, France.
"a general theory of causality which is interpreted accurately to the
part of isomorphism"
-- A. Markov, Associate fellow, USSR Academy of Sciences.
"a science concerned with the control of sophisticated dynamic systems,
which is theoretically based on mathematics and logic, and practically,
on the use of means of automation, electronic computers of primarily
control and data-processing types"
-- Axel Berg
"a science concerned with the laws of receiving, storing, transmitting,
and processing information in sophisticated systems of control"
-- Academician V. Glushkov, USSR.
"a science concerned with systems that have vitality, that is, which
behave so as to survive"
-- Stafford Beer, British mathematician
-- Vasant Honavar
(honavar@speedy.cs.wisc.edu)
------------------------------
Date: 26 Oct 87 06:02:22 GMT
From: rocky!wagner@labrea.stanford.edu (Juergen Wagner)
Subject: Re: Suggestions for Course
In my opinion, Prolog and AI are not that much interwoven as they are, just
because some people in a small room somewhere decided to use Prolog for their
(so-called) AI problems, but because Prolog is SUITABLE and ADEQUATE for this
class of problems for a number of reasons. One shouldn't argue that Prolog is
no good to be taught in an AI class because of bad experience with this type
of courses. If fact, requests for information on how to teach these courses
will hopefully improve them.
Juergen Wagner, (USENET) gandalf@portia.stanford.edu
Center for the Study of Language and Information (CSLI), Stanford CA
------------------------------
Date: 26 Oct 87 20:44:38 GMT
From: devvax!jplpro!des@elroy.jpl.nasa.gov (David Smyth)
Subject: Re: Suggestions for Course
In article <1746@unc.cs.unc.edu> bts@unc.UUCP (Bruce Smith) writes:
>Turbo Prolog for an AI course? Why not FORTRAN, for that matter?
>Quoting (without permission) from Alan Bundy's Catalog of AI Tools:
>
> 2. AI programs tend to be very poorly constructed, ...
> ... FORTRAN provides a special mechanism
> for achieving this, the so-called GOTO statement.
>
> 3. FORTRAN provides a very efficient data structure, the
> array, which is particularly useful if, for example, one
> wishes to process a collection of English sentences each
> of which has the same length.
Well, I must admit that I tried exactly this: I used FORTRASH for
my homework assignments in my "Intro to AI" course. The professor's
response: "What is this? Some kind of a joke?"
I explained that SUCKTRAN with a stack is Turing equivalent, and
so there was nothing he could do in Lisp that I could not do in
SUCKTRASH. Besides, the Lisp system at school ran on one of those
dinosaurs that all the undergrads had to use, so it was predictably
unreliable and SLOW. I, on the otherhand, had acess to all these
neat-o bitchen machines at work with various FORTRAN viruses,
which both worked and had good response.
It did take me awhile to develop libraries I needed, like
variable length array support (Lisp, at some level, has to
be concerned about running out of contiguous space too, you know -
or didn't you %↑)
Anyway, I passed. Probably got an A too.
------------------------------
Date: 26 Oct 87 20:30:31 GMT
From: decvax!necntc!ci-dandelion!bunny!mdf0@ucbvax.Berkeley.EDU
(Mark Feblowitz)
Subject: Re: Suggestions for Course
With regard to the use of Turbo Prolog, I would like to make bring up the
standard argument against "experience polution." The notion that an
educational tool can afford to be non-standard or inferior because it is
"only for beginners" assumes that the beginner will be able to reformulate
his/her attitudes or habits when the appropriate time arrives.
For this reason, I recommend the use of a Prolog implementation that is
more compatible with C&M Prolog. My favorite Prolog for the PC is
Arity Prolog. It is what I consider to be a production quality Prolog
development environment. It:
is FAST,
links to assembly code or C
has a full virtual memory system
can run either compiled or interpreted
...
The compiler comes with a "lint" facility for static precompilation analysis
of typical Prolog programming errors.
There is a low-end interpreter for the beginner, and I believe that there
are educational discounts available (contact Arity Prolog to verify this).
Although I have encountered a few bugs, the folks at Arity have been
quite supportive in fixing these bugs.
I am looking forward to their upcoming version 5, which aparently has
an integrated editor and enhanced user-interface capabilities,
among other things.
Arity Prolog is located in Concord, MA, (617) 371-1243.
I am NOT a representative of, nor do I have any financial
interest in Arity Corp. I am merely a satisfied user of Arity Prolog.
Mark Feblowitz GTE Laboratories, Inc., 40 Sylvan Rd. Waltham, MA 02254
(617) 466-2947
CSNET: feblowitz@GTE-LABS.CSNET
UUCP: feblowitz@bunny.UUCP old UUCP: harvard!bunny!mdf0
--
Mark Feblowitz GTE Laboratories, Inc., 40 Sylvan Rd. Waltham, MA 02254
(617) 466-2947
CSNET: feblowitz@GTE-LABS.CSNET
UUCP: feblowitz@bunny.UUCP old UUCP: harvard!bunny!mdf0
------------------------------
Date: 27 Oct 87 09:28:32 est
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Suggestions for Course
It seems to me that your list of reasons for using Lisp or
Prolog in an AI class didn't include the single substantive
reason for using Lisp, which is that that its use of just a
couple of primitive data types to represent both data and code
make it particularly easy to writing specialized languages and
interpreters or compilers for them. Especially pattern-directed
invocation languages.
The reason for using Prolog is that it embeds one particular
pattern-directed invocation paradigm for writing AI programs and
makes that extremely fast, although clearly your experience with
DCG notation suggests that it too has the unity of code and data
that is helpful in constructing alternative interpreters.
The reason it is important to be able to build specialized
languages and interpreters is that those are what makes it
possible to build specialized representations appropriate for
different problems. And the engineering of appropriate
representations is fundamental to AI. (which is not to claim
that we know how to do it very well yet :-)
------------------------------
Date: 27 Oct 87 15:42:21 GMT
From: gatech!hubcap!steve@bloom-beacon.mit.edu ("Steve" Stevenson)
Subject: Re: Suggestions for Course
in article <10475@duke.cs.duke.edu>, gleicher@duke.cs.duke.edu
(Michael Gleicher) says:
Xref: hubcap comp.lang.prolog:357 comp.ai:845
One of the reasons to use prolog is to give my students another language model.
It also motivates the study of certain topics in resolution. The question of
what's right or wrong with the exact prolog used is less important in my mind
as long as the students see that TurboPascal is not the world.
--
Steve (really "D. E.") Stevenson steve@hubcap.clemson.edu
Department of Computer Science, (803)656-5880.mabell
Clemson University, Clemson, SC 29634-1906
------------------------------
Date: 27 Oct 87 22:17:49 GMT
From: joglekar@riacs.edu (Umesh D. Joglekar)
Reply-to: joglekar@hydra.riacs.edu (Umesh D. Joglekar)
Subject: Re: Introductory books on Lisp
Try .. ANATOMY OF LISP - By Allen
------------------------------
Date: Tue, 27 Oct 87 17:28:11 est
From: ah4h+@andrew.cmu.edu (Andrew Hudson)
Subject: Re: neuro sources
This is in response to a query for connectionist simulator code.
Within a month, one of the most comprehensive back propagation
simulators will be available to the general public.
Jay McClelland and David Rumelhart's third PDP publication,
Exploring Parallel Distributed Processing: A Handbook of Models, Programs,
and
Exercises will be available from MIT Press. C source code for the complete
backprop simulator, as well as others, is supplied on two MS-DOS format
5 1/4" floppy discs. The simulator, called BP, comes with the
necessary files to run encoder, xor, and other problems. It supports
multiple layer networks, constrained weight, and sender to receiver options.
The handbook and source code can be ordered from MIT Press at the address
below. The cost for both is less than $30. Why spend thousands more for
second best?
The MIT Press
55 Hayward Street
Cambridge, MA 02142
Another version of the BP simulator which is not yet generally available
to the public has been modified to take full advantage of the vector
architecture of the Convex mini-supercomputer. For certain applications
this gives speed increases of 30 times that of a VAX 11/780. A study is
underway to see how well BP will perform on a CRAY XMP-48.
- Andrew Hudson
ah4h@andrew.cmu.edu.arpa
Department of Psychology
Carnegie Mellon
412-268-3139
Bias disclaimor: I work for Jay, I've seen the code.
------------------------------
Date: 27 Oct 87 15:45:21 GMT
From: ssc-vax!dickey@beaver.cs.washington.edu (Frederick J Dickey)
Subject: Re: The success of AI (misunderstandings)
In article <8710260721.AA26918@ucbvax.Berkeley.EDU>, nick@MC.LCS.MIT.EDU writes:
> For a good intro to chaos theory, see the article by Farmer,
> Packard, et. al. in Scientific American December 86..
Recently, on popular book on chaos has been published. Its title is
"Chaos" and the author is Gleick. Sorry, I don't remember any more details.
It seems to be a good book, but I don't have any idea if professional
chaoticians would like it.
------------------------------
End of AIList Digest
********************
∂28-Oct-87 0231 LAWS@KL.SRI.Com AIList V5 #251 - Kolmogorov, Supercomputing, Methodology
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 28 Oct 87 02:31:47 PST
Date: Tue 27 Oct 1987 22:06-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #251 - Kolmogorov, Supercomputing, Methodology
To: AIList@SRI.COM
AIList Digest Wednesday, 28 Oct 1987 Volume 5 : Issue 251
Today's Topics:
Obituary - A.N. Kolmogorov,
Review - Spang Robinson Report on Supercomputing, V1 N2,
Comments - AI Methodology
----------------------------------------------------------------------
Date: 26 Oct 1987 10:18:13-EST (Monday)
From: Leonid Levin <LND%BU-CS.BU.EDU@forsythe.stanford.edu>
Reply-to: TheoryNet List
Subject: The death of A.N. Kolmogorov.
I just learned that in Moscow died Andrei Nikolayevich Kolmogorov - a
great mathematician who also made crucial contributions to Theoretical
Computer Science, Probability and Statistics, Information Theory and
other fields. He also was one of those rare people whose personal
integrity influenced ethical and human standards to the extent possible
under the difficult conditions of a totalitarian state.
Any telegrams from organizations and persons who appreciated the
contributions of A.N. Kolmogorov will be gratefully received. They may
be directed to Moscow University, The Academy of Sciences of the
U.S.S.R. and the widow Anna Dmitriyevna Kolmogorov (117234, Moscow,
Moscow University, korpus (building) L, apartment 10, USSR).
------------------------------
Date: Sun, 25 Oct 1987 12:23 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Review - Spang Robinson Report on Supercomputing, V1 N2
Summary of Spang Robinson Report on Supercomputing and Parallel Processing
Volume 1 , No. 2
The lead article is on Hypercube based systems emphasizing the offerings
from Intel, NCUBE and Floating Point Systems.
The first implementation of the Hypercube based architectures was in the Soviet
Union in the 1970's. Spang Robinson estimates revenues from 15 to 20
million dollars per year from Hypercube companies in 1987. OVUM predicts 1.15
billion dollar revenue from hypercubes in 1990.
Intel Scientific Computers has benchmarked its 80286 based vector processor with
32 nodes against a Cray X-MP on a Fluid Dynamics Code and achieved equivalent
performance. The iPSC/2 has 80386 and 80387 in each node with 512KB. They
use Unix V.3 and a Concurrent Workbench which allows multiple users to share
the node. System prices ranges from $165,000 to $1.76 million for systems
from 16 nodes to 128 nodes. The 64 node vector processor sells for $929
thousand.
Floating Point Systems reports 1.2 GigaFlps on their T200 system. They have
made a total of ten installations. The node contains a T414 Transputer as
a control node, a vector processor, 1 meg of RAM and four communication links.
Each node takes one printed circuit board and eight nodes are grouped with
an 80 meg disk storage unit. A T-20 costing $400,000 contains 16 nodes and
is rated at 192 MFLOPS. A T200 with 128 nodes costs 3 millions. They
use a DEC micro VAX II to host the system and some system programming
is done in OCCAM. One is installed at Clemson University where they are
install SPICE.
Ametek sold several S-14 systems and is working on a second-geeneration
product with announcements planned before the end of 1987. They have doubled
their building space.
NCUBE uses a proprietary chip at each node with 512 kilobytes of memory and
twenty-two DMA channels. 64 nodes are on a single printed circuit board.
The NCUBE 7 goes to 128 nodes ($350,000 with 500 MB DISK) and the NCUBE 10
goes to 1024 nodes ($1.7 million). An NCUBE 4 that fits in a PC is from $20,000
to $60,000. They use a UNIX like operating system.
A total of 70 installations have been made with half in Universities.
___________________________________________________________________
Book Review: The Supercomputer Era by Sidney Karin and Norris Parker Smith
_________________________________________________________________________
Discussions of Cray Research changes included the departure of Steve Chen.
Steve Chen has formally announced a new corporation to continue the
research.
__________________________________________________________________________
The NSA has set up its own supercomputer development project, deciding that
industry will not produce products meeting its need.
------------------------------
Date: 23 Oct 87 16:35:26 GMT
From: umix!umich!dwt@uunet.UU.NET (Dave West)
Reply-to: umix!zippy.eecs.umich.edu!dwt@uunet.UU.NET (David West)
Subject: Re: Lenat's AM program
In article <8710211650.AA18715@orstcs.CS.ORST.EDU> tgd@ORSTCS.CS.ORST.EDU
(Tom Dietterich) writes:
>The exact reasons for the success of AM (and for its eventual failure
>to continue making new discoveries) have not been established. [...]
>
>The problem with all of these explanations is that they have not been
>subjected to rigorous experimental and analytical tests, so at the
>present time, we still (more than ten years after AM) do not
>understand why AM worked!
Some possible contributing reasons for this sort of difficulty in AI:
1) The practitioners of AI routinely lack access at the nuts-and-bolts level
to the products of others' work. (At a talk he gave here three years ago,
Lenat said that he was preparing a distribution version of AM. Has
anyone heard whether it is available? I haven't.) Perhaps widespread
availability and use of Common Lisp will change this. Perhaps not.
2) The supporting institutions (and most practitioners) have little
patience for anything as unexciting and 'unproductive' as slow,
painstaking post-mortems.
3) We still have no fruitful paradigm for intelligence and discovery.
4) We are still, for the most part, too insecure to discuss difficulties
and failures in ways that enable others as well as ourselves to learn
from them. (See an article on the front page of the NYTimes book review
two or three weeks ago for a review of a book claiming that twentieth-
century science writing in general is fundamentally misleading in this
respect.)
David West dwt@zippy.eecs.umich.edu
------------------------------
Date: 26 Oct 87 19:57:47 GMT
From: ritcv!cci632!mdl@cs.rochester.edu (Michael Liss)
Subject: Re: Goal of AI: where are we going? (the right way?)
In article <285@usl> khl@usl.usl.edu.UUCP (Calvin K. H. Leung) writes:
>I agree with the idea that there must be some mechanisms that our
>minds are using. But the different reasoning methods (proba-
>bilistic reasoning, for instance) that we are studying in the
>area of AI are not the way one reasons: we never use the Bayes'
>Theorem in our thinking process. The use of those reasoning
>methods, in my point of view, will never help increase our under-
>standing of human behavior. Because our minds just don't work
>that way.
I read an interesting article recently which had the title:
"If AI = The Human Brain, Cars Should Have Legs"
The author's premise was that most of our other machines that mimic human
abilites do not do so through strict copying of our physical processes.
What we have done, in the case of the automobile, is to make use of wheels and
axles and the internal combustion engine to produce a transportation device
which owes nothing tothe study of human legs.
In the case of AI, he state that artificial intelligence should not be
assumed to be the equivalent of human intelligence and thus, the disection of
the human mind's functionality will not necessarily yield a solution to AI.
He closes with the following:
"And I suspect it [AI] will develop without reference to natural intelligence
and should so develop. And I am sure it will not replace human thinking any
more than the autombile replaces human walking."
"Why am I so soft in the middle when the rest of my life is so hard?" -- P.Simon
Mike Liss {rochester, ritcv}!cci632!mdl (716) 482-5000
------------------------------
Date: 26 Oct 87 17:03:26 GMT
From: net1!todd@sdcsvax.ucsd.edu (Todd Goodman)
Subject: Re: The Success of AI
In article <131@glenlivet.hci.hw.ac.uk> gilbert@hci.hw.ac.uk
(Gilbert Cockton) writes:
>"Better" concepts related to mind than those found in cog. sci.
>already exist. The starting point is the elaboration of the observable human
>phenomena which we are attempting to unify within a study of mind. These
>phenomena have been studied since the dawn of time. There are many
>monumental works of schlarship which unify the phenomena grouped into
>well-defined subfields. The only problem for AI workers surveying all
>these masterpieces is that none of the authors are committed to
>computational models. Indeed, they would no doubt laugh at anyone who
>suggested that their work could be reduced to a Turing Machine compatible
>notation.
Please, please, please give us a bibliography of these works. In fact a
short summary would be great, along with the reasons that you find them to be
better than any current models. Also if you could point out which are at odds
with each and which you feel are "better" than others, then I would be greatly
appreciative.
This isn't a flame about your response to the earlier posting. I just want to
take a look at the monumental works you're talking about.
Todd Goodman
todd@net1.ucsd.edu
...!{ucbvax|ihnp4}!sdcsvax!net1!todd
------------------------------
Date: 26 Oct 87 03:31:00 GMT
From: uxc.cso.uiuc.edu!osiris.cso.uiuc.edu!goldfain@a.cs.uiuc.edu
Subject: Re: The Success of AI
> tsmith@gryphon.CTS.COM writes
> Now here's the interesting point. If you were to come to me and say--
> "Smith, you have a year to develop an automaton that will play some
> kind of major sport at a championship level, competing against humans.
> Money is no object, and you can have access to all the world's
> experts in AI and robotics, but you must design a robot that plays
> championship X in a year's time. What is X?" I would say, without a
> moment's hesistation, "tennis".
>
> Why? Of all the sports, tennis is the most bounded. It is played within
> a very restricted area (unlike golf or even baseball), it is a
> one-against-one sport (unlike football or soccer), the playing surfaces
> (aside from Wimbledon) are the truest of all the major sports, and it
> is indubitably the most boring of all the sports to watch (if not to
> play). A perfect candidate for automation.
> ----------------
Hmmm, by your own criterion, I would prefer table tennis, or to make life
really easy, bowling. I had heard that a table-tennis playing robot has been
developed that is really quite good. Bowling is really way too simple.
(If what I have heard is correct, othello would also be a good choice -
computers have already been claimed by some to outperform humans here, but
it's not a major sport.)
------------------------------
Date: 27 Oct 87 02:06:56 GMT
From: topaz.rutgers.edu!josh@rutgers.edu (J Storrs Hall)
Subject: Re: The Success of AI
> tsmith@gryphon.CTS.COM writes
> Now here's the interesting point. If you were to come to me and say--
> "Smith, you have a year to develop an automaton that will play some
> kind of major sport at a championship level, competing against humans.
> Money is no object, and you can have access to all the world's
> experts in AI and robotics, but you must design a robot that plays
> championship X in a year's time. What is X?" I would say, without a
> moment's hesistation, "tennis".
Goldfain says bowling, which is a very good choice, being in a
completely artificial environment. It might have (with ping-pong)
the problem of not "really being a sport". If we define "major sport"
as something done outside in real time against competition and often
televised on major networks, I would have to go with the 50 yard dash.
If we allow any olympic event, offhand sharpshooting looks promising,
javelin throwing looks easy, shot put looks trivial.
In fact, the more I think about it, tennis is probably one of the
*hardest* sports to implement. I imagine a team of football-playing
robots: they look something like tanks...
The point in all this is obviously that in the history of replacing
human effort with mechanical effort, brute force was the first success
story.
* * * *
"The Yankees pitcher steps to the mound. It is a Cincinnati Milacron
G97A22013 just brought up from the minors. Here's the pitch! Holy
cow! A 957 mph fastball on the inside corner for strike one! ..."
--JoSH
------------------------------
Date: 26 Oct 87 03:38:41 GMT
From: imagen!atari!portal!cup.portal.com!tony_mak_makonnen@ucbvax.Berk
eley.EDU
Subject: Re: The success of AI (misunderstandings)
this is exemplary of what happens when many perspectives enter the
picture and words flow . I submit the following :
It was Von Neuman himself ( I believe) who said that anything
that can be calculated precisely i.e. mathematically can be done
better by a computer . ( I think this should pass even by the
most rabid hater of computers )
I note that man who is getting lambasted used the words computed
and computational. I should think he would agree that if one began
to talk of reflection , intuition and so on , the conversation
would be totally different . Else are we to think that with great enough
and intensive computation the machine will eventually exhibit awareness
of itself as something that is .?!
------------------------------
End of AIList Digest
********************
∂29-Oct-87 0424 LAWS@KL.SRI.Com AIList V5 #252 - Neural Network Review, UK Mail, Seminars
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 29 Oct 87 04:24:25 PST
Date: Thu 29 Oct 1987 01:35-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #252 - Neural Network Review, UK Mail, Seminars
To: AIList@SRI.COM
AIList Digest Thursday, 29 Oct 1987 Volume 5 : Issue 252
Today's Topics:
Journal - Neural Network Review,
Binding - Transatlantic Netmail to UK,
Seminars - Dependency-Directed Prolog (BBN) &
Speech Recognition Using Connectionist Networks (UNISYS),
Conference - Expert Systems in Business and Finance
----------------------------------------------------------------------
Date: Wed, 28 Oct 87 15:30:08 EST
From: csed-1!will@hc.dspo.gov (Craig Will)
Subject: Announcing Neural Network Review
Announcing a new publication
NEURAL NETWORK REVIEW
The critical review journal
for the neural network community
Neural Network Review is intended to provide a forum
for critical analysis and commentary on topics involving
neural network research, applications, and the emerging
industry. A major focus of the Review will be publishing
critical reviews of the neural network literature, including
books, individual papers, and, in New York Review of Books
style, groups of related papers.
The Review will also publish general news about events
in the neural network community, including conferences,
funding trends, and announcements of new books, papers,
courses, and other media, and new hardware and software pro-
ducts.
The charter issue, dated October, 1987, has just been
published, and contains a review and analysis of 11 articles
on neural networks published in the popular press, a report
on the San Diego conference, a report on new funding initia-
tives, and a variety of other information, a total of 24
pages in length. The next issue, due in January, 1988, will
begin detailed reviews of the technical literature. Neural
Network Review is aimed at a national audience, and will be
published quarterly. It is published by the Washington
Neural Network Society, a nonprofit organization based in
the Washington, D.C. area.
Subscriptions to Neural Network Review are $ 10.00 for
4 issues, or $ 2.50 for a single copy. International rates
are slightly higher. Rates for full-time students are $5.00
for 4 issues. (Checks should be payable to the Washington
Neural Network Society). Subscription orders and inquiries
for information should be sent to:
Neural Network Review
P. O. Box 427
Dunn Loring, VA 22027
For more information on Neural Network Review, send your
physical, U. S. Postal mail address in a message to
will@hc.dspo.gov (Craig Will).
------------------------------
Date: 28 Oct 87 16:46 PST
From: hayes.pa@Xerox.COM
Subject: transatlantic netmail to UK
I recently had some correspondence about this with an informed UK
source, and here is his statement about what is going on and why, and
what the future should hold. Looks good.
Pat Hayes
----------
The costs of transatlantic traffic, in both directions, through the UCL
Arpanet gateway are borne by a UK funding agency, the Alvey
Directorate/SERC . Darpa does not pay for messages originating in the
USA and sent to the UK gateway, and UCL ( University College, part of
London University ) has no way of charging individual American
originators of messages.
Some time ago, UCL needed to get more accurate statistics about UK usage
to strengthen its case for more money to run the transatlantic link. To
show that the gateway was a vital facility, UCL instigated the policy of
requiring UK users to be properly authorised, ie officially registered
as users.
The cost of this bi-directional transatlantic traffic now exceeds the
budget granted by Alvey/SERC to UCL. Appeals by UCL to SERC brought
to light that much net traffic originating in the UK was being
channelled through the very few `official' accounts. Moreover, UCL
had no data on the number of US customers it serves.
More recently, the increased cost of running the link has meant that UCL
now wishes to track traffic originating in the USA, to help show the
importance of the link. As USA to UK messages are not funded by any USA
agency, then either the SERC pays for it all, via the UCL budget, or
some form of charge-back to UK recipients must be instigated. This is
the origin of the recent change in operating policy requiring USA users
to be registered as collaborating with some specific UK group ie
charging centre. Such a charge would then be allowable against
individual SERC grants, rather than UCL picking up the total cost.
There is no suggestion that any USA user will be refused authorisation.
It is clear to all parties that this is not a satisfactory mechanism,
either now or for the future. I am pleased to tell you that negotiations
are now well advanced for a more permanent and sensible solution.
The proposal is that the UK's SERC and the USA's NSF (more natural
counterparts than Darpa) will instigate a new USA-UK link, properly
jointly organised and funded for the benefit of academics. This link
will, on the USA side, gateway the UK's Janet (the official name of the
UK academic net) into most of the USA nets (arpa, NSF's own, Usenet
etc. ) The present Arpanet-Janet link will continue until this improved
NSF-Janet comes into service. There is no firm date for this yet, but I
think that if people in the USA cooperate with UCL in the short term,
and have a little patience and sympathy for UCL's predicament, then we
should all be able to keep communicating via UCL until the next
generation gateway comes into service.
------------------------------
Date: Tue 27 Oct 87 10:38:24-EST
From: Marc Vilain <MVILAIN@G.BBN.COM>
Subject: Seminar - Dependency-Directed Prolog (BBN)
BBN Science Development Program
AI Seminar Series Lecture
DEPENDENCY DIRECTED PROLOG
Jeffrey Mark Siskind
MIT Laboratory for Computer Science
(also: summer intern at Xerox PARC)
(Qobi@ZERMATT.LCS.MIT.EDU)
BBN Labs
10 Moulton Street
2nd floor large conference room
10:30 am, Tuesday November 3
In this talk I will describe an implementation of pure Prolog which uses
dependency directed backtracking as a control strategy for pruning the
search space. The implementation uses a strategy whereby the Prolog
program is compiled into a finite set of templates which characterize a
potentially infinite boolean expression which is satisfiable iff there
is a proof of the goal query. These templates are incrementally
unraveled into a sequence of propositional CNF SAT problems and
represented in a TMS which is used to find solutions using dependency
directed backtracking. The technique can be extended to use ATMS-like
strategies for searching for multiple solutions simultaneously.
Two different strategies have been implemented for dealing with
unification. The first compiles the unification constraints into SAT
clauses and integrates them in the TMS along with the and/or goal tree
produced by unraveling the templates. The second uses a separate module
for doing unification at run time. This unifier is novel in that it
records dependencies and allows nonchronological retraction. The
interface protocol between the TMS and the unifier module has been
generalized to allow integration of other "domains" of predicates, such
as linear arithmetic and simple linear inequalities, to be built into
the system while still preserving the soundness and completeness of the
pure logical interpretation of Prolog.
In the talk, time permitting, I will discuss the search prunning
advantages of this approach and its relation to previous approaches, the
implementation mechanism, and some recent work indicating the potential
applicability of this approach to parsing with disjunctive feature
structures, such as done with the LFG and related grammar formalisms.
------------------------------
Date: Tue, 27 Oct 87 15:35:57 EST
From: finin@bigburd.PRC.Unisys.COM (Tim Finin)
Subject: Seminar - Speech Recognition Using Connectionist Networks
(UNISYS)
AI Seminar
UNISYS Knowledge Systems
Paoli Research Center
Paoli PA
SPEECH RECOGNITION USING CONNECTIONIST NETWORKS
Raymond Watrous
Siemens Corporate Research
and
University of Pennsylvania
The thesis of this research is that connectionist networks are
adequate models for the problem of acoustic phonetic speech
recognition by computer. Adequacy is defined as suitably high
recognition performance on a representative set of speech recognition
problems. Six acoustic phonetic problems are selected and discussed
in relation to a physiological theory of phonetics. It is argued that
the selected tasks are sufficiently representative and difficult to
constitute a reasonable test of adequacy.
A connectionist network is a fine-grained parallel distributed
processing configuration, in which simple processing elements are
interconnected by simple links. A connectionist network model for
speech recognition has been defined called the TEMPORAL FLOW MODEL.
The model incorporates link propagation delay and internal feedback to
express temporal relationships.
It has been shown that temporal flow models can be 'trained' to
perform successfully some speech recognition tasks. A method of
'learning' using techniques of numerical nonlinear optimization has
been demonstrated for the minimal pair "no/go", and voiced stop
consonant discrimination in the context of various vowels. Methods for
extending these results to new problems are discussed.
10:00am Wednesday, November 4, 1987
Cafeteria Conference Room
Unisys Paloi Research Center
Route 252 and Central Ave.
Paoli PA 19311
-- non-UNISYS visitors who are interested in attending should --
-- send email to finin@prc.unisys.com or call 215-648-7446 --
------------------------------
Date: Thu 29 Oct 87 01:08:12-PST
From: Ken Laws <Laws@KL.SRI.Com>
Reply-to: AIList-Request@SRI.COM
Subject: Conference - Expert Systems in Business and Finance
John Feinstein [(703) 934-3280] asked me to send out a notice
about the first annual conference on expert systems in business
and finance -- but I see that John Akbari submitted a description
in AIList V5 N246, Oct. 25. I'll just repeat that it's at the
Penta Hotel in New York City, November 10-12, 1987, $525. Call
(609) 654-6266.
------------------------------
End of AIList Digest
********************
∂30-Oct-87 0100 LAWS@KL.SRI.Com AIList V5 #253 - LISP, NIL, Msc.
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 Oct 87 00:59:59 PST
Date: Thu 29 Oct 1987 21:41-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #253 - LISP, NIL, Msc.
To: AIList@SRI.COM
AIList Digest Friday, 30 Oct 1987 Volume 5 : Issue 253
Today's Topics:
Queries - Symbolic and Algebraic Computation Text &
Prediction-Producing Algorithms & Mental Models,
Bibliographies - Literature Classification,
AI Tools - LISP on the AMIGA & NIL (the LISP) & Character Recognition,
Correction - Spang Robinson Report on Supercomputing, V1 N2
----------------------------------------------------------------------
Date: 26 Oct 1987 13:54:48 EST
From: Walter.Daugherity@LSR
Subject: Symbolic and Algebraic Computation Text
There are a number of interesting AI people and projects here at
Texas A & M and we are expanding. [... looking for a CS department head.]
Also, I will be teaching a graduate course in Symbolic and Algebraic
Computation and am looking for useful textbooks, proceedings, citations,
etc., if you know of any.
Thanks,
Walter
BITNET: WCD7007@TAMLSR
WCD7007@TAMSIGMA
CSNET: WCD7007%LSR%TAMU@CSNET-RELAY
WCD7007%SIGMA%TAMU@CSNET-RELAY
Paper mail: Dr. Walter C. Daugherity
Texas A & M University
Department of Computer Science
Zachry Engineering Center, Room 238
College Station, Texas 77843-3112
U.S.A.
_________
------------------------------
Date: 29 Oct 87 04:22:27 GMT
From: mind!eliot@princeton.edu (Eliot Handleman)
Subject: Prediction-producing Algorithms
I am looking for any work done on predictive algorithms - by which I
mean something that, given some input, is able to make a reasonable stab
at a plausible continuation. I am decidedly not interested in things which
compute transition probablities. Something which is able to generated
some pattern of inference is more up my alley.
For example, if I fed the pattern a a b a a b a into this thing, I would
expect to get back a b as the most reasonable thing to expect.
Any pointers to articles, dissertations, texts, programs etc would be
extremely helpful. Please ship your replies to me directly, and many
thanks in advance.
------------------------------
Date: 24 Oct 87 08:39:37 GMT
From: cunyvm!byuvax!fordjm%psuvm.bitnet@ucbvax.Berkeley.EDU
Subject: Mental Models
I am getting ready to conduct a literature search to
learn more about mental models from a cognitive
psychology perspective. I am familiar with Gentner &
Stevens' (1983) "Mental Models" and P. Johnson-Laird's
(1983) book by the same name.
Can anyone point me to an existing bibliography or
recent references on this topic since 1983? Also, is
anyone out there currently doing research in this
area? Although I would find general references useful,
I am particularly interested in applications of
mental models theories in instructional/educational
psychology and measurement.
Please send responses to me via e-mail and I will
summarize to the net. Thanks in advance.
John M. Ford fordjm@byuvax.bitnet
------------------------------
Date: 28 Oct 87 15:32:14 GMT
From: sunybcs!rapaport@ames.arpa (William J. Rapaport)
Subject: Re: Literature classification - (nf)
In article <23600004@uklirb.UUCP> noekel@uklirb.UUCP writes:
>
>we're currently building a AI bibliography and are still searching for a
>suitable classification/key word scheme. If there are any schemes that have
>gained wide-spread use in the AI community I would be very interested to
>learn about them.
I don't know of any offhand, but here's an idea for getting one started:
why not use (or suitably modify) the list of entries in the new
Encyclopedia of Artificial Intelligence (ed. S. C. Shapiro; John Wiley
& Sons, 1987)?
William J. Rapaport
Assistant Professor
Dept. of Computer Science, SUNY Buffalo, Buffalo, NY 14260
(716) 636-3193, 3181
uucp: ..!{ames,boulder,decvax,rutgers}!sunybcs!rapaport
internet: rapaport@cs.buffalo.edu
[if that fails, try: rapaport%cs.buffalo.edu@relay.cs.net
or: rapaport@buffalo.csnet ]
bitnet: rapaport@sunybcs.bitnet
------------------------------
Date: 28 Oct 87 19:20:52 GMT
From: super.upenn.edu!eecae!nancy!umix!tardis!ronin!mike@rutgers.edu
(Michael Nowak)
Subject: Re: LISP on the AMIGA.
In article <2561@cbmvax.UUCP> phillip@cbmvax.UUCP (Phillip Lindsay GUEST)
writes:
>I would like to hear from people working on anything related to LISP and/or
>AI on the Amiga. This is important since I am trying to solicit a port of
>a LISP product. Any general interest also welcome. (the more bullets the
better)
I bought the MCC Lisp awhile back to use in my AI class and it was generally
useful for that. What would be really nice is an implementation of Common
Lisp for the Amiga.
Michael Nowak
------------------------------
Date: 28 Oct 87 19:01:45 GMT
From: wagner@rocky.STANFORD.EDU (Juergen Wagner)
Reply-to: gandalf@portia.stanford.edu (Juergen Wagner)
Subject: Re: NIL (the lisp)
>where can i get a copy (of the source code for) NIL (the lisp implementation)?
Contact MIT AI Lab, Glenn Burke. That's where I got a copy of NIL from (about
three years ago). But...
>does anyone out there have a small (minimal) fast lisp in C with
>free or at least royalty-free source code ?
...NIL is neither small, nor minimal. At least the version I worked with used
to eat up a fair amount of CPU time (especially when I compiled LISP code). I
don't know if there is a version of NIL under UNIX, I only know one under VMS.
If you are looking for a CommonLISP system which is reasonably small
(minimal), which provides the standard language capabilities (CLtL) plus some
extensions, which allows for dynamic loading of C modules (and thereby e.g.
interfacing to window systems), and which is royalty-free (non-commercial
use), I suggest Kyoto CommonLISP (KCL). Read comp.lang.lisp for more details
on how to get a copy of KCL (via anonymous FTP, direct order, etc.).
Juergen Wagner, (USENET) gandalf@portia.stanford.edu
Center for the Study of Language and Information (CSLI), Stanford CA
------------------------------
Date: 28 Oct 87 15:38:42 GMT
From: ihnp4!alberta!auvax!kevinc@ucbvax.Berkeley.EDU (Kevin Barry
Crocker)
Subject: Re: Character recognition
In article <2984@phri.UUCP>, roy@phri.UUCP (Roy Smith) writes:
> In article <641@zen.UUCP> vic@zen.UUCP (Victor Gavin) writes:
> > I have been asked to write some software which can (given an image
> > produced by the scanner) reproduce the original text of the paper in a
> > machine readable form.
>
> I don't know much about it, but a company called DEST markets a
> 300-dpi scanner for the Macintosh (and, I think, IBM-PC) for about $2k,
This may not be relevant to all, but a recent issue of PC Magazine does
a review of both Desktop Publishing and Scanners for the PC Market.
The issue is Volume 6 Number 17 October 13, 1987. Now, I realize that
for Mac users this may not be totally relevant but some of these
companies may make suitable software to make thier product usable on
the Mac - especially those that link to PageMaker. In fact I seem to
remember some vendors products being touted as both market products.
ihnp4!alberta!auvax!kevinc (Kevin Crocker Athabasca University)
Do our employers have opinions or is that what we get paid for!
------------------------------
Date: 29 Oct 87 15:27:04 GMT
From: steve@hubcap.clemson.edu ("Steve" Stevenson)
Subject: Correction to Review - Spang Robinson Report on
Supercomputing, V1 N2
in article <8710280643.AA22004@ucbvax.Berkeley.EDU>, E1AR0002@SMUVM1.BITNET
(Leff, Southern Methodist University) says:
>
> Summary of Spang Robinson Report on Supercomputing and Parallel Processing
> Volume 1 , No. 2
>
> Floating Point Systems reports 1.2 GigaFlps on their T200 system.
> .... One is installed at Clemson University where they are installing]
> SPICE.
Actually, we are writing a special FORTRAN and C for Hypercubes which
is also being used for IMPLEMENTING SPICE. A new sparse solver is
being developed by Dan Warner in MathSci. Roy Pargas and Keith
Allen are also involved in mapping algorithms. I'm heading the
language work.
--
Steve (really "D. E.") Stevenson steve@hubcap.clemson.edu
Department of Computer Science, (803)656-5880.mabell
Clemson University, Clemson, SC 29634-1906
------------------------------
End of AIList Digest
********************
∂30-Oct-87 0359 LAWS@KL.SRI.Com AIList V5 #254 - AI Methodology
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 30 Oct 87 03:58:55 PST
Date: Thu 29 Oct 1987 21:51-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #254 - AI Methodology
To: AIList@SRI.COM
AIList Digest Friday, 30 Oct 1987 Volume 5 : Issue 254
Today's Topics:
Comments - Methodology & The Success of AI
----------------------------------------------------------------------
Date: 26 Oct 87 19:26:01 GMT
From: rosevax!rose3!starfire!merlyn@uunet.uu.net (Brian Westley)
Subject: Re: The Success of AI
In one article...
> But AI research could at least be disciplined to study the existing work
> on the phenomena they seek to study. Exploratory, anarchic,
> uninformed, self-indulgent research at public expense could be stopped.
and, in another article...
>..Thus, I am not avoiding hard work; I am avoiding
>*fruitless* work...
> --
> Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
Tell me, how do you know WHICH AI methods WILL BE fruitless? You certainly
must know, for you to call it anarchic, uninformed, and self-indulgent (but why
'exploratory' is used as a put-down, I'll never know - I guess Gilbert already
knows how to build thinking machines, and just won't tell us).
Research is like advertising - most of the money spent is fruitless, but
you won't KNOW that until after you've TRIED it. (Of course it isn't
entirely wasted; you now know what doesn't work).
Fortunately, you have not convince me nor many other people that your
view is to be held paramount, and all other avenues of work are doomed
to failure.
By the way, I am not interested in duplicating or otherwise developing
models of how humans think; I am interested in building machines that
think. You may as well tell a submarine designer how difficult it is
to build artificial gills - it's irrelevant.
---
Merlyn LeRoy
"Anything a computer can do is immediately removed from those activities
that require thinking, such as calculations, chess, and medical diagnoses."
------------------------------
Date: 28 Oct 87 15:06:21 GMT
From: ig!uwmcsd1!uwm-cs!litow@jade.Berkeley.EDU (Dr. B. Litow)
Subject: AI
Recently postings have focused on the topic: 'AI - success or failure'. Some
postings have been concerned with epistemological or metaphysical matters.
Other postings have taken the view that AI is a vast collection of design
problems for which much of the metaphysical worry is irrelevant. Based
upon its history and current state it seems to me that AI is an area of
applied computer science largely aimed at design problems. I think that
AI is an unfortunate moniker because AI work is basically fuzzy programming
(more accurately the design of systems supporting fuzzier and fuzzier
programming) where the term 'fuzzy' is not being used in a pejorative sense.
All of the automation issues in AI work are support issues for really fuzzy
programming i.e. where humans can extend the interface with automata so
that human/automata interaction becomes increasingly complex and
'undisciplined'. Thus in a large sense AI is the frontier part of software
science. It could be claimed that at some stage of extension the interface
becomes so complex (by human standards at the time) that cognition can be
ascribed to the systems. Personally I doubt this will happen. On the other
hand the free use of play-like interfaces must have unforeseeable and
gigantic consequences for humans. This is where I see the importance of AI.
I distinguish between cognitive studies and AI. The metaphysics belongs to
the former,not the latter.
------------------------------
Date: 28 Oct 87 18:04:45 GMT
From: tgd@orstcs.cs.orst.edu (Tom Dietterich)
Subject: Re: Lenat's AM program
David West (dwt@zippy.eecs.umich.edu) writes:
Some possible contributing reasons for this sort of difficulty in AI:
1) The practitioners of AI routinely lack access at the nuts-and-bolts level
to the products of others' work. (At a talk he gave here three years ago,
Lenat said that he was preparing a distribution version of AM. Has
anyone heard whether it is available? I haven't.) Perhaps widespread
availability and use of Common Lisp will change this. Perhaps not.
In the biological sciences, publication of an article reporting a new
clone obligates the author to provide that clone to other researchers
for non-commercial purposes. I think we need a similar policy in
computer science. Publication of a description of a system should
obligate the author to provide listings of the system (a running
system is probably too much to ask for) to other researchers on a
non-disclosure basis.
2) The supporting institutions (and most practitioners) have little
patience for anything as unexciting and 'unproductive' as slow,
painstaking post-mortems.
3) We still have no fruitful paradigm for intelligence and discovery.
4) We are still, for the most part, too insecure to discuss difficulties
and failures in ways that enable others as well as ourselves to learn
from them. (See an article on the front page of the NYTimes book review
two or three weeks ago for a review of a book claiming that twentieth-
century science writing in general is fundamentally misleading in this
respect.)
I disagree with these other points. I think the cause of the problem
is lack of methodological training for AI and CS researchers. Anyone
could have reimplemented an approximation of AM based on the published
papers anytime in the past decade. I think the fact that people are
now beginning to do this is a sign that AI is becoming
methodologically healthier. A good example is the paper Planning for
Conjunctive Goals by D. Chapman in Artificial Intelligence, Vol 32,
No. 3, which provides a critical review and rational reconstruction of
the NOAH planning system. I encourage all students who are looking
for dissertation projects to consider doing work of this kind.
--Tom
------------------------------
Date: Thu 29 Oct 87 00:25:55-PST
From: Ken Laws <Laws@KL.SRI.Com>
Subject: Gilding the Lemon
Tom Dietterich suggests that AI students should consider doing
critical reviews and rational reconstructions of previous AI
systems. [There, isn't a paraphrase better than a lengthy
quotation?] I wouldn't discourage such activities for those
who relish them, but I disagree that this is the best way for
AI to proceed AT THE PRESENT TIME.
Rigorous critical analysis is necessary in a mature field where
deep understanding is needed to avoid the false paths explored
by previous researchers. I don't claim that shallow understanding
is preferable in AI, but I do claim that it is adequate.
AI should not be compared to current Biology or Psychology, but
to the heyday of mechanical invention epitomized by Edison. We
do need the cognitive scientists and logicians, but progress in
AI is driven by the hackers and the graduate students who "don't
know any better" than to attempt the unreasonable.
Progress also comes from applications -- very seldom from theory.
The "neats" have been worrying for years (centuries?) about temporal
logics, but there has been more payoff from GPSS and SIMSCRIPT (and
SPICE and other simulation systems) than from all the debates over
consistent point and interval representations. The applied systems
are ultimately limited by their ontologies, but they are useful up to
a point. A distant point.
Most Ph.D. projects have the same flavor. A student studies the
latest AI proceedings to get a nifty idea, tries to solve all the
world's problems from his new viewpoint, and ultimately runs into
limitations. He publishes the interesting behaviors he was able
to generate and then goes on the lecture circuit looking for his
next employment. The published thesis illuminates a new corner of
mankind's search space, provided that the thesis advisor properly
steered the student away from previously explored territory.
An advisor who advocates duplicating prior work is cutting his
students' chances of fame and fortune from the discovery of the
one true path. It is always true that the published works can
be improved upon, but the original developer has already gotten
80% of the benefit with 20% of the work. Why should the student
butt his head against the same problems that stopped the original
work (be they theoretical or practical problems) when he could
attach his name to an entirely new approach?
I am not suggesting that "artificial intelligence" will ever be
achieved through one graduate student project or by any amount
of hacking. We do need scientific rigor. I am suggesting that we
must build hand-crank phonographs before inventing information
theory and we must study the properties of atoms before debating
quarks and strings. Only when we have exploited or reached impass
on all of the promising approaches will there be a high probability
that critical review of already explored research will advance the
field faster than will trying something new.
[Disclaimer: The views expressed herein do not apply to my own
field of computer vision, where I'm highly suspicious of any youngster
trying to solve all our problems by ignoring the accumulated knowledge
of the last twenty years. My own tendency is toward critical review
and selective integration of existing techniques. But then, I'm not
looking for a hot new Ph.D. topic.]
-- Ken Laws
------------------------------
Date: Wed, 28 Oct 87 08:36:34 -0200
From: Eitan Shterenbaum <eitan%wisdom.bitnet@jade.berkeley.edu>
Subject: Success of AI
Had it ever come into you mind that simulating/emulating the human brain is
NP problem ? ( Why ? Think !!! ). Unless some smartass comes out with a proof
for NP=P yar can forget de whole damn thing ...
Eitan Shterenbaum
(*
As far as I know one can't solve NP problems even with a super-duper
hardware, so building such machine is pointless (Unless we are living on
such machine ...) !
*)
Eitan
------------------------------
Date: 29 Oct 87 13:15:51 GMT
From: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@uunet.uu.net>
Reply-to: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@uunet.uu.net>
Subject: Re: THE MIND
In article <8710120559.AA17517@ucbvax.Berkeley.EDU>
UUCJEFF@ECNCDC.BITNET writes:
>I read some of the MIND theories espoused in the Oct 2 list, and am
>frankly disappointed. All those debates are based on the Science vs
>Mysticism debates that were going on 10 years ago when I was an undergrad.
Isn't it a shame that so many people in AI are so ignorant of the
substance of these debates?
>5) AI should concern itself with solving problems, discovering new ways to
>solve and conceptialize problems. It is not as glamorous as making
>artificial souls, but more practical and fruitful.
Fortunately, this highly sensible view is attracting more support, and,
with luck, it should establish itself as the raison d'etre of AI
research. A change of name would help (viz demise of cyberbetics),
despite the view of many old hands (e.g. Simon), that they wouldn't
have chosen the name, but we are stuck with it now. I can't see how any
sensible person would want to stick with a term with such distasteful
connotations.
However, this orientation for post-AI advanced computer applications
research needs extension. It is not enough to develop new computerised
support for new problem solving techniques. Research is also needed
into the comprehensibility, ease of learning and validity of these
techniques. Determinants of their acceptability in real organisational
settings are also a vital research topic. Is research in medical expert
systems, for example, worth public funding when it seems that NO
medical expert system is being used in a real clinical setting? What
sorts of systems would be acceptable? Similarly, the theorem prover
based proof editors under development for software engineering seem to
require knowledge and skills which few practising software
professionals will have time to develop, so one can't really see proof
editors developing into real work tools until a major shift in their
underlying models occur.
Such a user-oriented change of direction is a major problem for AI
researchers, as few of them seem to have any real experience of
succesfully implementing a working system and installing it in a real
organisational setting, and then maintaining it. DEC's XCON is one of
the few examples. How much is PROSPECTOR used these days?
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
Date: 29 Oct 87 00:23:00 GMT
From: uxc.cso.uiuc.edu!osiris.cso.uiuc.edu!goldfain@a.cs.uiuc.edu
Subject: Re: The Success of AI (continued, a
Who says that ping-pong, or table tennis isn't a sport? Ever been to China?
------------------------------
End of AIList Digest
********************
∂03-Nov-87 0151 LAWS@KL.SRI.Com AIList V5 #255 - Future of AI & Speech & PDP Book & AI Categories
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 Nov 87 01:51:28 PST
Date: Mon 2 Nov 1987 22:08-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #255 - Future of AI & Speech & PDP Book & AI Categories
To: AIList@SRI.COM
AIList Digest Tuesday, 3 Nov 1987 Volume 5 : Issue 255
Today's Topics:
Queries - OPS5 Programs & Future of AI,
Comments - Future of AI & Speech Understanding,
References - PDP & AI Categories,
Comments - Success of AI
----------------------------------------------------------------------
Date: 30 Oct 87 18:11:41 GMT
From: ihnp4!alberta!ajit@ucbvax.Berkeley.EDU (Ajit Singh)
Subject: Need OPS5 Programs
I am currently working on analyzing static characteristics
as well as run-time behavior of large production system
programs for the purposes of rule-clustering and distributed
processing. I am using OPS5 as my production system model. I
need lots of large and small OPS5 programs. Does anybody know
of any publically accessible library of such programs? Any
help in this direction will be greatly appreciated.
If you have some OPS5 programs (plus data if necessary) that
you would like to send to me then you may send them directly
via e-mail at the following address:
{ubc-vision, ihnp4, mnetor}!alberta!ajit
Thanks in advance,
Ajit Singh
Department of Computing Science
University of Alberta
Edmonton, Alberta
Canada
------------------------------
Date: 30 Oct 87 20:30:06 GMT
From: kirby@ngp.utexas.edu (Bruce Kirby)
Subject: The future of AI.... (nothing about flawed minds)
I have a question for people:
What practical effects do you think AI will have in the next ten
years?
What I am interested in is discovering what people expect to actually
come out of AI research in the near future, and how that will affect
society, business and government. I am not interested in the
long-term questions of what AI will eventually accomplish.
Some supplementary questions:
- What field of AI will produce practical applications?
- What will be the effect of a new application? (e.g. how would an
effective translation mechanism affect the way people function?)
- Who is likely to produce these useful applications? How are they
to be introduced?
Any comments/responses are welcome. I am just trying to get a feel
for what other people see as the near-term effects of AI research.
Bruce Kirby
kirby@ngp.utexas.edu
...!ut-sally!ut-ngp!kirby
------------------------------
Date: 1 Nov 87 04:15:00 GMT
From: uxc.cso.uiuc.edu!osiris.cso.uiuc.edu!goldfain@a.cs.uiuc.edu
Subject: Re: The future of AI.... (nothing about
Re: Products in the next 10 years coming from AI.
One thing that is currently out there, is a growing body of expert systems.
Many new ones are being churned out as we speak, and I think they will
continue to be produced at a gently accelerating rate over the next decade.
But many expert systems are frightfully narrow. They tend to be simplistic
and only apply when problems are just right. So look for additional layers,
which begin to show some real sophistication. I expect
"multi-expert-system-management-systems" to appear and to exhibit qualities
that will begin to look like the human traits of "judgement" and "learning by
analogy", and systems that will improve with time (autonomously).
------------------------------
Date: 31 Oct 87 13:52:15 GMT
From: gatech!hubcap!ncrcae!gollum!rolandi@rutgers.edu (rolandi)
Subject: Practical effects of AI
In article <6667@ut-ngp.UUCP> you write:
>I have a question for people:
> What practical effects do you think AI will have in the next ten
>years?
>........[etc...]
I 'd say that AI will have at least two real and immediate effects.
1) given AI programming tools and techniques, many processes
previously assumed to be too complicated for automation
will be automated. the automation of these tasks will
take less time given the productivity gains that AI tools
can provide. expert systems will be common place within
the DP/MIS world.
2) AI will make computers easier to use and therefore extend
their usefulness to non-computer people.
Regarding #2 above...
It would seem to me that the single greatest practical advancement for
AI will be in speaker independent, continuous speech recognition. This
is NOT to imply total computer "comprehension" in the sense of being
able to carry on an unrestricted conversation. I am NOT referring to
abilities to process natural language. That, is a long way off, and
will most likely come about as a function of a redefinition of the NLP
problem in terms of a machine learning issue. What "simple" speaker
independent, continuous speech recognition will provide is the ultimate
alternative to keyboard entry. This would thereby provide all of
the functionality of current technology to anyone who could pronounce
the commands. This issue will have a major impact on the industry and
on society. By making "every body" a user, more machines will be sold,
and because "every body" will have different needs, tha range of
automation will be widely extended.
-w.rolandi
ncrcae!gollum!rolandi
disclaimer: i speak for no one but myself and usually no one else is
listening.
------------------------------
Date: 31 Oct 87 22:06:02 GMT
From: PT.CS.CMU.EDU!SPEECH2.CS.CMU.EDU!kfl@cs.rochester.edu (Kai-Fu
Lee)
Subject: Re: Practical effects of AI (speech)
In article <12@gollum.Columbia.NCR.COM>, rolandi@gollum.Columbia.NCR.COM
(rolandi) writes:
>
> In article <6667@ut-ngp.UUCP> you write:
> >I have a question for people:
> > What practical effects do you think AI will have in the next ten
> >years?
> >........[etc...]
> It would seem to me that the single greatest practical advancement for
> AI will be in speaker independent, continuous speech recognition. This
> is NOT to imply total computer "comprehension" in the sense of being
> able to carry on an unrestricted conversation. I am NOT referring to
> abilities to process natural language. That, is a long way off, and
> will most likely come about as a function of a redefinition of the NLP
> problem in terms of a machine learning issue. What "simple" speaker
> independent, continuous speech recognition will provide is the ultimate
> alternative to keyboard entry. This would thereby provide all of
> the functionality of current technology to anyone who could pronounce
> the commands. This issue will have a major impact on the industry and
> on society. By making "every body" a user, more machines will be sold,
> and because "every body" will have different needs, tha range of
> automation will be widely extended.
>
Those of us who work on speech will be very encourage by this enthusiasm.
However,
(1) Speaker-independent continuous speech is much farther from reality
than some companies would have you think. Currently, the best
speech recognizer is IBM's Tangora, which makes about 6% errors
on a 20,000 word vocabulary. But the Tangora is for speaker-
dependent, isolate-words, grammar-guided recognition in a benign
environment. Each of these four constraints cuts the error rate
by 3 or more times if used independently. I don't know how well
they will do if you remove all four constraints, but I would guess
about 70% error rate. So while speech recognition has made a lot
of advancements, it is still far from usable in the application you
mentioned.
(2) Spoken English is a harder problem than NLP of written English.
If you make the recognizer too constrained (small vocabulary, fixed
syntax, etc.), it will be harder to use than a keyboard. If you don't,
you have to understand spoken English, which is really hard.
(3) If this product were to materialize, it is far from clear that it
would be an advancement for AI. At present, the most promising
techniques are based on stochastic modeling, pattern recognition,
information theory, signal processing, auditory modeling, etc..
So far, very few traditional AI techniques are used in, or work well
for speech recognition.
>
> -w.rolandi
> ncrcae!gollum!rolandi
Kai-Fu Lee
Computer Science Department
Carnegie-Mellon University
------------------------------
Date: 30 Oct 87 03:16:05 GMT
From: ihnp4!homxb!homxc!del@ucbvax.Berkeley.EDU (D.LEASURE)
Subject: PDP by Rummelhart and McClelland
After posting about a good text on parallel distributed processing aka
neural nets, I've had several requests for a full reference from
people I can't reach on the net directly.
The books are:
Parallel Distributed Processing: Explorations in the Microstructure
of Cognition, Vols. 1 and 2, by David E. Rumelhart and James L.
McClelland, Bradford Books, The MIT Press, 0-262-63110-5
The two volumes in paper are about $25 together. A third volume
with software for the PC (IBM), is also out this month.
I still recommend them.
--
David E. Leasure - AT&T Bell Laboratories - (201) 615-5307
------------------------------
Date: Fri, 30 Oct 1987 17:20 EST
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList V5 #253 - LISP, NIL, Msc.
In reply to noekel@uklirb.UUCP who is
>
>currently building a AI bibliography and still searching for a
>suitable classification/key word scheme.
In the IRE Transactions on Human Factors in Electronics, March 1961, I
published a big (600 item) bibliography on AI. It may have been the
first published descriptor-index bibliography or, perhaps, the first
to use the term "descriptor", which I got from Calvin Mooers. Now
NOEKE wants one that has "gained wide-spread use in the AI community"
and my 1961 set of terms must be rather dated and does not reflect
many newer ideas. However, much of it may still be useful. And I
would be curious about how useful it might remain after all those
years.
The bibliography was a by-product of work on my other 1961 article,
"steps toward artificial intelligence" which appeared in the
Proceedings of the IRE (whose name later changed to Proc. IEEE.) The
reason the bibliographic appeared in the more obscure Human Factors
journal was that "Steps" was already too long and there was no more
room. Tom Marill was editing a special issue of the HF transactions
and offered to place it there because that issue contained other
AI-related topics.
------------------------------
Date: 31 Oct 87 03:44:44 GMT
From: honavar@speedy.wisc.edu (A Buggy AI Program)
Reply-to: honavar@speedy.wisc.edu (A Buggy AI Program)
Subject: Re: Success of AI
In article <8710280748.AA21340@jade.berkeley.edu> eitan@wisdom.BITNET
(Eitan Shterenbaum) writes:
>
>Had it ever come into you mind that simulating/emulating the human brain is
>NP problem ? ( Why ? Think !!! ). Unless some smartass comes out with a proof
>for NP=P yar can forget de whole damn thing ...
>
> Eitan Shterenbaum
>(*
> As far as I know one can't solve NP problems even with a super-duper
> hardware, so building such machine is pointless (Unless we are living on
> such machine ...) !
>*)
Discovering that a problem is NP-complete is usually just the
beginning of the work on the problem. The knowledge that a problem is
NP-complete provides valuable information on the lines of attack that
have the greatest potential for success. We can concentrate on algorithms
that are not guaranteed to run in polynomial time but do so most
of the time or those that give approximate solutions in polynomial time.
After all, the human brain does come up with approximate (reasonably good)
solutions to a lot of the perceptual tasks although the solution may not
always be the best possible. Knowing that a problem is NP-complete only
tells us that the chances of finding a polynomial time solution are minimal
(unless P=NP).
-- VGH
------------------------------
Date: 30 Oct 87 18:00:42 GMT
From: mcvax!ukc!its63b!hwcs!hci!gilbert@uunet.uu.net (Gilbert
Cockton)
Subject: Re: The Success of AI
In article <4171@sdcsvax.UCSD.EDU> todd@net1.UUCP (Todd Goodman) writes:
>>"Better" concepts related to mind than those found in cog. sci.
>>already exist. There are many monumental works of scholarship which unify
>> the phenomena grouped into well-defined subfields.
>
>Please, please, please give us a bibliography of these works.
Impossible at short notice. Obvious examples are Lyons' work on
semantics (1977?, 2 vols, Cambridge University Press). My answer to
anyone in AI about relevant scholarship is go and see your local
experts for a reading list and an orientation.
By "concepts related to mind", I intend all work concerned with
language, thought and action. That is, I mean an awful lot of work. My
first degree is in Education, which coupled with my earlier work in
History (especially social and intellectual history), brought me into
contact with a wide range of disciplines, and forced me to use each to
the satisfaction of those supervising me. However, I am now probably
out of date, as I've spent the last four years working in
Human-Computer Interaction.
Any work in linguistics under the heading of 'Semantics' should be of
great interest to people working in Knowledge Representation. There is
a substantial body of philosophical work under the heading of
"Philosophy of Mind". Unlike Cognitive Psychology (especially memory
and problem solving), this work has not become fixated on information
processing models. Anthropolgists are doing very interesting work on
category systems; the work of the "New" or "Cognitive" archaeologists
at Cambridge University (nearly all published by Cambridge University
Press) is drawing on much recent continental work on social action.
Any anthropologist should be able to direct you to the older work on
such cultures as the Subanum and the Trobriand Islanders - most of this
work was done by Americans and is more accessible, as it does not
require acquaintance with recent Structuralist and post-Structuralist
concepts, which can be very dense and esoteric.
>the reasons that you find them to be better than any current models.
This work is inherently superior to most work in AI because non of the
writers are encumbered by the need to produce computational models.
They are thus free to draw on richer theoretical orientations which
draw on concepts which are clearly motivated by everyday observations
of human activity. The work therefore results in images of man which
are far more humanist than mechanical computational models. Workers in
AI may be scornful of such values, but in reality they should realise
that adherents to a mechanistic view of human behaviour are very
isolated and in the minority, both now and throughout history. The
persistence of humanism as the dominant approach to the wider studies
of man, even after years of zealous attack from self-proclaimed
'Scientists', should be taken as a warning against the acceptability of
crude models of human behaviour. Furthermore, the common test of any
concept of mind is "can you really imagine your mind working this way?"
Many of the pillars of human societies, like the freedom and dignity of
democracy and moral values, are at odds with the so called 'Scientific'
models of human behaviour; indeed the work of misanthropes like Skinner
actively promote the connection between impoversihed models of man and
immoral totalitarian socities (B.F. Skinner, Beyond Freedom and Dignity).
In short, mechanical concepts of mind and the values of a civilised
society are at odds with each other. It is for this reason that modes
of representation such as the novel, poetry, sculpture and fine art
will continue to dominate the most comprehensive accounts of the human
condition.
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
End of AIList Digest
********************
∂03-Nov-87 0505 LAWS@KL.SRI.Com AIList V5 #256 - Analogy, Inference
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 Nov 87 05:04:58 PST
Date: Mon 2 Nov 1987 22:27-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #256 - Analogy, Inference
To: AIList@SRI.COM
AIList Digest Tuesday, 3 Nov 1987 Volume 5 : Issue 256
Today's Topics:
Reference - Chaos Theory,
Bindings - Langendoen and Postal & Netmail to UK,
Analogy - Knowledge Soup & Robert Frost,
Inference - Prediction-Producing Algorithms
----------------------------------------------------------------------
Date: Mon, 2 Nov 87 16:04 N
From: MFMISTAL%HMARL5.BITNET@wiscvm.wisc.edu
Subject: re: The success of AI (misunderstandings) - CHAOS theory
The august 1987 issue of the proceedings of the IEEE contains 9 papers
on chaotic systems It has a tutorial for engineers, 3 papers with
examples in electronic circuits, 2 papers on analytical tools and
3 papers on software and hardware tools.
Jan L. Talmon
University of Limburg, Dept. of Medical Informatics and Statistics.
Maastricht, the Netherlands
MFMISTAL@HMARL5.bitnet
------------------------------
Date: 2 Nov 87 17:00:55 GMT
From: sunybcs!rapaport@ames.arpa (William J. Rapaport)
Subject: Re: Langendoen and Postal (posted by: Berke)
In article <8941@shemp.UCLA.EDU> berke@CS.UCLA.EDU (Peter Berke) writes:
>I just read this fabulous book over the weekend, called "The Vastness
>of Natural Languages," by D. Terence Langendoen and Paul M. Postal.
>
>Are Langendoen or Postal on the net somewhere?
Langendoen used to be on the net as: tergc%cunyvm@wiscvm.wisc.edu
but he's moved to, I think, U of Arizona. Postal, I think, used to be
at IBM Watson.
------------------------------
Date: Thu, 29 Oct 87 16:13:01 GMT
From: "G. Joly" (Birkbeck) <gjoly@NSS.Cs.Ucl.AC.UK>
Subject: Re: transatlantic netmail mail to UK.
Pat Hayes has given us some propaganda. Yorick Wilkes informed us that
he cannot send mail, although he used to be able to do so.
If I can add may 1.34564 cents worth, the real issue is that the
ARPA tables (from SRI-NIC) do not allow a path to UCL-CS.ARPA and
beyond. This gateway is now known as nss.cs.ucl.ac.uk and nothing
else will work.
I am not a network person at UCL; they inform me that an official
response will be prepared (I am fairly sure that the unsigned note
to Pat was not it). The change away from UCL-CS.ARPA was advertised
at least two years ago.
"The plans have been on view at the planning office on ... "
after Douglas Adams.
Gordon Joly,
Computer Science,
Birkbeck College,
Malet Street,
LONDON WC1E 7HX.
+44 1 631 6468
ARPA: gjoly@nss.cs.ucl.ac.uk
BITNET: UBACW59%uk.ac.bbk.cu@AC.UK
UUCP: ...!seismo!mvcax!ukc!bbk-cs!gordon
------------------------------
Date: 28 October 1987, 20:02:20 EST
From: john Sowa <SOWA@ibm.com>
Subject: Knowledge Soup
Since my abstract on "Crystallizing Theories out of Knowledge Soup"
appeared in AIList V5 #241 and my clarification appeared in V5 #247,
I have received a number of requests for the corresponding paper.
I regret to say that the paper is still in the process of getting
itself crystallized. That talk was mostly a survey of current
approaches to the soup together with some suggestions about techniques
that I considered promising. Following is what I discussed:
1. The limits of conceptualization and the use of conceptual analysis
as a nonautomated way of extracting knowledge from the soup. This
material is discussed in my book, Conceptual Structures. See
Section 6.3 for conceptual analysis, and Chapter 7 for a discussion
of the limitations.
2. Dynamic belief revision, developed by Norman Foo and Anand Rao
from Sydney University, currently visiting IBM. This is a kind of
truth maintenance system based on the axioms for belief revision
by the Swedish logician Gardenfors. They have been adding some
interesting features, including levels of epistemic importance
(laws, facts, and defaults) where the revision process tries to
retain the more important propositions at the expense of losing
some of the less important. Their current system uses Prolog
style rules and facts, but they are adapting it to conceptual
graphs as part of CONGRES (their conceptual graph reasoning system).
3. Dynamic type hierarchies, an idea developed by Eileen Way in
her dissertation on metaphor. As in most treatments of metaphor,
Eileen compares matching relationships in the tenor and vehicle
domains. Her innovation is the recognition that the essential
meaning of a metaphor is the introduction of a new node in the
type hierarchy.
Example: "My car is thirsty." The canonical graph for THIRSTY
shows that it must be an attribute of something of type ANIMAL.
Since CAR is not a subtype of ANIMAL, the system finds a minimal
common supertype of CAR and ANIMAL, in this case MOBILE-ENTITY.
It then creates a new node in the type hierarchy above both
CAR and ANIMAL, but below MOBILE-ENTITY. To create a definition
for that type, it checks the properties of ANIMAL with respect to
THIRSTY, and finds a graph saying that THIRSTY is an attribute of
an ANIMAL that is in the sate of needing liquid:
[THIRSTY]<-(ATTR)<-[ANIMAL]->(STAT)->[NEED]->(PTNT)->[LIQUID]
It then generalizes ANIMAL to MOBILE-ENTITY and uses the resulting
graph to define a new type for mobile entities that need liquid.
The system can generalize schemata involving animals and liquid
to the new node, from which they can be inherited by CAR or any
similar subtype. The new node thereby allows schemata for DRINK
or GUZZLE to be inherited as well as schemata for THIRSTY.
4. Theory refinement. This is an approach that I have been discussing
with Foo and Rao as an extension to their belief revision system.
Instead of making revisions by adding and deleting propositions,
as they currently do, the use of conceptual graphs allows individual
propositions or even parts of propositions to be generalized or
specialized by adding and deleting parts or by moving up and down
the type hierarchy. This extension can still be done within the
framework of the Gardenfors axioms. As the topic changes, the
salience of different concepts and patterns of concepts in the
knowledge soup changes. The most salient ones become candidates
for crystallization out of the soup into the formalized theory.
The knowledge soup thus serves as a resource that the belief
revision process draws upon in constructing the crystallized
theories. Depending on the salience, different theories can be
crystallized from the same soup, each representing a different
point of view. Even though the soup may be inconsistent, each
theory crystallized from it is consistent, but specialized for
a limited domain.
People are capable of precise reasoning, but usually with short chains
of inference. They are also capable of dealing with enormous, but
loosely organized collections of knowledge. Instead of viewing formal
theories and informal associative techniques as competing or conflicting
approaches, I view them as complementary mechanisms that should be made
to cooperate. This talk discussed possible ways of doing that. Although
there is an enormous amount of work that remains to be done, there are
also some promising directions for future research.
References:
Foo, Norman Y., & Anand S. Rao (1987) "Open world and closed world
negations," Report RC 13122, IBM T. J. Watson Research Center.
Foo, Norman Y., & Anand S. Rao (in preparation) "Semantics of
dynamic belief systems."
Foo, Norman Y., & Anand S. Rao (in preparation) "Belief and ontology
revision in a microworld.
Rao, Anand S., & Norman Y. Foo (1987) "Evolving knowledge and logical
omniscience," Report RC 13155, IBM T. J. Watson Research Center.
Rao, Anand S., & Norman Y. Foo (1987) "Evolving knowledge and
autoepistemic reasoning," Report RC 13155, IBM T. J. Watson Research
Center.
Rao, Anand S., & Norman Y. Foo (1986) "Modal horn graph resolution,"
Proceedings of the First Australian AI Congress, Melbourne.
Rao, Anand S., & Norman Y. Foo (1986) "DYNABELS -- A dynamic belief
revision system," Report 301, Basser Dept. of Computer Science,
University of Sydney.
Sowa, John F. (1984) Conceptual Structures: Information Processing in
Mind and Machine, Addison-Wesley, Reading, MA.
Way, Eileen C. (1987) Dynamic Type Hierarchies: An Approach to
Knowledge Representation through Metaphor, PhD dissertation,
Systems Science Dept., SUNY at Binghamton.
For copies of the IBM reports, write to Distribution Services 73-F11;
IBM T. J. Watson Research Center; P.O. Box 218; Yorktown Heights,
NY 10598.
For the report from Sydney, write to Basser Dept. of Computer Science;
University of Sydney; Sydney, NSW 2006; Australia.
For the dissertation by Eileen Way, write to her at the Department
of Philosophy; State University of New York; Binghamton, NY 13901.
------------------------------
Date: 30 Oct 87 11:11:24 EST (Fri)
From: sas@bfly-vax.bbn.com
Subject: Robert Frost
I am forwarding this without permission from the 23 October 1987 issue
of Science:
Robert Frost on Thinking
Readers intrigured by "Causality, structure, and common sense" by M.
Mitchell Waldrop (Research News, 11 Sept., p1297) may be interested in
knowing that the role of analogy in reasoning has been discussed
eloquently by poet Robert Frost in an essay called "Education by
poetry". The following excerpts are among his most relevant comments:
"I have wanted in late years to go further and further in making
metaphor the whole of thinking. I find some one now and then to agree
with me that all thinking, except mathematical thinking, is
metaphorical, or all thinking except scientific thinking. The
mathematical might be difficult for me to bring in, but the scientific
is easy enough...."
"What I am pointing out is that unless you are at home in the
metaphor, unless you have had your proper poetical education in the
metaphor, you are not safe anywhere. Because you are not at ease with
figurative values: you don't know the metaphor in its strength and its
weakness. You don't known how far you may expect to ride it and when
it may break down with you. You are not safe in sciencel; you are not
safe in history...."
"... All metaphor breaks down somewhere. That is the beauty of it.
It is touch and go with the metaphor, and until you have lived with it
long enough you don't know when it is going. You don't know how much
you can get out of it and when it will cease to yield. It is a very
living thing. It is as life itself...."
"We still ask boys in college to think, as in the nineties, but we
seldom tell them what thinking means; we seldom tell them it is just
putting this and that together; it saying one thing in terms of
another. To tell them is to set their feet on the first rung of a
ladder the top of which sticks through the sky."
Perhaps researchers in artificial intelligence who are teaching
computers to reason by analogy should include in their curriculum a
course in poetry. If so, I suggest they start with Frost. His poems
have become an improtant feature of my own ecology courses because
they contain much insight into cause and effect in nature, rather than
mere appearance.
Dan M. Johnson
Dept of Biological Sciences
East Tennessee State University
Johnson City, TN 37614
------------------------------
Date: 30 Oct 87 0950 PST
From: John McCarthy <JMC@SAIL.Stanford.EDU>
Subject: Prediction-producing Algorithms
Eliot Handleman's request for information on prediction has
inspired me to inflict the following considerations on the community.
Roofs and Boxes
Many people have proposed sequence extrapolation as a prototype AI
problem. The idea is that a person's life is a sequence of sensory
stimuli, and that science consists of inventing ways of predicting the
future of this sequence. To this end many sequence extrapolating programs
have been written starting with those that predict sequences of integers
by taking differences and determining the co-efficients of a polynomial.
It has always seemed to me that starting this way distorts the
heuristic character of both common sense and science. Both of them think
about permanent aspects of the world and use the sequence of sense data
only to design and confirm hypotheses about these permanent aspects. The
following sequence problem seems to me to typify the break between
hypotheses about the world and sequence extrapolation.
The ball bouncing in the rectilinear world - roofs and boxes
Suppose there is a rectangular two dimensional room. In this room
are a number of objects having the form of rectangles. A ball moves in
the room with constant velocity but bounces with angle of incidence equal
to angle of reflection whenever it hits a wall or an object. The observer
cannot see the objects or the walls. All he sees is the x-co-ordinate of
the ball at integer times but only when the ball is visible from the front
of the room. This provides him with a sequence of numbers which he can
try to extrapolate. Until the ball bounces off something or goes under
something, linear extrapolation works.
Suppose first that the observer knows that he is dealing with this
kind of ball-in-room problem and only doesn't know the locations of the
objects and the walls. After he has observed the situation for a while he
will have partial information about the objects and their locations. For
example, he may note that he has never been in a certain part of the room
so there may be unknown objects there. Also he may have three sides of a
certain rectangle but may not know the fourth side, because he has never
bounced of that side yet. He may extrapolate that he won't have the
opportunity of bouncing off that side for a long time.
Alternatively we may suppose that the observer doesn't
initially know about balls bouncing off rectangles but only knows
the sequence and must infer this using a general sequence extrapolation
mechanism. Our view is that this observer, whether human or machine,
can make progress only by guessing the underlying model. At first
he may imagine a one dimensional bouncing model, but this will be
refuted the first time the ball doesn't bounce at an x-co-ordinate
where it has previously bounced. Indeed he has to keep open
the possibility that the room is really 3 or more dimensional or that
more general objects than rectangles exist.
We can elaborate the problem by supposing that when the ball
bounces off the front wall, the experimenter can put a paddle at an angle
and determine the angly of bounce so as to cause the ball to enter regions
where more information is wanted.
Assuming the rectangles having edges parallel to the axes makes
the problem easier in an obvious sense but more difficult in the sense
that there is less interaction between the observable x-co-ordinate and
the unobservable y-co-ordinate.
It would be interesting to determine the condition on the x-path
that distinguishes 2-dimensional from 3-dimensional worlds, if there is
one. Unless we assume that the room has some limited size, there need be
no distinction. Thus we must make the never-fully-verified assumption
that some of the repetititions in sequences of bounces are because the
ball hit the front or back wall and bounced again off the same surfaces
rather than similar surfaces further back.
A tougher problem arises when the observer doesn't get the
sequence of x-coordinates but only 1 or 0 according to whether the
ball is visible or invisible.
I am skeptical that an AI program fundamentally based on the idea
of sequence extrapolation is the right idea. Donald Michie suggested
that the "domain experts" for this kind of problem of inferring a
mechanism that produces a sequence are cryptanalysts.
------------------------------
End of AIList Digest
********************
∂03-Nov-87 0844 LAWS@KL.SRI.Com AIList V5 #257 - Methodology
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 Nov 87 08:44:13 PST
Date: Mon 2 Nov 1987 22:41-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #257 - Methodology
To: AIList@SRI.COM
AIList Digest Tuesday, 3 Nov 1987 Volume 5 : Issue 257
Today's Topics:
Methodology - Sharing Code & Critical Analysis and Reconstruction
----------------------------------------------------------------------
Date: 30 Oct 87 14:05:35 GMT
From: bruce@vanhalen.rutgers.edu (Shane Bruce)
Reply-to: bruce@vanhalen.rutgers.edu (Shane Bruce)
Subject: Re: Lenat's AM program
In article <774@orstcs.CS.ORST.EDU> tgd@ORSTCS.CS.ORST.EDU (Tom Dietterich)
writes:
>
>In the biological sciences, publication of an article reporting a new
>clone obligates the author to provide that clone to other researchers
>for non-commercial purposes. I think we need a similar policy in
>computer science. Publication of a description of a system should
>obligate the author to provide listings of the system (a running
>system is probably too much to ask for) to other researchers on a
>non-disclosure basis.
>
The policy which you are advocating, while admirable, is not practical. No
corporation which is involved in state of the art AI research is going to
allow listings of their next product/internal tool to made available to the
general scientific community, even on a non-disclosure basis. Why should
they give away what they intend to sell?
A more practical solution would be for all articles to include a section
on implementation which, while not providing listings, would at least provide
enough information that the project could be duplicated by another competent
researcher in the field.
--
Shane Bruce
HOME: (201) 613-1285 WORK: (201) 932-4714
ARPA: bruce@paul.rutgers.edu
UUCP: {ames, cbosgd, harvard, moss}!rutgers!paul.rutgers.edu!bruce
------------------------------
Date: 30 Oct 87 10:58:40 EST (Fri)
From: sas@bfly-vax.bbn.com
Subject: AIList V5 #254 - Gilding the Lemon
[Authors note: The following message has a bit more vituperation than
I had planned for, however I agree with the basic points.]
While I agree that AI is in a very early stage and it is still
possible to just jump in and get right to the frontier, an incredible
number of people seem to jump in and instead of getting to the
frontier, spend an awful lot of time tromping around the campfire. It
seems like the journals are replete with wheels being reinvented -
it's as if the physics journals were full of papers realizing that the
same force that makes apples fall to ground also moves the planets
about the sun. I'm not saying that there is no good research or that
the universal theory of gravitation is a bad idea, but as Newton
himself pointed out, he stood on the shoulders of giants. He read
other people's published results. He didn't spend his time trying to
figure out how a pendulum's period is related to its length - he read
Galileo.
Personally, I think everyone is entitled to come up with round things
that roll down hills every so often. As a matter of fact, I think
that this can form a very sound basis for learning just how things
work. Physicists realize this and force undergraduates to spend
countless tedious hours trying to fudge their results so it comes out
just the way Faraday or Fermi said it would. This is an excellent
form of education - but it shouldn't be confused with research.
With education, the individual learns something; with research, the
scientific community learns something. All too much of what passes as
research nowadays is nothing more than education.
The current lack of reproducibility is appalling. We have a
generation of language researchers who have never had a chance to play
with the Blocks World or and examine the limitiations of TAILSPIN.
It's as if Elias Howe had to invent the sewing machine without access
to steel or gearing. There's a good chance he would have reinvented
the bone needle and the backstitch given the same access to the fruits
of the industrial revolution that most AI researchers have to the
fruits (lemons) of AI research. Anecdotal evidence, which is really
what this field seems to be based on, just doesn't make for good
science.
Wow, did I write that?
Seth
------------------------------
Date: Fri, 30 Oct 87 15:48:16 WET
From: Martin Merry <mjm%hplb.csnet@RELAY.CS.NET>
Reply-to: Martin Merry <mjm%hplb.csnet@RELAY.CS.NET>
Subject: Once a lemon, always a lemon
Ken Laws argues that critical reviews and reconstructions of existing AI
software are at the moment only peripheral to AI.
> An advisor who advocates duplicating prior work is cutting his
> students' chances of fame and fortune from the discovery of the
> one true path. It is always true that the published works can
> be improved upon, but the original developer has already gotten
> 80% of the benefit with 20% of the work. Why should the student
> butt his head against the same problems that stopped the original
> work (be they theoretical or practical problems) when he could
> attach his name to an entirely new approach?
I had hoped that Drew McDermott's "AI meets Natural Stupidity" had exploded
this view, but apparently not. Substantial, lasting progress in any field of
AI is *never* achievable within the scope of a single Ph.D thesis. Progress
follows from new work building upon existing work - standing on other
researcher's shoulders (instead of, as too often happens, their toes).
This is not an argument for us all to become theorists, working on obscure
extensions to non-standard logics. However, a nifty program which is hacked
together and then only described functionally (i.e. publications only tell you
what it does, with little detail of how it does it, and certainly no
information on the very specialised kluges which make it work in this
particular case) does not advance our knowledge of AI.
Too often in AI, early results from a particular approach may appear promising
and may yield great credit to the discoverer ("80% of the benefit") but don't
actually go beyond solving toy problems. There is a lot of work to do in going
beyond these first sketches ("80% of the work") but if we don't encourage
people to do this we will remain in the sandbox.
Martin Merry Standard disclaimer on personal
HP Labs Bristol Research Centre opinions apply
P.S. For those who haven't seen it, the Drew McDermott paper appears in SIGART
Newsletter 57 (Aug 1976) and is reprinted in "Mind Design" (ed Haugeland),
Bradford Books 1981. It should be required reading for anyone working in
AI....
------------------------------
Date: Fri, 30 Oct 1987 17:03 EST
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList V5 #254 - AI Methodology
Hurrah for Ken Laws when he says that
>An advisor who advocates duplicating prior work is cutting his
>students' chances of fame and fortune from the discovery of the
>one true path.
AI is still in a great exploratory phase in which there is much to be
discovered. I would say that replicating and evaluating an older
experiment would be a suitable Master's degree topic. Replicating AM
and discovering how to extend its range would be a good doctoral topic
- but because of the latter rather than the former aspect.
As for those complaints about AI's fuzziness - and AI's very name -
those are still virtues at the moment. Many people who profess to be
working on AI recognize that what they are doing is to try to make
computers do things that we don't know yet how to make them do, so AI
is in that sense, speculative computer research. Then, whenever
something become better understood, it is moved into a field with a
more specific type of name. No purpose would be served by trying to
make more precise the name of the exploratory activity - either for
the public consumers or for the explorers themselves.
In fact, I have a feeling that most of those who don't like the name
AI also feel uncomfortable when exploring domains that aren't yet
clearly enough defined for their tastes - and are thus disinclined to
work in those areas. If so, then maintaining the title which some of
us like and others don't may actually serve a useful function. It is
the same reason, I think, why the movement to retitle science fiction
as "speculative fiction" failed. The people who preferred the
seemingly more precise definition were not the ones who were best at
making, and at appreciating, the kinds of speculations under discussion.
Ken Laws went on to say that he would make an exception in his own
field of computer vision. I couldn't tell how much of that was irony.
But in fact I'm inclined to agree at the level of lower level vision
processing - but it seems to me that progress in "high level" vision
has been somewhat sluggish since the late 60s and that this may be
because too many vision hackers tried to be too scientific - and have
accordingly not explored enough high level organizational ideas in
that domain.
- marvin minsky
------------------------------
Date: 1 Nov 87 23:37:01 GMT
From: tgd@orstcs.cs.orst.edu (Tom Dietterich)
Subject: Re: Gilding the Lemon
Ken Laws says
...progress in
AI is driven by the hackers and the graduate students who "don't
know any better" than to attempt the unreasonable.
I disagree strongly. If you see who is winning the Best Paper awards
at conferences, it is not grad students attempting the unreasonable.
It is seasoned researchers who are making the solid contributions.
I'm not advocating that everyone do rational reconstructions. It
seems to me that AI research on a particular problem evolves through
several stages: (a) problem definition, (b) development of methods,
(c) careful definition and comparative study of the methods, (d)
identification of relationships among methods (e.g., tradeoffs, or
even understanding the entire space of methods relevant to a problem).
Different research methods are appropriate at different stages.
Problem definition (a) and initial method development (b) can be
accomplished by pursuing particular application problems, constructing
exploratory systems, etc. Rational reconstructions and empirical
comparisons are appropriate for (c). Mathematical analysis is
generally the best for (d). In my opinion, the graduate students of
the past two decades have already done a great deal of (a) and (b), so
that we have lots of problems and methods out there that need further
study and comparison. However, I'm sure there are other problems and
methods waiting to be discovered, so there is still a lot of room for
exploratory studies.
--Tom Dietterich
------------------------------
Date: 1 Nov 87 23:45:25 GMT
From: tgd@orstcs.cs.orst.edu (Tom Dietterich)
Subject: Re: Gilding the Lemon (part 2)
Just a couple more points on this subject.
Ken Laws also says
Progress also comes from applications -- very seldom from theory.
My description of research stages shows that progress comes from
different sources at different stages. Applications are primarily
useful for identifying problems and understanding the important
issues.
It is particularly revealing that Ken is "highly suspicious
of any youngster trying to solve all our problems [in computer vision]
by ignoring the accumlated knowledge of the last twenty years."
Evidentally, he feels that there is no accumulated knowledge in AI.
If that is true, it is perhaps because researchers have not studied
the exploratory forays of the past to isolate and consolidate the
knowledge gained.
--Tom Dietterich
------------------------------
Date: Fri, 30 Oct 87 09:45:45 EST
From: Paul Fishwick <fishwick%fish.cis.ufl.edu@RELAY.CS.NET>
Subject: Gilding the Lemon
...From Ken Laws...
> Progress also comes from applications -- very seldom from theory.
> The "neats" have been worrying for years (centuries?) about temporal
> logics, but there has been more payoff from GPSS and SIMSCRIPT (and
> SPICE and other simulation systems) than from all the debates over
> consistent point and interval representations. The applied systems
> are ultimately limited by their ontologies, but they are useful up to
> a point. A distant point.
I'd like to make a couple of points here: both theory and practice are
essential to progress; however, too much of one without the other
creates an imbalance. As far as the allusion to temporal logics and
interval representations, I think that Ken has made a valuable point.
Too often an AI researcher will write on a subject without referencing
non-AI literature which has a direct bearing on the subject. An
illustration, in point, is the reference to temporal representations -
If one really wants to know what researchers have done with concepts
such as *time*, *process*, and *event* then one should seriously review work
in system modeling & control and simulation practice and theory. In doing
my own research I am actively involved in both systems/simulation
methodology and AI methods so I found Ken's reference to GPSS and SPICE
most gratifying.
What I am suggesting is that AI researchers should directly reference
(and build upon) related work that has "non-philosophical" origins. Note
that I am not against philosophical inquiry in principle -- where would
any of us be without it? The other direction is also important - namely,
that reseachers in more established areas such as systems theory and
simulation should look at the AI work to see if "encoding a mental model"
might improve performance or model comprehensibility.
Paul Fishwick
University of Florida
INTERNET: fishwick@fish.cis.ufl.edu
------------------------------
Date: Mon, 02 Nov 87 17:06:33 EST
From: Mario O Bourgoin <mob@MEDIA-LAB.MEDIA.MIT.EDU>
Subject: Re: Gilding the Lemon
In article <12346288066.15.LAWS@KL.SRI.Com> Ken Laws wonders why a
student should cover the same ground as that of another's thesis and
face the problems that stopped the original work. His objection to
re-implementations is that they don't advance the field, they
consolidate it. He is quick to add that he does not object to
consolidation but that he feels that AI must cover more of its
intellectual territory before it can be done effectively.
I know of many good examples of significant progress achieved
in an area of AI through someone's efforts to re-implement and extend
the efforts of other researchers. Tom Dietterich mentioned one when
he talked about David Chapman's work on conjunctive planning. Work on
dependency-directed backtracking for search is another area. AM and
its relatives are good examples in the field of automated discovery.
Research in Prolog certainly deserves mention.
I believe that AI is more than just ready for consolidation: I
think it's been happening for a while just not a lot or obviously. I
love exploration and understand its place in development but it isn't
the blind stab in the dark that one might gather from Ken's article.
I think he agrees as he says:
A student studies the latest AI proceedings to get a
nifty idea, tries to solve all the world's problems
from his new viewpoint, and ultimately runs into
limitations.
The irresponsible researcher is little better than a random
generator who sometimes remembers what he has done. The repetitive
bureaucrat is less than a cow who rechews another's cud. The AI
researcher learns both by exploring to extend the limits of his
experience and consolidating to restructure what he already knows to
reflect what he has learned.
In other fields, Masters students emphasize consolidation and
PHD students emphasize exploration (creativity.) But at MIT, the AI
program is an interdisciplinary effort which offers only a doctorate
and I don't know of a AI Masters elsewhere. This has left the job of
consolidation to accomplished researchers who are as interested in
exploration as their students. Maybe there would be a use for a more
conservative approach.
- --Mario O. Bourgoin
To Ken: The best paraphrase isn't a quote since quoting communicates
that you are interested in what the other said but not what you
understand of it.
------------------------------
End of AIList Digest
********************
∂03-Nov-87 1357 LAWS@KL.SRI.Com AIList V5 #258 - BBS Abstracts, Knowledge Acquisition Bibliography
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 3 Nov 87 13:57:08 PST
Date: Mon 2 Nov 1987 23:01-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #258 - BBS Abstracts, Knowledge Acquisition Bibliography
To: AIList@SRI.COM
AIList Digest Tuesday, 3 Nov 1987 Volume 5 : Issue 258
Today's Topics:
Journal Call - BBS Commentators
Bibliography - Knowledge Acquisition for Knowledge-Based Systems
----------------------------------------------------------------------
Date: 2 Nov 87 15:24:56 GMT
From: mind!harnad@princeton.edu (Stevan Harnad)
Subject: BBS Call for Commentators: 7 target articles
Below are the abstracts of seven forthcoming articles on which BBS --
Behavioral and Brain Sciences, an international, interdisciplinary Journal
of Open Peer Commentary, published by Cambridge University Press --
invites self-nominations from potential commentators. The procedure is
explained after the abstracts. The seven articles are:
(1) The Intentional Stance (Dan Dennett) [multiple book review]
(2) The Ethological Basis of Learning (A. Gardner & B. Gardner)
(3) Tactical deception in Primates (A. Whiten & R.W. Byrne)
(4) Event-Related Potentials and Memory: A Critique of the Context
Updating Hypothesis (Rolf Verleger)
(5) Is the P300 Component a Manifestation of Context Updating?
(E. Donchin & M. Coles) [article-length precommentary on (4)]
(6) Real and Depicted Spaces: A Cross-Cultural Perspective (J.B. Deregowski)
(7) Research on Self Control: An Integrating Framework (A.W. Logue)
-----
1. The Intentional Stance
Dan Dennett
Philosophy Department
Tufts university
The intentional stance is the strategy of prediction and
explanation that attributes beliefs, desires and other
"intentional" states to organisms and devices and predicts
future behavior from what it would be rational for an agent
to do, given those beliefs and desires. Any device or
organism that regularly uses this strategy is an
"intentional system," whatever its innards might be. The
strategy of treating parts of the world as intentional
systems is the foundation of "folk psychology," but it is
also exploited (and is virtually unavoidable) in artificial
intelligence and cognitive science in general, as well as in
evolutionary theory. An analysis of the role of the
intentional stance and its presuppositions supports a
naturalistic theory of mental states and events, their
"content" or "intentionality," and the relation between
"mentalistic" levels of explanation and neurophysiological
or mechanistic levels of explanation. As such, the analysis
of the intentional stance grounds a theory of the mind and
its relation to the body.
2. The Ethological Basis of Learning
A. Gardner & B. Gardner
Psychology Department
University of Nevada
One view of the basic nature of the learning process has
dominated theory and application throughout the century. It
is the view that the behavior of organisms is governed by
its positive and negative consequences. Anyone who has
attempted to use this principle to teach relatively complex
skills to free-living, well-fed subjects -- as we have done
in our sign language studies of chimpanzees -- is apt to
have been disappointed.
Meanwhile, recent ethological findings plainly contradict
the argument that most, or even much, of the learning that
takes place in the operant conditioning laboratory is based
on the "law of effect." The residue of support for the law
of effect that might be derived from operant conditioning
experiments depends entirely on the logic of a particular
experimental design. There is, however, a logical defect in
this design that cannot be repaired by any conceivable
improvement in procedure or instrumentation. However deeply
ingrained in our cultural traditions, the notion that
behavior is based on its positive consequences cannot be
supported by laboratory evidence. Several key phenomena of
conditioning can be dealt with in a more straightforward
manner by dispensing with hedonism altogether,
An impressive amount of human behavior persists, and
persists in spite of its negative consequences. The popular
notion that persistent maladaptive behavior is rare in other
animals is easily refuted by those who have observed other
animals closely in their natural habitats. We offer an
analysis of adaptive and maladaptive behavior in aversive
conditioning and of the design of experiments on the effect
of predictive contingencies in Pavlovian conditioning. The
latter attempt to demonstrate an effect of contingency fails
because it violates basic principles of experimental design.
We conclude that there is a fundamental logical defect in
all notions of contingency.
This reconsideration of the traditional behavioristic and
cognitive versions of the law of effect was originally
suggested by problems in teaching new and challenging
patterns of behavior to free-living subjects such as
children and chimpanzees, which we briefly describe in
closing.
3. Tactical Deception in Primates
A. Whiten & R.W. Byrne
Psychological Laboratories
University of St. Andrews, Scotland
Tactical deception occurs when an individual's is able to
use an "honest" act from his normal repertoire in a
different context to mislead familiar individuals. Although
primates have a reputation for social skill, most primate
groups are so intimate that any deception is likely to be
subtle and infrequent. Records are often anecdotal and not
widely known in the formal literature of behavioral science.
We have tackled this problem by drawing together records
from many primates and primatologists in order to look for
repeating patterns. This has revealed a many forms of
deceptive tactics, which we classify in terms of the
function they perform. For each class, we sketch the
features of another individual's state of mind that a
deceiver must be able to represent, acting as a "natural
psychologist." Our analysis clarifies and perhaps explains
certain taxonomic differences. Before these findings can be
generalized, however, behavioral scientists must agree on
some fundamental methodological and theoretical questions in
the study of the evolution of social cognition.
4. Event-Related Potentials and Memory:
A Critique of the Context Updating Hypothesis
Rolf Verleger
Mannheim, West Germany
P3 is the most prominent of the electrical potentials of the
human electroencephalogram that are sensitive to
psychological variables. According to the most influential
current hypothesis about its psychological significance [E.
Donchin's], the "context updating" hypothesis, P3 reflects
the updating of working memory. This hypothesis cannot
account for relevant portions of the available evidence and
it entails some basic contradictions. A more general
formulation of this hypothesis is that P3 reflects the
updating of expectancies. This version implies that P3-
evoking stimuli are initially unexpected but later become
expected. This contradiction cannot be resolved within this
formulation.
The alternative "context closure" hypothesis retains the
concept of "strategic information processing" emphasized by
the context updating hypothesis. P3s are evoked by events
that are awaited when subjects deal with repetitive, highly
structured tasks; P3s arise from subjects' combining
successive stimuli into larger units The tasks in which P3s
are elicited can accordingly be classified in terms of their
respective formal sequences of stimuli. P3 may be a
physiological indicator of excess activation being released
from perceptual control areas.
5. Is the P300 component a manifestation of Context Updating?
Emanuel Donchin and Michael G. H. Coles
Cognitive Psychophysiology Laboratory
University of Illinois at Urbana-Champaign
[article-length precommentary on Verleger]
To understand the endogenous components of the ERP we must
use from data about the components' antecedent conditions to
form hypotheses about the information processing function of
the underlying brain activity. These hypotheses, in turn,
generate testable predictions about the consequences of the
component. We review the application of this approach to the
analysis of the P300 component, whose amplitude is
controlled multiplicatively by the subjective probability
and the task relevance of the eliciting events and whose
latency depends on the duration of stimulus evaluation.
These and other factors suggest that the P300 is a
manifestation of activity occurring whenever one's model of
the environment must be revised. Tests of three predictions
based on this "context updating" model are reviewed.
Verleger's critique is based on a misconstrual of the model
as well as on a partial and misleading reading of the
relevant literature.
6. Real and Depicted Spaces:
A Cross-Cultural Perspective
J.B. Deregowski
Psychology Department
University of Aberdeen, Scotland
This paper examines the contribution of cross-cultural
studies to our understanding of the perception and
representation of space. A cross-cultural survey of the
basic difficulties in understanding pictures -- from the
failure to recognize a picture as a representation to the
inability to recognise the object represented -- indicates
that similar difficulties occur in pictorial and
nonpictorial cultures. Real and pictorial spaces must be
distinguished. The experimental work on pictorial space
derives from two distinct traditions: the study of picture
perception in "remote" populations and the study of
perceptual illusions. A comparison of the findings on
pictorial space perception with those on real space
perception and perceptual constancies suggests that cross-
cultural differences in the perception of both real and
depicted space involve two different kinds of skills: those
related only to real spaces or only to depicted spaces and
those related to both. Different cultural groups use
different skills to perform the same perceptual task.
7. Research on Self Control: An Integrating Framework
A.W. Logue
Department of Psychology
SUNY - Stony Brook
The tendency to choose a larger, more delayed reinforcer
over a smaller, less delayed one (self-control) depends on
the current physical values of the reinforcers. It also
varies according to a subject's experience and current
factors other than the reinforcers. Two local delay models
(Mischel's social learning theory and Herrnstein's matching
law) as well as molar maximization models have taken into
account these indirect effects on self control by
representing a subject's behavior as a function of a
perceived environment. A general evolutionary analysis of
all this research yields a better and more predictive
description of self control.
-----
This is an experiment in using the Net to find eligible commentators for
articles in Behavioral & Brain Sciences. [...]
Eligible individuals who judge that they would have a relevant
commentary to contribute should contact me at the e-mail address indicated at
the bottom of this message, or should write by normal mail to:
Stevan Harnad, Editor, Behavioral and Brain Sciences, 20 Nassau Street, Room 240
Princeton NJ 08542 (phone: 609-921-7771)
"Eligibility" usually means being an academically trained professional
contributor to one of the disciplines mentioned earlier, or to related academic
disciplines. The letter should indicate the candidate's general qualifications
as well as their basis for wishing to serve as commentator for the particular
target article in question. It is preferable also to enclose a Curriculum Vitae.
(Please note that the editorial office must exercise selectivity among the
nominations received so as to ensure a strong and balanced cross-specialty
spectrum of eligible commentators.) [...]
Stevan Harnad harnad@mind.princeton.edu (609)-921-7771
------------------------------
Date: 29 Oct 87 17:31:44 GMT
From: mcvax!ukc!reading!onion!spb@uunet.uu.net (Stephen)
Subject: Bibliography - Knowledge Acquisition for Knowledge-Based Systems
Proceedings of the first
European Workshop on
KNOWLEDGE ACQUISITION FOR
KNOWLEDGE - BASED SYSTEMS
Co - Sponsored by the
Institution of Electrical Engineers
2nd - 3rd September 1987
Reading University
There are only a limited number of Proceedings. These are
available on a first come first served basis. The cost will
be 35 pounds sterling, which includes post and packing
within the UK. Cheques should be made payable to 'The
University of Reading'.
Orders to: Professor T R Addis
Department of Computer Science
University of Reading
Whiteknights
Reading
RG6 2AX
BIBLIOGRAPHY
Broy, M., "Transformational Semantics for Concurrent Programs,"
Information Processing Letters, vol. 11, pp. 87-91, 1980.
Evans, D.J. and Shirley A Williams, "Analysis and Detection of
Parallel Processable Code," Computer Journal, vol. 23, pp.
66-72, 1980.
Kuck, D.J., in The Structure of Computers and Computations, vol.
1, John Wiley and Sons, 1978.
Roucairol, G., "Transformations of Sequential Programs into
Parallel Programs," Cambridge University Press, 1982.
Foster, C C, "Information storage and retrieval using AVL trees,"
ACM 20th National conference, 1965.
Knowlton, K C, "A fast storage allocator," CACM, vol. 8, no. 10,
pp. 623-625, October 1965.
Deuel, P, "On a storage mapping function for data structures,"
CACM, vol. 9, no. 5, May 1966.
Knowlton, K C, "A programmer's description of llllll," CACM, vol.
9, no. 8, Aug. 1966.
CODASYL, ACM, NY, April, 1971.
On Conceptual Modelling. Perspectives from Artificial Intelli-
gence, Databases and Programming Languages, Topics in Infor-
mation Systems, Springer-Verlag, 1984.
"Prolog-2 Reference Manual," 9 West Way, Oxford, OC2 0JB, UK, Ex-
pert Systems International Ltd., 1985.
Quintus Prolog Reference Manual, 6, Quintus Computer Systems
Inc., 1986.
"Arity/Prolog: The Programming Language," 358 Baker Avenue, Con-
cord MA 01742, USA, Arity Corporation, 1986.
Addis, T.R., "A Relation-Based Language Interpreter for a Content
Addressable File Store," ACM Trans on Database Systems, vol.
7, no. 2, pp. 125-163, 1982.
Addis, T.R., "Knowledge Refining for a Diagnostic Aid," Interna-
tional Journal of Man-Machine Studies, vol. 17, pp. 151-164,
1982.
Addis, T.R., Designing Knowledge-Based Systems, Kogan Page, 1985.
ISBN0-85038-859-7
Addis, T.R., "The Role of Explanation in Knowledge Elicitation,"
International Journal of Systems Research and Information
Science, vol. 2, pp. 101-110, 1986.
Addis, T.R., The Boundaries of Knowledge, Informatics 9, 1987.
ASLIB Conference at Kings College, Cambridge
Rawlings, C.J., Representing protein structures in Prolog: the
Prolog representation, Imperial Cancer Research Fund,
Biomedical Computing Unit, 1986. Submitted as part of
results of SERC Contract No: SO/351/84
Hamm, G.H. and G.N. Cameron, "The EMBL data library," Nucleic
Acids Research, vol. 14, no. 1, pp. 5-10, 1986.
Chothia, C., "Principles that determine the structure of pro-
teins," Annual Reviews of Biochemistry, vol. 53.
Codd, E.F., "A relational model of data for large shared data
banks," Comm. ACM, pp. 377-387, 1970.
Codd, E.F., "Further normalization of the database relational
model," IBM Research report, 1971. IBM Thomas Watson
Research Centre. N.Y.
Bridge, D., "Conceptual Data Models in Database Design," Final
year project report for BSc Computer Science at Brunel
University, 1986.
Kyte, J. and R.F. Doolittle, "A simple method for displaying the
hydropathic character of a protein," Journal of Molecular
Biology, vol. 157, pp. 105-132, 1982.
Duncan, T., PROPS 2 Reference Manual, Imperial Cancer Research
Fund, Biomedical Computing Unit, 1986.
Sweet, R.M. and D. Eisenberg, "Correlation of sequence hydropho-
bicities measures similarity in three dimensional protein
structure," Journal of Molecular Biology, vol. 171, pp.
479-488, 1983.
Elleby, P. and T.R. Addis, "Extending the Relational Database
Model to capture more Constraints," A KSG Technical Report,
1987.
Chou, P.Y. and G.D. Fasman, "Prediction of the secondary struc-
ture of proteins from their amino acid sequence," Advances
in Enzymology, vol. 47, pp. 45-148, 1980.
Ptitsyn, O.B. and A.V. Finkelstein, "Similarities of protein to-
pologies: evolutionary divergence - functional convergence
or principles of folding?," Annual Reviews of Biophysics,
vol. 13, pp. 339-386, 1980.
Bernstein, F.C., T. Koetzle, G.J.B. William, E. Meyer, M.D.
Brice, J.R. Rodger, O. Kennard, T. Shimanouchi, and M.
Tasumi, "The protein data bank: a computer-based archival
file for macromolecular structures," Journal of Molecular
Biology, vol. 112, pp. 535-542, 1977.
Harre, R., The Philosophy of Science: An Introductory Survey, Ox-
ford University Press, 1976.
George, D.G., W.C. Barker, and L.T. Hunt, "The protein informa-
tion resource (PIR)," Nucleic Acids Research, vol. 14, no.
1, pp. 17-20, 1986.
Cohen, F.E., R.M. Abarbanel, I.D. Kuntz, and R.J. Fletterick,
"Secondary structure assignment for A/B proteins by a com-
binatorial approach," Biochemistry, vol. 22, pp. 4894-4904,
1983.
Rawlings, C.J., W.R. Taylor, J. Nyakairu, J. Fox, and M.J.E.
Sternberg, "Reasoning about protein topology using the logic
programming language PROLOG," Journal of Molecular Graphics,
vol. 3, pp. 151-157, 1985.
Rawlings, C.J., W.R.T. Taylor, J. Nyakairu, J. Fox, and M.J.E.
Sternberg, Using Prolog to Represent and Reason about Pro-
tein Structure, Lecture Notes in Computer Science, p. 536,
Springer-Verlag, 1986.
Bruner, J.S., J.J. Goodnow, and G.A. Austin, in A Study of Think-
ing, Wiley, 1956.
Maizel, J. and R.P. Lenk, "Enhanced graphic matrix analysis of
nucleic acid and protein sequences," Proceedings of the Na-
tional Academy of Science USA, vol. 78, no. 12, pp. 7665-
7669, 1981.
Lim, V.I., "Structural principles of the globular organization of
protein chains. A sterochemical theory of globular protein
secondary structure," Journal of Molecular Biology, vol. 88,
pp. 857-872, 1974.
Bolton, N., in Concept Formation, Pergamon Press, 1977. ISBN 0-
08-0214940
Chen, P.P., "The Entity Relationship Model: Toward a Unified View
of Data," ACM Trans on Data Base Systems, vol. 1, no. 1, pp.
9-13, 1976.
Peirce, C.S., Charles S. Peirce: Selected Writings, Dover Publi-
cations Inc, 1966.
Kowalski, R., Logic for Problem Solving, Artificial Intelligence
Series, North Holland Press, Amsterdam, 1979.
Richardson, J., "B-sheet topology and the relatedness of pro-
teins," Nature, vol. 268, pp. 495-500, 1977.
Richardson, J., "The anatomy and taxonomy of protein structure,"
Advances in Protein Chemistry, vol. 34, pp. 167-339, 1981.
Garnier, J., D.J. Osguthorpe, and B. Robson, "Analysis of the ac-
curacy and implications of simple methods for predicting the
secondary structure of globular proteins," Journal of Molec-
ular Biology, vol. 120, pp. 97-120, 1978.
Kabsch, W. and C.Sander, "How good are predictions of protein
secondary structure?," FEBS Letters, vol. 155, pp. 179-182,
1983.
Blundell, T. and M.J.E. Sternberg, "Computer-aided design in pro-
tein engineering," Trends in biotechnology, vol. 3, pp.
228-235, 1985.
Fox, J., D. Frost, T. Duncan, and N. Preston, The PROPS 2 Primer,
Imperial Cancer Research Fund, Biomedical Computing Unit,
1986.
Eisenberg, D., R.M. Weiss, T.C. Terwilliger, and W. Wilcox, "Hy-
drophobic moments and protein structure," Faraday Symposia
Chemical Society, vol. 17, pp. 109-120, 1982.
Taylor, W.R., Protein Structure Prediction, A Practical Approach,
IRL, Oxford, 1987.
Cohen, F.E., M.J.E. Sternberg, and W.R. Taylor, "Analysis and
prediction of protein B-sheet structures by a combinatorial
approach," Nature, vol. 285, pp. 378-382, 1980.
Cohen, F.E., M.J.E. Sternberg, and W.R. Taylor, "Analysis and
prediction of the packing of B-sheet in the tertiary struc-
ture of globular proteins," Journal of Molecular Biology,
vol. 156, pp. 821-862, 1982.
Sternberg, M.J.E. and J.M. Thornton, "On the conformation of pro-
teins: the handiness of the connection between parallel B-
strands," Journal of Molecular Biology, vol. 110, pp. 269-
283, 1977.
Taylor, W.R. and J.M. Thornton, "Prediction of super-secondary
structure in proteins," Nature, vol. 301, pp. 540-542, 1983.
Burridge, J.M., A.J. Morffew, and S.J.P. Todd, "Experiments in
the use of PROLOG for protein querying," Journal of Molecu-
lar Graphics, vol. 3, p. 109, 1985. abstract 13
Lim, V.I., "Algorithms for prediction of A-helical and B-
structural regions in globular proteins," Journal of Molecu-
lar Biology, vol. 88, pp. 873-894, 1974.
Bobrow, D. and T. Wingrad, "An Overview of KRL, a Knowledge
Representation Language," Cognitive Science, vol. 1, no. 1,
1977.
Hopp, T.P. and K.R. Woods, "A computer program for predicting an-
tigenic determinants," Molecular Immunology, vol. 20, 1983.
Grant, T.J. and P. Elleby, An AI Aid for Scheduling Repair Jobs,
pp. 20-22, Paris, 1986. Conference of the Association Fran-
caise d'Intelligence et des Systems de Simulation
Sowa, J.F., Conceptual Structures: Information processing in mind
and machine, Addison-Wesley, 1984.
V.Begg,, Developing Expert CAD Systems, Kogan Page, 1984.
Ullman, J.D., Principles of Database Systems, Pitman Publishing,
1985.
Brueker, J.A. and B.J. Wielings, "Analysis Techniques for
Knowledge Based Systems," Part 2 Esprit Project 12 1.2,
University of Amsterdam, 1983.
Fikes, R. and T. Kehler, "The Role of Frame-Based Representation
in Reasoning," September Communication of the ACM, vol. 28,
no. 9, pp. 904-920, 1985.
Date, C J, An Introduction to Database Systems, Addison-Wesley,
1981.
Hendrix, G G, "Partitioned Networks for Mathematical Modelling of
Natural Language Semantics," Technical Report NL-28, 1975.
Department of Computer Science, University of Texas
Lakatos, I, "The Methodology of Scientific Research Programmes,"
Philosophical Papers, vol. 1, Cambridge University Press,
1978.
Lee, B, "Introducing Systems Analysis and Design," NCC, vol. I &
II, Manchester, 1978.
Pask, G, Conversation Theory: Applications in Education and Ep-
istemology, Oxford, 1976.
Phillips, B, A model for Knowledge and its Application to
Discourse Analysis, 1978. University of Illinois, Depart-
ment of Information Engineering KSL-9
Popper, K R, The Logic of Scientific Discovery, 1959. Hutchinson
10th impression 1980
Robinson, H, Database Analysis and Design, Chartwell-Bratt, 1981.
Rock-Evans, R, "Data Analysis," IPC Business Press, 1981.
Welbank, M, A review of Knowledge Acquisition Techniques for Ex-
pert Systems, 1983. British Telecommunications Martlesham
Consultancy Services
Wood-Harper, A T and C Fitzgerald, "A taxonomy of current ap-
proaches to systems analysis," Computer Journal, vol. 24,
no. 1, 1982.
--
******************************************************************************
* Stephen Bull * Phone: (0734) 875123 *
* Dept. of Computer Science * mail: bull@onion.reading.ac.uk *
* University of Reading, ENGLAND * *
------------------------------
End of AIList Digest
********************
∂05-Nov-87 0422 LAWS@KL.SRI.Com AIList V5 #259 - FORTRAN, Natural Language Interfaces
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 5 Nov 87 04:22:22 PST
Date: Thu 5 Nov 1987 01:09-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #259 - FORTRAN, Natural Language Interfaces
To: AIList@SRI.COM
AIList Digest Thursday, 5 Nov 1987 Volume 5 : Issue 259
Today's Topics:
Queries - Creativity & Adaptive Systems & Coarse Coding &
PROLOG for Various Machines,
AI Tools - FORTRAN,
Bibliographies - Classification Systems,
Applications - Natural Language Interfaces
----------------------------------------------------------------------
Date: 04 Nov 87 13:27:02 PST
From: oxy!hurley@csvax.caltech.edu (Mark Luke Hurley)
Subject: Creativity
I am a cognitive science major at Occidental College. I am presently
writing my senior thesis on the creative computational systems. I want
to examine the ability of automatic formal systems to capture various
forms of creativity including, but not limited to, artistic creativity,
problem solving, and music composition. I would appreciate any
suggestions or advice about specific literature in this area. I welcome
any leads you can give me that might help in my research.
Thank you.
Mark Hurley
Box 437
1600 Campus Rd.
Occidental College
Los Angeles, CA 90041
ARPANET: oxy!hurley@CSVAX.Caltech.EDU
BITNET: oxy!hurley@hamlet
CSNET: oxy!hurley%csvax.caltech.edu@RELAY.CS.NET
UUCP: ....{seismo, rutgers, ames}!cit-vax!oxy!hurley
------------------------------
Date: 2 Nov 87 17:36:11 GMT
From: stride!tahoe!unrvax!oppy@gr.utah.edu (Brian Oppy)
Subject: references for adaptive systems
i think the header summarizes this pretty well. what i am looking for are
references in the scientific literature, preferably journals, and as recent
as possible. the direction i wish to go with this is toward learning systems,
equivalences in the way computers and biological organisms learn.
thanks in advance for any help you can offer,
brian oppy (oppy@unrvax)
------------------------------
Date: 2 Nov 87 12:26:13 GMT
From: berke@locus.ucla.edu
Subject: "2**n events using only n units" references? (from Berke)
Many connectionist researchers have asserted that a
distributed representation provides efficient use of resources,
encoding 2**n patterns in n units. The "2**n states for
n units" argument is sketched below:
Replace unit-encoding (grandmother cells) with patterns of
activation over n (binary) units. Instead of representing only
n distinct "events," one with each unit, we can represent up to
2**n events using only n units. These patterns overlap, and
this overlap can be used to gain "associative" recall.
Does anyone have any references to such arguments? I've
heard this argument made verbally, but I don't recall exact
references in print. Do you? Also, is there a net-convention
for 2 to-the-n? I'm using 2**n above, (a vestige of my early
FORTRAN experience?) which I prefer to 2↑n. Anyone have any
others?
Perhaps it would be appropriate to "r" a reply to me
rather than posting a follow-up to net. If they are many or
interesting, I'll be sure to post them in one batch.
I would appreciate exact quotes, with references
including page numbers so that I could find the, as the NLP
people say, context.
Thanks
Pete
------------------------------
Date: Tue, 3 Nov 87 01:05 MST
From: DOLATA@rvax.ccit.arizona.edu
Subject: PROLOG for various machines
I have an IRIS 3130, a microVAX II running ULTRIX, and an NCUBE-4
parallel machine (along with a Mac II coming). I am looking for
a PROLOG system to run on all of my machines. I want the system
to have the same syntax on all machines, and the ability to link in
C and Fortran code for some number crunching. I will probably need
a system which is avaialble in source rather than executable products
since the software house which develops code for the NCUBE doesn't
know of any NCUBE prolog (per se').
Anybody know of such a beast? If not, whats the next best bet?
(If you reply to AIlist, please cc: directly to me too)
Thanks
Dan (dolata@rvax.ccit.arizona.edu)
------------------------------
Date: 1 Nov 87 08:38:52 GMT
From: psuvax1!vu-vlsi!swatsun!hirai@husc6.harvard.edu (Eiji "A.G."
Hirai)
Subject: Re: Suggestions for Course
In article <1746@unc.cs.unc.edu> bts@unc.UUCP (Bruce Smith) writes:
>Turbo Prolog for an AI course? Why not FORTRAN, for that matter?
>Quoting (without permission) from Alan Bundy's Catalog of AI Tools:
>
> FORTRAN is the programming language considered by many to
> be the natural successor of LISP and Prolog for AI research.
This must be some very sick joke or this book you quoted from
is majorly screwed up. Fortran is bad for almost anything, least of
all AI. There are zillion plus one articles which will support me in
attacking Fortran, so I won't list or quote them here.
Fortran is EVIL. You were kidding right? Please say you're kidding.
--
Eiji "A.G." Hirai @ Swarthmore College, Swarthmore PA 19081 | Tel. 215-543-9855
UUCP: {rutgers, ihnp4, cbosgd}!bpa!swatsun!hirai | "All Cretans are liars."
Inter: swatsun!hirai@bpa.bell-atl.com | -Epimenides
Bitnet: vu-vlsi!swatsun!hirai@psuvax1.bitnet | of Cnossus, Crete
------------------------------
Date: 2 Nov 87 17:14:56 GMT
From: nau@mimsy.umd.edu (Dana S. Nau)
Subject: Re: Suggestions for Course
In article <1746@unc.cs.unc.edu> bts@unc.UUCP (Bruce Smith) writes:
>Turbo Prolog for an AI course? Why not FORTRAN, for that matter? ...
In article <1361@byzantium.swatsun.UUCP> hirai@swatsun.UUCP writes:
> [lots of flames about FORTRAN]
To me, it seemed obvious that the original posting was a joke--in fact, a
rather good one. Too bad it got taken seriously.
--
Dana S. Nau ARPA & CSNet: nau@mimsy.umd.edu
Computer Sci. Dept., U. of Maryland UUCP: ...!seismo!mimsy!nau
College Park, MD 20742 Telephone: (301) 454-7932
------------------------------
Date: Mon 2 Nov 87 14:29:09-PST
From: Ken Laws <LAWS@IU.AI.SRI.COM>
Subject: In Defense of FORTRAN
Eiji Hirai asks whether FORTRAN is seriously considered an AI language.
I'm certain that Alan Bundy was joking about it. That leaves an opening
for a serious defender, and I am willing to take the job. Other languages
have already been much touted and debated in AIList, so FORTRAN deserves
equal time.
Many expert system companies have found that they must provide their
end-user programs in C (or occasionally PASCAL or some other traditional
language). A few such companies actually prefer to do their development
work in C. There are reasons why this is not insane. The same reasons
can be made to apply to FORTRAN, providing that one is willing to consider
a few language extensions. They apply with even more force to ADA, which
may succeed in giving us the sharable subroutine libraries that have been
promised ever since the birth of FORTRAN. I will concentrate on C because
I know it best.
The problem with traditional languages is neither their capability nor
their efficiency, but the way that they limit thought. C, after all,
can be used to implement LISP. A C programmer may be more comfortable
growing the tail end of a dynamic array than CONSing to the head of
a list, but that is simply an implementation option that should be
hidden within a package of list-manipulation routines. (Indeed, the
head/tail distinction for a 1-D array is arbitrary.) Languages that
permit pointer manipulation and recursive calls can do just about
anything that LISP or PROLOG can. (Dynamic code modification is
possible in C, although exceedingly difficult. It could be made more
palatable if appropriate parsing and compilation subroutines were made
available.)
My own definition of an "AI" program is any program that would never
have been thought of by a FORTRAN/COBOL programmer. (The past tense
is significant, as I will discuss below.) FORTRAN-like languages
are thus unlikely candidates for AI development. Why should this
be so? It is because they designed for low-level manipulations (by
modern standards) and are clumsy for expressing high-level concepts.
C, for instance, is so well suited to manipulating character strings
that it is unusual to find a UNIX system with an augmented library of
string-parsing routines. It is just so much easier to hack an
efficient ad hoc loop than to document and maintain a less-efficient
general-purpose string library that the library never gets written.
String-manipulation programs do exist (editors, AWK, GREP, etc.), but
the intermediate representations are not available to other than
system hackers.
FORTRAN, with its numeric orientation, is even more limiting. One can
write string-parsing code, but it is difficult. I suspect that string
libraries are therefore more available in FORTRAN, a step in the right
direction. People interested in string manipulation, though, are more
likely to use SNOBOL or some other language -- almost any other language.
FORTRAN makes numerical analysis easy and everything else difficult.
Suppose, though, that FORTRAN and C offered extensive "object oriented"
libraries for all the data types you were likely to need: lists, trees,
queues, heaps, strings, files, buffers, windows, points, line segments,
robot arms, etc. Suppose that they also included high-level objects
such as hypotheses, goals, and constraints. (These might not be just
what you needed, but you could use the standard data types as templates
for making your own.) These libraries would then be the language in
which you conduct your research, with the base language used only to
glue the subroutines together. A good macro capability could make the
base+subroutine language more palatable for specific applications,
although there are drawbacks to concealing code with syntactic sugar.
Given the appropriate subroutine libraries, there is no longer a mental
block to AI thought. A FORTRAN programmer could whip together a
backtrack search almost as fast as a PROLOG programmer. Indeed,
PROLOG would be a part of the FORTRAN environment. Current debugging
tools for FORTRAN and C are not as good as those for LISP machines,
but they are adequate if used by an experienced programmer. (Actually,
there are about a hundred types of FORTRAN/COBOL development tools
that are not commonly available to LISP programmers. Their cost and
learning time limit their use.) The need for garbage collection can
generally be avoided by explicit deallocation of obsolete objects
(although there are times when this is tricky). Programming in a
traditional language is not the same as programming in LISP or PROLOG,
but it is not necessarily inferior.
The problem with AI languages is neither their capability nor
their efficiency, but the way that they limit thought. Each makes
certain types of manipulations easy while obscuring others.
LISP is a great language for manipulating lists, and lists are an
exceptionally powerful representation, but even higher level constructs
are needed for image understanding, discourse analysis, and other
areas of modern AI research. No language is perfectly suited for
navigating databases of such representations, so you have to choose
which strengths and weaknesses are suited to your application.
If your concern is with automating intelligent >>behavior<<,
a traditional algorithmic language may be just right for you.
-- Ken Laws
------------------------------
Date: 4 Nov 87 15:55:46 GMT
From: ssc-vax!dickey@beaver.cs.washington.edu (Frederick J Dickey)
Subject: Re: AIList V5 #253 - LISP, NIL, Msc.
In article <MINSKY.12346702081.BABYL@MIT-OZ>, MINSKY@OZ.AI.MIT.EDU writes:
> In reply to noekel@uklirb.UUCP who is
> >
> >currently building a AI bibliography and still searching for a
> >suitable classification/key word scheme.
In "The AI Magazine" a couple of years ago, there was an article that presented
an AI classification scheme. If my memory serves me right, the author of the
article says he developed it for some sort of library/information retrieval
application. It sounds like it is fairly close to what noekel@uklirb wants.
I can't give a more specific citation because my collection of AI Magazines
is at home.
------------------------------
Date: 5 Nov 87 04:58:00 GMT
From: crawford@endor.harvard.edu (Alexander Crawford)
Subject: Re: The future of AI.... (nothing about flawed minds)
The first impact from AI on software in general will be natural
language interfaces. Various problems need to be solved, such as how
to map English commands completely onto a particular application's set
of commands COMPLETELY. (As Barbara Grosz says, if it can be said, it
can be said in all ways, e.g. "Give me the production report",
"Report", "How's production doing?".) Once this is completed for a
large portion of applications, it will become a severe disadvantage in
the marketplace NOT to offer a natural-language interface.
Coupled with a NLI, machine-learning will allow applications to
improve in different ways as they are used:
-Interfaces can be customized easily, automatically, for
different users.
-Complex tasks can be learned automatically by having the
application examine what the human operator does normally.
-Search of problem spaces for solutions can be eliminated and
replaced by knowledge. (This is called "chunking". See
MACHINE LEARNING II, Michalski et al. Chapter 10:
"The Chunking of Goal Hierarchies: A Generalized Model of
Practice" by Rosenbloom and Newell.)
-Alec (crawford@endor.UUCP)
------------------------------
End of AIList Digest
********************
∂05-Nov-87 0856 LAWS@KL.SRI.Com AIList V5 #260 - Resource Center for Software, AI Goals and Models
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 5 Nov 87 08:56:02 PST
Date: Thu 5 Nov 1987 01:24-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #260 - Resource Center for Software, AI Goals and Models
To: AIList@SRI.COM
AIList Digest Thursday, 5 Nov 1987 Volume 5 : Issue 260
Today's Topics:
Proposal - National Resource Center for Intelligent Systems Software &
Methodology - Sharing Software,
Comments - The Success of AI & Humanist Models of Mind
----------------------------------------------------------------------
Date: Tue, 3 Nov 87 11:59:50 EST
From: futrell%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: National Resource Center for Intelligent Systems Software
I will soon be in Washington talking to the National Science
Foundation about the possibility of setting up a National Resource
Center for Intelligent Systems Software. The center would have as its
goal the timely and efficient distribution of contributed public
domain software in AI, NLP, and related areas. Below I have listed,
very briefly, some of the points that I will be covering. I would
like to hear reactions from all on this.
0. Goals/Philosophy: Distribute software. The motivations are practical
(easier on the original author and requester) and philosophical
(accumulating a base of shared techniques and experience for the field).
1. Scope: Limited in the beginning until acquisition and distribution
experience is built up.
2. Possible Initial Emphasis: Natural language processing, large lexicons,
small exemplary programs/systems for teaching AI.
3. Selection: Limited selection balancing importance vs. the robustness and
detailed documentation of the contributed software.
4. What to Distribute: Source code plus paper documentation, reprints,
theses related to the software.
5. Mode of Distribution: Small: e-mail distribution server. Large: S-mail.
6. Support of Distributed Items: The Center should not offer true
software "support", but it would assure that the software runs on one
or more systems before distribution (& see next item).
7. User Involvement: Users of the distributed items are a source of both
questions and of answers. So the Center would support national mailings and
forums on the nets so that problems could be resolved primarily by users.
If we don't partially shield the developer, important items may never
be contributed.
8. Languages: Common Lisp would be the dominant exchange medium.
Hopefully other standards will emerge (CLOS, X windows).
9. Hardware: The center would maintain or have access to a dozen or so
systems for testing, configuring, and hard(tape)copy production.
10. Compatibility Problems: The Center would work with developers and users
to deal with the many compatibility issues that will arise.
11. Staff: Two to three full-time equivalents.
12. Management: An advisory board (working via e-mail and phone)?
13. Cost to Users: E-mail free, hardcopy and tapes at near cost.
14. Licensing: A sticky issue. A standard copyright policy could be
instituted. Avoid software with highly restrictive licensing.
Where this is coming from:
Our college is rather new but has 30 faculty and a fair amount of
equipment, mostly Unix. We have a PhD program and a large number of
MS and undergrad students. I am involved in a major project to parse
whole documents to build knowledge bases. My focus is on parsing
diagrammatic material, something that has received little attention.
I teach grad courses on Intro to AI, AI methods, Vision, and Lisp.
I am very familiar with the National Science Foundation, their goals
and policies.
You can reach me directly at:
Prof. Robert P. Futrelle
College of Computer Science 161CN
Northeastern University
360 Huntington Ave.
Boston, MA 02115
(617)-437-2076
CSNet: futrelle@corwin.ccs.northeastern.edu
------------------------------
Date: Tuesday, 3 November 1987, 21:23-EST
From: Nick Papadakis <@EDDIE.MIT.EDU:nick@MC.LCS.MIT.EDU>
Subject: Re: Lenat's AM program [AIList V5 #257 - Methodology]
In article <774> tgd@ORSTCS.CS.ORST.EDU (Tom Dietterich) writes:
>>In the biological sciences, publication of an article reporting a new
>>clone obligates the author to provide that clone to other researchers
>>for non-commercial purposes. I think we need a similar policy in
>>computer science.
Shane Bruce <bruce@vanhalen.rutgers.edu> replies:
>The policy which you are advocating, while admirable, is not practical. No
>corporation which is involved in state of the art AI research is going to
>allow listings of their next product/internal tool to made available to the
>general scientific community, even on a non-disclosure basis. Why should
>they give away what they intend to sell?
This is precisely why corporations involved in state of the art AI
research (and any other form of research) will find it difficult to make
major advances. New ideas thrive in an environment of openness and free
interchange.
- nick
------------------------------
Date: 30 Oct 87 19:45:09 GMT
From: gatech!udel!sramacha@bloom-beacon.mit.edu (Satish Ramachandran)
Subject: Re: The Success of AI (continued, a
In article <8300008@osiris.cso.uiuc.edu> goldfain@osiris.cso.uiuc.edu writes:
>
>Who says that ping-pong, or table tennis isn't a sport? Ever been to China?
Rightly put! Ping-pong may not be a spectator sport in the West and hence,
maybe suspected to be a 'sport' where little skill is involved.
But if you read about it, you would find that the psychological aspect
of the game is far more intense than say, baseball or golf!
The points are 21 each game and very quickly done with...(often with the
serves themselves !)
Granting the intense psychological factors to be considered while playing
ping-pong (as in many other games), would it be easier to make a machine play
a game where there is a lot of time *real-time* to decide its next move
as opposed to making it play a game where things have to be decided
more quickly, relatively?
Satish
P.S. Btw, ping-pong is also a popular sport in Japan, India, England,
Sweden and France.
------------------------------
Date: 31 Oct 87 17:16:06 GMT
From: trwrb!cadovax!gryphon!tsmith@ucbvax.Berkeley.EDU (Tim Smith)
Subject: Re: The Success(?) of AI
In article <171@starfire.UUCP> merlyn@starfire.UUCP (Brian Westley) writes:
+=====
| ...I am not interested in duplicating or otherwise developing
| models of how humans think; I am interested in building machines that
| think. You may as well tell a submarine designer how difficult it is
| to build artificial gills - it's irrelevant.
+=====
The point at issue is whether anyone understands enough about
"thinking" to go out and build a machine that can do it. My claim (I
was the one who started this thread) was that we do not. The common
train of thought of the typical AI person seems to be:
(1) The "cognitive" people have surely figured out by now what
thinking is all about.
(2) But I can't be bothered to read any of their stuff, because they
are not programmers, and they don't know how computers work.
Actually, the "cognitive" people haven't figured out what thinking is
at all. They haven't a clue. Of course they wouldn't admit that in
print, but you can determine that for yourself after only a few
months of intensive reading in those fields.
Now there's nothing wrong with naive optimism. There are many cases
in the history of science where younger people with fresh ideas have
succeeded where traditional methods have failed. In the early days of
AI, this optimism prevailed. The computer was a new tool (a fresh
idea) that would conquer traditional fields. But it hasn't. The naive
optimism continues, however, for technological reasons. Computers keep
improving, and many people seem to believe that once we have
massively parallel architectures, or connection machines, or
computers based on neural nets, then, finally, we will be able to
build a machine that thinks.
BS! The point is that no one (NO ONE) knows enough about thinking to
design a machine that thinks.
Look, I am not claiming that AI should come to a grinding halt. All I
am pleading for is some recognition from AI people that the
top-level problems they are addressing are VERY complicated, and are
not going to be solved in the near future by programming. I have seen
very little of this kind of awareness in the AI community. What I
see instead is a lot of whining to the effect that once a problem is
"solved", it is removed from the realm of thinking (chess, compilers,
and medical diagnosis are the usual examples given).
Now if you believe that playing chess is like thinking, you haven't
thought very much about either of these things. And if you believe
that computers can diagnose diseases you are certainly not a
physician. (Please, no flames about MYCIN, CADUCEUS, and their
offspring--I know about these systems. They can be very helpful tools
for a physician, just as a word processor is a helpful tool for a
writer. But these systems do not diagnose diseases. I have worked in
a hospital--it's instructive. Spend some time there as an observer!)
I don't remember any of the pioneer artificial intelligentsia
(Newell, Simon, Minsky, etc.) ever claiming that compilers were
artificial intelligence (they set their sights much higher than
that).
I am not trying to knock the very real advances that AI work has made
in expert systems, in advanced program development systems, and in
opening up new research topics. I just get so damn frustrated when I
see people continually making the assumption that thinking, using
language, composing music, treating the sick, and other basic human
activities are fairly trivial subjects that will soon be accomplished
by computers. WAKE UP! Go out and read some psychology, philosophy,
linguistics. Learn something about these things that you believe are
so trivial to program. It will be a humbling, but ultimately
rewarding, experience.
--
Tim Smith
INTERNET: tsmith@gryphon.CTS.COM
UUCP: {hplabs!hp-sdd, sdcsvax, ihnp4, ....}!crash!gryphon!tsmith
UUCP: {philabs, trwrb}!cadovax!gryphon!tsmith
------------------------------
Date: 3 Nov 87 00:19:57 GMT
From: PT.CS.CMU.EDU!SPEECH2.CS.CMU.EDU!yamauchi@cs.rochester.edu
(Brian Yamauchi)
Subject: Re: The Success of AI
In article <137@glenlivet.hci.hw.ac.uk>, gilbert@hci.hw.ac.uk
(Gilbert Cockton) writes:
> This work is inherently superior to most work in AI because none of the
> writers are encumbered by the need to produce computational models.
> They are thus free to draw on richer theoretical orientations which
> draw on concepts which are clearly motivated by everyday observations
> of human activity. The work therefore results in images of man which
> are far more humanist than mechanical computational models.
I think most AI researchers would agree that the human mind is more than a
simple production system or back-propagation network, but the more basic
question is whether or not it is possible for human beings to understand
human intelligence. If the answer is no, then not only cognitive
psychologists, but all psychologists will be doomed to failure. If the
answer is yes, then it should be possible to use build a system that uses
that knowledge to implement human-like intelligence. The architecture of this
system may be totally unlike today's computers, but it would be man-made
("Artificial") and possessing human-like intelligence.
This may require some completely different model than those currently
popular in cognitive science, and it would have to account for
"non-computational" human behavior (emotions, creativity, etc.), but as long
as it was well-defined, it should be possible to implement the model in some
system.
I suppose one could argue that it will never be possible to perfectly
understand human behavior, so it will never be possible to make an AI which
perfectly duplicates human intelligence. But even if this were true, it
would be possible to duplicate human intelligence to the degree that it was
possible to understand human behavior.
> Furthermore, the common test of any
> concept of mind is "can you really imagine your mind working this way?"
This is a generally useful, if not always accurate, rule of thumb. (It is
also the reason why I can't see why anyone took Freudian psychology
seriously.)
Information-processing models (symbol-processing for the higher levels,
connectionist for the lower levels) seem more plausible to me than any
alternatives, but they certainly are not complete and to the best of my
knowledge, they do not attempt to model the non-computational areas. It
would be interesting to see the principles of cognitive science applied to
areas such as personality and creativity. At least, it would be interesting
to see a new perspective on areas usually left to non-cognitive
psychologists.
> Many of the pillars of human societies, like the freedom and dignity of
> democracy and moral values, are at odds with the so called 'Scientific'
> models of human behaviour; indeed the work of misanthropes like Skinner
> actively promote the connection between impoversihed models of man and
> immoral totalitarian socities (B.F. Skinner, Beyond Freedom and Dignity).
True, it is possible to promote totalitarianism based on behaviorist
psychology (i.e. Skinner) or mechanistic sociology (i.e. Marx), both of
which discard the importance of the individual. On the other hand, simply
understanding human intelligence does not reduce its importance -- an
intelligence that understands itself is at least as valuable as one that
does not.
Furthermore, totalitarian and collectivist states are often promoted on the
basis of so-called "humanistic" rationales -- especially for socialist and
communist states (right-wing dictatorships seem to prefer nationalistic
rationales). The fact that such offensive regimes use these justifications
does not discredit either science or the humanities.
______________________________________________________________________________
Brian Yamauchi INTERNET: yamauchi@speech2.cs.cmu.edu
Carnegie-Mellon University
Computer Science Department
______________________________________________________________________________
------------------------------
Date: 4 Nov 87 22:01:03 GMT
From: topaz.rutgers.edu!josh@rutgers.edu (J Storrs Hall)
Subject: Re: The Success of AI
Brian Yamauchi:
... the more basic
question is whether or not it is possible for human beings to understand
human intelligence. If the answer is no, then not only cognitive
psychologists, but all psychologists will be doomed to failure.
Actually, it is probably possible to build a system that is more
complex than any one person can really "understand". This seems to be
true of a lot of the systems (legal, economic, etc) at large in the
world today. The system is made up of the people each of whom
understands part of it. It is conjectured by Minsky that the mind is
a similar system. Thus it may be that AI is possible where psychology
is not (in the same sense that economics is impossible).
--JoSH
------------------------------
Date: 3 Nov 87 12:06 PST
From: hayes.pa@Xerox.COM
Subject: Humanist Models of Mind
Gilbert Cockton makes a serious mistake, in lumping AI models together
with all other `mechanical' or `scientific' models of mind on the wrong
side of C P Snows cultural fence:
>In short, mechanical concepts of mind and the values of a civilised
>society are at odds with each other. It is for this reason that modes
>of representation such as the novel, poetry, sculpture and fine art
>will continue to dominate the most comprehensive accounts of the
>human condition.
The most exciting thing about computational models of the mind is
exactly that they, alone among the models of the mind we have, ARE
consistent with humanist values while being firmly in contact with
results of the hardest of sciences.
Cockton is right to be depressed by many of the scientific views of man
that have appeared recently. We have fallen from the privileged bearers
of divine knowledge to the lowly status of naked apes, driven by
primitive urges; or even to mere vehicles used by selfish genes to
reproduce themselves. Superficial analogies between brains and machines
make people into blind bundles of mechanical links between inputs and
outputs, suitable inhabitants for Skinners New Walden, of whose minds -
if they have any - we are not permitted to speak. Physicists often
assume that people, like everything else, are physical machines governed
by physical laws, and therefore whose behavior must be describable in
physical terms: more, that this is a scientific truth, beyond rational
dispute. None of these pictures of human nature has any place for
thought, for language, culture, mutual awareness and human
relationships. Many scientists have given up and decided that the most
uniquely human attributes have no place in the world given us by
biology, physics and engineering.
But the computational approach to modelling mind gives a central place
to symbolic structures, to languages and representations. While firmly
rooted in the hard sciences, this model of the mind naturally
encompasses views of perception and thought which assume that they
involve metaphors, analogies,inferences and images. It deals right at
its center with questions of communication and miscommunication. I can
certainly imagine my mind ( and Gilberts ) working this way: I consist
of symbols, interacting with one another in a rich dynamic web of
inference, perceptual encoding and linguistic inputs ( and other
interactions, such as with emotional states ). This is a view of man
which does NOT reduce us to a meaningless machine, one which places us
naturally in a society of peers with whom we communicate.
Evolutionary biology can account for the formation of early human
societies in very general terms, but it has no explanation for human
culture and art. But computer modellers are not surprised by the
Lascaux cave paintings, or the univeral use of music, ritual and
language. People are organic machines; but if we also say that they
are machines which work by storing and using symbolic structures, then
we expect them to create representations and attribute meaning to
objects in their world.
I feel strongly about this because I believe that we have here, at last,
a way - in principle - to bridge the gap between science and humanity.
Of course, we havnt done it yet, and to call a simple program
`intelligent' doesnt help to keep things clear, but Cocktons pessimism
should not be alllowed to cloud our vision.
Pat Hayes
------------------------------
End of AIList Digest
********************
∂06-Nov-87 0600 LAWS@KL.SRI.Com AIList V5 #261 - Seminars, CADE-9, HICSS-22
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 6 Nov 87 06:00:04 PST
Date: Thu 5 Nov 1987 21:28-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #261 - Seminars, CADE-9, HICSS-22
To: AIList@SRI.COM
AIList Digest Friday, 6 Nov 1987 Volume 5 : Issue 261
Today's Topics:
Seminars - A Hybrid Paradigm for Modeling of Complex Systems (TI) &
The Ecology of Computation (SRI) &
Evolving Knowledge and TMS (SRI) &
Conceptual Graphs (SRI) &
Hypothetical Reasoning (SRI) &
Application of Fuzzy Control in Japan (NASA Ames),
Conference - CADE-9 Automated Deduction &
HICSS-22 System Sciences
----------------------------------------------------------------------
Date: Tue, 3 Nov 87 13:51:42 CST
From: "Michael T. Gately" <gately%resbld.csc.ti.com@RELAY.CS.NET>
Subject: Seminar - A Hybrid Paradigm for Modeling of Complex Systems (TI)
Texas Instruments Computer Science Center Lecture Series
A Hybrid Paradigm for Modeling of Complex Systems
Prof. J. Talavage
Purdue University
10:00 am, Friday, 6 November 1987
North Building Cafeteria Room C-4
Abstract
The Network Modeling approach to simulation provides the modeler with
simple yet powerful concepts which can be used to capture the
significant aspects of the system to be modeled. Current network
modeling methodologies, though advanced, lack explicit concepts for
the representation of complex behavior such as decision-making .
Artificial Intelligence research, because of its emphasis on knowledge
representation, has provided several techniques which can be
succesfully applied to the modeling of decision-making behavior. A
hybrid methodology unifying the concepts of Object-oriented
programming, Logic programming and the Discrete-Event approach to
systems modeling should provide a very convenient vehicle for
representing complex systems. The approach has been implemented as a
top-level of CAYENE. CAYENE is a member of the class of programming
languages known as hybrid AI systems and it is based on a formalism of
distributed logic programming. SIMYON is an experimental network
simulation environment embedded in CAYENE. SIMYON is implemented by
defining a library of CAYENE objects analogous to the `blocks' of
network simulation languages and thus providing building blocks for
modeling. Examples of the use of SIMYON to model a job scheduler in a
manufacturing situation, and an adaptive material handling dispatch
mechanism for flexible manufacturing systems are given.
Biography
Dr. Talavage is a Professor of Industrial Engineering at Purdue
University. His teaching and research interests have focussed on the
areas of modeling and simulation, with application to manufacturing
systems. Professor Talavage's current research includes the
integration of artificial intelligence capabilities with those of
simulation/math modeling in order to provide a highly intelligent aid
for production decision support. Since receiving his Ph.D. from Case
Institute of Technology in 1968, Dr. Talavage has published over 100
papers and one book, and is on the Editorial board of the Journal of
Manufacturing Systems and an Associate Editor for the SIMULATION
journal. He has been a consultant to numerous companies and
government agencies.
----------------------------------------------------------------------
The lecture will be given in the North Building Cafeteria Room C-4 at
the Dallas Expressway site. Visitors to TI should contact Dr. Bruce
Flinchbaugh (214-995-0349) in advance and meet in the west entrance
lobby of the North Building by 9:45am.
------------------------------
Date: Tue, 3 Nov 87 09:30:20 PST
From: seminars@csl.sri.com (contact lunt@csl.sri.com)
Subject: Seminar - The Ecology of Computation (SRI)
SRI COMPUTER SCIENCE LAB SEMINAR ANNOUNCEMENT:
THE ECOLOGY OF COMPUTATION
Bernardo A. Huberman
Xerox Palo Alto Research Center
Monday, November 9 at 4:00 pm
SRI International, Computer Science Laboratory, Room EJ228
A most advanced instance of concurrent computation is provided by
distributed processing in open systems which have no global controls.
These emerging heterogeneous networks are becoming self-regulating
entities which in their behavior are very different from their individual
components. Their ability to remotely spawn processes in other computers
and servers of the system offers the possibility of having a community of
computational agents which, in their interactions, are reminiscent of
biological and social organizations. This talk will give a perspective
on computational ecologies, and describe a theory of their behavior which
explicitly takes into account incomplete knowledge and delayed information
on the part of its agents. When processes can choose among many possible
strategies while collaborating in the solution of computational tasks, the
dynamics leads to asymptotic regimes characterized by fixed points,
oscillations and chaos. Finally, we will discuss the possible existence of
a universal law regulating the way in which the benefit of cooperation is
manifested in the system.
NOTE FOR VISITORS TO SRI:
Please arrive at least 10 minutes early in order to sign in and
be shown to the conference room.
SRI is located at 333 Ravenswood Avenue in Menlo Park. Visitors
may park in the visitors lot in front of Building E (a tall tan
building on Ravenswood Ave; the turn off Ravenswood has a sign
for Building E), or in the visitors lot in front of Building A
(red brick building at 333 Ravenswood Ave), or in the conference
parking area at the corner of Ravenswood and Middlefield. The
seminar room is in Building E. Visitors should sign in at the
reception desk in the Building E lobby.
Visitors from Communist Bloc countries should make the necessary
arrangements with Fran Leonard (415-859-4124) in SRI Security as
soon as possible.
------------------------------
Date: Thu, 5 Nov 87 14:25:04 PST
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Evolving Knowledge and TMS (SRI)
EVOLVING KNOWLEDGE AND TMS
Anand S. Rao (ANAND@IBM.COM)
IBM T.J. Watson Research Center and Sydney University
(joint work with
Normal Y. Foo
IBM Systems Research Education Center and Sydney University)
11:00 AM, MONDAY, November 9
SRI International, Building E, Room EJ228
The traditional view of knowledge in the AI literature has been that
'Knowledge' is 'true belief'. The semantic account of this notion
suffers from a major problem called Logical Omniscience, where the
agent knows all valid formulas and his knowledge is closed under
implication. In this talk we propose an alternative viewpoint where
knowledge or EVOLVING KNOWLEDGE (as we call it) is treated as
'indefeasibly justified true belief'. This notion of knowledge solves
the problem of logical omniscience and also captures the
resource-bounded reasoning of agents in a natural way. We give the
semantics and axiomatization of this logic of evolving knowledge and
discuss its properties.
The logic of evolving knowledge also serves as the logical foundation
for the Truth Maintenance System (TMS). We provide a transformation to
and from TMS nodes to formulas in this logic. We show that a set of
nodes has a 'well founded labelling' iff their corresponding IN nodes
are 'satisfiable' in this logic and their corresponding OUT nodes are
'not satisfiable' in this logic. We conclude the talk by comparing our
logic with Autoepistemic Logic, Deduction model of Belief and the
Awareness model of belief.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Thu, 5 Nov 87 09:17:21 PST
From: luntzel@csl.sri.com (Elizabeth Luntzel)
Subject: Seminar - Conceptual Graphs (SRI)
SRI COMPUTER SCIENCE LAB SEMINAR ANNOUNCEMENT:
KNOWLEDGE REPRESENTATION WITH CONCEPTUAL GRAPHS
John F. Sowa
IBM Systems Research
and Stanford University
Wednesday, November 11 at 4:00 pm
SRI International, Computer Science Laboratory, Room A113B
Conceptual graphs form a complete system of logic designed to map
as simply as possible to and from natural languages. Like the predicate
calculus, they are general enough to represent anything that can be
represented in rules, frames, and other languages. But they also have
certain formal and practical advantages over the predicate calculus.
Their formal advantages arise from their treatment of objects, contexts,
and sets. Their practical advantages arise from the standard guidelines
they provide for mapping to and from natural languages. Because of their
generality and flexibility, they have been used as the knowledge
representation language for a variety of applications, including planning,
information retrieval, and interfaces between heterogeneous databases and
knowledge bases. This talk will introduce conceptual graphs and show how
they handle a variety of knowledge representation tasks.
John Sowa is a member of the IBM Systems Research Institute in Thornwood,
New York. This fall, he has been visiting the IBM Palo Alto Scientific
Center and teaching a course in the Stanford Computer Science Department.
His work on conceptual graphs has appeared in his book, Conceptual
Structures (Addison-Wesley, 1984), and a new collection of papers on
conceptual graphs will be released in the spring of 1988.
NOTE FOR VISITORS TO SRI:
Please arrive at least 10 minutes early in order to sign in and
be shown to the conference room.
SRI is located at 333 Ravenswood Avenue in Menlo Park. Visitors
may park in the visitors lot in front of Building A (red brick
building at 333 Ravenswood Ave) or in the conference parking area
at the corner of Ravenswood and Middlefield. The seminar room is in
Building A. Visitors should sign in at the reception desk in the
Building A lobby.
IMPORTANT: Visitors from Communist Bloc countries should make the
necessary arrangements with Fran Leonard (415-859-4124) in SRI Security
as soon as possible.
------------------------------
Date: Thu, 29 Oct 87 16:55:04 PST
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Hypothetical Reasoning (SRI)
DEFAULTS AND CONJECTURES:
HYPOTHETICAL REASONING FOR EXPLANATION AND PREDICTION
David Poole (dlpoole%watdragon.waterloo.edu@relay.cs.net)
Logic Programming and Artificial Intelligence Group
University of Waterloo
11:00 AM, MONDAY, November 2
SRI International, Building E, Room EJ228
Classical logic has been criticised as a language for common sense
reasoning as it is monotonic. In this talk I wish to argue that the
problem is not with logic, but with how logic is used. An alternate
way to use logic is by using theory formation; logic tells us what a
theory implies, an inconsistency means that the theory cannot be true
of the world. I show how the simplest form of theory formation, namely
where the user supplies the possible hypotheses, can be used as a
basis for default reasoning and model-based diagnosis. This is the
basis of the "Theorist" system being built at the University of
Waterloo. I will discuss what we have learned from building and using
our system. I will also discuss distinctions which we have found to
be important in practice, such as between explaining observations and
making predictions; and between normality conditions (defaults) and
abnormality conditions (prototypes, conjectures, diseases). The
effects of these distinctions on recognition and prediction problems
will be presented along with algorithms, theorems and examples.
------------------------------
Date: Fri, 30 Oct 87 17:55:10 PST
From: JARED%PLU@ames-io.ARPA
Subject: Seminar - Application of Fuzzy Control in Japan (NASA Ames)
NASA Ames Research Center
Intelligent Systems Forum
Professor Yamakawa, Kumamoto University
and
Professor Hirota, Hosei University (Japan)
The Application of 'Fuzzy Control' in Japan
SUMMARY:
A seminar on the application of 'Fuzzy Control' in Japan and recent work
leading to the creation of 'fuzzy chips', 'fuzzy hardwares', and 'Fuzzy
computers'.
The list of interesting applications include the famous control of the
trains (metro) in the city of Sendai, Japan and a fuzzy controlled in-
telligent robot. This seminar will include illustrations of these
systems.
An abstract of the talk will be sent-out as soon as its received.
Time: 2:00 -- 3:30 p.m.
Date: Nov. 5, 1987
Place: Conf. room 103, Buliding 244
Inquires: Hamid Berenji, (415) 694-6525, berenji%plu@ames-io.arpa
------------------------------
Date: Wed, 4 Nov 87 12:45:07 cst
From: stevens@anl-mcs.ARPA (Rick L. Stevens)
Subject: Conference - CADE-9 Automated Deduction
Final Call for Papers
9th International Conference on Automated
Deduction
May 23-26, 1988
CADE-9 will be held at Argonne National Laboratory (near
Chicago) in celebration of the 25th anniversary of the
discovery of the resolution principle at Argonne in the sum-
mer of 1963. Papers are invited in the following or related
fields:
Theorem Proving Logic Programming
Unification Deductive Databases
Term Rewriting ATP for Non-Standard Logics
Program Verification Inference Systems
The Program Committee consists of:
Peter Andrews Ewing Lusk
W.W. Bledsoe Michael MacRobbie
Alan Bundy Hans-Jorgen Ohlbach
Robert Constable Ross Overbeek
Seif Haridi William Pase
Larry Henschen Jorg Siekmann
Deepak Kapur Mark Stickel
Dallas Lankford Jim Williams
Jean-Louis Lassez
Papers are solicited in three categories:
Long papers: 20 pages, about 5000 words
Short papers: 10 pages, about 2500 words
Extended Abstracts of Working Systems: 2 pages
Problem sets: 5 pages
Long papers are expected to present substantial research
results. Short papers are a forum for briefer presentations
of the results of ongoing research. Extended abstracts are
descriptions of existing automated reasoning systems and
their areas of application. Problem sets should present a
complete, formal representation of some collection of
interesting problems for automated systems to attack. The
problems should currently unavailable in the existing
literature. Three copies should be sent to arrive before
November 23rd, 1987 to
Ewing Lusk and Ross Overbeek, chairmen
CADE-9
Mathematics and Computer Science Division
Argonne National Laboratory
9700 South Cass Avenue
Argonne, IL 60439
Schedule:
November 23, 1987: papers due
January 25, 1988: notification of authors
February 21, 1988: final manuscripts due
Questions should be directed to E. L. Lusk (lusk@anl-
mcs.arpa, phone 312-972-7852) or Ross Overbeek
(overbeek@anl-mcs.arpa, phone 312-972-7856)
------------------------------
Date: 5 November 1987, 17:09:31 EST
From: Bruce Shriver <SHRIVER@ibm.com>
Subject: Conference - HICSS-22 System Sciences
HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES
HICSS-22 SOFTWARE TRACK INTENT TO PARTICIPATE FORM
Twenty-Second Annual HICSS Conference
Jan. 3-6, 1989, Hawaii
GENERAL INFORMATION
HICSS provides a forum for the interchange of ideas, re-
search results, development activities, and applications
among academicians and practitioners in the information,
computing, and system sciences. HICSS is sponsored by the
University of Hawaii in cooperation with the ACM, the IEEE
Computer Society, and the Pacific Research Institute for In-
formation Systems and Management (PRIISM). HICSS-22 will
consist of tutorials, open forums, task forces, a distin-
guished lecturer series, and the presentation of accepted
manuscripts which emphasize research and development activ-
ities in software technology, architecture, decision support
and knowledge-based systems, emerging technologies and ad-
vanced applications. The best papers, selected by the pro-
gram committee in each of these areas, are given an award at
the meeting. There is a high degree of interaction and dis-
cussion among the conference participants as the meeting is
conducted in a workshop-like setting.
INSTRUCTIONS FOR SUBMITTING PAPERS
Manuscripts should be 22-26 typewritten, double-spaced pages
in length. Please do not send submissions that are signif-
icantly shorter or longer than this. Papers must not have
been previously presented or published, nor currently sub-
mitted for journal publication. Each manuscript will be put
through a rigorous refereeing process. Manuscripts should
have a title page that includes the title of the paper, full
name of its author(s), affiliation(s), complete physical and
electronic address(es), telephone number(s) and a 300-word
abstract of the paper.
DEADLINES FOR AUTHORS
o A 300-word abstract is due by March 1, 1988
o Feedback to author concerning abstract by March 31, 1988
o Six copies of the manuscript are due by June 6, 1988.
o Notification of accepted papers by September 1, 1988.
o Accepted manuscripts, camera-ready, are due by October
3, 1988.
DEADLINES FOR MINI-TRACK, SESSION, AND TASK-FORCE COORDINATORS
If you would like to coordinate a mini-track, session, or
task force, you must submit for consideration a 3 page ab-
stract in which you describe the topic you are proposing,
its timeliness and importance, and its treatment in recent
conferences and workshops before December 15, 1987.
PLEASE COMPLETE THE FOLLOWING FORM AND RETURN IT TO:
Bruce D. Shriver
HICSS-22 Conference Co-Chairman
and Software Technology Track Coordinator
IBM T. J. Watson Research Center
P.O. Box 704
Yorktown Heights, NY 10598
(914) 789-7626
CSnet: shriver@ibm.com
Bitnet: shriver@yktvmh
Name ______________________________________________________
Address: ______________________________________________________
City: ______________________________________________________
Phone No. ______________________________________________________
Electronic Mail Address: _______________________________________
I would like to coordinate a mini-track or session in:
I would like to coordinate a task-force in:
I will submit a paper in:
I will referee papers in:
___ ___ ___ ___ Algorithms, Their Analysis and Pragmatics
___ ___ ___ ___ Alternative Language and Programming Paradigms
___ ___ ___ ___ Applying AI Technology to Software Engineering
___ ___ ___ ___ Communication & Protocol Software Issues
___ ___ ___ ___ Database Formalisms, Software and Systems
___ ___ ___ ___ Designing & Prototyping Complex Systems
___ ___ ___ ___ Distributed Software Systems
___ ___ ___ ___ Electronic Publishing & Authoring Systems
___ ___ ___ ___ Language Design & Language Implementation Technology
___ ___ ___ ___ Models of Program and System Behavior
___ ___ ___ ___ Programming Supercomputers & Massively Parallel Systems
___ ___ ___ ___ Reuseability in Design & Implementation
___ ___ ___ ___ Software Design Tools/Techniques/Environments
___ ___ ___ ___ Software Related Social and Legal Issues
___ ___ ___ ___ Testing, Verification, & Validation of Software
___ ___ ___ ___ User Interfaces
___ ___ ___ ___ Workstation Operating Systems and Environments
___ ___ ___ ___ Other ______________________________
------------------------------
End of AIList Digest
********************
∂09-Nov-87 0258 LAWS@KL.SRI.Com AIList V5 #262 - Neuromorphics, Speech Recognition, Goals
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 9 Nov 87 02:57:54 PST
Date: Sun 8 Nov 1987 23:19-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #262 - Neuromorphics, Speech Recognition, Goals
To: AIList@SRI.COM
AIList Digest Monday, 9 Nov 1987 Volume 5 : Issue 262
Today's Topics:
Queries - Michael O. Rabin & Blackboard Sources & AI Programming Texts,
Neuromorphic Systems - Shift-Invariant Neural Nets for Speech Recognition,
Msc. - Indexing Schemes,
Applications - Speech Recognition,
Comments - Goal of AI & Humanist, Physicist, and Symbolic Models of the Mind
----------------------------------------------------------------------
Date: Thu, 5 Nov 87 08:56 EST
From: Araman@BCO-MULTICS.ARPA
Subject: Michael O. Rabin - location
One of my friends sent me this message. If anyone knows Mr. Rabin, or
if Mr. Rabin is reading this message, could you please send a response
to
Bensoussan -at BCO-Multics.ARPA
thanks
#1 (14 lines in body): Date: Wednesday, 4 November 1987 10:03 est
From: Bensoussan Subject: Michael O. Rabin To: Araman
Does anyone know Michael O. Rabin's address? An AI award is waiting
for him!
A friend of mine, Monica Pavel, asked me to find him. My friend teaches
a class on Pattern Recognition at Paris University, and she gave several
classes and presentations in Japan. The Japanese government decided to
maake an AI award available and asked her to select the person who
should receive it. Since she was impressed by one of Rabin's
publications, she selected him to receive the award,...that is, if she
can find him.
Can anyone in the AI community help locate him?
------------------------------
Date: 6 Nov 87 23:46:39 GMT
From: teknowledge-vaxc!jlevy@beaver.cs.washington.edu (sleeze hack)
Subject: Shopping list of sources wanted
I'm looking for the following:
1. Sample black board systems
Ideally, small black board systems written using a black board
tool of some kind, but no examples refused! I'd like these to
use as test cases for various black board work I do. The only
good examples I've seen are the two "AGE Example Series" by
Nii & Co. at Stanford's HPP.
2. A frame system in C (or maybe PASCAL)
Something like a C translation of the PFL code published in AI
EXPERT, Dec. 1986 by Finin.
3. A yacc grammer for english or any subset of english
If someone has yaccized Tomita's "Efficient Parsing for Natural
Language" that would be ideal.
These are in order of importance. I might be willing to pay for the
sample black board systems. I'm posting this to comp.source.wanted and
comp.ai because I think it belongs in both, and there is minimal overlap
in readership between the two. If I'm wrong, sorry.
Thanks in advance.
Name: Joshua Levy (415) 424-0500x357
Disclaimer: Teknowledge can plausibly deny everything.
Pithy Quote: "Give me action, not words."
jlevy@teknowledge-vaxc.arpa or {uunet|sun|ucbvax}!jlevy%teknowledge-vaxc.arpa--
Name: Joshua Levy (415) 424-0500x357
Disclaimer: Teknowledge can plausibly deny everything.
Pithy Quote: "You're just a bunch of CYNIX"
jlevy@teknowledge-vaxc.arpa or {uunet|sun|ucbvax|decwrl}!jlevy%teknow...
------------------------------
Date: 6 Nov 87 18:01:05 GMT
From: aplcen!jhunix!apl_aimh@mimsy.umd.edu (Marty Hall)
Subject: AI Programming texts?
I am teaching an AI Programming course at Johns Hopkins this coming
semester, and was wondering if there were any suggestions for texts
from people that have taught/taken a similar course. The course
will be using Common LISP applied to AI Programming problems. The
students have an Intro AI course as a prereq, and have only mild
exposure to LISP (Franz) at the end of that course. Both the
AI Programming course and the Intro are supposed to be graduate
level, but would probably be undergrad level in the day school.
My thoughts so far were to use the second edition of Charniak,
Riesbeck, etc's "Artificial Intelligence Programming", along with
"Common LISPCraft" (Wilensky). Steele (CLtL) will be included
as an optional reference.
Any alternate suggestions? Send E-mail, and if there is a consensus,
I would be glad to post it to the net.
Thanks!
- Marty Hall
hall@hopkins-eecs-bravo.arpa
------------------------------
Date: Fri, 30 Oct 87 20:31:32+0900
From: kddlab!atr-la.atr.junet!waibel@uunet.UU.NET (Alex Waibel)
Subject: Shift-Invariant Neural Nets for Speech Recognition
A few weeks ago, there was a discussion on AI-list, about connectionist
(neural) networks being afflicted by an inability to handle shifted patterns.
Indeed, shift-invariance is of critical importance to applications such as
speech recognition. Without it a speech recognition system has to rely
on precise segmentation and in practice reliable errorfree segmentation
cannot be achieved. For this reason, methods such as dynamic time warping
and now Hidden Markov Models have been very successful and achieved high
recognition performace. Standard neural nets have done well in speech
so far, but due to this lack of shift-invariance (as discussed on AI-list
a number of these nets have been limping along in comparison to these other
techniques.
Recently, we have implemented a time-delay neural network (TDNN) here at
ATR, Japan, and demonstrate that it is shift invariant. We have applied
it to speech and compared it to the best of our Hidden Markov Models. The
results show, that its error rate is four times better than the best of our
Hidden Markov Models.
The abstract of our report follows:
Phoneme Recognition Using Time-Delay Neural Networks
A. Waibel, T. Hanazawa, G. Hinton↑, K. Shikano, K.Lang*
ATR Interpreting Telephony Research Laboratories
Abstract
In this paper we present a Time Delay Neural Network (TDNN) approach
to phoneme recognition which is characterized by two important
properties: 1.) Using a 3 layer arrangement of simple computing
units, a hierarchy can be constructed that allows for the formation
of arbitrary nonlinear decision surfaces. The TDNN learns these
decision surfaces automatically using error backpropagation.
2.) The time-delay arrangement enables the network to discover
acoustic-phonetic features and the temporal relationships between
them independent of position in time and hence not blurred by
temporal shifts in the input.
As a recognition task, the speaker-dependent recognition of the
phonemes "B", "D", and "G" in varying phonetic contexts was chosen.
For comparison, several discrete Hidden Markov Models (HMM) were
trained to perform the same task. Performance evaluation over 1946
testing tokens from three speakers showed that the TDNN achieves a
recognition rate of 98.5 % correct while the rate obtained by the
best of our HMMs was only 93.7 %. Closer inspection reveals that
the network "invented" well-known acoustic-phonetic features (e.g.,
F2-rise, F2-fall, vowel-onset) as useful abstractions. It also
developed alternate internal representations to link different
acoustic realizations to the same concept.
↑ University of Toronto
* Carnegie-Mellon University
For copies please write or contact:
Dr. Alex Waibel
ATR Interpreting Telephony Research Laboratories
Twin 21 MID Tower, 2-1-61 Shiromi, Higashi-ku
Osaka, 540, Japan
phone: +81-6-949-1830
Please send Email to my net-address at Carnegie-Mellon University:
ahw@CAD.CS.CMU.EDU
------------------------------
Date: 5 Nov 87 17:11:52 GMT
From: dbrauer@humu.nosc.mil (David L. Brauer)
Reply-to: dbrauer@humu.nosc.mil (David C. Brauer)
Subject: Indexing Schemes
In regards to the recent request for keyword/indexing schemes for AI
literature, look up the April 1985 issue of Applied Artificial Intelligence
Reporter. It contains an article describing the AI classification scheme
used by Scientific DataLink when compiling their collections of research
reports.
------------------------------
Date: Fri, 6 Nov 87 10:29:44 EST
From: hafner%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: Practical effects of AI
In AIList V5 #255 Bruce Kirby asked what practical effects AI will have
in the next 10 years, and how that will affect society, business, and
government.
One practical effect that I expect to see is the integration of logic
programming with database technology, producing new deductive databases
that will replace traditional databases. (In my vision, in 15 years
no one will want to buy a database management system that does not support
a prolog-like data definition and query language.)
David D. H. D. Warren wrote a paper on this in the VLDB conference in 1981,
and the database research community is busy trying to work out the details
right now. Of course, the closer this idea comes to a usable technology,
the less AIish it seems to many people.
I can speculate on how this will affect society, business, and government:
it will make many new applications of databases possible, for management,
manufacturing, planning, etc. Right now, database technology is
very hard to use effectively for complex applications. (Many application
projects are never successfully completed - they are crushed by the complexity
of getting them working right. Ordinary programmers simply can't hack
these applications, and brilliant programmers don't want to.)
Deductive databases will be so much easier to create, maintain and use, that
computers will finally be able to fulfill their promise of making
complex organizations more manageable. White collar productivity will
be improved beyond anyone's current expectations.
A negative side effect of this development (along with personal computers
and office automation) will be serious unemployment in the white collar
work force. The large administrative and middle management work force
will shrink permanently, just as the large industrial work force has.
All of the above, of course, is simply an opinion, backed up by (hopefully)
common sense.
Carole Hafner
csnet: hafner@northeastern.edu
------------------------------
Date: 8 Nov 87 17:14:19 GMT
From: PT.CS.CMU.EDU!SPEECH2.CS.CMU.EDU!kfl@cs.rochester.edu (Kai-Fu
Lee)
Subject: Re: Practical effects of AI (speech)
In article <930001@hpfcmp.HP.COM>, gt@hpfcmp.HP.COM (George Tatge) writes:
> >
> >(1) Speaker-independent continuous speech is much farther from reality
> > than some companies would have you think. Currently, the best
> > speech recognizer is IBM's Tangora, which makes about 6% errors
> > on a 20,000 word vocabulary. But the Tangora is for speaker-
> > dependent, isolate-words, grammar-guided recognition in a benign
> > environment. . . .
> >
> >Kai-Fu Lee
>
> Just curious what the definition of "best" is. For example, I have seen
> 6% error rates and better on grammar specific, speaker dependent, continuous
> speech recognition. I would guess that for some applications this is
> better than the "best" described above.
>
"Best" is not measured in terms of error rate alone. More effort and
new technologies have gone into the IBM's system than any other system,
and I believe that it will do better than any other system on a comparable
task. I guess this definition is subjective, but I think if you asked other
speech researchers, you will find that most people believe the same.
I know many commercial (and research) systems have lower error rates
than 6%. But you have to remember that the IBM system works on a 20,000
word vocabulary, and their grammar is a very loose one, accepting
arbitrary sentences in office correspondences. Their grammar has a
perplexity (number of choices at each decision point, roughly speaking)
of several hundred. Nobody else has such a large vocabulary or such
a difficult grammar.
IBM has experimented with tasks like the one you mentioned. In 1978,
they tried a 1000-word task with a very tight grammar (perplexity = 5 ?),
the same task CMU used on Hearsay and Harpy. They achieved 0.1% error
rate.
> George (floundering in superlative ambiguity) Tatge
Kai-Fu Lee
------------------------------
Date: 29 Oct 87 14:22:46 GMT
From: clyde!watmath!utgpu!utcsri!utegc!utai!murrayw@rutgers.edu
(Murray Watt)
Subject: Re: Goal of AI: where are we going? (the right way?)
In article <2072@cci632.UUCP> mdl@cci632.UUCP (Michael Liss) writes:
.
.
>I read an interesting article recently which had the title:
>"If AI = The Human Brain, Cars Should Have Legs"
>
>The author's premise was that most of our other machines that mimic human
>abilites do not do so through strict copying of our physical processes.
>
>What we have done, in the case of the automobile, is to make use of wheels and
>axles and the internal combustion engine to produce a transportation device
>which owes nothing tothe study of human legs.
>
>In the case of AI, he state that artificial intelligence should not be
>assumed to be the equivalent of human intelligence and thus, the disection of
>the human mind's functionality will not necessarily yield a solution to AI.
>
"THE USE AND MISUSE OF ANALOGIES"
Transporation (or movement) is not a property unique to human beings.
If one were to refine the goal better, the analogy flips sides.
If the goal is to design a device that can climb rocky hills it may
have something like legs. If the goal is to design a device that can
fly it may have something like wings. (Okay so there not the same type of
wings, but what about streamlining?)
AS I UNDERSTAND IT, one goal of AI is to design systems that perform well
in areas that the human brain performs well. Current computer systems can do
things (like add numbers) better than we can. I would not suggest creating
an A.I. system for generating telephone bills! However, don't tell me
that understanding the human brain doesn't tell me anything about natural
language!
The more analogies I see the less I like them. However, they seem handy to
convince the masses of completely false doctrines.
e.g. "Jesus accepted food and shelter from his friends, so sign over
your paycheck to me." (I am waiting Michael) 8-)
Murray Watt (murrayw@utai.toronto.edu)
The views of my colleagues do not necessarily reflect my opinions.
------------------------------
Date: Fri, 6 Nov 87 02:44:05 PST
From: larry@VLSI.JPL.NASA.GOV
Subject: Success/Future of AI
NATURAL ENTITIES AS PROTOTYPES
Much of the confusion about the nature of intelligence seems to
be the result of dealing with it at abstraction levels that are
too low.
At a low level of detail an aircraft is obviously drastically
different from a bird, leading to the conclusion that a study of
birds has no relevance to aeronautical science. At a higher
level the relevance becomes obvious: air-flow over the chord of
birds' and aircrafts' wings produces lift in exactly the same
way. Understanding this process was crucial to properly
designing the first aircrafts' wings.
Once the basic form+function was understood engineers could
produce articial variations that surpassed those found in
nature--though with numerous trade-offs. Construction and repair
of artifical wings, for instance, are much more labor- and
capital-intensive.
Understanding birds' wings helped in other ways. Analytically
separating the lift and propulsion functions of wings allowed us
to create jet aircraft; combining them in creative ways gave us
rocket-ships (where propulsion IS lift) and helicopters.
THE NATURE OF INTELLIGENCE
The understanding of intelligence is less advanced than that of
flight, but some progress HAS been made. The quotes from Robert
Frost illuminate the basic nature of intelligence: creation,
exploration, and manipulation within an entity of a model of the
Universe. He labels this model and its parts "metaphor." I
prefer "analog."
The mechanism that holds the analog we call memory. Though low-
level details (HOW memory works) are important, it is much more
important to first understand WHAT memory does. For instance,
there is a lot of evidence that there are several kinds of
memory, describable along several dimensions. One dimension,
obviously, is time.
This has a number of consequences that have nothing to do with,
for instance, the fact that deci-second visual memory works via
interactions of photons with visual purple. Eyes that used a
different storage mechanism but had the same black-box
characteristics (latency, bandwidth, communication protocol,
etc.) would present the same image to their owner.
One consequence of the time dimension of human memory is that
memory decays in certain ways. Conventionally memory units that
do not forget are considered good, yet forgetting is as important
as retention. Forgetting emphasizes the important by hiding the
unimportant; it supports generalization because essential
similarities are not obscured by inessential differences.
MECHANICAL NATURE OF INTELLIGENCE
There have been other real advances in scientifically understand-
ing intelligence, but I believe the above is enough to convince
the convincable. As to whether human intelligence is
mechanical--this depends on one's perception of machines. When
the word is used as an insult it usually calls up last-century
paradigms: the steam engine and other rigid, simple machines. I
prefer to think of the human hand, which can be soft and warm, or
the heart, which is a marvel of reliability and adaptibility.
Scientific models of the mind can (and to be accurate, must) use
the more modern "warmware" paradigm rather than the idiotic hand-
calc simplicity of Behaviorism. One example is my memory-mask
model of creativity (discussed here a year ago).
ART AND INTELLIGENCE
The previous comments have (I perhaps naively believe) a direct
relevance to the near-future of AI. That can't be said of this
last section but I can't resist adding it. Though professionally
a software engineer, I consider myself primarily an artist (in
fiction-writing and a visual media). This inside view and my
studies has convinced me over the years that art and cognition
are much closer than is widely recognized.
For one thing, art is as pervasive in human lives as air--though
this may not be obvious to those who think of haut cultur when
when they see/hear the word. Think of all the people in this
country who take a boombox/Walkman/stereo with them wherever they
stroll/jog/drive. True, the sound-maker often satisfies because
it gives an illusion of companionship, but it is more often
simply hedonically satisfying--though their "music" may sound
like audio-ordure to others. Think of all the doodling people
do, the small artworks they make (pastries, knitting, sand-
castles, Christmas trees, candy-striped Camaros), the photos
and advertising posters they tape to walls.
Art enhances our survival and evolution as a species, partly
because it is a source of pleasure that gives us another reason
for living. It also has intellectual elements. Poetic rules are
mnemonic enhancers, as all know who survived high-school English,
though nowadays these rules most often are used in prose and so
reflexively they aren't recognized even by their users.
Artistic rules are also cognitive enhancers. One way they do
this is with a careful balance of predictibility and surprise;
regularity decreases the amount of attention needed to remember
and process data, discontinuities shock us enough to keep us
alert. Breaks can also focus attention where an artist
desires.
Larry @ jpl-vlsi
------------------------------
Date: Fri 6 Nov 87 12:47:35-EST
From: Albert Boulanger <ABOULANGER@G.BBN.COM>
Subject: Humanist, Physicist, and Symbolic Models of the Mind
Pat Hayes puts forth the view that the symbolic computational
model of the mind can bridge the gap between science and a
humanistic outlook. I see a FURTHER exciting bridge being
built that is actually more pervasive that just models of the
mind. Why should the physicist model of the mind be any
different than what one does when building models that use
symbolic representations? The answer to this question being
"NO!" is becoming clear. There is a profound change happening
in the natural sciences; we are accepting non-linear phenomena
for what it is. Amazing behavior occurs with non-linear
dynamical systems. Behavior that is changing the way one views
the world as simple rules with followable outcomes. We know know
that we can have simple rules with amazingly complex behavior.
Deterministic randomness sounds contradictory at first, but is a
concept that non-linear phenomena is forcing us to accept. The
manifold emergent phenomena in non-linear systems, including
self-organization, is a humbling experience. It is the setting
where we can see emergent symbolic representations. This should
not be too surprising, since we build computers to host
computational models of the mind using symbolic representations
with a very restrictive class of non-linear switching circuits.
Albert Boulanger
BBN Labs
------------------------------
End of AIList Digest
********************
∂09-Nov-87 0624 LAWS@KL.SRI.Com AIList V5 #263 - Methodology, FORTRAN
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 9 Nov 87 06:24:35 PST
Date: Sun 8 Nov 1987 23:57-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #263 - Methodology, FORTRAN
To: AIList@SRI.COM
AIList Digest Monday, 9 Nov 1987 Volume 5 : Issue 263
Today's Topics:
Comments - NP Completeness & Research Methodology & AI Languages
----------------------------------------------------------------------
Date: 5 Nov 87 14:31:12 GMT
From: eitan%WISDOM.BITNET@wiscvm.wisc.edu (Eitan Shterenbaum)
Reply-to: eitan%H@wiscvm.arpa (Eitan Shterenbaum)
Subject: Re: Success of AI
In article <> honavar@speedy.wisc.edu (A Buggy AI Program) writes:
>
>Discovering that a problem is NP-complete is usually just the
>beginning of the work on the problem. The knowledge that a problem is
>NP-complete provides valuable information on the lines of attack that
>have the greatest potential for success. We can concentrate on algorithms
>that are not guaranteed to run in polynomial time but do so most
>of the time or those that give approximate solutions in polynomial time.
>After all, the human brain does come up with approximate (reasonably good)
>solutions to a lot of the perceptual tasks although the solution may not
>always be the best possible. Knowing that a problem is NP-complete only
>tells us that the chances of finding a polynomial time solution are minimal
>(unless P=NP).
>
You are right and so am I,
a) There're no polynomial algorithms, which are known to us, that can
solve NP problems.
b) There are approximate and probabilistic *partial* solutions for NP
problems.
As to the claim "the brain does it so why shouldn't the computer" -
It seem to me that you forget that the brain is built slightly differently
than a Von-Neuman machine ... It's a distributed enviorment lacking boolean
algebra. I can hardly believe that even with all the partial solutions for
all the complicated sets of NP problems that emulating a brain brings up, one
might be able to present a working program. If you'd able to emulate mouse's
brain you'd become a legend in your lifetime !
Anyway, no one can emulate a system which has no specifications.
if the neuro-biologists would present them then you'd have something to start
with.
And last - Computers aren't meta-capable machines they have constraints,
not every problem has an answer and not every answermakes sense,
NP problems are the best example.
Eitan Shterenbaum
------------------------------
Date: Tue, 03 Nov 87 07:57:49 PST
From: Stephen Smoliar <smoliar@vaxa.isi.edu>
Reply-to: smoliar@vaxa.isi.edu.UUCP (Stephen Smoliar)
Subject: Re: Gilding the Lemon
In article <12346288066.15.LAWS@KL.SRI.Com> Laws@KL.SRI.COM (Ken Laws) writes:
>
>Progress also comes from applications -- very seldom from theory.
A very good point, indeed: Bill Swartout and I were recently discussing
the issue of the respective contributions of engineering and science.
There is a "classical" view that science is responsible for those
fundamental principles without which engineering could "do its thing."
However, whence come those principles? If we look at history, we see
that, in most fields, engineers are "doing their thing" long before
science has established those principles. Of course things don't always
go as smoothly as one would like. This pre-scientific stage of engineering
often involves sometimes-it-works-sometimes-it-doesn't experiences; but
the engineering practices are still useful. Often a major contribution
of the discovery of the underlying scientific principles is a better
understanding of WHEN "it doesn't work" and WHY that is so. Then
engineering takes over again to determine what is to be done about
those situations in which things don't work. At the risk of being
called on too broad a generality, I would like to posit that science
is concerned with the explanation of observed phenomena, while engineering
is concerned with achieving phenomena with certain desired properties.
From this point of view, engineering provides the very substance from
which scientific thought feeds.
I fear that what is lacking in the AI community is a respect for the
distinction between these two approaches. A student is likely to get
a taste of both points of view in his education, but that does not
necessarily mean that he will develop an appreciation for the merits
of each or the ways in which they relate to each other. As a consequence,
he may very well become very quickly channeled along a narrow path
involving the synthesis of some new artifact. If he has any form
of success, then he assumes that all his thesis requires is that he
write up his results.
I hope there is some agreement that theses which arise from this process
are often "underwhelming" (to say the least). There are usually rather
hefty tomes which devote significant page space to the twists and turns
in the path that leads to the student's achievement. There is also usually
a rather heavy chapter which surveys the literature, so that the student
can demonstrate the front along which his work has advanced. However,
such retrospective views tend to concentrate more on the artifacts of
the past than on the principles behind those artifacts.
Is it too much to ask that doctoral research in AI combine the elements
of both engineering and science? I have nothing against that intensely
focused activity which leads up to a new artifact. I just worry that
students tend to think the work is done once the artifact is achieved.
However, this is the completion of an engineering phase. Frustrating
as it may sound, I do not think the doctoral student is done yet. He
should now embark upon some fundamental portion of a scientific phase.
Now that he has something that works, he should investigate WHY it
works; and THIS is where the literature search should have its true
value. Given a set of hypothesized principles regarding the behavior
of his own artifact, how applicable are those principles to those
artifacts which have gone before? Once such an investigation has been
pursued, the student can write a thesis which provides a balanced diet
of both engineering and science.
------------------------------
Date: 3 Nov 87 18:31:13 GMT
From: gary%roland@sdcsvax.ucsd.edu (Gary Cottrell)
Reply-to: roland!gary@sdcsvax.ucsd.edu (Gary Cottrell)
Subject: Re: Gilding the Lemon
Note that the article Tom was referring to (David Chapman's "Planning
for Conjunctive Goals", AIJ 32 No. 3) is based on a MASTER's Thesis:
Even if Ken objects to PhD thesi being rational reconstructions, he may
be less inclined to object to Master's thesi in this vein. Of course,
this is probably equivalent to a PhD thesis at n-k other places, where
k is some small integer.
gary cottrell
cse deot
ucsd
------------------------------
Date: 5 Nov 87 17:13:39 GMT
From: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@uunet.uu.net>
Reply-to: Gilbert Cockton <mcvax!hci.hw.ac.uk!gilbert@uunet.uu.net>
Subject: Re: Gilding the Lemon
In article <12346288066.15.LAWS@KL.SRI.Com> Laws@KL.SRI.COM (Ken Laws) writes:
>......, but there has been more payoff from GPSS and SIMSCRIPT (and
>SPICE and other simulation systems)
e.g.?
>Most Ph.D. projects have the same flavor. A student ...
>... publishes the interesting behaviors he was able to generate
e.g.?
> ... we must build hand-crank phonographs before inventing information
>theory and we must study the properties of atoms before debating
>quarks and strings.
Inadmissable until it can be established that such relationships exist
in the study of intelligence - there may be only information theory
and quarks, in which case you have to head right for them now.
Anything else is liable to be a social construct of limited generality.
Most work today in fact suggests that EVERYTHING is going to be a social
construct, even the quarks. Analogies with the physical world do not
necessarily hold for the mental world, anymore than does animism for the
physical world.
>An advisor who advocates duplicating prior work is cutting his
>students' chances of fame and fortune from the discovery of the
>one true path. .... Why should the student
>work (be they theoretical or practical problems) when he could
>attach his name to an entirely new approach?
The aim of PhD studies is to advance knowledge, not individuals.
This amounts to gross self-indulgeance where I come from. I recognise
that most people in AI come from somewhere else though :-)
Perhaps there are no new approaches, perhaps the set of all imaginable
metaphysics, epistemology and ontology is closed. In the History of
Ideas, one rarely sees anything with no similar antecedents. More
problematic for AI, the real shifts of thinkers like Machiavelli, Bacon,
Hume, Marx and Freud did not involve PhD studies centred on computer
programming. I really do think that the *ABSENCE* of a computer is more
likely to produce new approaches, as the computational paradigm
severely limits what you can do, just as the experimental paradigm of
psychology puts many areas of study beyond the pale.
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
------------------------------
Date: Fri, 6 Nov 87 15:32:30 WET
From: Martin Merry <mjm%hplb.csnet@RELAY.CS.NET>
Reply-to: Martin Merry <mjm%hplb.csnet@RELAY.CS.NET>
Subject: FORTRAN
After the recent discussion on AIList I feel compelled to admit that I wrote
the entry on FORTRAN for the Catalogue of AI techniques, and that it was
roginally intended as a joke.
However, after subsequent exposure to Common Lisp, I'm not so sure....
Martin Merry
HP Labs Bristol Research Centre
------------------------------
Date: 05 Nov 87 12:03:55 EST (Thu)
From: sas@bfly-vax.bbn.com
Subject: FORTRAN for list processing
Check out Douglas K. Smith's article: An Introduction to the
List-Processing Language SLIP (anthologized in Rosen's 1960's classic
Programming Systems and Languages).
SLIP is a list processing language system distinguished by the
symmetry of its lists; each element is linked to both its
predecessor and its successor. It differs from most list
processing languages in that it does not prepresent an
independent language, but is intended to be embedded in a
general purpose [sic] language such as FORTRAN. Thus the
flexibility of the latter is combined with the specific
facility for manipulating lists. This paper will describe
SLIP as embedded in FORTRAN IV.
SLIP was developed by Professor Joseph Weizenbaum of MIT.
His original paper [1], published in 1963 while he was at
General Electric, presents a complete documentation of the
system, including a FORTRAN listing and a statement of the
underlying philosophy. The system has been implemented at
several installations, find application in the symbolic
manipulation of algebraic expressions [2], [3], [4], and in
other areas [5].
[1] Weizenbaum, J.: Symmetric List Processor, Comm. ACM, p 524,
Sept 1963
[5] Weizenbaum, J.: ELIZA - A Computer Program for the Study of Natural
Language Communication Between Man and Machine, Comm. ACM,
p 36, Jan 1966
Gee - I've even heard of ELIZA!
Seth
------------------------------
Date: 5 Nov 87 09:46:20 est
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: In Defense of FORTRAN
In any discussion where C and Fortran are defended as languages
for doing AI, if only they provided the constructs that Lisp and
Prolog already provide, I am reminded of the old Yiddish saying
(here poorly transliterated) ``Wenn mein Bubba zul huben
Bietzem, vol tzi gevain mein Zayda.'' Or, loosely, ``IF is a
big word.''
Date: Mon 2 Nov 87 14:29:09-PST
From: Ken Laws <LAWS@IU.AI.SRI.COM>
* * *
The problem with AI languages is neither their capability nor
their efficiency, but the way that they limit thought. * * *
Exactly so. Using Fortran or any language where you have to
spend mental energy thinking about the issues that Lisp and
Prolog already handle ``cuts your chances of fame and fortune
from the discovery of the one true path,'' to quote an earlier
contributor. Fortran's a fine language for writing programs
where the problem is well understood, but it's just a lousy
language for tackling new problems in. This doesn't just go for
academic research, either; same goes for doing applications that
have never been tackled before.
------------------------------
Date: Thu 5 Nov 87 08:55:59-PST
From: Ken Laws <LAWS@IU.AI.SRI.COM>
Subject: Re: In Defense of FORTRAN
Good points.
I happen to program in C and have built a software environment that
does provide many of the capabilities of LISP. It has taken me many
years, and I would not recommend that others follow this path.
My real point, though, was that LISP and PROLOG are also at too low
a level. The Lisp Machine environment, with its 10,000 predefined
functions, is a big factor in the productivity of LISP hackers. If
similar (or much better!) libraries were available to FORTRAN hackers,
similar productivity would be observed. LISP does permit many clever
programming techniques, as documented in Abelson and Sussman's book,
but a great deal can be done with the simple conditionals, loops,
and other control structures of a language like FORTRAN.
The AI community is spending too much time reprogramming graph search
algorithms, connected-component extraction, cluster analysis, and
hundreds of other solved problems. Automated programming isn't coming
to our rescue. As Fred Brooks has pointed out, algorithm development
is one of the most intricate, convoluted activities ever devised;
software development tools are not going to make the complexities
vanish. New parallel architectures will tempt us toward brute-force
solutions, ultimately leaving us without solutions. It's time we
recognize that sharable, documented subroutine libraries are essential
if AI programs are ever to be developed for real-world problems.
Such subroutines, which I envision in an object-oriented style, should
be the language of AI. Learned papers would discuss improvements to the
primitive routines or sophisticated ways of coordinating them, seldom
both together -- just as an earlier generation separated A* and
garbage collection. This would make it easier for others to repeat
important work on other computer systems, aiding scientific verification
and tech transfer as well as facilitating creativity.
-- Ken Laws
[This applies particularly in my own field of computer vision, where many
graduate students and engineers spend years reinventing I/O code, display
drivers, and simple image transformations. Trivial tasks such as mapping
buffers into display windows cease to be trivial if attempted with any
pretense to generality. Code is not transportable and even images are
seldom shared. The situation may not be so bad in mainstream AI research,
although I see evidence that it is.]
------------------------------
End of AIList Digest
********************
∂09-Nov-87 1128 LAWS@KL.SRI.Com AIList Digest V5 #264
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 9 Nov 87 11:27:50 PST
Date: Mon 9 Nov 1987 00:01-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #264
To: AIList@SRI.COM
AIList Digest Monday, 9 Nov 1987 Volume 5 : Issue 264
Today's Topics:
Bibliography - Leff File a62C
----------------------------------------------------------------------
Date: Thu, 5 Nov 1987 17:33 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Bibliography - Leff File a62C
%A E. Hudlicka
%A V. Lesser
%T Modeling and Diagnosing Problem-Solving System Behavior
%J MAG144
%P 407-419
%A J. L. Kolodner
%A R. M. Kolodner
%T Using Experience in Clinical Problem Solving: Introduction and Framework
%J MAG144
%P 420-431
%K AA01
%A B. Kuipers
%T Qualitative Simulation as Causal Explanation
%J MAG144
%P 432-444
%A J. R. Josephson
%A B. Chandrasekaran
%A J. R. Smith
%A M. C. Tanner
%J MAG144
%P 445-454
%A J. G. Witlink
%T A Deficiency of Natural Deduction
%J Information Processing Letters
%V 25
%N 4
%D JUN 17 1987
%P 233-234
%A D. G. Kouri
%T The Design and Use of a Prolog Trace Generator for CSP
%J Software Practice and Experience
%V 17
%N 7
%D JUL 1987
%P 423-438
%A M. Oyamaguchi
%T The church-Rosser Property for Ground Term-Rewriting Systems is Decidable
%J Theoretical Computer Science
%V 49
%N 1
%D 1987
%P 43-80
%A J. P. Delgrande
%T A Formal Approach to Learning From Examples
%J MAG145
%P 123-142
%A T. R. Gruber
%A P. R. Cohen
%T Design for Acquisition: Principles of Knowledge-System Design to Facilitate
Knowledge Acquisition
%J MAG145
%P 143-160
%A P. E. Johnson
%A I. Zaulkernan
%A S. Garbert
%T Specification of Expertise
%J MAG145
%P 161-182
%A C. M. Kitto
%A J. H. Boose
%T Heuristics for Expertise Transfer: An Implementation of a Dialog
Manager for Knowledge Acquisition
%J MAG145
%P 183-202
%A J. Kornell
%T Formal Thought and Narrative Thought in Knowledge Acquisition
%J MAG145
%P 203-212
%A E. A. Moore
%A A. M. Agogino
%T Inform: An Architecture for Expert-Directed Knowledge Acquisition
%J MAG145
%P 213-230
%A T. Bylander
%A B. Chandrasekaran
%T Generic Tasks for Knowledge-Based Reasoning: the "Right" Level of
Abstraction for Knowledge Acquisition
%J MAG145
%P 231-244
%K AI01
%A M. LaFrance
%T The Knowledge Acquisition Grid: A Method for Training Knowledge Engineers
%J MAG145
%P 245-256
%K AI01
%A D. D. Woods
%A E. Holnagel
%T Mapping Cognitive Demands in Complex Problem-Solving Worlds
%J MAG145
%P 257
%A W. Bruce Croft
%T Approaches to Intelligent Information Retrieval
%J MAG149
%P 249-254
%K AA14
%A Paul R. Cohen
%A Rick Kjeldsen
%T Information Retrieval by Constrained Spreading Activation in Semantic
Networks
%J MAG149
%P 255-268
%K AI12 AA14
%A Lisa F. Rau
%T Knowledge Organization and Access in a Conceptual Information System
%J MAG149
%P 269-284
%K AI16 AA14
%A Y. Chiaramella
%A B. Defude
%T A Prototype of an Intelligent System for Information Retrieval: IOTA
%J MAG149
%P 285-304
%K AA14
%A Giorgia Brajnik
%A Giovanni Guida
%A Carlo Tasso
%T User Modeling in Intelligent Information Retrieval
%J MAG149
%P 305-320
%K AI08 AA15 AA14
%A Robert F. Simmons
%T A Text Knowledge Base from the AI Handbook
%J MAG149
%P 321-340
%K AA14
%A Edward A. Fox
%T Developments of the CODER System: A Testbed for Artificial Intelligence
Methods in Information Retrieval
%J MAG149
%P 341-366
%K AA14 AI02
%A H. M. Brooks
%T Expert Systems and Intelligent Information Retrieval
%J MAG149
%P 367-382
%K AA14 AI01 AT08
%A D. A. Pospelov
%T Artificial Intellect - A New Phase of Development
%J Vestnik Akademii Nauk SSSR
%N 4
%D 1987
%P 40-47
%K AI16
%X in Russian
%A J. Grobelny
%T The Fuzzy Approach to Facilities Layout Problems
%J Fuzzy Sets and Systems
%V 23
%N 2
%D AUG 1987
%P 175-190
%K O04 AA05
%A M. A. Gil
%A M. T. Lopez
%A J. M. A. Garrido
%T An Extensive-Form Analysis for Comparing Fuzzy Information Systems by
Means of the Worth and Quiteness of Information
%J Fuzzy Sets and Systems
%V 23
%N 2
%D AUG 1987
%P 239-256
%K O04
%A Christopher Hogger
%T Prolog and Software Engineering
%J Microprocessors and Microsystems
%V 11
%N 6
%D JUL-AUG 1987
%P 308-318
%K T02
%T Consistent Clustering - Analog of Physical Model for the Observation
Object in Fuzzy Language
%J Avtomatika
%N 3
%D MAY-JUN 1987
%P 89
%K O04 O06
%X Article in Russian, English Abstract Available
%A I. V. Blauberg
%A V. V. Klokov
%T Systems Studies and Organization of Knowledge
%J Cybernetics and Systems
%V 18
%N 3
%D 1987
%P 195-202
%K AI16
%A Avi Rushinek
%A Sara F. Rushinek
%T Interactive Diagnostic System for Insurance Software: An Expert
System Using Artificial Intelligence (ESAI)
%J Cybernetics and Systems
%V 18
%N 3
%D 1987
%P 203-220
%K AA06 AI01
%A A. Hoogewijs
%T Partial Predicate Logic in Computer Science
%J Acta Informatica
%V 24
%N 4
%D 1987
%P 381-394
%K AI10
%A D. Kapur
%A P. Narendran
%A H. Zhang
%T On Sufficient-Completeness and Related Properties of Term Rewriting
Systems
%J Acta Informatica
%V 24
%N 4
%D 1987
%P 395-416
%K AI14
%A Gerard Medioni
%A Yoshio Yasumoto
%T Corner Detection and Curve Representation Using Cubic B-Splines
%J MAG150
%P 267-278
%K AI06
%A R. S. Acharya
%A P. B. Heffernan
%A R. A. Robb
%A H. Wechsler
%T High Speed 3D Imaging of the Beating Heart Using Temporal Estimation
%J MAG150
%P 279-290
%K AI06 AA01
%A Glenn L. Cash
%A Mehdi Hatamian
%T Optical Character Recognition by the Method of Moments
%J MAG150
%P 291-310
%K AI06
%A Andrew B. Watson
%T The Cortex Transform: Rapid Computation of Simulated Neural Images
%J MAG150
%P 311-327
%K AI06 AI08
%A Ken-ichi Kanatani
%T Camera Rotation Invariance of Image Characteristics
%J MAG150
%P 328-354
%K AI06
%A Steven M. Pizer
%A E. Philip Amburn
%A John D. Austin
%A Robert Cromarti
%A Ari Geselowitz
%A Trey Greer
%A Bart ter Haar Romeny
%A John B. Zimmerman
%A Karel Zuiderveld
%T Adaptive Histogram Equalization and Its Variations
%J MAG150
%P 355-368
%K AI06
%A J. Michel Fitzpatrick
%A Michael R. Leuze
%T A Class of One-to-One Two-Dimensional Transformations
%J MAG150
%P 369-382
%K AI06
%A Hemraj Nair
%T Reconstruction of Planar Boundaries from Incomplete Information
%J MAG150
%P 383
%K AI06
%A D. L. Sanford
%A J. W. Roach
%T Representing and Using Metacommunication to Control Speakers Relationships
in Natural Language Dialog
%J MAG151
%P 301-320
%K AI02
%A W. Siler
%A D. tucker
%A J. Buckley
%T A Parallel Rule Firing Fuzzy Production System with Resolution of Memory
Conflicts by Weak Fuzzy Monotonicity, Applied to the Classification of
Multiple Objects Characterized by Multiple Uncertain Features
%J MAG151
%P 321-332
%K O04 AI01 H03
%A G. S. Pospelov
%T Expert Systems. Experience with Dynamic Description
%J Soviet Journal of Computer and Systems Sciences
%V 25
%N 1
%D JAN-FEB 1987
%P 80-84
%K AI01
%A Johnson Aimie Edosomwan
%T Artificial Intelligence, Part 7: Ten Design Rules for Knowledge
Based Expert Systems
%J Industrial Engineering
%V 19
%N 8
%D AUG 1987
%P 78-80
%K AI01
%A H. Samet
%A C. A. Shaffer
%A R. C. Nelson
%A Y. G. Huang
%A A. Rosenfeld
%T Recent Developments in Linear Quadtree-Based Geographic Information Systems
%J MAG152
%P 187-198
%K AI06 AI16
%A E. R. Davies
%T Design of Optimal Gaussian Operators in Small Neighborhoods
%J MAG152
%P 199-205
%K AI06
%A S. K. Morton
%A S. J. Popham
%T Algorithm Design Specification for Interpreting Segmented
Image Data Using Schemas and Support Logic
%J MAG152
%P 206-216
%K AI06
%A I. Overington
%A P. Greenway
%T Practical First-Difference Edge Detection with Subpixel Accuracy
%J MAG152
%P 217-224
%K AI06
%A E. W. Elcock
%A I. Gargantini
%A T. R. Walsh
%T Triangular Decomposition
%J MAG152
%P 225-232
%K AI06
%A M. J. L. Orr
%A R. B. Fisher
%T Geometric Reasoning for Computer Vision
%J MAG152
%P 233
%K AI06
%A Y. B. Mityushin
%A A. E. Petrov
%A P. K. Fadeev
%T Measure of Semantic Information in Documents and Databases
of Automated Information Systems
%J Nauchno-Tekhnicheskaya Informatsiya. Seirya II - Informatsionnye
Protessy I Systemy
%P 1-4
%N 6
%D 1987
%K AA14
%A G. G. Gyulnazaryn
%T Development of Vocal Input Subsystems in Automated Information Systems
%J Nauchno-Tekhnicheskaya Informatsiya. Seirya II - Informatsionnye
Protessy I Systemy
%P 14-16
%N 6
%D 1987
%K AI05 AA14
%A S. V. Kazmenko
%T Use of Standard Language in Conversatin with Computers - Pessimistic
Point of View
%J Nauchno-Tekhnicheskaya Informatsiya. Seirya II - Informatsionnye
Protessy I Systemy
%P 32
%N 6
%D 1987
%K AI02
%A A. A. Grandhee
%A R. A. Moczadlo
%T Expert System and Symbolic Processing for Automation
%J MAG153
%P 6-10
%K AA05 AI01
%A D. S. Watts
%A H. K. Eldin
%T The Role of the Industrial Engineer in Developing Expert Systems
%J MAG153
%P 15-20
%K AI01 AA05
%A D. J. Sumanth
%A M. Dedeoglu
%T Application of Expert Systems to Productivity Measurement in Companies
Organization
%J MAG153
%P 21-25
%K AI01 AA05
%A F. M. Lesusky
%A Rhudy, R. L.
%W Wiginton, J. C.
%T The Development of a Knowledge-Based System for Information Systems
Project Development
%J MAG153
%P 29-33
%K AA08
%A T. C. Chang
%A J. Terwilliger
%T PWA Planner - A Rule Based System for Printed Wiring Assemblies
Process Planning
%J MAG153
%P 34-38
%A J. Jiang
%A R. R. Doraiswami
%T A Novel Structure of Real-Time Expert Control System for Process
Industry
%J MAG153
%P 39-43
%K AA20 O03
%A G. Chen
%A M. H. Williams
%T Executing Pascal Programs on a Prolog Architecture
%J Information and Software Technology
%V 29
%N 6
%D JUL-AUG 1987
%P 285-290
%K T02
%A Georgios I. Doukidis
%T An Anthology on the Homology of Simulation with Artificial Intelligence
%J Journal of the Operational Research Society
%V 38
%N 8
%D AUG 1987
%P 701-712
%K AA28
%A Robert M. O'Keefe
%A John W. Roach
%T Artificial Intelligence Approaches to Simulation
%J Journal of the Operational Research Society
%V 38
%N 8
%D AUG 1987
%P 713-722
%K AA28
%A A. M. Flitman
%A R. D. Hurrion
%T Linking Discrete-Event Simulation Models to Expert Systems
%J Journal of the Operational Research Society
%V 38
%N 8
%D AUG 1987
%P 701-712
%K AA28 AI01
%A G. K. Kozhevnikov
%T Topological Design of Distributed Control Systems Using the Prolog
Programming Language
%J Avtomatika I. Vychislitelnaya Tekhnika
%N 3
%D MAY-JUN 1987
%P 3-5
%K H03 AA20 T02
%A A. F. Rocha
%T Editorial: The Fuzziness of Language and Cerebral Processings
%J MAG154
%P 301-302
%K AT22 AI08 O04
%A G. Burstein
%A M. D. Nicu
%A C. Balaceanu
%T Simplicial Differential Geometric Theory for Language Cortical Dynamics
%J MAG154
%P 303-314
%K O04 AI08 AA10
%A J. Mira
%A A. E. Delgado
%A R. Moreno-Diaz
%T The Fuzzy Paradigm for Knowledge Representation in Cerebral Dynamics
%J MAG154
%P 315-330
%K AA10 AI16 O04
%A M. Theoto
%A M. R. Santos
%A N. Uchiyama
%T The Fuzzy Decodings of Educative Texts
%J MAG154
%P 331-346
%K AI02 O04 AA07
%A G. Greco
%A A. F. Rocha
%T The Fuzzy Logic of Text Understanding
%J MAG154
%P 347-360
%K AI02 O04
%A L. Lesmo
%A P. Torasso
%T Prototypical Knowledge for Interpreting Fuzzy Concepts and Quantifiers
%J MAG154
%P 361-370
%K O04 AI16
%A F. Casacuberta
%A E. Vidal
%A J. M. Benedi
%T Interpretation of Fuzzy Data by Means of Fuzzy Rules with Applications to
Speech Recognition
%J MAG154
%P 371-380
%K AI05 O04
%A A. A. Mitchell
%T The Use of Alternative Knowledge-Acquisition Procedures in the Development
of a Knowledge-Based Media Planning System
%J MAG155
%P 399-412
%K AI01
%A M. J. Pazzani
%T Explanation-Based Learning for Knowledge-Based Systems
%J MAG155
%P 413-434
%K AI01 AI04
%A A. Rappaport
%T Multiple-Problem Subspaces in the Knowledge-Design Process
%J MAG155
%P 435-452
%K AI16
%A B. R. Gaines
%T An Overview of Knowledge-Acquisition and Transfer
%J MAG155
%P 453-472
%K AI16
%A J. H. Alexander
%A M. J. Freiling
%A S. J. Shulman
%A S. Rehfuss
%A S. L. Messick
%T Ontological Analysis - An Ongoing Experiment
%J MAG155
%P 473-486
%K AI16
%A S. A. Hayward
%A B. J. Wielinga
%A J. A. Breuker
%T Structured Analysis of Knowledge
%J MAG155
%P 487-498
%K AI16
%A W. Buntine
%T Induction of Horn Clauses - Methods and the Plausible Generation Algorithm
%J MAG155
%P 499-520
%K AI10 AI04
%A C. Gargjanardan
%A G. Salvendy
%T A Conceptual Framework for Knowledge Elicitation
%J MAG155
%P 521-532
%K AI16
%A N. M. Cooke
%A J. E. MacDonald
%T The Application of Psychological Scaling Techniques to Knowledge Elicitation
for Knowledge-Based Systems
%J MAG155
%P 533
%K AI16
%A Takashi Toriu
%A Hiromichi Iwase
%A Masumi Yoshida
%T An Expert System for Image Processing
%J Fujitsu Scientific and Technical Journal
%V 23
%N 2
%D SUMMER 1987
%P 111-118
%K AI01 AI06
%A J. G. Llaurado
%T Computerized Speech-Recognition and Conversation
%J International Journal of Bio-Medical Computing
%V 21
%N 2
%D SEP 1987
%P 77-82
%K AI05 AT22
%X (Commentary)
%A W. S. Lim
%A S. Vajpayee
%T Development of a Vision-Based Inspection System on a Micro-computer
%J Computers and Industrial Engineering
%V 12
%N 4
%D 1987
%P 315
%K AI06 H01
%A S. M. Alexander
%T The Application of Expert Systems to Manufacturing Processing Control
%J Computers and Industrial Engineering
%V 12
%N 4
%D 1987
%P 307-314
%K AI01 AA26 AA20
%A Michael P. Georgeff
%T Planning
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%I Annual Reviews, Inc.
%K AT08 AI09
%X ISBN 0-8243-3202-4
%A Charles Thorp
%A Martial Hebert
%A Takeo Kanade
%A Steven Shafer
%T Vision and Navigation for the Carnegie-Mellon Navlab
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%I Annual Reviews, Inc.
%K AI06 AT08 AI07
%X ISBN 0-8243-3202-4
%A Steven W. Zucker
%T The Emerging Paradigm of Computational Vision
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%I Annual Reviews, Inc.
%K AT08 AI06
%X ISBN 0-8243-3202-4
%A Judea Pearl
%A Richard Korf
%T Search Techniques
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%I Annual Reviews, Inc.
%K AI03 AT08
%X ISBN 0-8243-3202-4
%A Raymond Reiter
%T Nonmonotonic Reasoning
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%I Annual Reviews, Inc.
%K AI15 AT08
%X ISBN 0-8243-3202-4
%A Scott E. Fahlman
%T Common Lisp
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%I Annual Reviews, Inc.
%K AT08 T01
%X ISBN 0-8243-3202-4
%A Kathleen McKeown
%A William Swartout
%T Language Generation and Explanation
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%I Annual Reviews, Inc.
%K AI01 AT08
%X ISBN 0-8243-3202-4
%A Joseph Halpern
%T Using Reasoning about Knowledge to Analyze Distributed Systems
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%I Annual Reviews, Inc.
%K H03 AT08
%X ISBN 0-8243-3202-4
%A Drew McDermott
%T Logic, Problem Solving, and Deduction
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%I Annual Reviews, Inc.
%K AI16 AT08
%X ISBN 0-8243-3202-4
%A David R. Barstow
%T Knowledge-Based Software Tools
%B Annual Review of Computer Science
%V 2
%D NOV 1987
%E Joseph F. Traub
%K AA08 AT08
%I Annual Reviews, Inc.
%X ISBN 0-8243-3202-4
%A S. L. Hardt
%A D. H. MacFadden
%T Computer Assisted Psychiatric Diagnosis: Experiments in Software Design
%J Computers in Biology and Medicine
%V 17
%N 4
%D 1987
%P 229-238
%K AA11 AA01 AI01
%A F. Wiener
%A M. Gabbai
%A M. Jaffe
%T Computerized Classification of Congenital Malformations using a Modified
Bayesian Approach
%J Computers in Biology and Medicine
%V 17
%N 4
%D 1987
%P 259-268
%K AA01 AI01
%A W. M. Dong
%A F. S. Wong
%T Propagation of Evidence in Rules Based Ssytems
%J International Journal of Man-Machine Studies
%V 26
%N 5
%D MAY 1987
%P 551-566
%K O04 AI01
%A J. A. Landau
%A K. H. Norwich
%A S. J. Evans
%A B. Pich
%T An Error Correcting Protocol for Medical Expert Systems
%J International Journal of Man-Machine Studies
%V 26
%N 5
%D MAY 1987
%P 617-626
%A B. J. Cragun
%A H. J. Steudel
%T A Decision-Table-Used Processor for Checking Completeness and Consistency
in Rule Based Systems
%J International Journal of Man-Machine Studies
%V 26
%N 5
%D MAY 1987
%P 633
%A Michael Potmesil
%T Generating Octree Models of 3D Objects from Their Silhouettes
in a Sequence of Images
%J MAG156
%P 1-29
%K AI06
%A Roland T. Chin
%A Hong-Khoon Wan
%A D. L. Stover
%A R. D. Iverson
%T A One-Pass Thinning Algorithm and Its Parallel Implementation
%J MAG156
%P 30-40
%K AI06 H03
%A Hiromitsu Yamada
%A Tony Kasvand
%T Transparent Object Extraction from Regular Textured Backgrounds by Using
Binary Parallel Operations
%J MAG156
%P 41-53
%K H03 AI06
%A Haluk Derin
%A Chee-Sun Won
%T A Parallel Image Segmentation Algorithm Using Relaxation with Varying
Neighborhoods and Its Mapping to Array Processors
%J MAG156
%P 54-78
%K H03 AI06
%A Vishvjit S. Nalwa
%A Eric Pauchon
%T Edgel-Aggregation and Edge Description
%J MAG156
%P 79-94
%K AI06
%A Abdol-Reza Mansouri
%A Alfred S. Malowany
%A Martin D. Levine
%T Line Detection in Digital Pictures: A Hypothesis Prediction/Verification
Paradigm
%J MAG156
%P 95-114
%K AI06
%A H. Bieri
%T Computing the Euler Characteristic and Related Additive Functionals of
Digital Objects from Their Bintree Representation
%J MAG156
%P 115
%K AI06
%A W. K. Pratt
%A P. F. Leonard
%T Review of Machine Vision Architectures
%B BOOK85
%P 2-12
%K AI06 AT08
%A R. Q. Fox
%T A Comparison of the Wire Frame and Mathematical Morphology
Approaches to Machine Vision
%B BOOK85
%P 13-22
%K AI06
%A W. M. Silver
%T Normalized Correlation Search in Alignment, Gauging, and Inspection
%B BOOK85
%P 23-34
%K AI06 AA26
%A T. Poggio
%T Computer Vision
%B BOOK85
%P 54-62
%K AI06
%A R. M. Haralick
%T Recognition Methodology - Algorithms and Architecture
%B BOOK85
%P 63-65
%K AI06
%A A. Rosenfeld
%T Parallel Algorithms for Real-Time Vision
%B BOOK85
%P 66-70
%K H03 O06 O03 AI06
%A T. N. Nudge
%T An Analysis of Hypercube Architectures for Image Pattern Recognition
Algorithms
%B BOOK85
%P 71-83
%K AI06 H03
%A D. Casasent
%T Optical Pattern Recognition and AI Algorithms and Architectures for ATR and
Computer Vision
%B BOOK85
%P 84-95
%K AI06
%A B. R. Hunt
%T Prospects for Self-Organizing Pattern Recognition via Adaptive
Network Systems
%B BOOK85
%P 96-98
%K AI06 AI12
%A C. W. R. Swonger
%T Tools for Productive Development of Image Analysis Algorithms
%B BOOK85
%P 99-113
%K AI06
%A K. R. Castleman
%A D. Fabian
%T User Interface Design for a General Purpose Pattern Recognition Package
%B BOOK85
%P 114-125
%K O01 AI06
%A J. Sklansky
%A K. H. K. Kim
%T Real Time Scene Understanding and Vision Automation - A Brief Overview
%B BOOK85
%P 126-131
%K AT08 O03 AI06
%A A. F. Lehar
%A R. Gonsalves
%A J. Weaver
%A L. Turnbaugh
%T Pattern Recognition Techniques for Finding the Address on Letters
and Parcels
%B BOOK85
%P 132-140
%K AI06
%A P. S. P. Wang
%T A More Natural Approach for Recognition of Line-Drawing Patterns
%B BOOK85
%P 141
%K AI06
%A T. D. Watts
%T Some Historical Currents Concerning the Societal Learning Approach
to Policy and Planning
%J Cybernetica
%V 30
%N 2
%D 1987
%P 43-58
%K AA11 O05 AI04
%A A. V. Reader
%T The Memory Channel Machine - Part of a Proposed Learning Machine
%J Cybernetica
%V 30
%N 2
%D 1987
%P 25-42
%K AI04
%A E. M. Oblow
%T A Probabilisitic-Propositional Framework for the O-Theory Intersection
Rule
%J MAG157
%P 187-202
%K O04
%A Ronald R. Yager
%T Toward a Theory of Conjunctive Variables
%J MAG157
%P 203-228
%K O04
%A Thomas B. Fowler
%T A Numerical Method for Propagation of Uncertainty in Nonlinear Systems
%J MAG157
%P 265
%K O04
%A Jonathan Vaughan
%A Graham Brookes
%A David Chalmers
%A Martin Watts
%T Transputer Applications to Speech Recognition
%J Microprocessors and Microsystems
%V 11
%N 7
%D SEP 1987
%K H01 AI05
%P 377-382
%A Shi-Kuo Chang
%A L. Leung
%T A Knowledge-Based Message-Management System
%J ACM TOIS
%V 5
%N 3
%D JUL 1987
%P 213-236
------------------------------
End of AIList Digest
********************
∂13-Nov-87 0224 LAWS@KL.SRI.COM AIList V5 #265 - Seminar, Conferences
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 Nov 87 02:24:24 PST
Date: Thu 12 Nov 1987 23:24-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #265 - Seminar, Conferences
To: AIList@SRI.COM
AIList Digest Friday, 13 Nov 1987 Volume 5 : Issue 265
Today's Topics:
Seminar - Generate, Test, and Debug (BBN),
Conference - Machine Translation &
Expert Systems and Software Engineering &
1st Australian Knowledge Engineering Congress &
Visual Form and Motion Perception
----------------------------------------------------------------------
Date: Tue 10 Nov 87 16:11:34-EST
From: Marc Vilain <MVILAIN@G.BBN.COM>
Subject: Seminar - Generate, Test, and Debug (BBN)
BBN Science Development Program
AI Seminar Series Lecture
GENERATE, TEST AND DEBUG: A PARADIGM FOR SOLVING
INTERPRETATION AND PLANNING PROBLEMS
Reid Simmons
MIT AI Lab
(REID%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU)
BBN Labs
10 Moulton Street
2nd floor large conference room
10:30 am, Tuesday November 17
We describe the Generate, Test and Debug (GTD) paradigm and its use in
solving interpretation and planning problems, where the task is to
find a sequence of events that could achieve a given goal state from a
given initial state. The GTD paradigm combines associational
reasoning in the generator with causal reasoning in the debugger to
achieve a high degree of efficiency and robustness in the overall
system. The generator constructs an initial hypothesis by finding
local domain-dependent patterns in the goal and initial states and
combining the sequences of events that explain the occurrence of the
patterns. The tester verifies hypotheses and, if the test fails,
supplies the debugger with a causal explanation for the failure. The
debugger uses domain-independent debugging algorithms which suggest
repairs to the hypothesis by analyzing the causal explanation and
models of the domain.
This talk describes how the GTD paradigm works and why its combination
of reasoning techniques enables it to achieve efficient and robust
performance. In particular, we will concentrate on the actions of the
debugger which uses a "transformational" approach to modifying
hypotheses that extends the power of the "refinement" paradigm used by
traditional domain-independent planners. We will also discuss our
models of causality and hypothesis construction and the role those
models play in determining the completeness of our debugging algorithms.
The GTD paradigm has been implemented in a program called GORDIUS. It
has been tested in several domains, including the primary domain of
geologic interpretation, the blocks world, and the Tower of Hanoi
problem.
------------------------------
Date: Fri, 6 Nov 87 16:19:20 EST
From: Machine.Translation.Journal@NL.CS.CMU.EDU
Subject: Conference - Machine Translation
CONFERENCE ON MACHINE TRANSLATION
CALL FOR PAPERS
The Second International Conference on Theoretical and
Methodological Issues in Machine Translation of Natural Languages
will be held June 12 - 14 at the Center for Machine Translation,
Carnegie-Mellon University, Pittsburgh, PA.
Contributions are solicited on all topics related to machine
translation, machine-aided translation, and, generally, automatic
analysis and generation of natural language texts, the structure
of lexicons and grammars, research tools, methodologies,
knowledge representation and use, and theory of translation.
Relevant submissions on other topics are also welcome.
Extended abstracts (not exceeding 1,500 words) should be sent
to
MT Conference Program Committee
Center for Machine Translation
Carnegie-Mellon University
Pittsburgh PA 15213, U.S.A.
(412) 268 6591
Submission Deadline: February 1, 1988
Notification of Acceptance: March 21, 1988
Final Version Due: April 18, 1988
All submissions will be refereed by the members of the Program Committee:
Christian Boitet (University of Grenoble)
Jaime Carbonell (Carnegie-Mellon University)
Martin Kay (Xerox PARC)
Makoto Nagao (Kyoto University)
Sergei Nirenburg (Carnegie-Mellon University)
Victor Raskin (Purdue University)
Masaru Tomita (Carnegie-Mellon University)
All inquiries should be directed to
Cerise Josephs
Center for Machine Translation
Carnegie-Mellon University
Pittsburgh, PA 15213 U.S.A.
(412) 268 6591
cerise@nl.cs.cmu.edu.ARPA
------------------------------
Date: Mon, 9 Nov 1987 02:29 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Conference - Expert Systems and Software Engineering
CALL FOR PARTICIPATION
A Joint IEEE Software and IEEE Expert Special Issue on
"The Interactions Between Expert Systems and Software Engineering"
In FJCC'87 a panel composed of R. Balzer (Information Sciences Institute),
C. V. Ramamoorthy (University of California at Berkeley), W. W. Royce
(Lockheed Software Technology Center), M. M. Tanik (Southern Methodist
University), W. Bledsoe (MCC), D. Y. Y. Yun (Southern Methodist University),
and Roger Bates (Texas Instruments), discussed the issues related to
interactions between AI and Software Engineering. It is observed that there
was a growing interest among practitioners of AI and SE to look into the
issues concerning both of these fields. Recent papers from C. V. Ramamoorthy
(IEEE Computer, Jan. 1987) and H. Simon (IEEE TSE, July 1986) summarizes some
of the interest areas and concerns.
Now, IEEE Software and IEEE Expert seek contributions for special issues that
will be published in November 1988. The focus of these issues will be on the
interactions between the fields of Artificial Intelligence and Software
Engineering.
Original research papers as well as general categories of tutorials, surveys,
and overviews are welcome.
Two hundred word abstracts should be submitted as soon as possible, and eight
copies of manuscripts are due by February 1, 1988 addressed to:
Murat M. Tanik
Southern Methodist University
Department of Computer Science and Engineering
Dallas, TX 75275-0122
(214) 692-2854
------------------------------
Date: 10 Nov 87 12:05:14 +1000 (Tue)
From: "ERIC Y.H. TSUI" <munnari!aragorn.oz.au!eric@uunet.UU.NET>
Subject: Conference - 1st Australian Knowledge Engineering Congress
(Nov. '88)
1ST
AUSTRALIAN
KNOWLEDGE
ENGINEERING
CONGRESS
NOVEMBER 15TH - 17TH 1988
CALL FOR PAPERS
Following the success of the 1st Australian Artificial Intelligence Congress
in November 1986, Melbourne will be the host to its successor -
the Australian Knowledge Engineering Congress - in November 1988.
Contributions are invited on every aspect of Knowledge Engineering and
Knowledge-base technology: Expressions of interest in the program and
supporting activities are now invited either on the following topics or
on any related theme:
Expert Systems case studies
Knowledge Engineering (including Prototyping) methodologies
Design and use of Conceptual Schemas
Natural Language Interfaces
Evaluation of tools and expert systems
Role of consultants in Knowledge Engineering
Design of Intelligent Tutors and Conversational Advisors
Knowledge Source Systems
Inference mechanisms
A preliminary indication of interest in offering a paper, management of
specific streams and/or tutorial presentations should be sent as soon
as possible to :-
Professor B. Garner
DEAKIN UNIVERSITY
VICTORIA 3217
AUSTRALIA
Electronic mail: brian@aragorn.oz
Eric Tsui eric@aragorn.oz
------------------------------
Date: Thu, 12 Nov 87 15:52:22 est
From: ennio@bucasb.bu.edu (Ennio Mingolla)
Subject: Conference - Visual Form and Motion Perception
VISUAL FORM AND MOTION PERCEPTION:
PSYCHOPHYSICS, COMPUTATION,
AND NEURAL NETWORKS
Friday and Saturday, March 4 and 5, 1988
Conference Auditorium, George Sherman Union, Boston University
775 Commonwealth Avenue, Boston, Massachusetts
This meeting has been dedicated to the memory of the late
KVETOSLAV PRAZDNY, who was to have been a speaker, and
whose tragic death has deprived the field of visual
perception of one of its most talented investigators.
Speakers include:
L. AREND Eye Research Inst. V. RAMACHANDRAN UCSD
S. ANSTIS York University A. REEVES Northeastern Univ.
I. BIEDERMAN Univ. of Minnesota W. RICHARDS MIT
P. CAVANAGH Univ. of Montreal R. SAVOY Rowland Inst.
J. DAUGMAN Harvard University G. SPERLING New York Univ.
S. GROSSBERG Boston University J. TODD Brandeis Univ.
J. LAPPIN Vanderbilt Univ. S. ZUCKER McGill University
E. MINGOLLA Boston University
This meeting is sponsored by the Boston Consortium for Behavioral and
Neural Studies, a group of researchers supported by the Air Force Office
of Scientific Research Life Sciences Program. A Howard Johnson's Motor
Lodge is located at 575 Commonwealth Avenue, and a limited number of rooms
at a reduced conference rate can be reserved until February 10, 1988 by
those attending the meeting. Total conference registration will be
limited by available meeting space, so early registration is advised.
Registration and hotel accomodations for the meeting are being
handled by:
UNIGLOBE--Vision Meeting Telephone:
40 Washington Street (800) 521-5144
Wellesley Hills, MA 02181 (617) 235-7500
A meeting registration and hotel reservation form is attached to this
announcement. For further information about travel or accomodation
arrangements, contact UNIGLOBE at the above address or telephone numbers.
[Contact the sender for the registration form. -- KIL]
------------------------------
End of AIList Digest
********************
∂13-Nov-87 0438 LAWS@KL.SRI.COM AIList V5 #266 - Queries
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 Nov 87 04:38:35 PST
Date: Thu 12 Nov 1987 23:30-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #266 - Queries
To: AIList@SRI.COM
AIList Digest Friday, 13 Nov 1987 Volume 5 : Issue 266
Today's Topics:
Queries - Event-Based Reasoning & Prolog Parser &
Object-Oriented Database & Full-Text Search Program &
Brain Science Programs & VTLISP & Statistical Expert Systems &
Expert System Benchmarking & Environmental Impact Assessment &
MacBrain & Animal Behavior
----------------------------------------------------------------------
Date: 6 Nov 87 06:43:21 GMT
From: kddlab!titcca!secisl!tau@uunet.uu.net ("Yatchan" TAUCHI)
Subject: What is Event-Based Reasoning (In English)
In <8710220645.AA25064@ucbvax.Berkeley.EDU> Seminar "Event-Based Reasoning
for Multiagent Domains (Bendix & BBN)" is announced.
Please someone tell me what Event-Based Reasoning is or introduce any
papers on this topics, if any.
Thanks in advance
-----
Yasuyuki TAUCHI, SECOM IS-Lab, Tokyo, JAPAN
Net: tau%seclab.junet@uunet.UU.NET
UUCP: ...!{seismo,uunet}!kddlab!titcca!secisl!tau
------------------------------
Date: 30 Oct 87 06:07:12 GMT
From: kddlab!icot32!nttlab!ouicsu!ics750!feng@uunet.uu.net (Hyou An)
Subject: A Parser writen in Prolog (In English)
I'm trying to construct a Prolog Based Translator Generator. What I wnat to do
is as follows:
1.To specify the translator in Attribute Grammar(AG)
(or a form based on AG)
2.To generate a translator specified by AG
(1)To translate AG into a efficient form automatically.
For example, rewrite a LL(k) grammar into LL(m) (m<k), etc.
(2)To generate a translator (in Prolog) from the optimized AG.
(3)To transforme the Prolog program into an efficient one.
This work is for my PhD degree. I am therefore interested in any work on:
. Attribute Grammar and Syntax Directed Translation
. Efficient LL(k) paser
. Language system based on Prolog
. Transformation system
Is there anyone out there doing or interested in similar work?
Any comments and suggestions will be helpful.
An Feng
Date: 29-Oct-1987
Tel No: 06-844-1151(Ext.4816)
Airmail: Department of Information and Computer Sciences
Faculty of Engineering Science
Osaka University
Toyonaka,Osaka
560, Japan
------------------------------
Date: 9 Nov 87 17:48:51 GMT
From: bbn!mfidelma@husc6.harvard.edu (Miles Fidelman)
Subject: object oriented database query
Can anyone point me to work in the area of applying database technology
to supporting object oriented environments?
It strikes me that database technology tends to focus on supporting large
production databases, with attention to fast processing speeds, maintaining
database integrity, journalizing/checkpointing, etc.; while object oriented
environments are basically prototyping environments.
Has anyone been working on making a production object oriented environment?
Thanks much,
Miles Fidelman
email to: mfidelman@bbn.com
------------------------------
Date: 9 Nov 87 21:22:59 GMT
From: cos!hqda-ai!merlin@uunet.uu.net (David S. Hayes)
Subject: Need Full-text-search program for AI work
We're looking for hardware/software to allow scanning of
hardcopy documents. After scanning, we want to be able to search
the text to look for keywords, and pull up the relevant portion of
the document. I've never seen anything exactly like this, but
maybe (hopefully :-) someone out there has.
How 'bout it? Any suggestions, for either hardware or
software. We've got Suns and Symbolics, so we're flexible.
Company names and phone numbers are nice, user recommendations
even better.
Please reply via mail.
--
David S. Hayes, The Merlin of Avalon PhoneNet: (202) 694-6900
UUCP: *!uunet!cos!hqda-ai!merlin ARPA: ai01@hios-pent.arpa
------------------------------
Date: 9 Nov 87 15:56:46 GMT
From: ihnp4!laidbak!spl1!wheaton!johnh@ucbvax.Berkeley.EDU (John Doc
Hayward)
Subject: Brain Science Programs
What CS courses are offered in Colleges and Universities which
are part of an undergraduate 'Brain Science' program?
Are the courses taught by CS faculty either individually or
team taught with members of different discipline?
What prerequisites in CS would be required for courses. What
does the 'program' consist of?
Any helpful comments or suggestions will be appreciated. If there is enough
interest I will summarize responses. johnh...
--
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
UUCP: ihnp4!wheaton!johnh telephone: (312) 260-3871 (office)
Mail: John Hayward Math/Computer Science Dept. Wheaton College Wheaton Il 60187
Act justly, love mercy and walk humbly with your God. Micah 6:8b
------------------------------
Date: 10 Nov 87 17:53:48 GMT
From: nrl-cmf!ukma!gatech!hubcap!ncrcae!gollum!dowell@ames.arpa
(dowell)
Subject: Request for VTLISP
Would some kind soul please send the source code for VTLISP.
It was recently written about in AIEXPERT magzine(May?).
Thanks,
ncrcae!gollum!dowell
------------------------------
Date: Wed 11 Nov 87 21:44:33-PST
From: Laurence I. Press <LPRESS@venera.isi.edu>
Subject: Statistical Exp. Sys. Query
Can anyone give me pointers to programs and/or papers on statistical
applications of expert systems?
Larry
------------------------------
Date: Wed 11 Nov 87 21:49:15-PST
From: Laurence I. Press <LPRESS@venera.isi.edu>
Subject: Exp. Sys. Benchmarking Query
Can anyone supply pointers to papers on benchmarking and performance
evaluation for expert system shells?
I have written a short program that generates stylized rule bases of
a specified length and have used it to generate comparative test cases
for PC Plus and M1. I'd be happy to give anyone a copy and would like
to learn of other efforts to compare expert system shells.
Larry
------------------------------
Date: 12 Nov 87 12:13 -0400
From: Jan Mulder <mulder@cs.dal.cdn>
Subject: Environmental Impact Assessment
The school for Resource and Environmental Studies at Dalhousie
University is initiating a research project for the Canadian Federal
Environmental Assessment and Review office (FEARO), of current and
potential uses of computer-based expert systems, artificial
intelligence, and decision support tools for environmental impact
assessment (EIA) and management. FEARO has recently begun supporting
some development work in this field, but has commissioned this project
to provide strategic guidance for any further commitments of support
which it may make.
Although the project encompasses applications of these technologies
in all aspects of EIA, we are particularly interested in these
applications as they may relate to the initial screening and scoping
stages of the impact assessment process.
With regard to potential applications of these systems we are interested
in the details of any recent or on-going research and development, and
the resulting prospects and problems identified. With regard to actually
operational systems, there are a number of aspects of interest to us:
the structure and scope of such systems, when and how the system was
developed, present users of the system and the purpose of use, evaluations
of the advantages/disadvantages of the system, and the costs of
development, maintenance and updating.
If you are, or have been involved in any research or development work
applied to environmental assessment and management, would you please
send details to Alan Gray (Project Manager) at the address below. We
are planning to produce a draft report by December 31, 1987, and
conduct a symposium in January, 1988. We therefore request your reply
at your earliest convenience. Please do not hesitate to contact us
for any matter of clarification.
Alan Gray
School for Resource and Environmental Studies
Dalhousie University
1312 Robie St.
Halifax, Nova Scotia
Canada B3H 3E2
phone: (902) 424-2589 or (902) 424-3632
e-mail: DUAB005@DAL.BITNET
Would you please bring the request to the attention of any of your
colleagues who may be able to help us.
------------------------------
Date: 12 Nov 87 18:01:13 GMT
From: sgi!wdl1!jtd@ucbvax.Berkeley.EDU (Jeffrey T. DeMello)
Subject: MacBrain - Nural-Network Simulator
Has anyone out there in "network-land" ever
seen/heard of/used/reviewed a nural-network
simulator called MACBRAIN?
If so, please enlighten me!!!
jtd@ford-wdl1.arpa
------------------------------
Date: Tue, 10 Nov 87 19:03:09 PST
From: Dan Shapiro <dan@ads.arpa>
Subject: animal behavior and AI
I am looking for someone who would be interested in discussing some
ideas that involve both the fields of animal behavior and planning as
a subdiscipline of AI. My goal is to develop a realistic view of what
planning means to simple animals (at the level of ants for example)
and use that information to motivate planning architectures within AI.
Within this context, my focal point is to look at *errors* in animal
behavior, as when ants build circular bridges out of their own bodies,
and the ones on top simply run themselves to death. This should give
a sense for the limitations of animal planning and also prevent us
from anthropormorphizing to extremes; the temptation is to view
behavior like the above as goal directed and related to our concept of
"bridge building", when the presence of the error indicates that
something much more primitive is going on. From the little I have
seen of literature in the behavioral sciences, this type of
projection is fairly common.
In any case, as a first step, I'd like to gather multiple examples of
errors in animal behavior. If there are any ethologists,
sociobiologists, neuroanatomists, computer scientists or just plain
armchair behaviorists out there who have something to say on this
topic, please contact me.
Dan Shapiro
dan@ads.com
415 941-3912
------------------------------
End of AIList Digest
********************
∂13-Nov-87 0724 LAWS@KL.SRI.COM AIList Digest V5 #267
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 Nov 87 07:23:58 PST
Date: Thu 12 Nov 1987 23:42-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #267
To: AIList@SRI.COM
AIList Digest Friday, 13 Nov 1987 Volume 5 : Issue 267
Today's Topics:
AI Tools - Source Libraries & Object-Oriented Databases,
Binding - Michael O. Rabin,
Neuromorphic Systems - References,
Pattern Recognition - Character Recognition,
Education - Brain Science Programs,
Law - Who Owns the Output of an AI?
----------------------------------------------------------------------
Date: 9-NOV-1987 10:44:40 GMT
From: POPX@VAX.OXFORD.AC.UK
Subject: Source Libraries
From Jocelyn Paine
St Peter's College
New Inn Hall Street
Oxford OX1 2DL
I was pleased to read in AIList Bulletin V5 #260, Robert Futrelle's proposal
to set up a net-accessible National Resource Centre of public domain AI
software. I teach AI in Prolog to undergraduates at Oxford University; it's
very hard to obtain source code (whether in Prolog or Lisp) for many of the
"landmark" programs which occur in textbooks: GPS, Analogy, Talespin, AM, Sam,
and so on. Published descriptions just don't give enough information for me to
re-implement these programs from scratch.
In saying this, I agree very much with Seth (sas@bfly-vax.bbn.com)'s comments
in AIList V5 #257:
> The current lack of reproducibility is appalling. We have a
> generation of language researchers who have never had a chance to play
> with the Blocks World or and examine the limitiations of TAILSPIN.
> It's as if Elias Howe had to invent the sewing machine without access
> to steel or gearing. There's a good chance he would have reinvented
> the bone needle and the backstitch given the same access to the fruits
> of the industrial revolution that most AI researchers have to the
> fruits (lemons) of AI research. Anecdotal evidence, which is really
> what this field seems to be based on, just doesn't make for good
> science.
I have considered setting up a library of such programs, which I'd send to
anyone who can be reached from the British Academic Network (Janet). Before
distributing these programs to others, I would test-run them to check that
they conform to a reasonable standard (I'd have to limit this to Prolog
programs, since I don't know enough about Lisp implementations to know what
features are undesirably non-standard). I'd test them for conformance to
Edinburgh syntax and predicates, by running under VAX/VMS Poplog Prolog). I
would also check to see that the instructions for running are correct.
Anyone want to help?
------------------------------
Date: Fri, 6 Nov 87 05:49 PST
From: nesliwa%nasamail@ames.arpa (NANCY E. SLIWA)
Subject: Public dissemination of AI software
Just a note in response to recent board postings about the desireability
of having research software made available to other researchers for
duplication of experiments and for extensions to programs: NASA has been
required to do that all along, and that is probably true of most other
government labs (other that sensitive military work). NASA's software
clearinghouse is COSMIC, associated with the University of Georgia, and
all software is available for a minimum fee which covers dissemination
costs. Although most of COSMIC's library is more aerospace-science
related, there has been some interesting AI research in NASA in recent
years, and researchers are *strongly encouraged* to submit all
programs (with documentation and research papers) to COSMIC.
More information about COSMIC (and a catalog of available software) is
available from:
COSMIC
112 Barrow Hall
The University of Georgia
Athens, Georgia 30602
(404)542-3265
Nancy Sliwa
NASA Langley Research Center
nesliwa%nasamail@ames.arpa
nancy@grasp.cis.upenn.edu
------------------------------
Date: 10 Nov 87 16:25:34 GMT
From: cos!hqda-ai!merlin@uunet.uu.net (David S. Hayes)
Subject: Re: object oriented database query
A very nice object-oriented database is produced by Graphael
(a French company). This system supports text, and numbers, and
mouse-sensitive graphics, and sound, and digitized pictures as
part of the database. IE, your entry for Company X can include a
streetmap of their area. Alternatively, a floorplan of your
building can be mouse-sensitive. Mouse on some office, and the DB
can tell you who works there.
This software runs on Symbolics Lisp Machines, and some
others I can't recall right now. Their US contact is:
Eric Sansonetti, National Sales Manager
Graphael, Inc.
255 Bear Hill Road
Waltham, MA 02154
Phone: 617-890-7055
--
David S. Hayes, The Merlin of Avalon PhoneNet: (202) 694-6900
UUCP: *!uunet!cos!hqda-ai!merlin ARPA: ai01@hios-pent.arpa
------------------------------
Date: 10 Nov 87 16:07:05 GMT
From: uh2%psuvm.bitnet@ucbvax.Berkeley.EDU (Lee Sailer)
Subject: Re: object oriented database query
The ACM journals and SIG newsletters on Data Base and Office Info Systems
often have stuff about Object Oriented Database management.
Typically, the O approach is most useful when the world be
modeled is object like. For example, consider building a database to
manage geographic info for a city the size of New York. Support
queries like "What offices are within 15 minutes of the UN building?"
or "Whose view will be blocked by a 200 stofry building at 5th and
Broadway?"
Likewise, systems for managing blueprints, specifications, and
change requests in a manufacturing environment profit immensly
from Object orientations.
lee
------------------------------
Date: Mon, 9 Nov 87 11:59:39 EST
From: rapaport@cs.Buffalo.EDU (William J. Rapaport)
Subject: Michael O. Rabin
He is Professor of CS at Harvard and also Hebrew University--very well
known.
John
------------------------------
Date: 5 Nov 87 16:53:00 GMT
From: necntc!adelie!mirror!ishmael!inmet!justin@husc6.harvard.edu
Subject: Re: references for adaptive systems
/* Written 12:36 pm Nov 2, 1987 by oppy@unrvax.UUCP in inmet:comp.ai */
/* ---------- "references for adaptive systems" ---------- */
The direction i wish to go with this is toward learning systems,
equivalences in the way computers and biological organisms learn.
brian oppy (oppy@unrvax)
One of my former professors, a Richard Alterman of Brandeis University
(Waltham, MA) was doing some interesting work in that direction when last
I spoke to him. You might look him up.
-- Justin du Coeur
------------------------------
Date: 9 Nov 87 04:15:31 GMT
From: ihnp4!homxb!mtuxo!mtgzz!drutx!clive@ucbvax.Berkeley.EDU (Clive
Steward)
Subject: Re: Character recognition
in article <641@zen.UUCP>, vic@zen.UUCP (Victor Gavin) says:
>
>
> I have been puttering about for the past few weeks with an HP ScanJet (one
> of those 300dpi digitizers). I have been asked to write some software which
> can (given an image produced by the scanner) reproduce the original text of
> the paper in a machine readable form.
> If someone has already tackled this problem, any help I can get will be much
> appreciated.
>
Yes, there's some software for the Macintosh which is purported to do
just this, with text. Presumably, like other such systems, it's
pretty much confined to non-proportional fonts. Since numbers are
often non-proportional even in otherwise proportional fonts so that
columns will look right, this sounds like it would do your job.
There's at least one package which purports to do this; it's called
Read-it!, said to be for 'popular' scanners, which presumably includes
all the 300 dpi ones as well as Thunderscan etc. which can do more.
It was apparently demo'ed in 'pre-release form' at MacWorld Expo in August.
It's from:
Olduvai Software, Inc.
6900 Mentone
Coral Gables, Florida 33146
USA
Phone (305) 665-4665
They list it in the September MacUser ad for $295 list. Reading that,
I find they say it works on "including AST Turboscan, Microtek, Abaton 300,
MacScan, LoDown, Spectrum, Datacopy, Dest, etc." "Type tables form
most popular typewriter and LaserWriter fonts are included, or you can
use it's unique "learning mode" to teach it to recognize an unlimited
number of fonts, includeing foriegn and special characters." (sic).
They also say, "Read-It TS, a special version of Read-It! optimized
for the Thunderscan is also available" $149.00 list. But though I
have and like Thunderscan, I don't know that it's what you want for
high volume. It's 1/10 the price, and 1/10 the speed, though often
with better looking results for pictures.
Good Luck!
And if you get it and have results, would appreciate mail to see what
it's like; probably others would like a posting too!
Clive Steward
------------------------------
Date: 11 Nov 87 15:43:43 GMT
From: steinmetz!stern@uunet.uu.net (harold a stern)
Subject: Re: Brain Science Programs
In article <653@wheaton.UUCP> johnh@wheaton.UUCP (John Doc Hayward) writes:
>
>What CS courses are offered in Colleges and Universities which
>are part of an undergraduate 'Brain Scince' program?
>Are the courses taught by CS faculty either individually or
>team taught with members of different discipline?
>What prerequisites in CS would be required for courses. What
>does the 'program' consist of?
The following are (roughly) the requirements for MIT's program in "Brain and
Cognitive Sciences". Courses marked (EECS) are offered by the Department of
Electrical Engineering and Computer Science; those marked (BCS) are offered
by the Department of Brain and Cognitive Sciences; and those marked (LP) are
offered by the Deparment of Linguistics and Philosophy.
1) Introduction to Cognitive Science (BCS)
2) Logic I (LP)
3) Introduction to Algebraic Systems (EECS)
4) Automata, Computability, and Complexity (EECS)
four of the following six:
4) The Study of Language (LP)
5) Cognitive Processes (BCS)
6) Structure and Interpretation of Computer Programs (EECS)
7) Neuroscience and Behavior (BCS)
8) Perceptual Information Processing (BCS)
9) Minds and Machines (LP)
and four additional courses selected from approved subjects in
experimental cognitive psychology, aspects of natural language,
neurological foundations of cognition, perception, natural computation,
and the philosophy of mind.
Structure and Interpretaiton of Computer Programs is the introductory
course in computer science required of students majoring in either
EE or CS.
Introduction to Algebraic Systems and Automata, Computability, and Complexity
are required courses for computer scientists (actually, Algebraic Systems is
offered by the Department of Mathematics, but only CS students take it).
harold a. stern <stern@ge-crd.arpa>
room k1-5c8, ge corporate r&d center
p.o. box 8, schenectady, ny 12301
------------------------------
Date: 10 Nov 87 18:08:54 GMT
From: houpt@svax.cs.cornell.edu (Charles )
Subject: Who owns the output of an AI?
I read an interesting news item in this weeks NewScientist magazine.
It said that the British parliment is reorganizing the UKs intellectual
property law. The interseting thing is that it has a section dealing with
intellectual property generated by Artificial Intelligences.
The law says that the output of an AI is owned by the user running the
AI, NOT the programmer who designed it.
Is this fare? Should copywrites go to the user or the programmer? (or to
the AI :-)? To me the British law seems unfair. If my AI program discovered
a new high temperature super-conductor, shouldn't I get some profit? The
user running my program may know nothing about super-conductors, why should
he get the patent?
What do you think?
-Chuck Houpt houpt@svax.cs.cornell.edu
KY3Y@CORNELLA.BITNET
------------------------------
Date: 11 Nov 87 06:17:30 GMT
From: speedy!honavar@speedy.wisc.edu (A Buggy AI Program)
Subject: Re: Who owns the output of an AI?
In article <1778@svax.cs.cornell.edu> houpt@svax.cs.cornell.edu
(Charles (Chuck) Houpt) writes:
>
>property law. The interseting thing is that it has a section dealing with
>intellectual property generated by Artificial Intelligences.
>
> The law says that the output of an AI is owned by the user running the
>AI, NOT the programmer who designed it.
>
> Is this fare? Should copywrites go to the user or the programmer? (or to
>the AI :-)? To me the British law seems unfair. If my AI program discovered
>a new high temperature super-conductor, shouldn't I get some profit? The
>user running my program may know nothing about super-conductors, why should
>he get the patent?
Any such law that does not call for a full consideration of
the particulars of each case is bound to be unfair. One may write a
learning program that draws inferences based on data presented to it -
in other words, it has the potential to discover something significant,
given enough raw data to work on. Let us say, X writes the program and
sells it to Y. Y runs the program on data he has gathered in some domain,
superconductivity and the program discoveres a new high temperature
superconductor. Although the program was written by X, Y was instrumental
in getting the observed behavior out of the program by virtue of the
data he provided to the program. In this situation, it is not clear
how the credit for the discovery made by the program should be apportioned
among X, Y, and the program itself.
each case
------------------------------
Date: 11 Nov 87 13:55:51 GMT
From: super.upenn.edu!eecae!lawitzke@rutgers.edu (John Lawitzke)
Subject: Re: Who owns the output of an AI?
$ The law says that the output of an AI is owned by the user running the
$ AI, NOT the programmer who designed it.
$
$ Is this fare? Should copywrites go to the user or the programmer? (or to
$ the AI :-)? To me the British law seems unfair. If my AI program discovered
$ a new high temperature super-conductor, shouldn't I get some profit? The
$ user running my program may know nothing about super-conductors, why should
$ he get the patent?
$ What do you think?
For the author of an AI to get the copyright/ownership of a users
results is like the author of SPICE (or similar programs) getting
the rights to all designs generated with it. Or UCB getting the rights
to all programs designed under 4.2BSD, et al. Or the author of a CAD
program having the copyright on all designs generated with the package.
The point of this is that it is rather absurd for the results of a
user's work under an AI to go to the author of the AI. For one thing,
the AI would never be used by anyone because they couldn't keep the
credit for their own work!
The one glaring loophole here is that the license for the AI could state
that the author reserves ownership of all results (then no one would
buy it) or that the author receives a royalty from all results
(reasonable but people wouldn't go for it)
--
j UUCP: ...ihnp4!msudoc!eecae!lawitzke
"And it's just a box of rain..." ARPA: lawitzke@eecae.ee.msu.edu (35.8.8.151)
------------------------------
Date: 11 Nov 87 06:57:22 GMT
From: jason@locus.ucla.edu
Subject: Re: Who owns the output of an AI?
In article <1778@svax.cs.cornell.edu> houpt@svax.cs.cornell.edu
(Charles (Chuck) Houpt) writes:
>
>The interseting thing is that it has a section dealing with
>intellectual property generated by Artificial Intelligences.
>
> The law says that the output of an AI is owned by the user running the
>AI, NOT the programmer who designed it.
>
> Is this fare? Should copywrites go to the user or the programmer?
> What do you think?
>
The computer should get the credit. It does the thinking. If it put in the
time and research, it should be justly rewarded. As Dr. Chandra says in
2010, a thinking being should be respected and valued as such.
Granted, an AI is very dependent on the people around it, particularly
the person who designed it (the programmer and/or computer architect), and
EQUALLY the user. Any intelligence is worthless without a means of learning
from its surroundings. Without a decent teacher and provider of information
(the user), an AI will not produce anything useful, except perhaps a detailed
and logical analysis of Cartesian doubt. Information provided by the user
is inherrently different than that created by the programmer. The programmer
simply creates a mechanism with which an AI can learn. The user then
fills in the blank slate with news of the world.
Jason Rosenberg
jason@cs.ucla.edu
------------------------------
End of AIList Digest
********************
∂13-Nov-87 1034 LAWS@KL.SRI.COM AIList V5 #268 - Spang Robinson 3/10, Bibliography, Methodology
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 13 Nov 87 10:34:16 PST
Date: Thu 12 Nov 1987 23:52-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #268 - Spang Robinson 3/10, Bibliography, Methodology
To: AIList@SRI.COM
AIList Digest Friday, 13 Nov 1987 Volume 5 : Issue 268
Today's Topics:
Review - Spang Robinson V3 N10,
Bibliography - Leff File bm846,
Comments - Success of AI & Gilding the Lemon & FORTRAN
----------------------------------------------------------------------
Date: Mon, 9 Nov 1987 02:29 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Review - Spang Robinson V3 N10
Summary of the Spang Robinson Report on Artificial Intelligence
October 1987, Volume 3, No. 10
The lead story is on Financial Expert Systems:
A survey of insurance and companies show that 21 per cent are using
expert systems with 20 per cent having no activity and the others in
various stages of development or research. For banks, the figures are
12 and 47 per cent respectively. The article gives information on
management attitudes, uses and comparisons of activity in property and
casualty and life insurance, use of PC's, mainframes and lisp machines and
type of language.
(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑(↑
Review of video tape classes on expert systems, "AI Masters"
by Addison-Wesley. This set has courses given by Patrick H. Winston,
Randall Davis and J. Ross Quinlan. The training aid has work books and
a simple PC expert tools. The workbooks have checklists to be used
in tool and application selection and test. The training system maligns,
perhaps due to datedness, PC-based expert systems and induction tools.
The three courses run for $2500-$3500 apiece with additional workbooks
for $10.00 a piece.
()()()()()()()()()()()()()()()()()()()()()()()()()()()()()()
Programs in Motion's Fusion allows user to put in examples and
generate production rules. The system can accept an example matrix of
32 factors and 32 resultsants and up to 255 different examples to
generate rules. (There can be more than 255 cases if some of the cases
are redundant.)
The system does allow chaining of the decision rules. Fusion can
generate C, Pascal and production code and read in dBase files.
(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_(_
shorts:
Symantec Corporation has merged with THINK technologies.
Digitalk has released a new version of Smalltalk/V with high resolution
object oriented programming for IBM PS-2/25 and 30 computers.
Cognitive Systems, Inc. has developed a system to read messages and route
them to the appropriate people in a bank.
Teknowledge has been awarded a $1.2 million contract for work on Pilot's
Associate.
U. S. Army is purchasing ART plus various services from Inference Corporation
(more than $3 million worth)
Palladian Software has sold its Operations Advisor to Blue Cross and Blue
Shield.
Odetics got a contract to apply AI to residual heat removal in
nuclear power plants.
Gold Hill Computer has signed a distriubtion agreement with
Computer Engineering and Consulting of Japan.
System Research and Development Co. of Tokyo
has developed a new expert system building
tool called ESPARON.
_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)_)
Discussion of the Gigamos vs. Gensym dispute.
Gigamos and Gensym are both headed by former leaders of LMI who sold
all assets to Gigamos. Gigamos charges Gensym with using trade secrets
and confidential information to develop a new expert system for
real time applications (G2) in competitition with Gigamos. Gigamos
charges Gensym founders
with "planning to resign from LMI and to use LMI proprietary
information in the new GENSYM business venture." They also accuse Gensym
of causing other LMI resignations helping defeating LMI financing.
Gigamos is asking for a copy of the software and source code to be
deposited.
------------------------------
Date: Thu, 12 Nov 1987 02:53 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Bibliography - Leff File bm846
Defs for a62C
D MAG144 IEEE Transactions on Systems, Man, and Cybernetics\
%V 17\
%N 3\
%D MAY-JUN 1987
D MAG145 International Journal of Man-Machine Studies\
%V 26\
%N 2\
%D FEB 1987
D MAG149 Information Processing and Management\
%V 233\
%N 4\
%D 1987
D MAG150 Computer Vision, Graphics, and Image Processing\
%V 39\
%N 3\
%D SEP 1987
D MAG151 International Journal of Man-Machine Studies\
%V 26\
%N 3\
%D MAR 1987
D MAG152 Image and Vision Computing\
%V 5\
%N 3\
%D AUG 1987
D MAG153 Computers and Industrial Engineering\
%V 13\
%N 1-4\
%D 1987
D MAG154 Fuzzy Sets and Systems\
%V 23\
%N 3\
%D SEP 1987
D MAG155 International Journal of Man-Machine Studies\
%V 26\
%N 4\
%D APR 1987
D MAG156 Computer Vision, Graphics, and Image Processing\
%V 40\
%N 1\
%D OCT 1987
D BOOK85 Image Pattern Recognition: Algorithm Implementations,\
Techniques, and Technologies\
%S Proceedings of the Society of Photo-Optical Instrumentation Engineers\
%V 755\
%E F. J. Corbett\
%I SPIE - International Society Optimal Engieering (Bellingham)\
%D 1987
D MAG157 International Journal of General Systems\
%V 13\
%N 3\
%D 1987
------------------------------
Date: 9 Nov 87 16:57:20 GMT
From: honavar@speedy.wisc.edu (A Buggy AI Program)
Reply-to: honavar@speedy.wisc.edu (A Buggy AI Program)
Subject: Re: Success of AI
In article <4357@wisdom.BITNET> eitan%H@wiscvm.arpa (Eitan Shterenbaum) writes:
>
>As to the claim "the brain does it so why shouldn't the computer" -
>It seem to me that you forget that the brain is built slightly differently
>than a Von-Neuman machine ... It's a distributed enviorment lacking boolean
>algebra. I can hardly believe that even with all the partial solutions for
>all the complicated sets of NP problems that emulating a brain brings up, one
>might be able to present a working program. If you'd able to emulate mouse's
>brain you'd become a legend in your lifetime !
>Anyway, no one can emulate a system which has no specifications.
>if the neuro-biologists would present them then you'd have something to start
>with.
I use the term "computer" in a sense somewhat broader than a
Von-Neuman machine. We can, in principle, build machines that
incorporate distributed representations, processing and control.
It is not clear what you mean by a "distributed environment lacking
boolean algebra."
The use of fine-grained distributed representations naturally results
in behavior indicative of processes using fuzzy or probabilistic logic.
The goal is, not necessarily to emulate the brain in all its detail:
We can study birds to understand the principles of aerodynamics that
explain the phenomenon of flying and then go on to build an aeroplane
that is very different from a bird but still obeys the same laws of
physics. As for specifications, they can be provided in different
forms and at different levels of detail; Part of the exercise is
to discover such specifications - either by studying actual existing
systems or by analyzing the functions needed at an abstract level to
determine the basic building blocks and how they are to be put
together.
>
>And last - Computers aren't meta-capable machines they have constraints,
> not every problem has an answer and not every answermakes sense,
> NP problems are the best example.
>
Are you implying that humans are "meta-capable" - whatever that means?
VGH
------------------------------
Date: 10 Nov 1987 10:29-EST
From: Spencer.Star@B.GP.CS.CMU.EDU
Subject: Re: Guilding the Lemon
Something I was reading the other day may be of interest to those
involved in this discussion of doing a Ph.D. thesis that follows
closely someone else's work as opposed to striking off in some
completely new direction.
In Allen Newell's presidential address to AAAI in 1981, he comments on
the SIGART "Special Issue of Knowledge Representation" in which Ron
Brachman and Brian Smith present the answers to an elaborate
questionnaire sent to members of the AI community to find out their
views on knowledge representation.
"The main result was overwhelming diversity--a veritable jungle of
opinions. There is no consensus on any question of substance. ...
Many (but of course not all?) respondents themselves felt the same way.
As one said, 'Standard practice in the representation of knowledge is
the scandal of AI.'
"What is so overwhelming about the diversity is that it defies
characterization. ... There is no tidy space of underlying issues in
which respondents, hence the field, can be plotted to reveal a pattern
of concerns or issues. Not that Brachman and SMith could see. Not
that this reader could see."
By encouraging students to do their research on a subject by taking a
completely new approach, we are denying the value of previous work.
Certainly there is room for some Ph.D. students to take this path. But
a large part of what AI should be doing is building on the foundations
laid by the previous generations of researchers.
Spencer Star
------------------------------
Date: Mon, 9 Nov 87 15:11:19 PDT
From: ladkin@kestrel.ARPA (Peter Ladkin)
Subject: the wonder of words
gee, first ken laws says that maybe ai researchers don't need to think
too deeply, but maybe build whimsical experimental systems, and now
he's saying that automatic programming won't work because algorithms
are just too hard to design. i praise him for his consistency - one view
certainly follows from the other. i might use the old five-letter
expletive popularised by t.j. watson.
peter ladkin
ladkin@kestrel.arpa
------------------------------
Date: Tue, 10 Nov 87 11:25:52 MET
From: Laurent Siklossy <mcvax!cs.vu.nl!siklossy@uunet.UU.NET>
Subject: In Defense of FORTRAN
FORTRAN and other "standard" programming languages have
been used for years for advanced AI. One of the French AI
pioneers (if not THE pioneer, Ph.D. around 1961(?)),
Dr. Jacques Pitrat, has programmed for years in FORTRAN
with his own extensions. His programs included
discovering interesting logical theorems, learning in
the domain of games (chess), and many other areas.
Prof. Jean-Louis Lauriere wrote his Ph.D. thesis
(Universite de Paris VI, 1976; see his 100+ pages
article about that in the AI Journal, 1977 I think) in
PL/1. Lauriere's system was, in my opinion, the first
real (powerful) general problem solver, and remains a top
performing system in the field. (Lauriere may have been
pushed into using PL/1 by lack of other more appealing
choices, I cannot remember for sure.)
So it has been done, therefore you can do it too. I would
not recommend it, but that may be a matter of taste or
of limitations.
Laurent Siklossy
Free University, Amsterdam
siklossy@cs.vu.nl
---------------------------------------------------
Ken:
You are welcome to send above via the net if you find
it useful.
Cheers, LS
------------------------------
Date: Wed 11 Nov 87 21:42:50-PST
From: Laurence I. Press <LPRESS@venera.isi.edu>
Subject: FORTRANecdote
As a student assistant to Earl Hunt in the mid 1960s I wrote "concept
acquisition" programs in FORTRAN -- see the book Experiments in Induction,
Hunt, Marin and Stone, Academic Press, around 1965 if you don't believe it.
After that I wrote induction programs in JOVIAL too.
Larry
------------------------------
End of AIList Digest
********************
∂16-Nov-87 0101 LAWS@KL.SRI.COM AIList V5 #269 - Inference, Sphexishness, Object-Oriented Databases
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 16 Nov 87 01:01:01 PST
Date: Sun 15 Nov 1987 22:09-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #269 - Inference, Sphexishness, Object-Oriented Databases
To: AIList@SRI.COM
AIList Digest Monday, 16 Nov 1987 Volume 5 : Issue 269
Today's Topics:
Neuromorphics - Inference,
Methodology - Animal Behavior and AI & Traditional Techniques,
Bibliography - Object-Oriented Databases
----------------------------------------------------------------------
Date: Sun, 15 Nov 87 11:53:10 EST
From: Brady@UDEL.EDU
Subject: bpsim code
I am interested in inferring concepts from data, and have
been reading about back propagation in neural nets as a
way to make such inferences.
I am confused about the little red riding hood article in BYTE.
The article seems to suggest that the nodes in the middle layer
(representing the concepts wolf, granny, woodcutter)
are INFERRED during training. Other literature on back propagation
that I have seen also suggest that concepts can be inferred
that way. But a look at the BPSIM code that implements the little red
riding hood network seems to suggest the existance of these three nodes
before training begins. So my question is: if one wants to infer
concepts from data, can one do that by using back propagation?
Or do you still have to a priori anticipate the existance of the
concepts?
[I haven't seen the example in question, but the usual neural network
learning procedure does use predefined nodes. The nodes of the center
layer are identical except for random variations in the initial
weights. After training, these nodes take on very different roles
characterized by their weight vectors. Determining what these roles
are can be quite difficult, so it is not clear how much of the inference
is done by the network and how much by the human -- but clearly the
network has done part of the work. This strategy permits nodes to be
deleted (via zeroed weights), but not created. For creation of nodes
you may have to investigate genetic learning algorithms. -- KIL]
------------------------------
Date: 13 Nov 87 23:30:58 GMT
From: Michael P. Smith <mps@cs.duke.edu>
Reply-to: mps@duke.UUCP (Michael P. Smith)
Subject: Re: animal behavior and AI
Article-I.D.: duke.10631
In article <8711110303.AA28544@ADS.ARPA> dan@ADS.ARPA (Dan Shapiro) writes:
> ... My goal is to develop a realistic view of what
>planning means to simple animals (at the level of ants for example)
>and use that information to motivate planning architectures within AI.
>Within this context, my focal point is to look at *errors* in animal
>behavior, as when ants build circular bridges out of their own bodies,
>and the ones on top simply run themselves to death.
Hofstadter calls such revealing lapses of animal cunning "sphexishness"
after a famous example from Wooldridge. Chapter 2 of Dennett provides
more philosophical analysis of the phenomenon.
Dennett, Daniel C. _Elbow Room_, MIT 1984.
Hofstadter, Douglas. "On the Seeming Paradox of Mechanizing
Creativity," _Scientific American_ (September 1982), reprinted as
chapter 23 of _Metamagical Themas_, Basic Books, 1985.
Wooldridge, Dean. _The Machinery of the Brain_, McGraw Hill, 1963.
----------------------------------------------------------------------------
Michael P. Smith mps@cs.duke.edu / {seismo,decvax}!mcnc!duke!mps
"V. That which a lover takes against the will of his beloved has no relish."
Andreas Capellanus' "Rules of Love" from _The Art of Courtly Love_
------------------------------
Date: 9 Nov 87 01:53:52 GMT
From: clyde!burl!codas!killer!usl!usl-pc!jpdres10@rutgers.edu (Green
Eric Lee)
Subject: Re: Practical effects of AI (speech)
In message <267@PT.CS.CMU.EDU>, kfl@SPEECH2.CS.CMU.EDU (Kai-Fu Lee) says:
>In article <12@gollum.Columbia.NCR.COM>, rolandi@gollum.Columbia.NCR.COM
(rolandi) writes:
>> It would seem to me that the single greatest practical advancement for
>> AI will be in speaker independent, continuous speech recognition. This
>(3) If this product were to materialize, it is far from clear that it
> would be an advancement for AI. At present, the most promising
> techniques are based on stochastic modeling, pattern recognition,
> information theory, signal processing, auditory modeling, etc..
> So far, very few traditional AI techniques are used in, or work well
> for speech recognition.
Very few traditional AI techniques have resulted in much at all :-)
(sorry, I couldn't help it).
But seriously, considering that sciences such as physics and
mathematics have been ongoing for centuries, can we REALLY say that AI
has "traditional techniques"? Certainly there is a large library of
techniques available to AI researchers today, but 30 years is hardly
a long enough time to call something "traditional". Remembering how
going beyond the "traditional" resulted in many breakthroughs in
mathematics and physics, saying that "it is far from clear that it
would be an advancement for AI" presupposes that one defines AI as
"that science which uses certain traditional methods", which, I
submit, is false.
--
Eric Green elg@usl.CSNET from BEYOND nowhere:
{ihnp4,cbosgd}!killer!elg, P.O. Box 92191, Lafayette, LA 70509
{ut-sally,killer}!usl!elg "there's someone in my head, but it's not me..."
------------------------------
Date: 14 Nov 87 17:43:45 GMT
From: nosc!humu!uhccux!lee@sdcsvax.ucsd.edu (Greg Lee)
Subject: Re: Practical effects of AI (speech)
In article <244@usl-pc.UUCP> jpdres10@usl-pc.UUCP (Green Eric Lee) writes:
>In message <267@PT.CS.CMU.EDU>, kfl@SPEECH2.CS.CMU.EDU (Kai-Fu Lee) says:
>>In article <12@gollum.Columbia.NCR.COM>, rolandi@gollum.Columbia.NCR.COM
(rolandi) writes:
>>> It would seem to me that the single greatest practical advancement for
>>> ...
>> So far, very few traditional AI techniques are used in, or work well
>> for speech recognition.
>
>Very few traditional AI techniques have resulted in much at all :-)
I suppose that applying AI to speech recognition would involve
making use of what we know about the perceptual and cognitive nature
of language sound-structures -- i.e. the results of phonology. I don't
know that this has ever been tried. If it has, could someone supply
references? I'd be very interested to know what has been done in this
direction.
Greg Lee, lee@uhccux.uhcc.hawaii.edu
------------------------------
Date: 13 Nov 87 22:11:40 GMT
From: clyde!burl!codas!killer!pollux!ti-csl!!peterson@rutgers.edu
(Bob Peterson)
Subject: Re: object oriented database query
In article <4528@cc5.bbn.COM> mfidelma@bbn.COM (Miles Fidelman) writes:
>Can anyone point me to work in the area of applying database technology
>to supporting object oriented environments?
Sure. See the short bibliography attached to the end of this message.
It is about two pages in length. Several publications are of special
interest: Proceedings of OOPSLA '86 and '87, and the Proceedings of the
OODB Workshop held in '86 in Pacific Grove, CA. In each of these you'll
find interesting articles addressing OODB issues, as well as many
additional references following each article.
>It strikes me that database technology tends to focus on supporting large
>production databases, with attention to fast processing speeds, maintaining
>database integrity, journalizing/checkpointing, etc.; while object oriented
>environments are basically prototyping environments.
I don't believe OODB's are, as you put it, "...basically prototyping
environments." Indeed, there are applications, such as VLSI CAD and
hypertext, that are not well-supported by conventional databases.
When implemented using an object-oriented style, these applications
use many objects with rather complex and dynamic interconnections.
Conventional data models, i.e., hierarchical, network, and relational,
don't handle the complex, dynamic interconnected objects very well.
At least that's my opinion.
>Has anyone been working on making a production object oriented environment?
Yes, we at Texas Instruments are working on just such an effort. In
addition there are at least three companies now offering for sale
object-oriented database systems.
Hardcopy and Electronic Addresses:
Bob Peterson Compuserve: 76703,532
P.O. Box 1686 Usenet: peterson@csc.ti.com
Plano, Tx USA 75074 (214) 995-6080
(Skip the rest of this message if you aren't interested in two pages
of bibliographic references.)
!
OBJECT-ORIENTED DATABASE SYSTEMS BIBLIOGRAPHY
[BCG*87]J. Bannerjee, H.T. Chou, J.F. Garza, W. Kim, D.
Woelk, N. Ballou, and H.J. Kim. Data Model Issues For
Object-Oriented Applications. ACM Transactions on Office
Information Systems, January 1987.
[BD81] A. J. Baroody and D. J. DeWitt. An Object-
Oriented Approach to Database System Implementation.
ACM Transactions on Database Systems, 6(4):576-601,
December 1981.
[bFL85] Edited by F. Lochovsky. IEEE Database Engineering.
December 1985. A quarterly bulletin of the IEEE Computer
Society Technical Committee on Database Engineering,
Special Issue on Object-Oriented Systems.
[But86] M. H. Butler. An Approach to Persistent LISP Objects. In
Proc. COMPCON, pages 324-329, IEEE, San Fransisco, CA,
March 1986.
[CAC*84]W. Cockshott, M. Atkinson, K. Chisholm, P. Bailey,
and R. Morrison. Persistent Object Management System.
Software Practice and Experience, 14:49-71, 1984.
[Mis84] N. Mishkin. Managing Permanent Objects. Technical
Report YALEU/DCS/RR-338, Department of Computer Science,
Yale University, New Haven, CT, November 1984.
[ML87] T. Merrow and J. Laursen. A Pragmatic System for Shared
Persistent Objects. In N. Meyrowitz, editor, OOPSLA '87
Conference Proceedings, pages 103-110, ACM, ACM, New
York, NY, Oct 4-8 1987.
[Nie85] O. M. Nierstrasz. Hybrid: A Unified Object-Oriented
System. IEEE Database Engineering, 8(4):49-57, December
1985.
[OBS86] P. O'Brien, B. Bullis, and C. Schaffert. Persistent
and Shared Objects in Trellis/Owl. In Proceedings
of the 1986 International Workshop on Object-Oriented
Database Systems, pages 113-123, ACM, Pacific Grove,
CA, September 1986.
!
[OOD86] Proceedings of the International Workshop on Object
Oriented Database Systems, Pacific Grove, CA, September
1986. ACM.
[OOP86] ACM. Conference Proceedings for the Object-Oriented
Programming Systems, Languages and Applications '86
Conference (OOPSLA '86), Portland, OR, Sept 29-Oct 2 1986
Panel Discussion.
[Pet87] R. W. Peterson. Object-Oriented Database Design. AI
Expert, 2(3):27-31, March 1987.
[SR86] M. Stonebraker and L. Rowe. The Design of POSTGRES. In
Proceedings of SIGMOD, pages 340-355, Washington D.C.,
December 1986.
[SZ86] A. Skarra and S. Zdonik. The Management of Changing
Types in an Object-Oriented Database. In Norman
Meyrowitz, editor, OOPSLA '86 Conference Proceedings,
pages 483-495, ACM, ACM, Portland, OR, September 1986.
[SZ87] K. Smith and S.B. Zdonik. Intermedia: A Case Study of
the Differences Between Relational and Object-Oriented
Database Systems. In N. Meyrowitz, editor, OOPSLA '87
Conference Proceedings, pages 452-465, ACM, ACM, New
York, NY, Oct 4-8 1987.
[SZR86] A. S. Skarra, S. Zdonik, and S. Reiss. An Object
Server for an Object Oriented Database System. In
International Workshop on Object Oriented Database
Systems, pages 196-205, Pacific Grove, CA, September
1986.
[Tho86] C. Thompson. Object-oriented databases. Texas In-
struments Engineering Journal, 3(1):169-175, Jan. 1986.
[TMT86] C.W. Thompson, S. Martin, and S. Thatte. Real-Time
Object-Oriented Manufacturing Databases. In AAAI 1986
Workshop on AI in Manufacturing, Aug 1986.
[Wie86] G. Wiederhold. Views, Objects, and Databases. IEEE
Computer, ():37-44, December 1986.
Hardcopy and Electronic Addresses: Office:
Bob Peterson Compuserve: 76703,532 NB 2nd Floor CSC Aisle C3
P.O. Box 1686 Usenet: peterson@csc.ti.com
Plano, Tx USA 75074 (214) 995-6080 (work) or (214) 596-3720 (ans. machine)
------------------------------
End of AIList Digest
********************
∂18-Nov-87 0233 LAWS@KL.SRI.COM AIList V5 #270 - Games, Learning, Pattern Recognition, Law
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 18 Nov 87 02:33:37 PST
Date: Tue 17 Nov 1987 23:30-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #270 - Games, Learning, Pattern Recognition, Law
To: AIList@SRI.COM
AIList Digest Wednesday, 18 Nov 1987 Volume 5 : Issue 270
Today's Topics:
Queries - AI systems in Design & KAT Acronym,
Games - Mancala/Kalah,
Learning - Genetic Algorithms,
Pattern Recognition - Measures of "Englishness",
Law - Who Owns the Output of an AI?
----------------------------------------------------------------------
Date: 16 Nov 87 15:43:59 GMT
From: ece-csc!ncrcae!ncr-sd!ncrlnk!rd1632!king@mcnc.org (James King)
Subject: Survey of AI systems in Design
I am in need of information about one topic and a subtopic.
I am compiling a list of AI systems used in the design phase of:
- products
- materials
- costs
- scheduling
- etc.
My focus is on the first two, but any and all are welcome. I am
looking for AI systems in CAD and in Pre-CAD design. Typical
intelligent CAD systems I am interested in assist in:
- Saving integrity between drawings - products with multiple
drawings are structured to recognize a change in one drawing
and pass it to other associated drawings.
- Management systems in CAD for information, integrity, design
experience representation, etc.
- Encapsulation of designer experience into KB's
- Uses of OOP, frames, etc.
- Application of situational reasoning
- Hardware implementations
- etc.
The second topic deals with developing knowledge bases of designer
experience, techniques, rules in the design phase. I am interested in the
representational techniques, elicitation techniques, etc. that have been used
to encapsulate the design experience associated with:
- A part
- A specific domain
- An entire system
- A manufacturing line
- Etc.
I would appreciate any information on these two areas and associated
topics of Design automation and AI.
Thank you in advance
James A. King j.a.king@dayton.ncr.com
------------------------------
Date: Tue, 17 Nov 87 08:43 N
From: MFMISTAL%HMARL5.BITNET@wiscvm.wisc.edu
Subject: Request for info in acronym KAT
We are planning to submit a grant proposal for the development of
a knowledge acquisition tool. To us it looks obvious to use "KAT"
as the acronym. However, maybe someone else uses KAT already.
If anyone has information on one or more systems named KAT,
please let me know.
Thanks in advance.
Jan L. Talmon
Dept. Medical Informatics and Statistics
University of Limburg
The Netherlands
EMAIL: MFMISTAL@HMARL5.bitnet
------------------------------
Date: 16 Nov 87 17:58:42 GMT
From: mit-caf!jtkung@media-lab.media.mit.edu (Joseph Kung)
Subject: AI gaming : mancala
Anybody out there have any interesting gaming strategies for the
African game, mancala? I need some for an AI game that a friend of
mine is working on. Thanks.
- Joe
--
Joseph Kung
Arpa Internet : jtkung@caf.mit.edu
------------------------------
Date: 17 Nov 87 05:22:20 GMT
From: srt@locus.ucla.edu
Subject: Re: AI gaming : mancala
In article <542@mit-caf.UUCP> jtkung@mit-caf.UUCP (Joseph Kung) writes:
>Anybody out there have any interesting gaming strategies for the
>African game, mancala? I need some for an AI game that a friend of
>mine is working on. Thanks.
If 'mancala' is any variant of Kalah, you might want to look at *The
Art of Prolog* by Sterling and Shapiro, which includes a Prolog implementation
of Kalah.
Scott R. Turner
UCLA Computer Science "Love, sex, work, death, and laughs"
Domain: srt@cs.ucla.edu
UUCP: ...!{cepu,ihnp4,trwspp,ucbvax}!ucla-cs!srt
------------------------------
Date: 16 Nov 87 18:59:26 GMT
From: tsai%pollux.usc.edu@oberon.usc.edu (Yu-Chen Tsai)
Reply-to: tsai%pollux.usc.edu@oberon.usc.edu (Yu-Chen Tsai)
Subject: Re: bpsim code
In article <8711151153.aa02040@Dewey.UDEL.EDU> Brady@UDEL.EDU writes:
>I am confused about the little red riding hood article in BYTE.
>The article seems to suggest that the nodes in the middle layer
> .....
and KIL's comment follows:
> This strategy permits nodes to be
> deleted (via zeroed weights), but not created. For creation of nodes
> you may have to investigate genetic learning algorithms. -- KIL]
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
I am interested in these genetic learning algorithms used in a neural network
implementaion. Can somebody in the Netland gives me some references? Please
response by e-mail to me. Thanks in advance!
Y. C. Tsai :-)
tsai@pollux.usc.edu fot Internet, {sdcrdc,cit-cav}!uscvax!tsai for UUCP
EE-Systems,
University of Southern California, Ca. 90089-0781
------------------------------
Date: 17 Nov 87 06:16:54 GMT
From: deneb.ucdavis.edu!g523116166ea@ucdavis.ucdavis.edu
(0040;0000004431;0;327;142;)
Subject: Re: references for adaptive systems
Another, obligatory, reference, is John Holland, et al, INDUCTION, new this
year or last. The first three chapters are about Holland's genetic algorithms,
which are sucessful algorithms for adding new rules to a formal system, based
on experience. Not so high profile as neural nets, but more general and more
enduring, I'll wager. Holland has been at this since the early 60's; he's
at U. Michigan. The remainder of the book is fascinating studies of how
people generally use 'rules', in contrast to how machines use them. This
latter material is clearly about induction 'au natural', and nicely summarized
in a paper in the 10/30 issue of Science by some of the same authors, sans
Holland.
Holland's PhD students do odd theses: adaptive control of a refinery; pallett-
loading scheduling; other pragmatic stuff. Why?
Ron Goldthwaite
UCalif, Davis, Psychology & Animal Behavior
------------------------------
Date: 15 Nov 87 19:27:10 GMT
From: cunyvm!byuvax!fordjm@psuvm.bitnet
Subject: Measures of "Englishness"?
Recently someone on the net commented on a program or method of rating
the "Englishness" of words according to the frequency of occurance of
various letters in sequence, etc.
I am currently involved in a project in which this approach might prove
useful, but I have lost the original posting. Could the author please
contact me with more information about his or her project?
Thanks in advance,
John M. Ford fordjm@byuvax.bitnet
131 Starcrest Drive
Orem, UT 84058
------------------------------
Date: 17 Nov 87 17:48:04 GMT
From: PT.CS.CMU.EDU!SPEECH2.CS.CMU.EDU!kfl@cs.rochester.edu (Kai-Fu
Lee)
Subject: Re: Measures of "Englishness"?
In article <32fordjm@byuvax.bitnet>, fordjm@byuvax.bitnet writes:
>
> Recently someone on the net commented on a program or method of rating
> the "Englishness" of words according to the frequency of occurance of
> various letters in sequence, etc.
>
I don't know anything about the said post. But you might be interested
in the following article:
Cave and Neuwirth, Hidden Markov Models for English, Proceedings
of the Symposium on Appication of Hidden Markov Models to Text
and Speech, Princeton, NJ 1980.
Here's the editor's summary of the paper:
L.P. Neuwirth discusses the application of hidden Markov analysis to
English newspaper text (26 letters plus word space, without
punctuation). This work showed that the technique is capable
of automatically discovering linguistically important categorizations
(e.g., vowels and consonants). Moreover, a calculation of the
entropy of these models shows that some of them are stronger than
the ordinary digraphic model, yet employ only half as many parameters.
But one of the most interesting points, from a philosophical point
of view, is the completely automatic nature of the process of
obtaining the model: only the size of the state space, and a
long example of English text, are give. No a priori structure of the
state transition matrix, or of the output probabilities is assumed.
Since hidden Markov models can be used for generation and recognition,
it is possible to train a model for English, and "score" any previously
unseen word with a probability that it was generated by the model for
English.
> Thanks in advance,
> John M. Ford fordjm@byuvax.bitnet
> 131 Starcrest Drive
> Orem, UT 84058
>
Kai-Fu Lee
Computer Science Department
Carnegie-Mellon University
------------------------------
Date: 12 Nov 87 11:12:03 GMT
From: ihnp4!homxb!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT)
Subject: Re: Who owns the output of an AI?
In article <4631@spool.wisc.edu>, honavar@speedy.WISC.EDU
(A Buggy AI Program) writes:
> In article <1778@svax.cs.cornell.edu> houpt@svax.cs.cornell.edu
(Charles (Chuck) Houpt) writes:
> > The law says that the output of an AI is owned by the user running the
> >AI, NOT the programmer who designed it.
> > ....
> > ... To me the British law seems unfair.....
It's just like the law governing real intelligence. Your
teachers created (or at least created a lot of value added in)
your intelligence, but a stroke of your pen will assign any
patents you create to your employer. Though your teachers may
know more about your work than your employer, they have no claim
on the intellectual property you create after you leave their
campus.
M. B. Brilliant Marty
AT&T-BL HO 3D-520 (201)-949-1858
Holmdel, NJ 07733 ihnp4!houdi!marty1
------------------------------
Date: 13 Nov 87 13:15:14 GMT
From: nosc!humu!uhccux!lee@sdcsvax.ucsd.edu (Greg Lee)
Subject: Re: Who owns the output of an AI?
M. Brilliant writes:
>...
>patents you create to your employer. Though your teachers may
>know more about your work than your employer, they have no claim
I assume that in this analogy, the programmer
is the "teacher", the AI program is "you" and
the user of the program is the "employer".
------------------------------
Date: 14 Nov 87 12:27:59 GMT
From: speedy!honavar@speedy.wisc.edu (A Buggy AI Program)
Subject: Re: Who owns the output of an AI? (actually wonders of rn)
In article <1412@houdi.UUCP> marty1@houdi.UUCP (M.BRILLIANT) writes:
>In article <4631@spool.wisc.edu>, honavar@speedy.WISC.EDU (A Buggy AI Program)
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑ ↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
writes:
>> In article <1778@svax.cs.cornell.edu> houpt@svax.cs.cornell.edu
(Charles (Chuck) Houpt) writes:
>> > The law says that the output of an AI is owned by the user running the
>> >AI, NOT the programmer who designed it.
>> > ....
>> > ... To me the British law seems unfair.....
>
>It's just like the law governing real intelligence.
> ......
>
>M. B. Brilliant Marty
>AT&T-BL HO 3D-520 (201)-949-1858
>Holmdel, NJ 07733 ihnp4!houdi!marty1
It's probably about time some AI was put into the news software so that it can
make sure that the pieces of article/s quoted are really from the authors
to whom the quotes attributed.
--VGH
------------------------------
Date: 14 Nov 87 17:29:00 GMT
From: kadie@b.cs.uiuc.edu
Subject: Re: Who owns the output of an AI?
If your AI program (or any program) is really great there
are a number of ways to make more money per user from it.
One way that was already mentioned is to licence it. I remember
that some of the first compilers for microcomputers said that
you had to pay them money for any programs you sold that
were compiled with their product.
Another method is to charge for each run of your program. You do
this by setting up your own computer and having people dial in to
it. I know that this system is used by some companies that
have (non AI) programs that solve financial optimization problems.
The trouble with both these methods is that the
users don't like them as well as owning the program,
so you will not have as many costumers.
Carl Kadie
Inductive Learning Group
University of Illinois at Urbana-Champaign
UUCP: {ihnp4,pur-ee,convex}!uiucdcs!kadie
CSNET: kadie@UIUC.CSNET
ARPA: kadie@M.CS.UIUC.EDU (kadie@UIUC.ARPA)
------------------------------
Date: 16 Nov 87 15:07:14 GMT
From: yale!kthomas@NYU.EDU (Kevin Thomas)
Subject: Re: Who owns the output of an AI?
In article <1778@svax.cs.cornell.edu> houpt@svax.cs.cornell.edu (Charles
(Chuck) Houpt) writes:
> Is this fair? Should copywrites go to the user or the programmer?
> If my AI program discovered
>a new high temperature super-conductor, shouldn't I get some profit?
The copyrights and patents should all go to the user, absent any contractual
agreements to the contrary. This is the same debate that went on about
10-15 years ago with compilers. Updated to the mid-80's, if I write a
program in Turbo C that Peugeot sells, should Borland be entitled to royalties?
The answer is "no, unless they say so in the sale contract, and the buyer
clearly agrees to the language in that contract".
Actually, in the case of derived products, it's worse: If Peugeot uses a
Turbo C program to design a car, should Borland get a cut of the profits that
result from the sale of the car, in the absence of any language in the
sale contract? I would again say "no". Borland is free to put language
into the contract that does or does not reserve whatever rights it wants or
does not want.
/kmt
------------------------------
Date: 18 Nov 87 02:39:12 GMT
From: allegra!jac@ucbvax.Berkeley.EDU (Jonathan Chandross)
Subject: My parents own my output.
If I write a program that generates machine code from a high level language
do I not own the output? Of course I own it. I also own the output from
a theorum prover, a planner, and similar systems, no matter how elaborate.
One of the assumptions being made in this discussion is that an AI can be
treated as a person. Let us consider, for the moment, that it is merely
a clever piece of programming. Then I most *certainly* do own its output
(assuming I wrote the AI) by the reason given above. (Software piracy is a
whole other ball of wax.)
The alternative is to view the AI as an sentient entity with rights, that
is, a person. Then we can view the AI as a company employee who developed
said work on a company machine and on company time. Therefore the employer
owns the output, just as my employer owns my output done on company time.
The real question should be: Did the AI knowlingly enter into a contract with
the employer.
I wonder if the ACLU would take the case.
Jonathan A. Chandross
AT&T Bell Laboratories
Murray Hill, New Jersey
{moss, rutgers}!allegra!jac
------------------------------
End of AIList Digest
********************
∂25-Nov-87 0216 LAWS@KL.SRI.COM AIList V5 #271 - Genetic Learning, Statistics, Benchmarking, Msc.
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 25 Nov 87 02:15:59 PST
Date: Sun 22 Nov 1987 23:13-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #271 - Genetic Learning, Statistics, Benchmarking, Msc.
To: AIList@SRI.COM
AIList Digest Monday, 23 Nov 1987 Volume 5 : Issue 271
Today's Topics:
Queries - Constraint Satisfaction & Systems Developed using AI Tools/Shells,
Learning - Genetic Learning Systems & Adaptive Systems,
Expert Systems - Statistical Expert Systems & Benchmarking,
Games - Mancala Reference,
Applications - Speech Understanding,
Comments - Success of AI & Who Owns the Output of an AI?
----------------------------------------------------------------------
Date: Fri 20 Nov 87 17:27:35-CST
From: Charles Petrie <AI.PETRIE@MCC.COM>
Reply-to: Petrie@MCC.com
Subject: Constraint Satisfaction Query
Does someone know a pointer to software and algorithms that relax
constraints and reason about which to relax first? In particular,
does anyone know of a linear programming system which does not
satisfy all constraints and which allows a partial ordering on the
satisfaction of the constraints?
------------------------------
Date: 19 Nov 87 12:00:00 GMT+109:13
From: santino@esdvax.arpa
Reply-to: <santino@esdvax.arpa>
Subject: INFO REQUESTED ON SYSTEMS DEVELOPED USING AI TOOLS/SHELLS
I N T E R O F F I C E M E M O R A N D U M
Date: 19-Nov-1987 12:00
From: Fred Santino
Username: SANTINO
Dept: ESD/SCPM
Tel No: x5316
TO: _MAILER! ( _DDN[AILIST@SRI.COM] )
Subject: INFO REQUESTED ON SYSTEMS DEVELOPED USING AI TOOLS/SHELLS
1. We're interested in knowing of examples of "real world" expert
systems developed using commercially available expert system
tools/shells, particularly those which have applicability to our
present "CGADS" development, and any other information useful prior to
our selecting a tool. Some preliminary background on our "CGADS"
project is provided:
2. The Computer Generated Acquisition Document System (CGADS) is the USAF
Electronic Systems Division (ESD) first-generation expert system which
assists DOD program managers and engineers in creation of acquisition
documents such as "Statements of Work" which become part of Government
"Request For Proposals" (RFP's) for major DOD systems projects.
CGADS, presently running on a VAX 8600, is used operationally by the USAF
Electronic Systems Division, as well by a large number of other DOD
acquisition agencies nationwide. CGADS is also used at the Air Force
Institute of Technology to teach systems acquisition management.
CGADS, used equally by experienced and inexperienced engineers,
presents a series of yes/no questions, such as type of equipment,
logistics, safety, production, phase of development, and degree of
commercial off-the-shelf components. Based on the engineer's
choices, CGADS generates the proper "boiler-plate" text and MIL-STD
references to form a draft Statement of Work.
Since the system text and rules are updated periodically by experts
who represent several dozen technical disciplines, the resulting
document meets most requirements, and needs only minimum review. The
system also allows newly assigned engineers, having only minimum
training, to create draft acquisition documents.
Since CGADS was first developed in 1981 exclusively in Fortran 77, and
without using a database, it has become unnecessarily expensive to
keep the text updated. Also, its structure lacks the flexibility for
planned capabilities, such as producing the greatly varying system
specifications for major DOD acquisition programs.
3. We plan to use an ORACLE database to improve the text storage, and to
select a commercial expert system tool/shell to minimize development
of an inference engine, and maintenance utility. Some examples of
AI tools we may evaluate:
Knowledge Engineering Environment (KEE), Intellicorp, Menlo Park, CA
Knowledge Engineering System (KES), Software A&E, Arlington, VA
The Intelligent Machine Model (TIMM), Gen Research, Santa Barbara, CA
OPS5, Carnegie Mellon Univ, Pittsburgh, PA
Expert, Rutgers Univ, New Brunswick, NJ
S1 or M1, Teknowledge, Inc., Palo Alto, CA
Automated Reasoning Tool (ART), Inference Corp, Los Angeles, CA
4. We'd be interested in knowing the type of application, the amount of
programming that was required to "tailor" the commercial shell/tool
for the application, and the amount of maintenance required.
In addition to providing information on actual systems developed
using commercial tools, we'd appreciate hearing any lessons learned,
or recommendations both positive and negative that anyone is willing
to share, even "horror stories" about developments that never made it,
or products to avoid (if any).
5. Please answer on AILIST, or directly to SANTINO@ESDVAX.ARPA,
or call Autovon 478-5316, or Commercial 617-377-5316.
Thanks,
Fred Santino
Project Engineer
USAF Electronic Systems Division (ESD/SCP)
Hanscom AFB, MA 01731
------------------------------
Date: Wed, 18 Nov 87 08:42:55 est
From: John Grefenstette <gref@nrl-aic.ARPA>
Subject: Re: references for genetic learning systems
The following books give a good overview of genetic learning
systems:
Adaptation in Natural and Artificial Systems,
J. H. Holland, Univ. Michigan Press: Ann Arbor, 1975.
Induction: Processes of Inference, Learning, and Discovery,
J. H. Holland, K. J. Holyoak, R. E. Nisbett and P. A. Thagard,
MIT Press: Cambridge, 1986.
Genetic Algorithms and Simulated Annealing,
L. Davis (ed.), Pitman: London, 1987.
Genetic Algorithms and Their Applications:
Proceedings of the 2nd Intl. Conf. Genetic Algorithms,
J. J. Grefenstette (ed.), Lawrence Erlbaum Assoc: Hillsdale, 1987.
There is also a bulletin board devoted to genetic algorithms
and related topics. To join, send a request to:
GA-List-Request@NRL-AIC.ARPA
-- JJG
------------------------------
Date: Wed, 18 Nov 87 08:54:55 est
From: Lashon Booker <booker@nrl-aic.ARPA>
Subject: Re: references for adaptive systems
Ron Goldthwaite of UCalif, Davis asks
> Holland's PhD students do odd theses: adaptive control of a refinery;
> pallett-loading scheduling; other pragmatic stuff. Why?
In fact, a large number of Holland's PhD students have done theses that
are not "pragmatic" at all in the way you indicate. Here are a few examples
that come to mind:
Rosenberg, R. S. (1967) "Simulation of genetic populations with biochemical
properties", studies the evolution of populations of single-celled organisms.
Reynolds, R. G. (1979) "An adaptive computer model of the evolution of
agriculture for hunter-gatherers in the valley of Oaxaca, Mexico",
a study that explains a body of archaeological findings.
Booker, L. B. (1982) "Intelligent behavior an an adaptation to the task
environment", a computational model of cognition and learning
in simple creatures.
Perry, Z. A. (1984) "Experimental study of speciation in ecological
niche theory using genetic algorithms"
Grosso, P. B. (1985) "Computer simulation of genetic adaptation: Parallel
subcomponent interaction in a multilocus model", studies diploid
representations and explicit migration among subpopulations.
There are many other articles and tech reports of a similar nature having to do
with genetic algorithms and classifier systems. The "pragmatic stuff" seems
to be the work that is most interesting to the AI community.
Lashon Booker
booker@nrl-aic.arpa
------------------------------
Date: 19 Nov 87 22:58:22 GMT
From: eric@aragorn.cm.deakin.OZ (Eric Y.H. Tsui)
Reply-to: eric@aragorn.UUCP (Eric Y.H. Tsui)
Subject: Re: Statistical Exp. Sys. Query
In article <563694273.0.LPRESS@VENERA.ISI.EDU> LPRESS@VENERA.ISI.EDU
(Laurence I. Press) writes:
>Can anyone give me pointers to programs and/or papers on statistical
>applications of expert systems?
>
>Larry
>-------
See Artificial Intelligence and Statistics, edited by William A. Gale,
Addison-Wesley, Reading, 1986.
---------------------------------------------------------------------------
Eric Tsui >> CSNET:eric@aragorn.oz <<
Division of Comp./Maths.>> UUCP: seismo!munnari!aragorn.oz!eric <<
Deakin University >> decvax!mulga!aragorn.oz!eric <<
Victoria 3217 >> ARPA: munnari!aragorn.oz!eric@seismo.arpa <<
Australia >> decvax!mulga!aragorn.oz!eric@Berkeley <<
------------------------------
Date: 19 Nov 87 23:03:27 GMT
From: eric@aragorn.cm.deakin.OZ (Eric Y.H. Tsui)
Reply-to: eric@aragorn.UUCP (Eric Y.H. Tsui)
Subject: Re: Exp. Sys. Benchmarking Query
In article <563694555.0.LPRESS@VENERA.ISI.EDU> LPRESS@VENERA.ISI.EDU
(Laurence I. Press) writes:
>Can anyone supply pointers to papers on benchmarking and performance
>evaluation for expert system shells?
>
>I have written a short program that generates stylized rule bases of
>a specified length and have used it to generate comparative test cases
>for PC Plus and M1. I'd be happy to give anyone a copy and would like
>to learn of other efforts to compare expert system shells.
>
>Larry
>-------
On evaluation of Expert System tools, see J.F. Gilmore, K. Pulaski
and C. Howard, A Comprehensive evaluation of expert system tools,
Applications of AI III, J.F. Gilmore, Editor, Proc. 635, p2-16.
(The above group has published a few papers on the evaluation of ES
and the above paper is only a recent one of many from them.)
---------------------------------------------------------------------------
Eric Tsui >> CSNET:eric@aragorn.oz <<
Division of Comp./Maths.>> UUCP: seismo!munnari!aragorn.oz!eric <<
Deakin University >> decvax!mulga!aragorn.oz!eric <<
Victoria 3217 >> ARPA: munnari!aragorn.oz!eric@seismo.arpa <<
Australia >> decvax!mulga!aragorn.oz!eric@Berkeley <<
------------------------------
Date: 18 Nov 87 14:27:22 GMT
From: uvaarpa!virginia!uvacs!dsr@umd5.umd.edu (Dana S. Richards)
Subject: Re: AI gaming : mancala
>In article <542@mit-caf.UUCP> jtkung@mit-caf.UUCP (Joseph Kung) writes:
>>Anybody out there have any interesting gaming strategies for the
>>African game, mancala? I need some for an AI game that a friend of
>>mine is working on. Thanks.
There is a book "Mancala Games" by Laurence Russ, Reference Publ. Inc., 1984.
I haver not read it but it was reviewed in Math. Intelligencer 9(1987)68.
------------------------------
Date: 18 Nov 87 10:25:00 GMT
From: uxc.cso.uiuc.edu!osiris.cso.uiuc.edu!goldfain@a.cs.uiuc.edu
Subject: Re: Practical effects of AI (speech
I would like to echo the sentiment in Eric Green's comment.
Let us NOT try to define AI in terms of techniques. It is defined by its
domain of inquiry, and that clearly includes speech recognition. I do not for
a moment believe that continuous speaker-independent speech recognition,
if/when it is achieved, will be considered primarily a work of physics. No
matter how it is achieved, that is just not a viable statement.
- Mark Goldfain
------------------------------
Date: 16 Nov 87 17:43:50 GMT
From: PT.CS.CMU.EDU!SPEECH2.CS.CMU.EDU!kfl@cs.rochester.edu (Kai-Fu
Lee)
Subject: Re: Practical effects of AI (speech)
In article <244@usl-pc.UUCP>, jpdres10@usl-pc.UUCP (Green Eric Lee) writes:
> But seriously, considering that sciences such as physics and
> mathematics have been ongoing for centuries, can we REALLY say that AI
> has "traditional techniques"? . . . "it is far from clear that it
> would be an advancement for AI" presupposes that one defines AI as
> "that science which uses certain traditional methods", which, I
> submit, is false.
>
By "traditional techniques", I was referring to the older popular
techniques in AI, such as expert systems, predicate calculus, semantic
networks, etc. Also, I was trying to exclude neural networks,
which may be promising for speech recognition. I have heard of
"traditionalist vs. connectionist AI", and that is why I used the
term "traditional techniques".
Kai-Fu Lee
Computer Science Dept.
Carnegie-Mellon University
P.S. - I did not say that AI is a science.
------------------------------
Date: 15 Nov 87 13:56:12 GMT
From: eitan%WISDOM.BITNET@wiscvm.wisc.edu (Eitan Shterenbaum)
Reply-to: eitan%H@wiscvm.arpa (Eitan Shterenbaum)
Subject: Re: Success of AI
In article <> honavar@speedy.wisc.edu (A Buggy AI Program) writes:
>
>In article <4357@wisdom.BITNET> eitan%H@wiscvm.arpa (Eitan Shterenbaum) writes:
>>
>>Anyway, no one can emulate a system which has no specifications.
>>if the neuro-biologists would present them then you'd have something to start
>>with.
>
> I use the term "computer" in a sense somewhat broader than a
> Von-Neuman machine. We can, in principle, build machines that
↑↑↑↑↑↑↑↑↑↑↑↑
↑↑↑↑↑↑↑↑↑↑↑↑
> incorporate distributed representations, processing and control.
> It is not clear what you mean by a "distributed environment lacking
> boolean algebra."
> The use of fine-grained distributed representations naturally results
> in behavior indicative of processes using fuzzy or probabilistic logic.
> The goal is, not necessarily to emulate the brain in all its detail:
> We can study birds to understand the principles of aerodynamics that
> explain the phenomenon of flying and then go on to build an aeroplane
> that is very different from a bird but still obeys the same laws of
> physics. As for specifications, they can be provided in different
> forms and at different levels of detail; Part of the exercise is
> to discover such specifications - either by studying actual existing
> systems or by analyzing the functions needed at an abstract level to
> determine the basic building blocks and how they are to be put
> together.
>
a) You can't understand the laws under which a system works without
understanding the structure of the system ( I believe that our
intelligence is the result of our brain's structure )
b) The earodynamics example just prooves my point. Only after understanding
*WHY* the birds are built in a certain form the researchers would've
been able to understand the pronciples. The fact is that Leonardo de Vinci
knew more about aerodynamics than the pioneers of flight is acknowlodged
to the *research* he has done on birds. It seems to me that many AI
scientists disregard 2 facts a- They have no definition of AI
b- They disregard the fact that the best
way to have more knowledge about a certain
phenomennon is to observe and research it.
It seems to me that
1) You have no definition for Intelligence.
2) You want to have the rules of Itelligence.
3) Thus you build systems inorder to simulate Intelligence.
4) Since you don't know you're looking for and since you have no
basic rules to simulate the intelligence on, you invent your
own local definition and rules for Intelligence.
5) Then youtry to mach your results with your expectations of what
the results should be.
Sometimes it works some time it doesn't.
This method reminds me "random sort" I.E The computer has N numbers, It
randomly prints them out one by one and then it tries to check whether
they are ordered, if not - he does the above again. I hope that you've
noticed that the probability that you'd be correct is quite slime
( actually 1/N! ... )
>>
>>And last - Computers aren't meta-capable machines they have constraints,
>> not every problem has an answer and not every answermakes sense,
>> NP problems are the best example.
>>
> Are you implying that humans are "meta-capable" - whatever that means?
>
I'm trying to imply that human beings aren't Turing equivalent ...
( not even when compared to a non-determinitstic turing machine )
Correct me if I'm wrong but I do feel that the neuro-biologists chaps are
in the right track and that the Computer scientists should combine efforts
with them instead of messing around with AI.
(I'm not saying that AI isn't usefull, it is, just that it's very little
success in Inteligence and a grand success in Artificial artifacts ...)
Eitan Shterenbaum
Disclaimer - My ideas are mine and only mine !
@@@@@@@@@@@@@@@@@@@@@@@@@@@@
------------------------------
Date: 18 Nov 87 09:55:00 GMT
From: uxc.cso.uiuc.edu!osiris.cso.uiuc.edu!goldfain@a.cs.uiuc.edu
Subject: Re: Who owns the output of an AI?
Just to fan the flames, let me throw in 1 totally outlandish, 2 mildly
outlandish answers and a 4th that is not so bad (but I'm not sure whether I
buy the analogy.)
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
1) Newsflash. Microsoft today filed lawsuit against 250,000 authors of
various books and papers for violation of copyright. Said a Microsoft
spokesman, "Yes, these people really wrote the manuscripts, but then they
gave them, in very raw form, to our program which then took it upon itself
to edit, layout, and publish them. Our program actually owns the copy
rights to these items." When asked how his company managed to file a
quarter of a million legal documents in one day, the spokesman said "No
trouble, we just used Think Technology's 'legal councillor' program." A
second later, the Microsoft representative ran from the room muttering "Oh
no ..."
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
2) If the computer program is not intelligent enough to reply to the "raw"
data with :
"I don't know, nothing looks interesting here ..."
then to phone its author and say
"Hey Jaime, this formula makes a wonderful superconductor.
Do you want it, or should I tell Tom? "
then I doubt it has enough intelligence to "deserve" the credit itself.
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
3) In today's environment the user can shut off the machine and go get the
patent himself, claiming to have made the discovery without any computer
assistance. (Those who believe "an unenforceable law should not be a law"
may see some point in this.)
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
4) The user can claim "I did not ask the machine to find me a good
superconductor. All I asked it was whether this particular math problem
had a solution. The analogy leads us to the conclusion that we should give
credit to the author for a math theorem (and he probably already has that
credit in the literature), credit to the program for applying the theorem
to solve a particular math problem (usually quite technically difficult but
quite uninteresting to humans) and to the user for having applied the
solution of a math problem to discovery of a new superconductor.
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
Mark Goldfain arpa: goldfain@osiris.cso.uiuc.edu
US Mail: Mark Goldfain
(just a student in the) --> Department of Computer Science
1304 West Springfield Avenue
Urbana, Illinois 61801
------------------------------
End of AIList Digest
********************
∂25-Nov-87 0439 LAWS@KL.SRI.COM AIList V5 #272 - Expert System Survey
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 25 Nov 87 04:39:04 PST
Date: Sun 22 Nov 1987 23:24-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #272 - Expert System Survey
To: AIList@SRI.COM
AIList Digest Monday, 23 Nov 1987 Volume 5 : Issue 272
Today's Topics:
Expert Systems - Survey Results
----------------------------------------------------------------------
Date: 19 Nov 87 14:42:38 GMT
From: portal!cup.portal.com!Barry_A_Stevens@uunet.uu.net
Subject: expert system survey results
EXPERT SYSTEM SHELL SURVEY
Copyright 1987 Applied AI Systems, Inc.
We recently sent a questionnaire to 1700 users of PC-based expert
system development shells. One hundred seventy nine firms responded.
The survey was intended as a snapshot of the expert system market
during the preparation stages of a business plan. It was understood in
advance by all parties concerned that:
IT WAS NEVER MEANT TO BE AN ACADEMICALLY CORRECT SURVEY.
IT WAS ONLY TO PROVIDE SOME GENERAL INFORMATION.
If you can accept the above limits, what follows may be of interest to
you. If an imperfect survey is an abomination, you can skip the
remainder of this file.
The purpose of the survey was to educate and inform, on a gross level,
about the expert system shell marketplace. Information sought
included:
profiles of the shell users and their organizations;
general strengths and weaknesses of expert system shells;
the decision process followed by users when buying a shell;
the reasons for getting into expert systems;
expert system software in use;
job titles of people using expert system tools; and
applications that have been implemented using shells.
One hundred seventy-nine questionnaires were completed and
returned. The survey contained some questions whose answers are
confidential. We thought that some of the results, summarized for
bervity and sanitized to maintain confidentiality, might be of
interest.
WHAT CHARACTERISTICS MAKE A GOOD - AND BAD - EXPERT SYSTEM
DEVELOPMENT SHELL?
Many of the questionnaire respondents indicated that they had made
studies of multiple expert system development shells. Thirty two of
those respondents offered the following general comments about factors
that they viewed as strengths and weaknesses of those tools. A
strength was defined as a reason they would buy a tool as a
result of a product evaluation, while a weakness would cause them to
reject a tool.
Strengths
General strengths are described below, with the number of
respondents mentioning each factor shown.
The tool should be useful in many microcomputer,
minicomputer, and mainframe environments, under different
operating systems. (6)
The capability to access other programs and data should be
provided. (5)
The tool should be capable of frames and/or object
representation as well as representation by rules. (4)
Math functions and numeric and text variables should be
usable in rules (2)
Rules should be easy to structure; (2)
The product should be easy to learn. (2)
The product should be easy to use. (2)
Both editor and user interface should be in English, or
natural language;
Graphics and a good user interface should be available;
Procedural components should be available for sequencing and
interaction, including the ability to clear previous answers
and ask questions again;
The tool should handle probabilities, including fuzzy
logic;
The tool should learn by examples;
Sophisticated WHY and HOW capability should be available to
explain reasoning;
Good support and training should be available;
Good documentation should be available.
Weaknesses
General weaknesses of expert system development shells that were
identified by users are described below.
Cost of a product should be appropriate for its capabilities
and performance; (the survey indicated that users are
price sensitive, and price is a significant factor in
purchasing a product.) (12)
Special hardware requirements are a problem. The tool should
run on a standard PC or other commonly available
environment. (5)
Knowledge base size limitations are a problem. Several
available products limit the number of rules that can be
defined. (3)
Slow execution speed is a problem. Execution speed should
be such that a large number of rules can be executed in a
reasonable time. (2)
Lack of flexibility in knowledge representation and use is a
problem. (2)
THE PROCESS OF MAKING THE DECISION TO BUY
We asked about the process of decision making that went into the
purchase of a PC-based expert system shell at a price of $400. We
wanted to know who made the decision, and how it was made.
Who (by organizational unit) made the decision to buy?
INTERNAL
ORGANIZATION NUMBER % RESPONSE
Research and Development 58 31.9%
MIS/Data Processing 36 19.8%
Independent individuals 31 17.0%
Operating (line) organizations 26 14.3%
Management/staff function 19 10.4%
Advanced Planning 10 5.5%
Other 2 1.1%
TOTALS 182 100%
Who (by reporting relationship) made the decision to buy?
WHO MADE
DECISION NUMBER % RESPONSE
Me 151 88.8%
My Boss 17 10.0%
Different department 1 0.6%
My subordinate 1 0.6%
My boss's boss 0 0.0%
TOTALS 170 100%
How was the decision to buy made?
DECISION PROCESS NUMBER % RESPONSE
No formal decision process 99 40.9%
Product review and comparison 64 26.4%
Internal needs assessment 26 10.7%
Cost justification 40 16.5%
Formal review and planning process 6 2.5%
Other 7 2.9%
TOTALS 242 100%
What were the reasons for getting into expert systems?
REASON NUMBER % RESPONSE
To capture knowledge 76 16.0%
It's a training tool 71 14.9%
Part of overall corporate strategy 60 12.6%
To improve quality of work 47 9.9%
To improve quality of product 41 8.6%
To learn expert systems 41 8.6%
It's a competitive weapon 34 7.2%
It's in fashion 27 5.7%
To achieve a cost savings 23 4.8%
It's a marketing tool 22 4.6%
To provide an MIS/DP capability 19 4.0%
Other 14 2.9%
TOTALS 475 100%
What types of expert system software are installed?
We found that 76 distinct products were in use from nearly as many
vendors. It is interesting to note the categories into which these
products fell.
Lisp Based Tools:
total units installed: 80
number of products installed: 15
Prolog Based Tools:
total units installed: 120
number of products installed: 12
Development tools/shells:
total units installed: 223
number of products installed: 49
JOB TITLES OF PEOPLE USING SHELLS
We were interested in the job titles of people who had built
expert systems using shells. You may be interested as well.
Advanced Programmer/Analyst
Advanced R&D Project Engineer
Advanced Technology Group
Advisory Engineer
AI Branch Chief
Analyst
Assistant Professor
Assistant Vice President
Associate Professor
Audit Manager
CEO
Chairman of the Board
Chair, Department of Communications
Chemist
Computer Scientist
Computer Specialist
Consultant
Cost Analyst
Design specialist
Director Clinical Laboratories
Director, AI in Business
Director, Clinical Research
Director, Computation Center
Education Specialist
Engineer
Executive Consultant
Financial Services Officer
Graduate Assistant
Group Leader
Head Intelligent Systems. Lab.
Instructor
Learning Center Manager
Lecturer
Manager, R&D
Manager, Analytical Chemistry
Manager, Information Resource Management
Manager, Operations
Manager, Product Evaluation Office Automation
Manager, Proposals
Manager, Remote Sensing Lab
Managing Vice President
Materiel Operations Manager
Owner
Physician
President
Principal
Professor of AI & ES
Professor of Chemistry
Professor of Real Estate
Program Manager
Programmer
Project Coordinator
Project Engineer
Regional Manager
Research Agronomist
Research Assistant
Research Forester
Research Manager
Research Scientist
Seismic Processing Analyst
Senior Analyst
Senior Engineer
Senior Research Chemist
Senior Research Fellow
Senior System Analyst
Senior Tax Manager
Senior VP & Senior Trust Officer
Special Projects Director
Staff Machinery Engineer
Staff Research Engineer
Staff Scientist
Systems Officer
Technical Advisor
Technical Consultant
Technical Journalist
Technical Staff Member
Technology Assessor
Underwriting Director
Unit Head Conventional Safety Standards
Vice President
Wildlife Ecologist
While there are a few titles that indicate specialization in AI,
most are seen to be outside that category. Expert systems are
being built by technical professionals even with limited
computer experience.
APPLICATIONS FOR SHELLS
We asked about the applications that were either built or in
development using shells. In many cases, the reply indicated that the
nature of the application was confidential and no application name was
given. The names below are those that were listed in user
responses, with little editing and no attempt to explain.
Account business assessment
Advertising copy development
Advice on single family home purchase
Advice on stock and commodities trading
Advise nursing students on the care of patients
Advising on choices for new technology
Advisor on choosing soy bean varieties
Advisor on design of new magnetic components
Aid for financial futures traders
Aid for isolating failing chips
Aid in salmon stocking rates, species selection
Alarm management system
Analysis of simulation results in bank product planning
Analysis of soil site characteristics
Analysis of X-rays
Application sizing based on similar applications
Assist in compiling tax planning ideas
Assist in diagnosis of computer console messages
Assist in identification of rare antibodies
Assist new users of DOS
Assist service desk in troubleshooting application problems
Assistance in search for part numbers
Augment expertise of resource manager
Broker syndication planner
Call screening to interview users with application problems
Career development
Causal model of account marketing
Chemical process diagnosing and troubleshooting
Choosing a living or testamentary trust
Choosing an executor for trusts
Classification of data from satellites
Classifications of software programs
Closing and issuance assistance
Commercial loan credit analysis
Commercial loan documentation check list
Computer modeling support
Computer system configurator
Configurator for selecting, sizing, and writing parts list
Configuring programmable controller system
Conservation equipment tillage selector
Correct selection of cost codes
Cost/benefit assistant
Create standard loan documents based on characteristics
Credit control system
Crop management and irrigation simulation
Customer assistance in selecting types of investments
Customer service advisor for problem resolution
Customer water quality analysis
Data communications troubleshooting
Decision support for correct testing by auditing
Detailed analysis of hardware and software problems
Detailed design for asphalt concrete pavement
Determine correct mixture for propellant ingredients
Determining best shipping documentation and routes
Diagnose telecommunications difficulties
Diagnosis of sports related injuries
Diagnostic advisor for pulp bleaching
DP production support system
Epidemiology expert system
Equipment fault diagnosis
Equipment troubleshooting
Estimate employee's potential retirement salary
Estimating construction costs
Evaluation of commodities purchases
Evaluation of multi-family housing projects
Evaluation of stock purchases
Fault diagnosis for electronic hardware
Federal contract management
Fertilizer recommendations
Fertilizer, climate, and soil interaction
Finding phases present in super alloys
Forecast snowfall accumulation
Forecasting severe convecting weather
Futures, stocks, and options trading
Gas turbine troubleshooting
Geographic information system analysis aid
Grading of graft vs. host disease
Hardware and software selection
Hardware failure analysis
Hardware sizing assistant
Hazardous chemical ranking
Implementation planning assistant
Industrial training
Interpretation of statistical quality control data
Invention patentability expert
Irrigation and pest control management
Lime recommendation system
Line diagnosis and fault detection
Local area network selection
Machine advisor for grinding, milling, turning
Manufacturing resource planning aid
Market segmentation and positioning
Marketing advisor for process control systems
Material selection by engineers
Materials selection for specialized component parts
Medical decision making
Medical diagnosis
MIS decision support system
Mortgage credit analysis
Network operations systems diagnosis
Papaya management system
Pavement performance diagnosis
Pavement rehabilitation
PC configuration
PC Hardware and software configurator
Perform hematological diagnosis
Personal tax advisor
Pest management and soil interaction analysis
Portfolio construction
Power plant boiler tube failure identification
Problem diagnosis for local area networks
Problem diagnosis for printers on a SNA network
Product development support system
Product performance troubleshooting for salesmen
Product selection system
Production scheduling
Psychiatric interview
Quick proposal estimator
Radar mode design workstations
Rating for substandard life insurance
Real estate appraisal
Real estate site selection
Real time process control
Real time troubleshooting for wastewater process control
Recommend documentation to computer users
Relay diagnosis
Risk assessment of error or fraud in financial statements
Salary planning
Sales order analysis
Salmon diagnosis and treatment
Select pension types
Select, recommend library reference materials
Selection of non-materials in aerospace applications
Selection of solvents for chemical compounds
Service network assistant
Software development risk analysis
Software system diagnosis model
Software vendor risk analysis
Soil acidity analysis
Soil characterization and utilization
Solid waste disposal management assistant
Space shuttle payload on-orbit analysis
Strategic alternatives for a fragmented industry
Strategic marketing and planning aid
Structural damage assessment
Student financial aid eligibility
Submarine approach officer training
System to identify feasible rehabilitation strategies
System to prepare process estimates
Tactical battle management
Teaching mineral and rock identification
Telephone system configurator
Toxicity of laboratory chemicals
Training in gas turbines
Training new financial planners
Troubleshooting airplane starting systems
Underwriting assistance
Underwriting guidance for line underwriters
Weed identification
When to perform a physical audit
Applied AI Systems, Inc. and Barry Stevens may be reached at PO Box
2747, Del Mar, CA, 619-755-7231.
------------------------------
End of AIList Digest
********************
∂25-Nov-87 0710 LAWS@KL.SRI.COM AIList V5 #273 - Seminars, Conferences
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 25 Nov 87 07:10:43 PST
Date: Tue 24 Nov 1987 23:29-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #273 - Seminars, Conferences
To: AIList@SRI.COM
AIList Digest Wednesday, 25 Nov 1987 Volume 5 : Issue 273
Today's Topics:
Seminars - Notes Toward a New Philosophy of Logic (SUNY) &
The Soar Project (ISI) &
Theories of Comparative Analysis (BBN) &
Performance in Practical Problem Solving (Bell Labs),
Conference - Workshop on Meta-Programming in Logic (England) &
CMU Meeting on Metadeduction &
Prolog Benchmarking Workshop &
AI in Economics and Management
----------------------------------------------------------------------
Date: Fri, 20 Nov 87 12:09:44 EST
From: rapaport@cs.Buffalo.EDU (William J. Rapaport)
Subject: Seminar - Notes Toward a New Philosophy of Logic (SUNY)
STATE UNIVERSITY OF NEW YORK AT BUFFALO
BUFFALO LOGIC COLLOQUIUM
COLIN McLARTY
Department of Philosophy
Case Western Reserve University
NOTES TOWARD A NEW PHILOSOPHY OF LOGIC
Today, logic is generally conceived as, more or less, describing pure
laws of thought. But categorial logic has given an extensive, rigorous,
formalized version of the claim that logic is simply the most abstracted
aspect of concrete knowledge. In particular, different subject matters
may have different logics.
Categorial logic also urges a kind of structuralism: A subject matter
(represented by a category) is seen as being determined by the relations
to be considered among objects rather than by any specification of the
individual constitutions of the objects.
These points are illustrated by two examples. Differential geometry is
one abstract representation of the world, one subject matter, with its
own non-classical logic. Set theory is another, later, subject, with
classical logic. I discuss the way set theory was derived from geometry
in the 19th Century.
Other philosophic applications of topos theory are based on the idea of
a topos as a world in which truth varies over a range of viewpoints,
which might be the situations of situation semantics or times in tense
logic. All these considerations together argue that there is no one
logic or one fundamental structure to the world.
Wednesday, December 2, 1987
4:00 P.M.
Diefendorf 8, Main Street Campus
For further information, contact John Corcoran, (716) 636-2438.
------------------------------
Date: Mon, 23 Nov 87 09:56:21 PST
From: Ana C. Dominguez <anad@vaxa.isi.edu>
Subject: Seminar - The Soar Project (ISI)
Date: Wednesday, November 25th
Time: 1:00pm - 3:00pm
Place: Information Sciences Institute/USC
11th Floor Large Conference Room
4676 Admiralty Way
Marina Del Rey, CA 90292-6695
The Soar Project
Current Status and Future Plans
Paul Rosenbloom
The Soar project is an interdisciplinary, multi-site, research group that is
attempting to build a system capable of general intelligent behavior. Our
long-term goal is to build a system that is capable of working on the full
range of tasks -- from highly routine to extremely difficult open-ended
problems -- and of employing the full range of problem solving, knowledge
representation, learning, and perceptual-motor capabilities required for
these tasks. In this talk I will describe the current status of the
project, including the version of the system currently implemented (Soar
4.4) and the results that have been generated to date, and describe our
research plans for the next couple of years.
------------------------------
Date: Tue 24 Nov 87 18:22:10-EST
From: Marc Vilain <MVILAIN@G.BBN.COM>
Subject: Seminar - Theories of Comparative Analysis (BBN)
BBN Science Development Program
AI Seminar Series Lecture
THEORIES OF COMPARATIVE ANALYSIS
Daniel S. Weld
MIT Artificial Intelligence Lab
(WELD@REAGAN.AI.MIT.EDU)
BBN Labs
10 Moulton Street
2nd floor large conference room
10:30 am, Tuesday December 1
This talk analyzes two approaches to a central subproblem of automated
design, diagnosis, and intelligent tutoring systems: comparative
analysis. Comparative analysis may be considered an analog of
qualitative simulation. Where qualitative simulation takes a structural
model of a system and qualitatively describes its behavior over time,
comparative analysis is the problem of predicting how that behavior will
change if the underlying structure is perturbed and also explaining why
it will change.
For example, given Hooke's law as the model of a horizontal,
frictionless spring/block system, qualitative simulation might generate
a description of oscillation. Comparative analysis, on the other hand,
is the task of answering questions like: ``What would happen to the
period of oscillation if you increase the mass of the block?'' I have
implemented, tested, and proven theoretical results about two different
techniques for solving comparative analysis problems, differential
qualitative (DQ) analysis and exaggeration.
DQ analysis would answer the question above as follows: ``Since force is
inversely proportional to position, the force on the block will remain
the same when the mass is increased. But if the block is heavier, then
it won't accelerate as fast. And if it doesn't accelerate as fast, then
it will always be going slower and so will take longer to complete a
full period (assuming it travels the same distance).''
Exaggeration can also solve this problem, but it generates a completely
different answer: ``If the mass were infinite, then the block would
hardly move at all. So the period would be infinite. Thus if the mass
was increased a bit, the period would increase as well.''
Both of these techniques has advantages and limitations. DQ analysis is
proven sound, but is incomplete. It can't answer every comparative
analysis problem, but all of its answers are correct. Because
exaggeration assumes monotonicity, it is unsound; some answers could be
incorrect. Furthermore, exaggeration's use of nonstandard analysis makes
it technically involved. However, exaggeration can solve several
problems that are too complex for DQ analysis. The trick behind its
power appears to have application to all of qualitative reasoning.
------------------------------
Date: Mon, 23 Nov 23:10:39 1987
From: dlm%research.att.com@RELAY.CS.NET
Subject: Seminar - Performance in Practical Problem Solving (Bell
Labs)
Date: November 20 (Friday)
Time: 1:30 p.m. - 2:30 p.m.
Place: AT&T Bell Labs Murray Hill 3D-473
Speaker: Leo Hartman
Department of Computer Science
University of Rochester
Rochester, New York
Performance in practical problem solving
Abstract
The quantity of resources that an agent expends in solving problems in a
given domain is determined by the representations and search control
strategies that it employs. The value of individual representations or
strategies to the agent is determined by their contribution to the
resource expenditure. We argue here that in order to choose the component
representations and strategies appropriate for a particular problem domain
it is necessary to measure their contribution to the resource expenditure
on the actual problems the agent faces. This is as true for a system
designer making such choices as it is for an autonomous mechanical agent.
We present one way to measure this contribution and give an example in
which the measure is used to improve problem solving performance.
Sponsor: Henry Kautz
------------------------------
Date: Tue, 17 Nov 87 10:29:26 GMT
From: mcvax!ux63.bath.ac.uk!cc_is@uunet.uu.net
Subject: Conference - Workshop on Meta-Programming in Logic (England)
WORKSHOP ON META-PROGRAMMING IN LOGIC PROGRAMMING
A 3-day workshop on Meta-Programming in Logic Programming will
be held at the University of Bristol on June 22-24, 1988. The workshop
will be both small and informal. In particular, attendance will be
strictly limited to the first 60 people who register.
The workshop will cover (but not be limited to) the following
topics:
* Foundations of meta-programming
* Design and implementation of language facilities for
meta-programming
* Knowledge representation for meta-programming
* Meta-level reasoning and control
* Applications of meta-programming
Submitted papers will be refereed by a program committee
consisting of Harvey Abramson, Pat Hill, John Lloyd, Mike Rogers
and John Shepherdson. Authors should submit full papers of at most
12 A4 pages. Accepted papers will appear without revision in the
proceedings. The timetable for submission of papers is as follows:
Closing date April 15, 1988
Acceptance/rejection notification May 15, 1988
Papers should be submitted to:
John Lloyd
Department of Computer Science
University of Bristol
University Walk
Bristol BS8 1TR
U.K.
(JANET: jwl@uk.ac.bristol.compsci)
Registration forms for the workshop will be available in
January 1988. Bristol is about 120 miles due west of London.
Heathrow Airport is about 1 3/4 hours away by a direct bus service.
There is also a local airport at Bristol. Accommodation for
registrants will be booked in nearby university halls of residence.
All e-mail enquiries should be directed to (JANET:)
meta88@uk.ac.bristol
--
Mr I. W. J. Sparry Phone: +44 225 826826 x 5983
University of Bath JANET: cc_is@UK.AC.BATH.UX63
Bath BA2 7AY UUCP: seismo!mcvax!ukc!bath63!cc_is (bath63.UUCP)
England ARPA: cc_is%ux63.bath.ac.uk@ucl-cs.arpa
------------------------------
Date: 16 Nov 1987 10:17:49-EST (Monday)
From: DANIEL.LEIVANT%THEORY.CS.CMU.EDU@forsythe.stanford.edu
Reply-to: TheoryNet List
Subject: Conference - CMU meeting on metadeduction
[Forwarded from TheoryNet.]
Below is the schedule of a meeting that has taken place at
Carnegie Mellon University, on
METALANGUAGE AND TOOLS FOR MECHANIZING FORMAL DEDUCTIVE THEORIES
Please address requests for abstracts of talks
to jfm@k.gp.cs.cmu.edu (ARPAnet).
Friday, November 13
9:00 Using a Higher-Order Logic Programming Language to Implement
Program Transformations
Dale Miller, University of Pennsylvania
9:45 Building Proof Systems in an Extended Logic Programming Language
Amy Felty, University of Pennsylvania
10:45 The Categorical Abstract Machine, State of the Art
Pierre-Louis Curien, Ecole Normale Superieure, Paris VII
1:15 A Very Brief Look at NuPRL
Joseph Bates, Carnegie Mellon University
1:45 Reasoning about Programs that Construct Proofs
Robert Constable, Cornell University
2:30 Theorem Proving via Partial Reflection
Douglas Howe, Cornell University
3:15 MetaPrl: A Framework for Knowledge Based Media
Joseph Bates, Carnegie Mellon University
4:00 Discussion: The Role of Formal Reasoning in Software Development
5:00 Demos until 6:30
NuPRL in Wean Hall 4114 by Doug Howe
Lambda Prolog in WeH 4623 by Dale Miller, Gopalan Nadathur, and Amy Felty
Saturday, November 14
9:00 A Framework for Defining Logics
Robert Harper, Edinburgh University
9:45 The Logician's Workbench in the Ergo Support System
Frank Pfenning, Carnegie Mellon University
10:45 A Tactical Approach to Algorithm Design
Douglas Smith, Kestrel Institute
11:30 Reusing Data Structure Designs
Allen Goldberg, Kestrel Institute
1:15 Paddle: Popart's Development Language
David Wile, University of Southern California
2:00 Mechanizing Construction and Modification of Specifications
Martin Feather, University of Southern California
3:00 The TPS Theorem Proving System
Peter Andrews, Carnegie Mellon University
3:45 ONTIC: Knowledge Representation for Mathematics
David McAllester, Cornell University
4:30 Demos until 6:00
Popart and Paddle in the KBSA, Wean Hall 4114,
by David Wile and Martin Feather
The LF Proof Editor, Wean Hall 4623, by Robert Harper
------------------------------
Date: Fri, 20 Nov 87 15:20:20 cst
From: stevens@anl-mcs.ARPA (Rick L. Stevens)
Subject: Conference - Prolog Benchmarking Workshop
ANNOUNCING
=============
A PROLOG BENCHMARKING WORKSHOP
During the last SLP there was some concern that the benchmark programs
being quoted in the literature did not reflect real Prolog programming
practices. Now is your chance to do something about it. A workshop
on benchmarking Prolog programs will be held at The Aerospace
Corporation in Los Angeles. The main function of this workshop is to
collect and measure a large number of modern production (real
application) Prolog programs.
The workshop will last three days, and will be held sometime during
the first two weeks of February. The exact date will be selected to
enable the most people to attend. The workshop will be sponsored by
The Aerospace Corporation and is being held under the auspices of the
Association of Logic Programming. Since resources for running the
benchmarks will be limited the meeting will be open only to those who
contact the organizers.
The first half of the workshop will be spent discussing the performance
issues we wish to address, porting of code, and instrumenting of
Prolog programs and implementations. The second half will be spent
running the code and collecting and analyzing the data.
We hope to publish the results either as a widely available Technical
Report or as a special journal article in a journal such as the Journal
of Logic Programming or New Generation Computing.
Attendance at the workshop will be limited to those who either bring
an implementation of Prolog or 1,000 or more lines of "original"
Prolog source. Programs with more than 1,000 lines will certainly be
accepted. The thing we wish to guard against is toy programs that
don't reflect the serious use of the language.
Of course, we would like code that has been written recently and that
reflects the best of Prolog style. But any ``real'' Prolog application
would be acceptable. ( No code with more that 3 cuts per clause.
:-)). Hopefully those in attendance will represent a balance between
University and Commercial applications.
The code brought should be covered by a GNU type ``copyleft''. That
is unlimited distribution of unmodified sources. The object is to get
unmodified copys of programs and input data sets to as many people as
possible. The Aerospace Corporation, a non-profit organization will
distribute the benchmark suite.
We would like to have the environment set up in advance so as much time
as possible can be spent on performance analysis. To do this
we will set up a mail address where code can be e-mailed in advance.
Participants can also bring a UNIX tar tape. The computers available at
Aerospace include a Sequent, VAXes, Suns, and various types of
PCs. We will try to have as many different implementations of Prolog
available as possible.
A limited amount of financial support from the Aerospace Corporation
will be available for University attendees.
Please let us know by December 15, 1987 if you intend to attend.
If you want to attend, please send us your
name,
e-mail address,
country of citizenship,
smail address,
date, if you have a preference
if you will need financial support
date that would be best for you, and
what you'll bring.
Send responses to:
prolog-workshop@anl-mcs.arpa
If you can't get ahold of us through e-mail, you can use:
Carl Kesselman Rick Stevens
MS M1/102 Math and Computer Science Division
The Aerospace Corporation Argonne National Laboratory
P.O. Box 92957 Argonne IL 60439
Los Angeles, CA 90009-9295 (312) 972-3378
(213) 336-6691
If you have a problem with the distribution agreement, questions or
suggestions, please contact us at the above address.
Hope to see you there.
Rick Stevens Carl Kesselman
stevens@anl-mcs.arpa carl@aerospace.aero.org
Argonne National Laboratory The Aerospace Corporation
------------------------------
Date: Fri, 20 Nov 87 16:30:21 SST
From: Joel Loo <ISSLPL%NUSVM.BITNET@wiscvm.wisc.edu>
Subject: Conference - AI in Economics and Management
+-----------------+
! CALL FOR PAPERS !
+-----------------+
2nd International Workshop
on Artificial Intelligence
in Economics and Management
11-13 January,1989
Singapore
This workshop will address research and applications of AI in the areas
of finance, banking, insurance, economics, DSS, public and private
services, OA, law, manufacturing planning, personnel and assets admini-
stration.
The techniques to be presented should include knowledge representation,
search and inference, knowledge acquisition, intelligent interfaces,
KB validation, planning procedures and task support systems.
For details contact:
Desai Narasimhalu
Institute of Systems Science
National University of Singapore
Kent Ridge, Singapore 0511
Singapore
or,
BITNET: ISSAD@NUSVM
------------------------------
End of AIList Digest
********************
∂25-Nov-87 1024 LAWS@KL.SRI.COM AIList Digest V5 #274
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 25 Nov 87 10:24:35 PST
Date: Tue 24 Nov 1987 23:33-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList Digest V5 #274
To: AIList@SRI.COM
AIList Digest Wednesday, 25 Nov 1987 Volume 5 : Issue 274
Today's Topics:
Psychology - Mental Models Summary,
Conference - Int. Neural Network Society
----------------------------------------------------------------------
Date: 22 Nov 87 10:08:22 GMT
From: cunyvm!byuvax!fordjm@psuvm.bitnet
Subject: Mental Models Summary (long)
The following is a summary of the references
I have received from the net in response to
my request for information on mental models
from a cognitive psychology perspective. I
appreciate the help and look forward to
commenting on these sources as I read them.
In some cases more than one person suggested the
same source. In such cases I have only included
comments from the first person to mention each
source.
If anyone would like to comment on these
references, or has additional comments on
research in this area, please contact me.
_______
stever@EDDIE.MIT.EDU (Steve Robbins) suggests
that the literature on Neurolinguistic Programming
might be useful:
>For information on the cognitive psych slant of NLP,
>I'd recommend "NLP I" by Dilts et al., Meta Publications, 1979.
>A book I'm in the middle of is "Meta-cation: Prescriptions for
>Some Ailing Educational Processes" by Sid Jacobson, also available
>from Meta Publications (Cupertino, CA). META-Cation is written n
>a very "casual" style, but it's easy to read and seems to have some
>good material.
>For information about the technology in general, the "standard"
>books are "Frogs into Princes," "Reframing," and "Using Your Brain",
>by Bandler and Grinder. The main problem with these books is that
>they're all transcripts of training workshops. As such, the material
>isn't organized particularly well for presentation through writing.
Stephen Smoliar <smoliar@vaxa.isi.edu> suggests the following:
>...Chapters 12 and 13 of Alvin Goldman's EPISTEMOLOGY AND
>COGNITION...
>..."Mental Muddles" by Lance Rips. It was supposed to be published
>in the book THE REPRESENTATION OF KNOWLEDGE AND BELIEF, edited
>by Myles Brand and Robert Harnish. I do not know if this book is out
>yet.
(I have not yet been able to locate the second book.)
Robert Virzi <rv01%gte-labs.csnet@RELAY.CS.NET> writes:
>I am interested in mental models of everyday appliances. Things like
>VCRs and telephones, stuff like that. In fact, I am about to start a
>series of experiments on peoples mental models of their TV/cable/VCR
>setups. (This sounds very interesting!--JMF)
He suggests:
>1986 IEEE Conf. on Systems, Man & Cybernetics has a couple of sessions
>on Mental Models. One paper by Gentner and Schumacher and another by
>Sebrechts & DuMont seem pretty good.
>ACM CHI'83 has one of the better papers I've seen on the topic written
>by Halasz and Moran. The look at the effect of mental models on
>subjects use of an Reverse Polish Notation calculator.
>Harvard U. Press has a book out by Johnson-Laird called Mental models.
>I don't have it yet but it looked promising from what I could glean from
>reviews.
(I mentioned the Johnson-Laird book in my original posting. I have read
it and find it to be a refreshing alternative to much of the earlier
logic-based explanations of human reasoning.)
Rich Sutton <rich%gte-labs.csnet@RELAY.CS.NET> supplies:
>R.~Sutton \& A.~Barto, ``An adaptive network that constructs and uses
>an internal model of its environment," {\it Cognition and Brain Theory
>Quarterly}, {\sl 4}, 1981, pp.~217--246.
>R.~Sutton \& B.~Pinette, ``The learning of world models by
>connectionist networks," {\it Proceedings of the Seventh Annual
>Conf.~of the Cognitive Science Society}, 1985, pp.~54--64.
"Brad Erlwein Of. (814) 863-4356" <ET2@PSUVM> suggests:
>a good book that you might find helpful is Gardner (1985) The Mind's
>New Science.
( I have also read this book and find it enjoyable, but it is more of
an historical overview of the field of cognitive science than a
research review or integration. The latter is more my interest
at present.)
munnari!gitte%humsun.@husc6.BITNET (Gitte Lingarrd) responds:
>Rouse, W.B., and Morris, N.M. (1986). On Looking Into the Black Box:
>Prospects and Limits in the Search for Mental Models, Psychological
>Bulletin, 100, (3), 349-363.
>
>Lindgaard, G. (1987). Who Needs What Information About Computer Systems:
>Some Notes on Mental Models, Metaphpors and Expertise, Customer Services
>and Systems Branch Paper No. 126, Telecom Australia Research Laboratories,
>Clayton, Australia.
>
>Copies of the latter may be obtained from me if wanted.
Bob Weissman <decwrl!acornrc!bob@ucbvax.Berkeley.EDU> writes:
>Suggest you pick up a copy of ``The Psychology of Human-Computer Interaction''
>by Card, Moran, and Newell. Aside from being a wonderful book (probably
the
>definitive work in its field), it has an extensive bibliography.
>Published by Lawrence Erlbaum Associates, Inc., Hillsdale, NJ., 1983.
>ISBN 0-89859-243-7
lambert@cod.nosc.mil (David Lambert) responds:
>Personnel and Training Research Programs
>Office of Naval Research (Code 1142 PT) (Dr. Susan Chipman (202) 696-4318
)
>Arlington, VA 22217-5000
>has been funding work in mental models. One recent report funded by them,
>which contains references and a distribution list, is:
>
>Jeremy Roschelle and James G. Greeno, Mental Models in Expert Physics
>Reasoning; University of California, Berkeley, CA 94720; Report No. GK-2,
>July 1987.
Jane Malin <malin%nasa-jsc.csnet@RELAY.CS.NET> comments:
>Dedre Gentner gave an outstanding invited survey at AAAI-87 on
>mental models and
>analogy. Hopefully some written version would be available soon.
Thad.Polk@centro.soar.cs.cmu.edu (Thad Polk) responds:
>I'm currently doing research in the area of mental models (of the
>Johnson-Laird variety). Specifically, I'm trying to revise and implement
>his theory of syllogisms within Soar (Laird, Newell, & Rosenbloom, AI
>Journal Sept. 1987).
He recommends the following references:
>A paper by Johnson-Laird & Bruno Bara that appears in Cognition, 16
>(1984) 1-61.
>Revlin, R. & Mayer, R., Human Reasoning, V.H. Winston & Sons,
>Washington D.C., 1978.
>Falmagne, R. (ed.), Reasoning: Representation and Process, Lawrence
>Erlbaum Associates, Hillsdale N.J., 1975.
>A paper by Robert Inder in "Artificial Intelligence and its Applications"
>by A.G. Cohn and J.R. Thomas, John Wiley & Sons, 1986.
meulen@sunybcs.BITNET (Alice ter Meulen) suggests:
>E. Traugott, A. ter Meulen, C. Ferguson and J. Reilly, (eds.)
>On Conditionals
>Cambridge University Press, Cambridge (Engl.) 1986.
which contains a chapter by Johnson-Laird entitled
'Conditionals and mental models'
GA3182@SIUCVMB (John Dinsmore) comments:
>There seem to be two currents of activity in research in mental models:
> 1. work on the contents of the models, i.e., what knowledge they contain.
> This includes work in naive physics and is the main thrust of the
> Gentner and Stevens book.
> 2. work on general mechanisms of knowledge representation and inference.
> This is the thrust of Johnson-Laird's work.
>I'm not sure where your interests lie, but I can offer two references con-
>cerning the second current:
>
> John Dinsmore. 1987. Mental Spaces from a Functional Perspective.
> Cognitive Science 11: 1-21.
> Gille Fauconnier. 1985. Mental Spaces. MIT/Bradford.
_________
Once again, thanks to all. I will communicate more to the net
on this topic as it seems appropriate.
John M. Ford fordjm@byuvax.bitnet
(*Not* the "John M. Ford" that writes science fiction.)
------------------------------
Date: Fri, 20 Nov 87 12:28:33 est
From: mike@bucasb.bu.edu (Michael Cohen)
Subject: Conference - Int. Neural Network Society
November 16, 1987
-----CALL FOR PAPERS-----
INTERNATIONAL NEURAL NETWORK SOCIETY
1988 ANNUAL MEETING
September 6--10, 1988
Boston, Massachusetts
The International Neural Network Society (INNS) invites all
those interested in the exciting and rapidly expanding field of
neural networks to attend its 1988 Annual Meeting. The meeting
includes plenary lectures, symposia, contributed oral and poster
presentations, tutorials, commercial and publishing exhibits, a
placement service for employers and educational institutions,
government agency presentations, and social events.
---INNS OFFICERS AND GOVERNING BOARD---
Stephen Grossberg, President; Demetri Psaltis, Vice-President;
Harold Szu, Secretary/Treasurer.
Shun-ichi Amari, James Anderson, Gail Carpenter, Walter Freeman, Kunihiko
Fukushima, Lee Giles, Teuvo Kohonen, Christoph von der Malsburg, Carver Mead,
David Rumelhart, Terrence Sejnowski, George Sperling, Bernard Widrow.
---MEETING ORGANIZERS---
General Meeting Chairman: Bernard Widrow
Technical Program Co-Chairmen: Dana Anderson and James Anderson
Organization Chairman: Gail Carpenter
Tutorial Program Co-Chairmen: Walter Freeman and Harold Szu
Conference Coordinator: Maureen Caudill
---SPEAKERS---
Plenary:
Stephen Grossberg
Carver Mead
Terrence Sejnowski
Nobuo Suga
Bernard Widrow
Cognitive and Neural Systems:
James Anderson
Walter Freeman
Christoph von der Malsburg
David Rumelhart
Allen Selverston
Vision and Pattern Recognition:
Gail Carpenter
Max Cynader
John Daugman
Kunihiko Fukushima
Teuvo Kohonen
Ennio Mingolla
Eric Schwartz
George Sperling
Steven Zucker
Combinatorial Optimization and Content Addressable Memory:
Daniel Amit
Stuart Geman
Geoffrey Hinton
Bart Kosko
Applications and Implementations:
Dana Anderson
Michael Buffa
Lee Giles
Robert Hecht-Nielsen
Demetri Psaltis
Thomas Ryan
Bernard Soffer
Harold Szu
Wilfrid Veldkamp
Motor Control and Robotics:
Jacob Barhen
Daniel Bullock
James Houk
Scott Kelso
Lance Optican
---ABSTRACTS---
Submit abstracts for oral and poster presentation on biological and
technological models of:
--Vision and image processing
--Local circuit neurobiology
--Speech and language
--Analysis of network dynamics
--Sensory-motor control and robotics
--Combinatorial optimization
--Pattern recognition
--Electronic implementation (VLSI)
--Associative learning
--Optical implementation
--Self-organization
--Neurocomputers
--Cognitive information processing
--Applications
Abstracts must be typed on the INNS abstract form in camera-ready format.
Request abstracts from: INNS Conference, 16776 Bernardo Center Drive,
Suite 110B, San Diego, CA 92128 USA. INNS members will be directly sent
an abstract form.
----------ABSTRACT DEADLINE: MARCH 31, 1988----------
Acceptance notifications will be mailed in June, 1988. Accepted abstracts
will be published as a supplement to the INNS journal, Neural Networks,
and mailed to meeting registrants and Neural Networks subscribers in
August, 1988.
---PROGRAM COMMITTEE---
Joshua Alspector Teuvo Kohonen
Shun-ichi Amari Bart Kosko
Dana Anderson Daniel Levine
James Anderson Richard Lyon
Jacob Barhen Ennio Mingolla
Michael Buffa Paul Mueller
Daniel Bullock Lance Optican
Terry Caelli David Parker
Gail Carpenter Demetri Psaltis
Michael Cohen Adam Reeves
Max Cynader Thomas Ryan
John Daugman Jay Sage
David van Essen Eric Schwartz
Federico Faggin Allen Selverston
Nabil Farhat George Sperling
Walter Freeman David Stork
Kunihiko Fukushima Harold Szu
Lee Giles David Tank
Stephen Grossberg Wilfrid Veldkamp
Morris Hirsch Bernard Widrow
Scott Kelso
---PARTICIPATING SOCIETIES---
American Mathematical Society; Cognitive Science Society; Optical Society
of America; Society for Industrial and Applied Mathematics; Society of
Photo-Optical Instrumentation Engineers; and others pending.
---TUTORIALS---
Tutorials will consist of eight one-hour introductory lectures by distinguished
scientists. The lectures will help prepare the audience for the more advanced
presentations at the meeting. The tutorial topics include:
1. Vision and image processing
2. Pattern recognition, associative learning, and self-organization
3. Cognitive psychology for information processing
4. Local circuit neurobiology
5. Adaptive filters
6. Nonlinear dynamics for brain theory (competition, cooperation, equilibria,
oscillations, and chaos)
7. Applications and combinatorial optimization
8. Implementations (electronic, VLSI, and optical neurocomputers)
Tutorials will be held on Tuesday, September 6, 1988, from 8AM to 6PM. The
general conference will begin with a reception at 6PM, followed by the
conference opening and a plenary lecture.
---REGISTRATION AND HOTEL---
Fill out attached forms.
Registration fees partially pay for abstract handling, the books of abstracts,
two evening receptions, coffee breaks, mailings, and administrative expenses.
---TRAVEL---
Call UNIGLOBE (800) 521-5144 or (617) 235-7500 to get discounts of up to 65%
off coach fares.
---COMMERCIAL AND GOVERNMENT FUNCTIONS---
Conference programs have been designed for commercial vendors, government
agencies and research laboratories, publishers, and educational institutions.
These include a large exhibit area (the Boston Park Plaza Castle); a placement
service for employment interviews; catered hospitality suites; and special
presentations. A professional exposition service contractor will carry out
exhibit arrangements. Organizations wishing to be put on a mailing list for
participants in these programs should fill out the enclosed form.
---STUDENTS AND VOLUNTEERS---
Students are welcome to join INNS and to participate in its meeting. See
attached forms for reduced registration, tutorial, and membership fees.
Financial support is anticipated for students and meeting volunteers. To
apply, attach a letter of request and a brief description of interests to
the conference registration form.
[Contact the author if you need the various registration and
membership forms. -- KIL]
------------------------------
End of AIList Digest
********************
∂01-Dec-87 0054 LAWS@KL.SRI.COM AIList V5 #275 - Pattern Recognition, VLSI Design, Philosophy, Law
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 1 Dec 87 00:53:56 PST
Date: Mon 30 Nov 1987 22:31-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #275 - Pattern Recognition, VLSI Design, Philosophy, Law
To: AIList@SRI.COM
AIList Digest Tuesday, 1 Dec 1987 Volume 5 : Issue 275
Today's Topics:
Queries - STRIPS and its Derivatives & VM/CMS Software &
ES Tools for the Mac,
Binding - Cugini Mailer Problem,
Pattern Recognition - Recognizing Humpback Fins,
Application - NCR VLSI Design Expert System,
Philosophy - Research Methodology,
Law - Software Ownership
----------------------------------------------------------------------
Date: 24 Nov 87 21:45:09 GMT
From: steve@hubcap.clemson.edu ("Steve" Stevenson)
Subject: STRIPS and its derivatives
I am interested in finding out the current status of the
STRIPS model (Fike and Nilsson) and its successors. Any
help would be appreciated. Any compiler/interpreters?
--
Steve (really "D. E.") Stevenson steve@hubcap.clemson.edu
Department of Computer Science, (803)656-5880.mabell
Clemson University, Clemson, SC 29634-1906
------------------------------
Date: Fri, 27 Nov 87 14:28:10 EST
From: Jim Buchanan <ACAD8005%RYERSON.BITNET@wiscvm.wisc.edu>
Subject: Looking for software
I would appreciate any information or leads on the following software:
1) LISP for an IBM VM/CMS system
I have copies of XLISP(version 1.4) and MTS lisp and know about IBM's
LISP/VM but I am looking for the latest XLISP (that will run on VM/CMS)
or other Public domain or inexpensive Lisps
2) Smalltalk for IBM VM/CMS
Again Public Domain or cheap would be best.
Thanks again for any information
Jim Buchanan
Supervisor, Academic Computing Services
Ryerson Polytechnical Institute
Toronto, Ontario
Canada
------------------------------
Date: 30 Nov 87 14:16:19 EST
From: Mary.Lou.Maher@CIVE.RI.CMU.EDU
Subject: ES tools for Mac
I have to give a tutorial and workshop on Expert Systems at an engineering
conference and would like to use the Mac since it has relatively little
start up time. I am interested in simple rule based tools and object
oriented tools that run on a Mac. Simplicity is more important
than sophistication. Can anyone help? Mary Lou Maher maher@cive.ri.cmu.edu
------------------------------
Date: 30 Nov 87 06:58:00 EST
From: cugini@icst-ecf.arpa
Reply-to: <cugini@icst-ecf.arpa>
Subject: mailer problem
My mailer hasn't been able to receive any mail for the past 2-3 weeks.
If anyone has tried to mail me something, apologies, and please try again.
John Cugini <Cugini@icst-ecf.arpa>
------------------------------
Date: 23 Nov 87 02:57:54 GMT
From: nosc!humu!uhccux!cs313s19@sdcsvax.ucsd.edu (Mike Morton)
Subject: pattern recognition software (recognizing humpback fins!)
wanted
A friend does research work spotting humpbacks by recognizing their
dorsal fins. The researchers finish each day by comparing the day's
photos with 300-400 photos of known whales to recognize individuals.
They're looking for a way to do this with a computer database.
They could code the data and enter them as numbers: size and shape of
fins, etc. Then the database just needs to search for close matches.
This could be done with a simple Basic program or spreadsheet macro; any
suggestions for a turnkey system which does this?
Better, but presumably harder to find or implement, would be a graphics
recognition system, scanning images or allowing them to be traced by
hand and entered. I doubt there's anything like this available off-the-
shelf, but would be interested to hear about it if there is.
Solutions for the Mac are especially of interest, but any micro is OK.
Please reply by email. Thanks in advance.
-- Mike Morton // P.O. Box 11378, Honolulu, HI 96878, (808) 456-8455 HST
INTERNET: cs313s19@uhccux.uhcc.hawaii.edu
UUCP: {ihnp4,uunet,dcdwest,ucbvax}!sdcsvax!nosc!uhccux!cs313s19
BITNET: cs313s19%uhccux.uhcc.hawaii.edu@rutgers.edu
------------------------------
Date: 25 Nov 87 16:19:38 GMT
From: uh2@psuvm.bitnet (Lee Sailer)
Subject: Re: pattern recognition software (recognizing humpback
fins!) wanted
I can think of some pretty good ways to do this, but not with
database software, unless the matching problem is really simple.
The current masters of *sequence matching* are the molecular biologists,
who spend a lot of time matching LONG sequences of RNA, DNA, etc.
One approach
Can the fins be described with a simple sequence of tokens or symbols, like
<big gap> <small notch> <small gap> <big notch> <tip> ? If so, then you've
got the DWIM (do what I mean) or spelling correction problem. Given a
sequence of symbols, find the set of legal sequences that are close.
This turns out to be a graph search.
Another approach
Are accurate measurements needed to distinguish nearly identical fins?
If so, then a fin must be described something like this:
gap of 15.2mm
notch width 5mm depth 3mm
gap of 45 mm
notch width 3mm depth 5mm
tip
etc etc etc
If you think of a 'gap' as a notch with width 0, and the tip as a notch
of width and depth 0, then each feature characterized by a triple
of real numbers. Using the <start> <stop> and <tip> as
landmarks, it ought to be possible to think up some way to convert
each fin to a point in N-space, and then to compute the distance
between a new fin and the 300-400 fins already in the database.
------------------------------
Date: 25 Nov 87 23:21:55 GMT
From: portal!cup.portal.com!David_Bat_Masterson@uunet.uu.net
Subject: Re: pattern recognition software (recognizing humpback
fins!) w
This request sounds vaguely familiar. I thought I had seen a show about
a few students for a college doing a study of humpback whales. They
also were having trouble keeping track of which whales were which (maybe
it was killer whales). The way they went about handling it was to
classify the dorsal fin shape by things like size, shape, bites, extra
spots, barnacles, etc. (their fingerprint). I forget if they used a
database system to keep track of this or just a file card approach. If
you use a DB, this information could be entered into a relational database
for scanning purposes (Dbase perhaps). This would not provide an automatic
mechanism for processing the photographs, but its a start. Additional ideas
would be to implement an expert system as front end to this process. The
expert system could be trained to ask the right questions about a photograph
to get a good classification. On top of this could be added a laser scanner
(for about $3K) that would bring the photo into the database; there may be
database systems that would allow you to store the image of the whale right in
the database (I know the Amiga databases can). Think about it, you can build
up from a basic capability, but don't try to do the whole thing at once.
David_Bat_Masterson@cup.portal.com
------------------------------
Date: 27 Nov 87 03:48:33 GMT
From: portal!cup.portal.com!Bob_Robert_Brody@uunet.uu.net
Subject: Re: pattern recognition software (recognizing humpback
fins!) w
There is an organization I belong to re Moclips Cetological Society
which is non profit and centered around whales and whale sightings
and cataloging. Maybe they could be of help re using databases to
maintain the catalogs. You can call 206 378-4710.
The Whale Museum
P.O. Box 945
Friday Harbor, Washington 98250
Moclips Cetological Society is a non profit research and educational
corporation.
Bob Brody
Los Angeles
------------------------------
Date: Sat 28 Nov 87 12:09:26-CST
From: Charles Petrie <AI.PETRIE@MCC.COM>
Reply-to: Petrie@MCC.com
Subject: Re: INFO REQUESTED ON SYSTEMS DEVELOPED USING AI TOOLS/SHELLS
Robin Steele of NCR has built a commercial expert system of some note:
. It represents and reasons about real circuit designs consisting
between 10 and 20K gates
. Customers pay $4,000+ to come into NCR's shop and use the system.
Reference: "An Expert System Application in Semicuston VLSI Design",
Robin L. Steele, _Proc. 24th ACM/IEEE Design Automation Conference_,
Miami Beach, 1987.
------------------------------
Date: 23 Nov 87 22:33:55 GMT
From: honavar@speedy.wisc.edu (A Buggy AI Program)
Reply-to: honavar@speedy.wisc.edu (A Buggy AI Program)
Subject: Research methodology in AI (was Re: Success of AI)
In article <4739@wisdom.BITNET> eitan%H@wiscvm.arpa (Eitan Shterenbaum) writes:
>
>a) You can't understand the laws under which a system works without
> understanding the structure of the system ( I believe that our
> intelligence is the result of our brain's structure )
Not entirely true. We can often gain insights into what structures
are needed to produce a certain observed behavior simply by observing
the system's behavior. This would
then enable us to hypothesize about the structures that actually
produce such behavior. We would then test the hypotheses by
putting them through experimental validation. Just as one can have
several different computers that are functionally equivalent, it
is reasonable to expect that there several possible architectures (the
human brain being one of them) that are capable of intelligence.
>
>It seems to me that
> 1) You have no definition for Intelligence.
> 2) You want to have the rules of Itelligence.
> 3) Thus you build systems inorder to simulate Intelligence.
> 4) Since you don't know you're looking for and since you have no
> basic rules to simulate the intelligence on, you invent your
> own local definition and rules for Intelligence.
> 5) Then youtry to mach your results with your expectations of what
> the results should be.
This is an oversimplified view of the research methodology in AI
and Cognitive sciences.
It is true that we don't have a good definition of intelligence.
For purposes of AI, it is sufficient to say that we want to build
systems that exhibit the kinds of behavior that are believed
to require intelligence if performed by humans (I forget the author
that first suggested this definition of AI). This is an operational
definition or at least a basis for an operational definition of
artificial intelligence. Given this, there are several alternative
approaches one could adopt in building intelligent systems -
including the one of simulating a system that most of us agree is
capable of intelligence, the human brain (plus the sensory mechanisms).
The search for architectures for intelligence is by no means an
unconstrained, blind search. The hypothesis can be constrained by
utilizing data gathered from experimental research in psychology,
neuroscience, and related areas as well as theoretical analysis
of complexity of the tasks involved and so on.
>
>Correct me if I'm wrong but I do feel that the neuro-biologists chaps are
>in the right track and that the Computer scientists should combine efforts
>with them instead of messing around with AI.
>
I agree that AI researches can benefit from the research findings in
neuroscience. It is also true that computational theories advanced
in AI can provide insights to neuroscientists as well. In fact, there
is evidence of this interaction in the works of David Marr, Shimon
Ullman, and others. Cognitive psychology is another field which
is at least as relevent as neuroscience to work in AI.
------------------------------
Date: 22 Nov 87 21:01:00 GMT
From: mnetor!utzoo!dciem!nrcaer!cognos!roberts@uunet.uu.net (Robert
Stanley)
Subject: Re: My parents own my output.
In article <7880@allegra.UUCP> jac@allegra.UUCP (Jonathan Chandross) writes:
>If I write a program that generates machine code from a high level language
>do I not own the output? Of course I own it. I also own the output from
>a theorum prover, a planner, and similar systems, no matter how elaborate.
You do indeed, unless you perform (or fail to perform) some act or acts which,
in the eyes of the Law, strip you either of your status as owner or of your
right to compensation for its use. Giving a copy to a friend without explicit
(read: a witnessed contract) injunction against passing it on, using it other
than for private purposes, etc. is just as much a reduction of your legal
writes as selling it under a contract of sale/lease. There is still some
considerable controversy as to the status of software license agreements under
a variety of legal systems, which is why no consensus has been reached on the
subject of how best to protect your software against theft.
Failing to take positive legal steps to protect your rights of ownership of a
piece of software is tantamount to surrendering those rights once you have
made, or allowed to be made, even one copy of the (suite of) programs. This
may not be fair, but it is what appears to have been established by precedent
in all the major industrialized nations where cases involving software rights
have been tried. At present, in the US and to a large degree in Canada, the
only really successful legal defences have been for ROM software, notably the
Apple Macintosh, which is why there are as yet *no* Macintosh clones in the
market place. It is rumoured (comment anyone?) that this is one of the reasons
for IBM's approach to the design of the PS2, with critical components of the
system architecture in ROM.
For those with a speculative approach to the future, it will be interesting if
history repeats itself. In the 1970's, IBM was taken to court by a number
of PCM's (Plug-Compatible Manufacturers) and eventually lost a ruling, being
forced to disclose the details of their internal architecture to a degree
sufficient to allow other manufacturers to design compatible equipment. At the
time IBM was viewed as holding a monopolistic position, which is not currently
the case with any one personal computer manufacturer nor, as yet, for any
specific piece of software.
>The alternative is to view the AI as an sentient entity with rights, that
>is, a person. Then we can view the AI as a company employee who developed
>said work on a company machine and on company time. Therefore the employer
>owns the output, just as my employer owns my output done on company time.
Whether your employer owns your output is exactly and only a matter of legal
contract. Either you have signed a legally binding contract of employment with
your employer or your (and your employer's) rights are protected by clauses in
one or more current labour relations bills. Precise terms of the latter will,
of course, vary from country to country. It is possible that some aspects of
an explicit contract of employment may be challengeable in court as being overly
restrictive; there have been several US and Canadian precedents within the last
year.
I, for instance, have a contract of emplyment into which I insisted be written
several waivers, simply because the wording of the standard contract gave my
employer the right to everything I did anywhere at any time (24 hours a day,
365.25 days per year) while I was still their employee. I doubt that the
original contract would actually have withstood a challenge in court, but that
would have taken money and time; much, much better to avoid the situation
completely.
>The real question should be: Did the AI knowlingly enter into a contract with
>the employer.
This will only be an issue if an AI can first be demonstrated to be a legal
individual within the eyes of the court. Remember, there are plenty of humans
who do not have this status, but for whom some other legal individual is deemed
to have legal responsibility: the legally insane and the under-aged, to name
but two.
>I wonder if the ACLU would take the case.
Not until there is seen to be some benefit to be gained from protecting the
rights of an AI. Let's face it, more working human beings are likely to oppose
the establishment of such precedents right now than are going to be for it.
How soon do you see this attitude changing? Especially if white-collar workers
start being displaced by intelligent management systems!
Robert_S
--
R.A. Stanley Cognos Incorporated S-mail: P.O. Box 9707
Voice: (613) 738-1440 (Research: there are 2!) 3755 Riverside Drive
FAX: (613) 738-0002 Compuserve: 76174,3024 Ottawa, Ontario
uucp: decvax!utzoo!dciem!nrcaer!cognos!roberts CANADA K1G 3Z4
------------------------------
End of AIList Digest
********************
∂04-Dec-87 0248 LAWS@KL.SRI.COM AIList V5 #276 - Planning Bibliography
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 4 Dec 87 02:48:35 PST
Date: Thu 3 Dec 1987 23:46-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #276 - Planning Bibliography
To: AIList@SRI.COM
AIList Digest Friday, 4 Dec 1987 Volume 5 : Issue 276
Today's Topics:
Bibliography - Planning
----------------------------------------------------------------------
Date: Wed, 2 Dec 87 12:55:42 PST
From: Richard Shu <rshu@ads.arpa>
Subject: Planning Bibliography
Ken,
A while back, Dickson Lukose posted a request for references on
planning. I delayed posting this bibliography because it is based
on one compiled by a co-worker who was on vacation. He has since
given his assent for its distribution.
Disclaimer: The field of planning is very large. This bibliography
is by no means complete. It is simply a compendium of
sources encountered by a few people in the Planning
Division at ADS.
Additions and corrections are welcome. Please mail
them to me and I will aggregate them and repost to
the net.
Richard Shu
------------------- *** Bibliography follows *** ---------------------------
@InProceedings{Agre87,
key "Agre87",
author "Agre, P.E. and Chapman, D.",
title "Pengi: An Implementation of a Theory of Activity",
booktitle "Proceedings of AAAI-87, Seattle, Wa.",
Organization "AAAI",
month "July",
pages "268-272",
year "1987"}
@Book(albus,
key "albus",
author "ALBUS, J.",
title "Brains, Behavior and Robotics",
publisher "Byte Books",
address "Chichester, England",
pages "chapter 5",
year "1985" )
@InProceedings{alterman85,
key "alterman85",
author "ALTERMAN, R.",
title "Adaptive planning: refitting old plans to new situations",
booktitle "Proceedings 7th Cognitive Science Society",
year "1985"}
@InProceedings{alterman86,
key "alterman86",
author "ALTERMAN, R.",
title "An adaptive planner",
booktitle "Proceedings AAAI",
year "1986",
pages "65ff" }
@InBook(amarel,
key "amarel68",
author "AMAREL, S.",
title "On representations of problems of reasoning about actions",
editor "MICHIE, D.",
booktitle "Machine Intelligence 3",
publisher "Ellis Horwood",
address "Chichester, England",
pages "131-171",
year "1968" )
@TechReport{appelt82a,
key "appelt82a",
author "APPELT, D.E.",
title "Planning natural language utterances to satisfy multiple goals",
type "Tech Note",
institution "SRI International, Menlo Park, California",
Pages = "259",
year = "1982"}
@Book(bratman,
key "bratman",
author "BRATMAN, M.",
title "Intentions, Plans and Practical Reason",
publisher "Harvard University Press",
year "forthcoming" )
@TechReport(functions,
key "bundy77",
author "BUNDY, A.",
title "Exploiting the properties of functions to control search",
type "Research Report",
number "45",
institution "Department of AI, University of Edinburgh",
year "1977" )
@TechReport{carbonell80a,
key "carbonell80a",
author "CARBONELL, J.G.",
title "The POLITICS project: subjective reasoning in a multi-actor planning
domain",
journal "Carnegie-Mellon Computer Science Research Review",
year "1980"}
@Article{carbonell81,
key "carbonell81",
author "CARBONELL, J.G.",
title "Counterplanning: a strategy-based model of adversary planning in
real-world situations",
journal "Artificial Intelligence",
volume "16",
pages "295-329",
year "1981"}
@TechReport(chapman85,
key "chapman85",
author "CHAPMAN, D.",
title "Planning for conjunctive goals.",
type "Memo",
number "AI-802",
institution "AI Lab, MIT",
year "1985" )
@InProceedings{coles75,
key "coles75",
author "Coles, L.S., Robb, A.M., Sinclair, P.L., Smith, M.H. AND Sobek, R.R",
title "Decision Analysis for an Experimental Robot with Unreliable Sensors",
booktitle "Proceedings of 4th IJCAI 1975",
organization "IJCAI",
pages "749-754",
year "1975"}
@InProceedings(corkill79,
key "corkill79",
author "Corkill, D.",
title "Hierarchical Planning in a Distributed Environment",
booktitle "Proceedings of the 6th IJCAI",
year "1979",
pages "168-175" )
@TechReport(daniel77,
key "daniel77",
author "Daniel, L.",
title "Planning: Modifying Non-linear Plans.",
type "Working Paper",
number "24",
institution "Department of AI, University of Edinburgh",
year "1977" )
@TechReport(doyle80,
key "doyle80",
author "DOYLE, J.",
title "A Model for Deliberation, Action and Introspection",
type "Technical Report",
number "419",
institution "MIT",
year "1980" )
@InProceedings{Drummond85,
key "drummond85",
author "DRUMMOND, M.",
title "Refining and Extending the Procedural Net",
booktitle "Proceedings of the 9th IJCAI 1985",
organization "IJCAI",
pages"528-531",
month "August",
year "1985"}
@InProceedings(and-or-plans,
key "demello86",
author "DeMELLO, L.H. AND SANDERSON, A.C.",
title "And/Or graph representation of assembly plans",
organization "AAAI",
booktitle "Proceedings of AAAI-86",
year "1986",
pages "1113ff" )
@Article{soft-goals,
key "descotte85",
author "DESCOTTE, Y. AND LATOMBE, J.-C.",
title "Making compromises among antagonist constraints in a planner",
journal "Artificial Intelligence",
volume "27",
pages "183-217",
year "1985"}
@InProceedings(verification,
key "doyle86",
author "DOYLE, R.J., ATKINSON, D.J. AND DOSHI, R.S.",
title "Generating perception requests and expectations to verify the
execution of plans",
organization "AAAI",
booktitle "Proceedings of AAAI",
year "1986",
pages "81ff" )
@Book(gps,
key "ernst69",
author "ERNST, G. AND NEWELL, A.",
title "GPS: a Case Study in Generality and Problem Solving",
publisher "ACM Monograph Series, Academic Press, New York",
year "1969" )
@Article{fahlman74,
key "fahlman74",
author "FAHLMAN, S.",
title "A Planning System for Robot Construction Tasks",
journal "Artificial Intelligence",
volume "5",
pages "1-49",
year "1974"}
@InProceedings(faletti82,
key "faletti82",
author "FALETTI, J.",
title "PANDORA: a program for doing common-sense planning in complex
situations",
organization "AAAI",
booktitle "Proceedings of AAAI-82",
year "1982")
@Article(strips,
key "fikes71",
author "FIKES, R.E. AND NILSSON, N.J.",
title "STRIPS: a new approach to the application of theorem proving to
problem solving.",
journal "Artificial Intelligence",
volume "2",
year "1971",
pages "189ff" )
@TechReport{feldman75,
key "feldman75",
author "FELDMAN, J.A. AND SPROULL, R.F.",
title "Decision Theory and Artificial Intelligence II: The Hungry Monkey",
institution "University of Rochester, Department of Computer Science",
year "1975"}
@Article(fikes71,
key "fikes71",
author "FIKES, R.E. AND NILSSON, N.J.",
title "STRIPS: A new approach to the application of theorem proving to
problem solving",
journal "Artificial Intelligence",
volume "2",
year "1971",
pages "189-208" )
@Article(fikes72,
key "fikes72",
author "FIKES, R.E., HART, P.E. AND NILSSON, N.J.",
title "Learning and executing generalized robot plans",
journal "Artificial Intelligence",
volume "3",
year "1972",
pages "251-288" )
@TechReport{finger86,
key "finger86",
author "FINGER, J.J.",
title "Exploiting constraints in deductive design synthesis",
type "Ph.D. thesis",
institution "Stanford University",
note "to appear",
year "1986"}
@Article{spex,
key "friedland85",
author "FRIEDLAND, P.E. AND IWASAKI, Y.",
title "The concept and implementation of skeletal plans",
journal "Journal of Automated Reasoning",
volume "1",
pages "161-208",
year "1985"}
@TechReport(mrs1,
key "genesereth81",
author "GENESERETH, M.R. AND SMITH, D.E.",
title "Metalevel architecture",
type "Memo",
number "HPP-81-6",
institution "Stanford University",
year "1981" )
@TechReport(mrs2,
key "russell85",
author "RUSSELL, S.",
title "The compleat guide to MRS",
type "Report",
number "KSL-85-12",
institution "Stanford University",
year "1985" )
@InProceedings{georgeff83,
key "georgeff83",
author "GEORGEFF, M.P.",
title "Communication and interaction in multi-agent planning",
booktitle "Proceedings of AAAI-83",
pages "125-129",
month "August",
year "1983"}
@InProceedings(pes,
key "georgeff83",
author "GEORGEFF, M. AND BONOLLO, U.",
title "Procedural expert systems",
booktitle "Proceedings of the 8th IJCAI",
year "1983",
pages "151ff" )
@InProceedings(georgeff84,
key "georgeff84",
author "GEORGEFF, M.",
title "Procedural expert systems",
booktitle "Proceedings of AAAI-84",
year "1984",
pages "121-125" )
@InProceedings(prs-logic,
key "georgeff85",
author "GEORGEFF, M., LANSKY, A. AND BESSIERE, P.",
title "A procedural logic",
booktitle "Proceedings of the 9th IJCAI",
year "1985" )
@TechReport(prs-flakey,
key "georgeff86",
author "GEORGEFF, M., LANSKY, A. AND SCHOPPERS, M.",
title "Reasoning and planning in dynamic domains: an experiment with a mobile
robot",
type "Technical Note",
number "380",
institution "AI Center, SRI International",
year "1986" )
@TechReport(recovery,
key "gini85",
author "GINI, M., DOSHI, R., GARBER, S., GLUCH, M., SMITH, R. AND
ZUALKERNAIN, I.",
title "Symbolic reasoning as a basis for automatic error recovery in robots",
type "Tech Rept",
number "85-24",
institution "University of Minnesota",
year "1985" )
@InProceedings{pwplanning,
key "ginsberg86a",
author "GINSBURG, M.L.",
title "Possible Worlds Planning",
booktitle "Proceedings of the Workshop on Planning and Reasoning About Action",
pages "291-317",
month "July",
year "1986"}
@InProceedings(counterfactuals,
key "ginsberg85",
author "GINSBURG, M.",
title "Counterfactuals",
booktitle "Proceedings 9th IJCAI",
year "1985",
pages "80-86" )
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key "green81",
author "GREEN, C.C.",
title "Application of theorem proving to problem solving",
journal "Readings in Artificial Intelligence",
year "1981"}
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key "hammond83",
author "HAMMOND, K.J.",
title "Planning and Goal Interaction:
The use of past solutions in present situations",
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pages "148-151",
month "August",
year "1983"}
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key "hayes75",
author "HAYES, P.",
title "A representation for robot plans",
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pages "181ff")
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key "hayes79",
author "Hayes-Roth, Barabara, Hayes-Roth, Frederic, Rosenschein, Stan
and Cammarata, Stephanie",
title "Modeling Planning as an Incremental, Opportunistic Process",
booktitle "Proceedings of 6th IJCAI",
year "1979",
pages "375-383")
@Article(Hendrix73,
key "Hendrix73",
author "Hendrix, G.",
title "Modeling Simultaneous Actions and Continuous Processes",
journal "Artificial Intelligence",
volume "4",
year "1973",
pages "145-180")
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@TechReport(hewitt72,
key "hewitt72",
author "HEWITT, C.",
title "Description and Theoretical Analysis (Using Schemata) of PLANNER:
A Language for Proving Theorems and Manipulating Models in a Robot",
type "Technical Report",
number "258",
institution "MIT",
month "April",
year "1972" )
@InProceedings(lansky85a,
key "lansky85a",
author "LANSKY, A.",
title "Behavioral Planning for Multi-Agent Domains",
booktitle "Proceedings of 1985 Workshop on Distributed Artificial
Intelligence",
year "1985")
@TechReport(lansky85b,
key "lansky85b",
author "LANSKY, A.",
title "Behavioral Planning for Multi-Agent Domains",
type "Technical Note",
number 360,
institution "AI Center, SRI International",
year "1985" )
@TechReport(lansky87a
key "lansky87a",
author "Lansky, A.",
title "A Representation of Parallel Activity Based on Events, Structure,
and Causality",
year "1987",
number 401,
institution "AI Center, SRI International",
year "1987" )
@InBook(lansky87a1,
key "lansky87a1",
author "Lansky, A.",
title "A Representation of Parallel Activity Based on Events, Structure,
and Causality",
booktitle "Reasoning About Actions and Plans, Proceedings of the 1986
Workshop at Timberline, Oregon",
publisher "Morgan Kaufman",
pages "123-160",
year 1987
)
@comment("also submitted to the Computational Intelligence Journal
Special Issue on Planning")
@TechReport(lansky87b
key "lansky87b",
author "Lansky, A.",
title "Localized Event-based Reasoning for Multiagent Domains",
year "1987",
number 423,
institution "AI Center, SRI International",
year "1987" )
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key "Lansky87c",
author "Lansky, A. and Fogelsong, D.",
title "Localized Representation and Planning Methods for Parallel Domains",
booktitle "Proceedings of AAAI-87, Seattle, Wa.",
Organization "AAAI",
month "July",
pages "",
year "1987"}
@InProceedings(alv,
key "linden86",
author "LINDEN, T.A., MARSH, J.P. AND DOVE, D.L.",
title "Architecture and early experience with planning for the ALV",
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organization "IEEE",
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title "Unsolved problems in the blocks world",
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@TechReport(real-time,
key "marsh86",
author "MARSH, J.P. AND GREENWOOD, J.R.",
title "Real-time AI: software architecture issues",
type "White Paper",
institution "Planning Division, Advanced Decision Systems",
year "1986" )
@TechReport(elmer78,
key "mccalla78",
author "McCALLA, G., SCHNEIDER, P., COHEN, R. AND LEVESQUE, H.",
title "Investigations into planning and executing in an independent and
continuously changing microworld",
type "AI Memo",
number "78-2",
institution "Department of Computer Science, University of Toronto",
address "Toronto, Ontario, CANADA M5S 1A7",
year "1978" )
@InProceedings(elmer79,
key "mccalla79",
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year "1979",
pages "553ff" )
@InProceedings(elmer82a,
key "mccalla82a",
author "McCALLA, G. AND SCHNEIDER, P.",
title "Planning in a dynamic microworld",
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pages "248ff" )
@Article(elmer82b,
key "mccalla82b",
author "McCALLA, G., REID, L. AND SCHNEIDER, P.F.",
title "Plan creation, plan execution and knowledge acquisition in a
dynamic microworld",
journal "Int'l J of Man-Machine Studies",
volume "16",
year "1982",
pages "89ff" )
@InProceedings(elmer82c,
key "ward82",
author "WARD, B. AND McCALLA, G.",
title "Error detection and recovery in a dynamic planning environment",
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pages "172ff" )
@InBook(philosophy,
key "mccarthy69",
author "McCARTHY, J. AND HAYES, P.J.",
title "Some philosophical problems from the standpoint of artificial
intelligence",
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pages "463ff",
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@Article{circumscription,
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title "Circumscription: a form of non-monotonic reasoning",
volume "13",
pages "27-39",
journal "Artificial Intelligence",
year "1980"}
@Article{nasl,
key "mcdermott78",
author "McDERMOTT, D.",
title "Planning and acting",
journal "Cognitive Science",
volume "2",
pages "78ff",
year "1978"}
@Article{mcdermott82,
key "mcdermott82",
author "McDERMOTT, D.",
title "A temporal logic for reasoning about processes and plans",
journal "Cognitive Science",
volume "6",
pages "101-155",
year "1982"}
@PhDThesis(miller85,
key "miller85",
author "MILLER, D.P.",
title "Planning by Search Through Simulations",
institution "Yale University",
year "1985" )
@Article{attending1,
key "miller83",
author "MILLER, P.L.",
title "ATTENDING: critiquing a physician's management plan",
journal "IEEE Trans PAMI",
volume "5",
pages "449ff",
year "1983"}
@TechReport(shakey,
key "nilsson84",
author "NILSSON, N.J.",
title "Shakey the robot",
type "Tech Note",
number "323",
institution "AI Center, SRI International",
year "1984" )
@TechReport(tritables,
key "nilsson85",
author "NILSSON, N.J.",
title "Triangle tables: a proposal for a robot programming language",
type "Tech Note",
number "347",
institution "AI Center, SRI International",
year "1985" )
@TechReport(pednault85,
key "pednault85",
author "PEDNAULT, E.",
title "Preliminary Report on a Theory of Plan Synthesis",
type "Technical Note",
number "358",
institution "AI Center, SRI International",
month "September",
year "1985" )
@Article{pitrat,
key "pitrat77",
author "PITRAT, J.",
title "A chess combination program which uses plans",
volume "8",
pages "275-321",
journal "Artificial Intelligence",
year "1977"}
@InBook(id3,
key "quinlan",
author "QUINLAN, J.R.",
title "Inductive inference as a tool for the construction of efficient
classification programs",
editors "MICKALSKI, R., CARBONELL, J. AND MITCHELL, T.",
booktitle "Machine Learning: an Artificial Intelligence Approach",
publisher "Tioga",
address "Palo Alto, CA",
year "1983" )
@InProceedings(r1-soar,
key "rosenbloom84",
author "ROSENBLOOM, P.S. et al",
title "R1-SOAR: an experiment in knowledge-intensive programming in a
problem-solving architecture",
booktitle "Proceedings IEEE Workshop on Principles of KBSs (Denver)",
year "1984",
pages "65-71" )
@InProceedings(rosenschein81,
key "rosenschein81",
author "ROSENSCHEIN, S.J.",
title "Plan synthesis: A Logical Perspective",
booktitle "Proceedings 7th IJCAI",
year "1981",
pages "331-337" )
@InProceedings(rosenschein82,
key "rosenschein82",
author "ROSENSCHEIN, J.S.",
title "Synchronization of Multi-Agent plans",
organization "AAAI",
booktitle "Proceedings of AAAI-82",
year "1982",
pages "115-119")
@Article(rex1,
key "rosenschein85a",
author "ROSENSCHEIN, S.J.",
title "Formal theories of knowledge in AI and robotics",
journal "New Generation Computing",
volume "3",
year "1985",
pages "345-357" )
@InProceedings(rex2,
key "rosenschein85b",
author "ROSENSCHEIN, S.J. AND KAELBLING, L.P.",
title "A formal approach to the design of intelligent embedded systems",
booktitle "Proceedings Conf on Theoretical Aspects of Reasoning",
year "1985" )
@InProceedings(rex3,
key "kaelbling86",
author "KAELBLING, L.",
title "An architecture for intelligent reactive systems",
booktitle "Proceedings Workshop on Planning and Reasoning about Action",
year "1986",
organization "AAAI" )
@Article{sacerdoti74,
key "sacerdoti74",
author "SACERDOTI, E.D.",
title "Planning in a hierarchy of abstraction spaces",
journal "Artificial Intelligence",
volume "5",
pages "115-135",
year "1974"}
@Book(sacerdoti77,
key "sacerdoti77",
author "SACERDOTI, E.D.",
title "A Structure for Plans and Behavior",
publisher "Elsevier North-Holland",
address "New York",
year "1977" )
@InProceedings(sacerdoti79,
key "sacerdoti79",
author "SACERDOTI, E.D.",
title "Problem Solving Tactics",
booktitle "Proceedings of the 6th IJCAI",
year "1979",
pages "1077-1085" )
@InProceedings(concurrency,
key "sandewall86a",
author "SANDEWALL, E. AND RONNQUIST, R.",
title "A representation of action structures",
year "1986",
pages "89ff",
organization "AAAI",
booktitle "Proceedings of AAAI-86" )
@InProceedings(schoppers87,
key "schoppers87",
author "SCHOPPERS, M.J.",
title "Universal plans for unpredictable environments",
booktitle "Proceedings 10th IJCAI",
year "1987",
pages "to appear" )
@InProceedings(lawaly,
key "siklossy73",
author "SIKLOSSY, L. AND DREUSSI, J.",
title "An efficient robot planner which generates its own procedures",
booktitle "Proceedings 3rd IJCAI",
year "1973",
pages "423ff" )
@Article{smith80,
key "smith80",
author "SMITH, R.",
title "The contract net protocol: high-level communication and control
in a distributed problem solver",
journal "IEEE Trans Computers",
volume "29",
year "1980"}
@InProceedings(side-effects,
key "sridharan77",
author "SRIDHARAN, N.S. AND HAWRUSIK, F.",
title "Representation of actions that have side effects",
booktitle "Proceedings 5th IJCAI",
year "1977",
pages "265ff" )
@Article{ddb2,
key "stallman78",
author "STALLMAN, R.M. AND SUSSMAN, G.J.",
title "Forward reasoning and dependency-directed backtracking in a system
for computer-aided circuit analysis",
journal "Artificial Intelligence",
volume "9",
pages "135ff",
year "1978"}
@TechReport(steele-thesis,
key "steele80",
author "STEELE, G.L.",
title "The definition and implementation of a computer programming language
based on constraints",
type "Memo",
number "595",
institution "AI Lab, MIT",
year "1980" )
@Article(steele-aij,
key "sussman80",
author "SUSSMAN, G.J. AND STEELE, G.L.",
title "CONSTRAINTS: a language for expressing almost-hierarchical
descriptions",
journal "Artificial Intelligence",
volume "14",
year "1980" )
@Article{molgen1,
key "stefik81a",
author "STEFIK, M.J.",
title "Planning with constraints (MOLGEN: Part 1)",
journal "Artificial Intelligence",
volume "16",
pages "141-169",
year "1981"}
@Article{molgen2,
key "stefik81b",
author "STEFIK, M.J.",
title "Planning and meta-planning (MOLGEN: Part 2)",
journal "Artificial Intelligence",
volume "16",
pages "141-169",
year "1981"}
@InProceedings(stuart85,
key "stuart85",
author "STUART, C.J.",
title "An implementation of a multi-agent plan synchronizer using a temporal
logic theorem prover",
booktitle "Proceedings 9th IJCAI",
year "1985",
pages "1031ff" )
@TechReport(hacker,
key "sussman73",
author "SUSSMAN, G.J.",
title "HACKER: a computational model of skill acquisition",
type "Memo",
number "297",
institution "AI Lab, MIT",
year "1973" )
@TechReport(tate74,
key "tate74",
author "Tate, A.",
title "INTERPLAN: A plan generation system
which can deal with interactions between goals",
type "Research Memorandum",
number "MIP-R-109",
institution "Machine Intelligence Research Unit, University of Edinburgh",
year "1974" )
@PhDThesis(tate75,
key "tate75",
author "TATE, A.",
title "Using Goal Structure to Direct Search in a Problem Solver",
institution "Department of AI, University of Edinburgh",
year "1975" )
@TechReport(tate76,
key "tate76",
author "Tate, A.",
title "Project Planning Using a Hierarchic Non-Linear Planner",
type "Research Report",
number 245,
institution "Department of AI, University of Edinburgh",
year "1976" )
@InProceedings(tate77,
key "tate77",
author "TATE, A.",
title "Generating Project Networks",
booktitle "Proceedings 5th IJCAI",
year "1977",
pages "888-893" )
@InProceedings(tate84,
key "tate84",
author "TATE, A.",
title "Planning and Condition Monitoring in a FMS",
booktitle "Proceedings of the International Conference on
Flexible Manufacturing Systems",
year "1984")
@InProceedings(diversions,
key "vanbaalen84",
author "VanBAALEN, J.",
title "Exception handling in a robot planning system",
booktitle "Workshop on Principles of Knowledge-Based Systems",
year "1984",
pages "1ff",
organization "IEEE" )
@InBook(waldinger77,
key "waldinger77",
author "WALDINGER, R.",
title "Achieving several goals simultaneously",
editor "MICHIE, D.",
booktitle "Machine Intelligence 8",
publisher "Ellis Horwood",
address "Chichester, England",
pages "94-136",
year "1977" )
@TechReport(warren74,
key "warren74",
author "Warren, D.",
title "WARPLAN: A System For Generating Plans",
type "Memo",
number 76,
institution "Department of Computational Logic, University of Edinburgh",
month = "June",
year "1976" )
@InProceedings(ward82,
key "ward82",
author "WARD, B. and McCALLA, G.",
title "Error Detection and Recovery in a Dynamic Planning Environment",
organization "AAAI",
booktitle "Proceedings of AAAI",
year "1982",
pages "172-175")
@Article{wilensky81,
key "wilensky81",
author "WILENSKY, R.",
title "Meta-planning: representing and using knowledge about planning in
problem solving and natural language understanding",
journal "Cognitive Science",
volume "5",
year "1981"}
@Book{wilensky83,
key "wilensky83",
author "WILENSKY, R.",
title "Planning and Understanding: A Computational Approach to
Human Reasoning",
publisher "Addison-Wesley Publishing Company, Reading, Massachusetts",
year "1983"}
@Article(paradise1,
key "wilkins82",
author "WILKINS, D.E.",
title "Using knowledge to control tree searching",
journal "Artificial Intelligence",
volume "18",
year "1982")
@InProceedings(wilkins83,
key "wilkins83",
author "Wilkins, D.E.",
title "Representation in a Domain-Independent Planner",
booktitle "Proceedings of the 8th IJCAI",
year "1983")
@Article(paradise2,
key "wilkins80",
author "WILKINS, D.E.",
title "Using patterns and plans in chess",
journal "Artificial Intelligence",
volume "14",
year "1980")
@Article(sipe,
key "wilkins84",
author "WILKINS, D.E.",
title "Domain-independent planning: representation and plan generation",
journal "Artificial Intelligence",
volume "22",
year "1984",
pages "269ff" )
@Article(sipe-exec,
key "wilkins85",
author "WILKINS, D.E.",
title "Recovering from execution errors in SIPE",
journal "Computational Intelligence",
volume "1",
year "1985",
pages "33ff" )
@Article(sipe-flakey,
key "wilkins86",
author "WILKINS, D.E.",
title "High-level planning in a mobile robot domain",
journal "J Man-Machine Systems",
year "to appear" )
------------------------------
End of AIList Digest
********************
∂04-Dec-87 0602 LAWS@KL.SRI.COM AIList V5 #277 - Seminars, Conferences
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 4 Dec 87 06:02:40 PST
Date: Thu 3 Dec 1987 23:52-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #277 - Seminars, Conferences
To: AIList@SRI.COM
AIList Digest Friday, 4 Dec 1987 Volume 5 : Issue 277
Today's Topics:
Seminars - Dynamical Connectionism (MIT) &
Ideonomy (MIT) &
Rapid Prototyping via Executable Specifications (SMU) &
On the Threshold of Knowledge (MIT) &
Belief and Knowledge with Self-Reference and Time (SUNY) &
Knowledge-Based Software Activity Management (AT&T) &
Reasoning Under Uncertainty (BBN),
Conferences - Intelligent Tutoring Systems &
CHI'88 Workshop on Analytical Models
----------------------------------------------------------------------
Date: Monday, 9 November 1987 12:20-EST
From: Elizabeth Willey <ELIZABETH%OZ.AI.MIT.EDU at XX.LCS.MIT.EDU>
Subject: Seminar - Dynamical Connectionism (MIT)
From: Peter de Jong <DEJONG%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU>
Subject: Cognitive Science Calendar [Extract - Ed]
[Forwarded from the IRList digest.]
DYNAMICAL CONNECTIONISM
Elie Bienenstock
Universite de Paris-Sud
Wednesday, 11 November
E25-406, 12:00
In connectionist models, computation is usually carried out in a space
of activity levels, the connectivity state being frozen. in contrast,
dynamical connectionist models manipulate connectivity states. For
instance, they can solve various graph matching problems. They also
have the typical associative memory and error-correcting properties of
usual connectionist models. Applications include invariant pattern
recognition; dynamical connectionist models are able to generalize
over transformation groups rather than just Hamming distance. It is
proposed that these principles underlie much of brain function; fast-
modifying synapses and high-resolution temporal correlations may
embody the dynamical links used in this new connectionist approach.
------------------------------
Date: Monday, 9 November 1987 12:20-EST
From: Elizabeth Willey <ELIZABETH%OZ.AI.MIT.EDU at XX.LCS.MIT.EDU>
Subject: Seminar - Ideonomy (MIT)
Friday, 13 November 12:00pm E25-401
Ideonomy: Founding a 'Science of ideas'
In a book published in 1601, Francis Bacon urged that modern science
should have the equivalent of an 'ideonomic' character, as well as
being based on experimentation and induction. My talk concerns a
five-year effort to lay foundations for a science of ideas which I
call Ideonomy.
Whereas the field of Artificial intelligence is primarily aimed at the
automation of mind, cognitive science at the modeling of human
intelligence and thought, and logic at the formalization of reasoning,
ideonomy is preoccupied with the discovery, classification, and
systematization of universal ideas, with aiding and abetting man's use
of ideas, and with automating the generation of ideas. The ideonomist
holds that inattention to the latter things has hobbled the
development, and limited the success of the other fields; and that
properly all four subjects should be developed simultaneously and in
close coordination, being mutually necessary and synergistic.
At present ideonomy is divided into some 320 subdivisions, a few of
which are: the study of ignorance, the study of analogies, the study
of form, the study of causes, the study of questions, the study of
answers, the study of processes, and the study of cognitive and
heuristice principles. In each of these cases it seeks to identify:
the types (of these things), higher and lower taxa, examples,
interrelationships, causes, effects, reasons for studying, needed
materials and methods, fundamental concepts, abstract and practical
relations to other ideonomic divisions, and the like.
We can also characterize ideonomy in another way, such as:
the study of how elementary ideas can be combined, permuted, and
trnsformed as exhaustive groups of ideas;
A new language designed to facilitate thought and creativity;
An attempt to exploit the qualitiative laws of the universe.
------------------------------
Date: Sun, 29 Nov 1987 20:53 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Seminar - Rapid Prototyping via Executable Specifications
(SMU)
December 2, 1987, 1:30 PM Science Information Center, Southern Methodist
University
Express: Rapid Prototyping and Product Development via Integrated,
Knowledge-Based, Executable Specifications
ABSTRACT
Express includes integrated, knowledge-based, executable specifi-
cations and related tools to support the software development life
cycle, both rapid prototyping and full-scale engineering development.
We are building a prototype of Express at the Lockheed Software
Technology Center.
Express uses and extends powerful technologies--knowledge-based--
in relevant ways for aerospace products--domain languages, etc.--
across the software development lifecycle. Express builds on Cordell
Green's Refine technology from Reasoning Systems and extends it in
ways useful for aerospace software development.
Express provides knowledge-base support for
- programming knowledge and
- domain knowledge.
Express will provide executable languages, which are
- brief, in comparison to conventional high-level languages, and
- easy to comprehend.
Express makes a knowledge-based technology usable
- by systems engineers and applications specialists
- who are not experts in knowledge-based systems and
- who may use the system infrequently.
We employ human-factors analysis and the following approaches:
- Object-oriented user's model
- Direct manipulation: The user in control
- Bit-mapped graphical displays
- Point-and-select capabilities.
BIOGRAPHY
John W. McInroy joined the Lockheed Software Technology Center in
Austin, Texas, in November, 1986. He performs research in human
interface for Express, a prototype of a knowledge-based software
development environment. He published work-in-progress at the Fall
Joint Computer Conference in October, 1987, with Phillip J. Topping,
W. M. Lively, and Sallie V. Sheppard. In 1986, McInroy performed
research in human interface for the Proto software development
environment at International Software Systems, Inc. (ISSI), in
Austin, Texas.
>From 1978-1986, McInroy worked at IBM in Austin, Texas. He patented
eleven inventions and published nineteen others. He developed
fundamental user interface concepts for the Common User Access
portion of IBM's Systems Application Architecture (SAA). Earlier,
he specified parts of the user interface for Reportpack on the IBM
Displaywriter.
McInroy received an M.S. and a Ph.D. in Computer Science from the
University of North Carolina. In both graduate education and
subsequent career, he has pursued interests in human interface
and in software engineering.
McInroy can be contacted at the following address:
John W. McInroy
Lockheed Software Technology Center
Org. 96-01/Bldg. 30E
2100 E. St. Elmo Rd. 512/448-9715
Austin, Texas 78744 CSNET: McInroy@Lockheed.com
------------------------------
Date: Monday, 9 November 1987 12:20-EST
From: Elizabeth Willey <ELIZABETH%OZ.AI.MIT.EDU at XX.LCS.MIT.EDU>
Subject: Seminar - On the Threshold of Knowledge (MIT)
NE43, 8TH FLOOR
THUR, 11/12, 4:00PM
ON THE THRESHOLD OF KNOWLEDGE
The Case for Inelegance
Dr. Douglas B. Lenat
Principal Scientist, MCC
In this talk, I would like to present a surprisingly compact, powerful,
elegant set of reasoning methods that form a set of first principles
which explain creativity, humor, and common sense reasoning -- a sort of
"Maxwell's Equations" of Thought. I'd like very much to present them,
but, sadly, I don't believe they exist. So, instead, I'll tell you what
I've been working on down in Texas for the last three years.
Intelligent behavior, especially in unexpected situations, requires
being able to fall back on general knowledge, and being able to
analogize to specific but far-flung knowledge. As Marvin Minsky said,
"the more we know, the more we can learn".
Unfortunately, the flip side of that comes into play every time we build
and run a program that doesn't know too much to begin with, especially
for tasks like semantic disambiguation of sentences, or open-ended
learning by analogy. So-called expert systems finesse this by
restricting their tasks so much that they can perform relatively narrow
symbol manipulations which nevertheless are interpreted meaningfully
(and, I admit, usefully) by human users. But such systems are
hopelessly brittle: they do not cope well with novelty, nor do they
communicate well with each other.
OK, so the mattress in the road to AI is Lack of Knowledge, and the
anti-mattress is Knowledge. But how much does a program need to know,
to begin with? The annoying, inelegant, but apparently true answer is:
a non-trivial fraction of consensus reality -- the few million things
that we all know, and that we assume everyone else knows. If I liken
the Stock Market to a roller-coaster, and you don't know what I mean, I
might liken it to a seesaw, or to a steel spring. If you still don't
know what I mean, I probably won't want to deal with you anymore.
It will take about two person-centuries to build up that KB, assuming
that we don't get stuck too badly on representation thorns along the
way. CYC -- my 1984-1994 project at MCC -- is an attempt to build that
KB. We've gotten pretty far along already, and I figured it's time I
shared our progress, and our problems, with "the lab." Some of the
interesting issues are: how we decide what knowledge to encode, and how
we encode it; how we represent substances, parts, time, space, belief,
and counterfactuals; how CYC can access, compute, inherit, deduce, or
guess answers; how it computes and maintains plausibility (a sibling of
truth maintenance); and how we're going to squeeze two person-centuries
into the coming seven years, without having the knowledge enterers'
semantics "diverge".
------------------------------
Date: 1 Dec 87 19:57:14 GMT
From: sunybcs!rapaport@ames.arpa (William J. Rapaport)
Subject: Seminar - Belief and Knowledge with Self-Reference and Time
(SUNY)
STATE UNIVERSITY OF NEW YORK AT BUFFALO
GRADUATE GROUP IN COGNITIVE SCIENCE
PRESENTS
NICHOLAS ASHER
Department of Philosophy
and
Center for Cognitive Science
University of Texas at Austin
REASONING ABOUT BELIEF AND KNOWLEDGE WITH SELF-REFERENCE AND TIME
This talk will consider some aspects of a framework for investigating
the logic of attitudes whose objects involve an unlimited capacity for
self-reference. The framework, worked out in collaboration with Hans
Kamp, is the daughter of two well-known parents--possible worlds seman-
tics for the attitudes and the revisionist, semi-inductive theory of
truth developed by Herzberger and Gupta. Nevertheless, the offspring,
from our point of view, was not an entirely happy one. We had argued in
earlier papers that orthodox possible worlds semantics could never give
an acceptable semantics for the attitudes. Yet the connection between
our use of possible worlds semantics and the sort of reporesentational
theories of the attitudes that we favor remained unclear. This talk
will attempt to provide a better connection between the framework and
representational theories of attitudes by developing a notion of reason-
ing about knowledge and belief suggested by the model theory. This
notion of reasoning has a temporal or dynamic aspect that I exploit by
introducing temporal as well as attitudinal predicates.
Thursday, December 17, 1987
4:00 P.M.
Baldy 684, Amherst Campus
Co-sponsored by:
Graduate Studies and Research Initiative in Cognitive and Linguistic Sciences
Buffalo Logic Colloquium
There will be an informal discussion at a time and place to be
announced. Call Bill Rapaport (Dept. of Computer Science, 636-3193 or
3180) or Gail Bruder (Dept. of Psychology, 636-3676) for further infor-
mation.
------------------------------
Date: Wed, 2 Dec 11:49:20 1987
From: dlm%research.att.com@RELAY.CS.NET
Subject: Seminar - Knowledge-Based Software Activity Management (AT&T)
Title: Knowledge Based Software Activity Management:
An Approach to Planning, Tracking and Repairing
Software Projects
Speaker: Mark S. Fox
Associate Professor of Computer Science and Robotics
Carnegie-Mellon University
Date: Thursday, December 17, 1987
Time: 9:00 AM to 11:00 AM Central Time
(10:00 AM to Noon Eastern Time)
Place: AT&T Bell Laboratories - Indian Hill Main Auditorium
Video & audio simulcast to: AT&T Bell Labs Holmdel Room 1N-612 (Capacity: 85)
AT&T Bell Labs Murray Hill Auditorium
AT&T Bell Labs Whippany Auditorium
This talk will be video-taped.
Sponser: William Opdyke (ihlpf!opdyke)
Holmdel: Wendy A. Waugh -homxc!wendy
Murray Hill: Deborah L. McGuinness allegra!dlm
Whippany: David Lewy - whuts!lewy
----------
Talk Abstract
The management of activities is a central part of many tasks
such as project management, software engineering and factory
scheduling. Successful activity management leads to better
utilization of resources over shorter periods of time. Over
the past eight years we have been conducting research into
the process of activity management, including:
1. activity representation
2. planning and scheduling of activities
3. chronicling and reactive repair of activities
4. display and explanation of activities
5. distributed activity management
This presentation will briefly review the projects underway
in the Intelligent Systems Laboratory, describe the research
in each of the above areas, and demonstrate its application to
software engineering and project management.
----------
Speaker Bio.
Dr. Fox received his BSc in Computer Science from the
University of Toronto in 1975 and his PhD in Computer Science
from Carnegie-Mellon University in 1983. In 1979 he joined
the Robotics Institute of Carnegie-Mellon University as a
Research Scientist. In 1980 he started and was appointed
Director of the Intelligent Systems Laboratory. He
co-founded Carnegie Group in 1984. Carnegie-Mellon University
appointed him Associate Professor of Computer Science and
Robotics in 1987. His research interests include knowledge
representation, constraint directed reasoning and applications
of artificial intelligence to engineering and manufacturing
problems.
------------------------------
Date: Tue 1 Dec 87 16:11:42-EST
From: Marc Vilain <MVILAIN@G.BBN.COM>
Subject: Seminar - Reasoning Under Uncertainty (BBN)
BBN Science Development Program
AI Seminar Series Lecture
REASONING UNDER UNCERTAINTY
Andee Rubin
Education Department, BBN Labs
RUBIN@G.BBN.COM
BBN Labs
10 Moulton Street
2nd floor large conference room
10:30 am, Tuesday December 8
Statistical reasoning is an important prerequisite for both ordinary and
scientific thinking. Yet statistical reasoning is seldom taught to
pre-college students, and when it is, the emphasis is often on formulaic
manipulation, rather than on the concepts that are the foundation of
reasoning about statistical matters.
To address these concerns, we have developed, with funding from the
National Science Foundation, a computer-enhanced curriculum in
statistical reasoning called Reasoning Under Uncertainty that
incorporates the ELASTIC (TM) software system. The course is designed to
help high school students develop statistical reasoning abilities by
using real world activities with which they have practical experience.
The ELASTIC (TM) software, implemented on a Macintosh computer, is a tool
for recording, representing, and manipulating statistical information.
It has standard capabilities such as the ability to represent different
types of variables and create appropriate graphs, including confidence
intervals. Its most experimental features are three interactive
programs: Stretchy Histograms, Sampler, and Shifty Lines, each of which
allows students to interact directly with statistical graphics in order
to achieve a deeper understanding of the underlying statistical
concepts.
The curriculum and software were field-tested in Belmont and Cambridge
High Schools in the spring of 1987. The talk will describe and
demonstrate the pedagogical principles underlying the course and
software, some results of the field test, and our plans for future
development.
------------------------------
Date: 26 Nov 87 02:58:31 GMT
From: mind!bjr@princeton.edu (Brian J. Reiser)
Subject: Conference - Intelligent Tutoring Systems
Updated Call for Papers
INTERNATIONAL CONFERENCE ON
INTELLIGENT TUTORING SYSTEMS
1-3 JUNE 1988
MONTREAL, CANADA
Conference Objectives: ITS 88 will be a forum for presenting new
results in research, development, and applications of intelligent
tutoring systems. The aims of the conference are to bring together
specialists in the field of Artificial Intelligence and Education, to
share state of the art information among the attendees and to outline
future developments of ITS and their applications.
Topics of interest: The ITS 88 Conference will accept scientific and
techincal papers on all areas of ITS development, but will primarily
focus on the following areas:
Learning environments
Methodologies and architectures for educational systems
AI programming environments for educational use
Student modelling and cognitive diagnosis
Curriculum and knowledge representation
Evaluation of tutoring systems
Theoretical foundations of ITS
Knowledge acquisition in ITS
Design issues in building ITS
Practical uses of ITS
Empirical aspects of ITS
Program Committee Chairs are Prof. Gregor Bochmann of the University
of Montreal and Dr. Marlene Jones of the Alberta Research Council.
Program Committee: Ehud Bar-On, Dick Bierman, Jeffrey Bonar, Lorne
Bouchard, Jacqueline Bourdeau, Bernard Causse, Andy diSessa, Philippe
Duchastel, Gerhard Fischer, Jim Greer, Wayne Harvey, Lewis Johnson,
Heniz Mandl, Stuart Macmillan, Gordon McCalla, Vitoro Midoro, Riichiro
Mizoguchi, Andre Ouellet, Maryse Quere, Brian Reiser, Lauren Resnick,
John Self, Derek Sleeman, Elliot Soloway, Hans Spada, Georges Stamon,
Harold Stolovitch, Akira Takeuchi, Martial Vivet, Karl Wender, Beverly
Woolf, Massoud Yazdani.
Authors are requested to submit 5 copies (in English or French) of a
double-spaced manuscript of up to 5000 words by 15 December 1987 to:
Prof. Gregor Bochmann
Department d'informatique et de recherche operationnelle
Universite de Monteal
C.P. 6128, Succ "A"
Montreal CANADA
H3C 3J7
Authors will be notified of acceptance by February 29, 1988. Camera-ready
copies will be due April 10, 1988.
------------------------------
Date: Mon, 30 Nov 87 11:29:34 pst
From: Keith Butler <keith@BOEING.COM>
Subject: Conference - CHI'88 Workshop on Analytical Models
CALL FOR PARTICIPATION
CHI'88 Workshop on Analytical Models:
Predicting the Complexity of Human-Computer Interaction
In current practice, designs for human-computer interaction (HCI) can only
be evaluated empirically- after a prototype has been built in some form.
The empirical cycle is lengthy, expensive, and makes it difficult for HCI
designers to contribute timely revisions.
A more effective approach may be possible based on cognitive modeling and
perception research, currently underway at a number of sites. Cognitive
complexity models based on knowledge representation techniques, and computer-
based perceptual evaluations may provide tools to analyze HCI designs. These
tools would allow early evaluation of designs and design options before
actual implementation. The payoff of this approach could be great, but
substantial work remains before effective commercial application can be proven.
The Workshop on Analytical Models is scheduled as part of the CHI'88 Conference
in Washington, D.C. The one-day workshop will be held on Sunday, May 15, 1988.
The objective is to determine the current state of computational models for
perceptual and cognitive complexity, and then examine how such models might be
used as part of the HCI design process in industry and government. The goal of
the workshop is to provide guidance for further research, to stimulate thinking
about development, to facilitate the exchange of research findings, and to
encourage higher levels of activity.
Attendance at the workshop will be by invitation- limited to about twenty
people. People from two distinct backgrounds are sought: researchers who can
survey or critique a body of relevant work, and appliers of new technology to
HCI problems. The program committee, consisting of Keith Butler, Boeing
Advanced Technology Center, John Bennett, IBM Almaden Research Center, Peter
Polson, University of Colorado, and Tom Tullis, McDonnell Douglas Astronautics
Co., will invite researchers working on models that are relevant to HCI design
and representatives from industry and government who are concerned with HCI
and experienced with technology transfer. All attendees will participate in
roles such as speakers, discussants, panelists, or moderators.
Persons wishing to participate are requested to submit four copies of a
position paper. Researchers should provide a 2,000 word survey of work based
on their research. Representatives from industry and government should provide
a 1,000 word description of their organization's interest in HCI and their
experience with technology transfer.
Please send hard copies only to arrive by January 25, 1988 to:
Keith Butler For information:
Boeing Advanced Technology Center
PO Box 24346, M/S 7L-64 keith@boeing.com
Seattle, WA 98124 (206) 865-3389
Invitations will be mailed by February 23, 1988. Participants will also be
sent copies of selected papers along with a final agenda for the workshop.
------------------------------
End of AIList Digest
********************
∂04-Dec-87 0900 LAWS@KL.SRI.COM AIList V5 #278 - Queries, Daedalus, Neural Network Reports
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 4 Dec 87 09:00:05 PST
Date: Fri 4 Dec 1987 00:05-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #278 - Queries, Daedalus, Neural Network Reports
To: AIList@SRI.COM
AIList Digest Friday, 4 Dec 1987 Volume 5 : Issue 278
Today's Topics:
Queries - Expert Systems for Restoring Load-Flow &
Applied Neural-Network Experiences &
Training Sets for Rule Induction & Medical CAI References &
Portable OPS-5 and CLIPS 4.0 & CogSci Call for Papers &
RACTER & DCG Parser & Recording Mouse Input,
Journal Issue - AI in DAEDALUS,
Reports - Neural Network Reports
----------------------------------------------------------------------
Date: Tue, 24 Nov 87 18:50:01 GMT
From: A385%EMDUCM11.BITNET@CUNYVM.CUNY.EDU
Subject: Expert systems restoring load-flow andbiliography
Date: 24 November 1987, 18:31:46 GMT
From: Javier Lopez Torres Tf: (91) 7113887 A385 at EMDUCM11
Hello AI community from Spain!
The AI department of this University (Complutense de Madrid) along with a great
Spanish electric company are planning to develop an expert system to restore
high tension networks when overloading on the load flow appears.
We are interested in dynamic determination of speed and voltage governors at
electric centrals to perform dynamic simulation studies -Stability and calcula-
tion analysis.
At the moment we are using the PSS/E package to calculate the load flow dis-
tribution, running on a VAX/750 and have a lot of problems to connect it to our
MODCOMP computer. So, please:
(1) Is there anyone who have done the above studies or knows someone who ha
ve done it?.
(2) Is anyone aware of any survey publications related to the above mentio-
ned areas?
(3) Has anyone got any bibliography related to the above subject areas?
We are most interested in communicating with researchers currently involved
in this kind of expert systems.
Thanks you very much in advance for any help or suggestion as we're really
very misled.
Sincerely:
Javier Lopez Torres
Universidad Complutense de Madrid
A385%EMDUCM11.BITNET
------------------------------
Date: 1 Dec 87 06:26:36 GMT
From: portal!cup.portal.com!Barry_A_Stevens@uunet.uu.net
Subject: request for information, offer to share info on neural nets
REQUEST FOR INFORMATION ON NEURAL NETWORKS
Barry A Stevens
Applied AI Systems
-
I am conducting a survey to identify the "useful" neural network
paradigms. There are many available, but few have established
themselves as robust and trainable in the commercial environment.
-
I seek either: pointers to information sources, or information itself.
With enough response, I will summarize and post to the net. The three
types of information sought are:
-
***The usefulness of the network paradigms listed below when applied
to real problems with real data;
-
***The tests that a set of training data must meet to be useable with
each of the paradigms;
-
***The classes of problems for which each paradigm is useful.
-
-
Comments on stability, robustness, ease of construction and test, and
results obtained from the application would be useful and welcome.
Pointers to sources that contain such information are equally welcome.
-
I already have access to numerous technical papers that talk about
such things as "spatiotemporal uses" as a class of applications. What
is of more interest is "The Spatiotemporal Paradigm was successfully
used to identify specific waveforms and patterns in foreign currency
trading data... etc.". Or this: "a backpropogation network was used to
implement a consumer loan approval system, with performance exceeding
both that of human loan officers making the loans and a rule-based
expert system designed for the same purpose. The network was trained
in three weeks, the expert system took two manyears to build."
-
These network paradigms are of specific interest:
-
Back Propogation
Back Propogation - shared weights
Counter Propogation
Adaptive Resonance 1 and 2
Binary Associative Memory
Spatiotemporal Network
Neocognitron
Hopfield Network
Kohonen Feature Map
Boltzman Machine
Group Method of Data Handling
Barron Associates: polynomial synthesis
-
If there are others that you feel are also of interest, please feel
free comment on them as well. Also, I realize that some of these are
not neural network paradigms per se, but they have been used in the
same situations and are therefore of interest.
-
I can be reached by email or at this address and phone:
-
Barry A Stevens
Applied AI Systems, Inc.
PO Box 2747
Del Mar, CA 92014
619-755-7231
------------------------------
Date: 2 Dec 87 02:22:18 GMT
From: stuart%warhol@ads.arpa (Stuart Crawford)
Reply-to: stuart@ads.arpa ()
Subject: Training Sets Needed for Rule Induction System
I'd like to start a collection of training sets for use with a rule induction
system. The basic requirements are that a training set be composed of a
collection of observations, each of which consists of a *known* class
assignment, and a vector of observed features. The features may be integer,
real or nominal (categorical) valued.
Ideally, I am looking for training sets which are drawn from a medical domain,
and have from 50-500 observations. Real data is preferred, but simulated data
is ok too. However, if the data is simulated, please supply the relevant
information needed to re-generate the data (program used, random number
generator used, random number seeds used, etc.).
If you have a training set, please contact stuart@ads.arpa.
Stuart Crawford
Advanced Decision Systems
201 San Antonio Circle, Suite 286
Mountain View, CA 94040
(415) 941-3912 x325
Stuart
------------------------------
Date: 30 Nov 87 19:13:02 GMT
From: cunyvm!byuvax!cockaynes@psuvm.bitnet
Subject: Medical CAI References?
I am conducting a literature
search of research studies
demonstrating the effectiveness
of computer assisted instruction,
especially computer simulations,
in medical education. Does anyone
know of recent or on-going
research?
Please e-mail responses to me
and I will summarize to the net.
Contact Susan Cockayne at
CockayneS@byuvax.bitnet
------------------------------
Date: 1 Dec 87 16:38:50 GMT
From: ihnp4!homxb!whuts!mtune!codas!ufcsv!beach.cis.ufl.edu!mfi@ucbvax
.Berkeley.EDU (Mark Interrante)
Subject: Portable OPS-5? and CLIPS 4.0?
In a recent paper I saw a references to portable ops5 and clips 4.0.
It is my understanding that these are public domain. Dose anyone have
copies that could be Emailed?
------------------------------
Date: 3 Dec 87 00:56:31 GMT
From: A.GP.CS.CMU.EDU!spiro@PT.CS.CMU.EDU (Spiro Michaylov)
Subject: CogSci call for papers wanted
Does anybody have a soft copy of the call for papers for the next CogSci
conference? If so could you please e-mail it to me directly?
Otherwise pointers to a hard copy would be appreciated.
Thanks in advance.
Spiro Michaylov.
CMU-CS.
spiro@a.gp.cs.cmu.edu
------------------------------
Date: Thu, 03 Dec 87 20:04:39 EST
From: Michael Nosal <ST502042%BROWNVM.BITNET@WISCVM.WISC.EDU>
Subject: Request for RACTER
Howdy!
I am interested in locating the (in)famous 'AI' program RACTER. Unfortunately I
don't remember too much about it except that I first heard about it in an arti
cle in Scientific American and that a book called "The Policeman's Beard is Hal
f Constructed" that contained bits of prose that it created was published a few
years ago. I am interested in finding any version of the program (source code
would be fantastic) If there is a group or company that owns the rights to it o
r is selling a commercial version, I would love to know their address. While I'
m on the subject, if anyone knows of other 'Eliza-like' AI programs out there,
please let me know.
Thanks in advance,
Michael Nosal (please respond to this account if possible)
------------------------------
Date: Thu, 03 Dec 87 20:27:46 EST
From: ganguly@ATHENA.MIT.EDU
Subject: DCG
Hi!
Does someone have a Definite Clause Grammar parser written in
Edinburgh PROLOG that I may use as an user interface ?
Thanking in advance,
Jaideep Ganguly
------------------------------
Date: Thu 3 Dec 87 11:42:56-CST
From: CS.MARTINICH@R20.UTEXAS.EDU
Subject: recording mouse input
Does anyone know of a program that "records" mouse input on a
SUN workstation? I need a program that "records" mouse input
which can be "played back" as input to a program.
I would appreciate any information on such a program.
--Leslie Martinich
cs.martinich@r20.utexas.edu
------------------------------
Date: Mon, 23 Nov 87 15:54:46 EST
From: amcad!alyson@husc6.harvard.edu
Reply-to: alyson%amcad.uucp@husc6.harvard.edu
Subject: AI DAEDALUS
To: Robert Engelmore Editor-in-chief AI Magazine Menlo Park, CA.
Re: New issue of DAEDALUS on AI
Parl Gerald (BCS) has suggested that I be in touch with you concerning
our Winter 1988 issue of DAEDALUS - journal of the American Academy of
Arts and Sciences - which deals exclusively with "Artificial Intelligence."
Both he and Mike Hamilton (AAAI) have suggested that it might be useful
to get news of this forthcoming issue onto the ARPANET AI Bulletin Board.
Authors in the forthcoming issue include: Papert, Dreyfus H & S, Sokolowski,
McCorduck, Cowan & Sharp, Jacob Schwartz, Reeke & Edelman, Hillis, Waltz,
Hurlbert & Poggio, Sherry Turkle, Putnam, Dennett and McCarthy. Subjects
include, among others, the following: Natural and AI, Neural Nets and AI,
Real Brains and AI, Making Machines See, AI and Psychoanalysis, Philos-
ophers Encounter AI, and Mathematical Logic and Ai.
Copies from printer avialable by mid-December.
Best wishes,
Guild Nichols
DAEDALUS
------------------------------
Date: Wed, 2 Dec 87 12:26:33 EST
From: takefuji%uniks.ece.scarolina.edu@RELAY.CS.NET
Subject: Neural Network Reports
A Conductance programmable "neural" chip based on a Hopfield model employs
deterministically/stochastically controlled switched resistors
Yutaka Akiyama*, Yoshiyasu Takefuji**, Yong B. Cho**, Yoshiaki Ajioka*,
and Hideo Aiso*
* Keio University
Department of Electrical Engineering
3-14-1 Hiyoshi, Kouhoku-ku, Yokohama 223
JAPAN
** University of South Carolina
Department of Electrical and Computer Engineering
Columbia, SC 29208
(803)-777-5099
Abstract
The artificial neural net models have been studied for many years.
There has been a recent resurgence in the field of artificial neural
nets caused by Hopfield. Hopfield models are suitable for VLSI
implementations because of the simple architecture and components such
as OP Amps and resistors. However VLSI techniques for implementing the
neural models face difficulties dynamically changing the values of the
conductances Gij to represent the problem constraints.
In this paper, VLSI neural network architectures based on a Hopfield
model with deterministically/stochastically controlled variable
conductances are presented. The stochastic model subsumes both
functions of the hopfield model and Boltzmann machine in terms of
neural behaviors. We are under implementations of two CMOS VLSI
neural chips based on the proposed methods.
_______________________________________________________________________________
Multinomial Conjunctoid Statistical Learning Machines
Yoshiyasu Takefuji, Robert Jannarone, Yong B. Cho, and Tatung Chen
Unversity of South Carolina
Department of ECE
Columbia, SC 29208
(803)777-5099
ABSTRACT
Multinomial Conjunctoids are supervised statistical modules that learn
the relationships among binary events. The multinomial conjunctoid
algorithm precluded the following problems that occur in existing
feedforward multi-layerd neural networks:(a) existing networks often
cannot detemine underlying neural architectures, for example how many
hidden layers should be used, how many neurons in each hidden layer are
required, and what interconnections between neurons should be made;(b)
existing networks cannot avoid convergence to suboptimal solutions
during the learning process; (c) existing networks require many
iterations to converge, if at all, to stable states; and (d) existing
networks may not be sufficiently general to reflect all learning
situations.
By contrast multinomial conjunctoids are based on a well-developed
statistical decision theory framework, which guarantees that learning
algorithms will converge to optimal learning states as the number of
learning trials increases, and that convergence during each trial will
be very fast.
_________________________________________________________________________
Conjunctoids: Statistical Learning Modules for Binary Events
Robert Jannarone, Kai Yu, and Y. Takefuji
University of South Carolina
Department of ECE
Columbia, SC 29208
(803)777-7930
ABSTRACT
A general family of fast and efficient PDP learning modules for binary events
is introduced. The family (a) subsumes probabilistic as well as functional
event associations; (b) subsumes all levels of input/output associations; (c)
yields truly parallel learning processes; (d) provides for optimal parameter
estimation; (e) points toward a workable description of optimal model
performance; (f) provides for retaining and incorporating previously learned
information; and (g) yields procedures that are simple and fast enough to
be serious candidates for reflecting both neural functioning and real time
machine learning. Examples as well as operationial details are provided.
_________________________________________________________________________
If you need the full copies of those papers, please state which papers you are
requesting through Email, phone, or USmail.
For Multinomial and VLSI neural chips papers:
Dr. Y. Takefuji
University of South Carolina
Deparment of Electrical and Computer Engineering
Columbia, SC 29208
(803)777-5099
(803)777-4195
takefuji@uniks.ece.scarolina.edu
For Conjuncoids papers:
Dr. Robert Jannarone
University of South Carolina
Department of Electrical and Computer Engineering
Columbia, SC 29208
(803) 777-7930
jann@uniks.ece.scarolina.edu
Thank you...
------------------------------
End of AIList Digest
********************
∂07-Dec-87 2352 LAWS@KL.SRI.COM AIList V5 #279 - Prolog Source Library, Seminar, Conference
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 7 Dec 87 23:52:20 PST
Date: Sun 6 Dec 1987 22:04-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #279 - Prolog Source Library, Seminar, Conference
To: AIList@SRI.COM
AIList Digest Monday, 7 Dec 1987 Volume 5 : Issue 279
Today's Topics:
Announcement - Prolog Source Library,
Seminar - Composing and Decomposing Universal Plans (SRI),
Conference - AI Workshop in Singapore 1989
----------------------------------------------------------------------
Date: 3-DEC-1987 22:48:59 GMT
From: POPX@VAX.OXFORD.AC.UK
Subject: Prolog Source Library
From: Jocelyn Paine,
St. Peter's College,
New Inn Hall Street,
Oxford OX1 2DL.
Janet Address: POPX @ OX.VAX
PROLOG SOURCE LIBRARY
I teach AI to undergraduates, as a one-term practical course in the
Experimental Psychology degree. For the course, I use Poplog Prolog, on
a VAX under VMS. During the course, I talk about topics like scripts,
mathematical creativity, planning, natural language analysis, and expert
systems; I exemplify them by mentioning well-known programs like GPS,
Sam, and AM.
I would like my students to be able to run these programs, and to
investigate their mechanism and limitations. For students to incorporate
into their own programs, I'd also like to provide a library of Prolog
tools such as chart parsers, inference engines, search routines, and
planners. Unfortunately, published descriptions of the famous programs
give much less information than is necessary to re-implement them. As
for tools like planners and inference engines: the literature is often
more helpful, but I still have to do a lot of work which must have been
done before, even if it's merely typing in code from excellent textbooks
like "The Art of Prolog".
I'm sure other Prolog programmers have this problem too.
I have therefore set up a LIBRARY OF PROLOG SOURCE CODE, which I will
distribute over the British academic network (Janet) and nets like
Bitnet connected to Janet, to anybody who wants it. I will take
contributions from anyone who wants to provide them, subject to a few
conditions mentioned below. I proposed this in AIList Bulletin V5 267:
here are the details of how the library works. If you want to contribute
entries, or to request them, please read on...
How to send contributions.
Please send Prolog source for the library, to user POPX at Janet
address OX.VAX (the Vax-Cluster at Oxford University Computing
Service). If a file occupies more than about 1 megabyte, please send a
short message about it first, but don't send the large file itself
until I reply with a message requesting it. This will avoid the
problems we sometimes have where large files are rejected because
there isn't enough space for them.
I accept source on the understanding that it will be distributed to
anyone who asks for it. I intend that the contents of the library be
treated in the same way as (for example) proofs published in the
mathematical literature, and algorithms published in computer science
textbooks - as publicly available ideas which anyone can experiment
with, criticise, and improve.
I will try to put an entry into the library within one working week of
its arrival.
Catalogue of entries.
I will keep a catalogue of contributions available to anyone who asks
for it.
The catalogue will contain for each entry: the name and geographical
address of the entry's contributor (to prevent contributors receiving
unwanted electronic mail, I won't include their electronic mail
addresses unless I'm asked to do so); a description of the entry's
purpose; and an approximate size in kilobytes (to help those whose
mail systems can't receive large files easily).
I will also include my evaluations of its ease of use, of its
portability and standardness (by the standards of Edinburgh Prolog);
and my evaluation of any documentation included.
Quality of entries.
Any contribution may be useful to someone out there, so I'll start by
accepting anything. I'm not just looking for elegant code, or logical
respectability. However, it would be nice if entries were to be
adequately documented, to come with examples of their use, and to run
under Edinburgh Prolog as described in "Programming in Prolog" by
Clocksin and Mellish. If you can therefore, I'd like you to follow the
suggestions below.
The main predicate or predicates in each entry should be specified
so that someone who knows nothing about how they work can call them.
This means specifying: the type and mode of each argument, including
details of what must be instantiated on call, and what will have
become instantiated on return; under what conditions the predicate
fails, and whether it's resatisfiable; any side-effects, including
transput and clauses asserted or retracted; whether any initial
conditions are required, including assertions, operator
declarations, and ancilliary predicates. In some cases, other
information, like the syntax of a language compiled by the
predicate, may be useful.
A set of example calls would be useful, showing the inputs given,
and the outputs expected. Use your discretion: if you contribute an
expert system shell for example, I'd like a sample rulebase, and a
description of how to call the shell from Prolog, and some
indication of what questions I can ask the shell, but I don't
require that the shell's dialogue be reproduced down to every last
carriage return and indentation.
For programmers who want to look inside an entry, adequate comments
should be given in the source code, together perhaps with a more
general description of how the entry works, including any relevant
theory.
In the documentation, references to the literature should be given,
if this is helpful.
Entries should be runnable using only the predicates and operators
described in "Programming in Prolog" (if they are not, I may not be
able to test them!). I don't object to add-on modules being included
which are only runnable under certain implementations - for example,
an add-on with which a planner can display its thoughts in windows
on a high-resolution terminal - but they will be less generally
useful.
As mentioned earlier, I will evaluate entries for documentation and
standardness, putting my results into the catalogue. If I can, I
will also test them, and record how easy I found them to use, by
following the instructions given.
I emphasise that I will accept all entries; the comments above suggest
how to improve the quality of entries, if you have the time.
Requesting entries.
I can't afford to copy lots of discs, tapes, papers, etc, so I can
only deal with requests to send files along the network. Also, I can't
afford to send along networks that I have to pay to use from Janet.
You may request the catalogue, or a particular entry in it. I will
also try to satisfy requests like "please send all the natural
language parsers which you have" - whether I can cope with these will
depend on the size of the library.
I will try to answer each request within seven working days. If you
get no reply within fourteen working days, then please send a message
by paper mail to my address. Give full details of where your
electronic mail messge was sent from, the time, etc. If a message
fails to arrive, this may help the Computing Service staff discover
why.
Although I know Lisp, I haven't used it enough to do much with it,
though I'm willing just to receive and pass on Lisp code, and to try
running it under VAX Lisp or Poplog version 12 Lisp.
------------------------------
Date: Thu, 3 Dec 87 16:03:52 PST
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Composing and Decomposing Universal Plans (SRI)
COMPOSING AND DECOMPOSING UNIVERSAL PLANS
Marcel Schoppers
Advanced Decision Systems (MARCEL@ADS.ARPA)
11:00 AM, MONDAY, December 7
SRI International, Building E, Room EJ228
``Universal plans'' are representations for robot behavior; they are
unique in being both highly reactive and automatically synthesized. As
a consequence of this plan representation, subplans have conditional
effects, and hence there are conditional goal conflicts. When block
promotion (= subplan concatenation) cannot remove an interaction, I
resort not to individual promotion (= subplan interleaving) but to
confinement (falsifying preconditions of the interaction). With
individual promotion out of the way, planning is a fundamentally
different problem: plan structure directly reflects goal structure,
plans can be conveniently composed from subplans, and each goal
conflict needs to be resolved only once during the lifetime of the
problem domain. Conflict analysis is computationally expensive,
however, and interactions may be more easily observed at execution
time than predicted at planning time.
All conflict elimination decisions can be cached as annotated
operators. Hence it is possible to throw away a universal plan, later
reconstructing it from its component operators without doing any
planning. Indeed, an algorithm resembling backchaining mindlessly
reassembles just enough of a universal plan to select an action that
is helpful in the current world state. Since the selected action is
both a situated response and part of a plan, recent rhetoric about
situated action as *opposed* to planning is defeated.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Thu, 03 Dec 87 10:46:56 SST
From: Joel Loo <ISSLPL%NUSVM.BITNET@wiscvm.wisc.edu>
Subject: Conference - AI Workshop in Singapore 1989
Thanks for those who expressed interest in the call for papers
posted by me recently. Due to the overwhelming queries, it might
be beneficial to post a detailed one here for your convenience.
2nd International IFIP/IFAC/IFORS
Workshop on
ARTIFICIAL INTELLIGENCE
IN ECONOMICS AND MANAGEMENT
SINGAPORE
January 11-13, 1989
Organized by the Institute of Systems Science
National University of Singapore
+-----------------+
! CALL FOR PAPERS !
+-----------------+
The Second International Conference on AI in Economics and
Management will be held in Singapore during the 2nd week of
January 1989. The workshop will address issues relevant to the
use of AI Technology in Economic and Management communities.
Topics for the workshop will cover both technology and
applications.
Professor Herbert Simon, Nobel Laureate will be the Keynote
Speaker.
This workshop will address research and applications of
artificial intelligence techniques and tools, in the areas of:
finance, accounting, marketing, banking, insurance, economics,
human-resource management, assets adminstration, decision
support systems, public and private services, office automation,
law, and manufacturing planning.
The techniques to be presented should be explicitly relevant to
the above application areas, and include: knowledge
representation, search and inference, knowledge acquisition,
intelligent interfaces, knowledge base validation, natural
language analysis, planning procedures, and task support systems.
The tools to be presented should also be specific in design or in
use to the application areas discussed at the workshop, and may
cover: application specific expert systems, front-ends to
decision support systems, interfaces to database systems,
interfaces between symbolic and procedural processors, object
oriented environment.
The workshop will have contributed papers and case sessions.
There will be separate tutorials on the use of AI technology on
January 9 & 10.
** Paper Submission Procedure **
Authors should submit 700 word extended abstracts, typed with
double-spacing, in 2 copies before July 1, 1988 to:
Mrs Vicky TOH
Institute of Systems Science
National University of Singapore
Kent Ridge
Singapore 0511
Each abstract should include full address of all authors, and
references in numerical order. Authors of accepted submission
will be notified by September 1, 1988. Papers not received in
full by this date will not be included for presentation. All
papers must be in English.
** Software Submission Procedure **
Authors not willing to submit a paper, but ready to demonstrate
an artifical intelligence software program are encouraged to do
so. The submission procedure is the same as for papers. The host
computers, operating systems, utilities and all interfaces must
be specified exactly, as well as the architecture and principles
underlying the program. Authors will have to be responsible for
all logistics, including supply of computers etc.
All authors of accepted papers or of accepted software demos, are
expected to present their work in person. Failure to do so will
result in the corrsponding paper not appearing in the workshop
proceedings.
** Exhibit **
Companies interested in exhibiting publications equipment or
software falling within the scope of the workshop, should contact
the organizing committee.
---------------------------------
Important Dates
Tutorials : 9 & 10 Jan 1989
Workshop : 11-13 Jan 1989
For submission
of extended
abstract : 1 Jul 1988
Notification of
Acceptance : 1 Sep 1988
Camera Ready
Papers Due : 1 Nov 1988
---------------------------------
Language : Throughout the workshop, English will be the
official language. Translation facilities will NOT
be available.
Proceedings : Proceedings will be published after the workshop,
with Y.H. Pao, L.F.Pau, J.Motiwalla and H.H.Teh as
editors. Copyrights for accepted papers are thus
transferred to the publishers.
Registration: US$200 for Tutorials
Fees US$200 for Workshop
US$300 for the complete Workshop & Tutorials.
(fees cover freshments, lunches and conference
documentation)
Hotels : The price range for 5-star hotels in Singapore is
US$50-US$75
Travel : Arrangements will be made for special excursion air
fares.
(Request for information should be directed as well to Mrs Vicky
Toh at the above address (Telex: ISSNUS RS 39988, Fax: 7782571,
BITNET: ISSVCT@NUSVM))
*** Conference Committee ***
Chairman : Juzar MOTIWALLA, Institute of Systems Science,
National University of Singapore
Program Committee Chairmen:
Yoh-Han PAO, Case Institute of Technology, US
L.F. PAU, Technical University, Denmark
Hoon-Heng TEH, Institute of Systems Science, Singapore
Organizing Committee Chairman:
Desai NARASIMHALU, Institute of Systems Science, Singapore
*** International Program Committee *** (tentative)
Jan Alkins, AION, US
Jason Catlett, Univ. of Sydney, AUS
C.H. Hu, Academy of Sciences, PRC
Jae Kyu Lee, KAIST, KOREA
Peng Si Ow, CMU, US
Suzanne Pinson, Univ. of Paris, FRANCE
Edison Tse, Stanford Univ., US
Andrew Whinston, Purdue Univ., US
------------------------------
End of AIList Digest
********************
∂07-Dec-87 2354 LAWS@KL.SRI.COM AIList V5 #280 - Robot Kits, Mac ES Tools, Scientific Method
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 7 Dec 87 23:53:19 PST
Date: Sun 6 Dec 1987 22:13-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #280 - Robot Kits, Mac ES Tools, Scientific Method
To: AIList@SRI.COM
AIList Digest Monday, 7 Dec 1987 Volume 5 : Issue 280
Today's Topics:
Queries - Semantic Network Software & CHAT80 &
Portable OPS-5 and Pseudo-Scheme & Expert System Liability,
Education - Robotic "kits" for Kids,
AI Tools - Expert System Tools for the Mac,
Philosophy - Neural Nets are Science
----------------------------------------------------------------------
Date: 4 December 1987, 21:24:47 LCL
From: KANNAN@SUVM
Reply-to: AIList@Stripe.SRI.Com
Subject: Semantic Network Software
I would like to have information on any software package (shells or
specific AI languages) that supports semantic networks. I am at present
using semantic networks as a documentation tool and would like to
represent the same using a shell.
Thanks
Reply to KANNAN at SUVM
Ramu Kannan
------------------------------
Date: Sat, 05 Dec 87 20:10:21 EST
From: ganguly@ATHENA.MIT.EDU
Subject: chat80
Hi !
I am interested in using the program CHAT80 developed
by Fernando Periera. I would appreciate very much if
someone could send me a copy of this program. I understand
that this program is documented in the following technical report:
Logic for Natural Language Analysis -
SRI Technical Note 275 - Frenando Periera
------------------------------
Date: 6 Dec 87 17:54:59 GMT
From: USENET Master <uunet!gould!ufcsv!news@RUTGERS.EDU>
Reply-to: mfi@beach.cis.ufl.edu (Mark Interrante)
Subject: Portable OPS-5 and Pseudo-Scheme
I am looking for two systems I saw referenced recently: Portable OPS-5 written
in CL and Pseudo-Scheme written in CL. If anyone has these or has pointers to
these, I would appriciate hearing about it.
Mark Interrante CIS Department
University of Florida
Internet: mfi@beach.cis.ufl.edu Gainesville, FL 32611
------------------------------
Date: 4 Dec 87 05:05:00 GMT
From: portal!cup.portal.com!Barry_A_Stevens@uunet.uu.net
Subject: Can you sue an expert system?
I am interested in the legal aspects of using expert systems.
Consider, and please comment on, this scenario.
* * * * * * * * * * *
A well-respected, well-established expert systems(ES) company constructs
an expert financial advisory system. The firm employs the top ES
applications specialists in the country. The system is constructed with
help from the top domain experts in the financial services industry. It
is exhaustively tested, including verification of rules, verification of
reasoning, and further analyses to establish the system's overall value.
All results are excellent, and the system is offered for sale.
Joe Smith is looking for a financial advisory system. He reads the sales
literature, which lists names of experts whose advice was used when
building the system. It lists the credentials of the people in the
company who were the implementors. It lists names of satisfied users,
and quotes comments that praise the product. Joe wavers, weakens, and
buys the product.
"The product IS good,", Joe explains. "I got it up and running in less
than an hour!" Joe spends the remainder of that evening entering his own
personal financial data, answering questions asked by the ES, and
anticipating the results.
By now, you know the outcome. On the Friday morning before Black Monday,
the expert system tells Joe to "sell everything he has and go into the
stock market." ESs can usually explain their actions, and Joe asks for
an explanation. The ES replies "because ... it's only been going UP for
the past five years and there are NO PROBLEMS IN SIGHT."
Joe loses big on Monday. Since he lives in California, (where there is
one lawyer for every four households, or so it seems, and a motion
asking that a lawsuit be declared frivolous is itself declared
frivolous) he is going to sue someone. But who?
The company that implemented the system?
The domain experts that built their advice into the system?
The knowledge engineers who turned expertise into a system?
The distributor who sold an obviously defective product?
Will a warranty protect the parties involved? Probably not. If real
damages are involved, people will file lawsuits anyway.
Can the domain experts hide behind the company? Probably not. The
company will specifically want to use their names and reputations as the
source of credibility for the product. The user's reaction could be,
"There's the so-and-so who told me to go into the stock market."
Can the knowledge engineers be sued for faulty construction of a system?
Why not, when people who build anything else badly can be sued?
How about the distributor -- after all, he ultimately took money from
the customer and gave him the product.
* * * * * * * * * * *
I would be very interested in any of your thoughts on this subject. I'd
be happy to summarize the responses to the net.
Barry A. Stevens
Applied AI Systems, Inc.
PO Box 2747
Del Mar, CA 92014
619-755-7231
------------------------------
Date: 4 Dec 87 19:47:27 GMT
From: pitstop!sundc!potomac!garybc@sun.com (Gary Berg-Cross)
Subject: Robotic "kits" for kids
Does anybody have experience with robotic kits appropriate for
kids 9-14? I'm thinking of robot arms up to more complete systems that
might be assembled over a period of weeks and serve to introduce one
or two younsters to the engineering issues before they enjoy the
fruits of their work. Do any worthwhile products exist out there and
are there ones that might be in the price range of start-up computer
system costs?
Expereiences and references would be appreciated.
--
Gary Berg-Cross. Ph.D. (garybc@Potomac.ADS.COM)
Advanced Decision Systems vi .signature
ZZ
a
------------------------------
Date: 5 Dec 87 07:29:38 GMT
From: glacier!jbn@labrea.stanford.edu (John B. Nagle)
Subject: Re: Robotic "kits" for kids
Edmund Scientific, of Barrington, NJ, offers a number of robot
devices in kit form. Prices are in the $30-50 range.
Fischerteknik, the magnificent German construction set, now offers
a line of electrical, pneumatic, and electronic components intended for
the building of robots and other servomechanisms. For the very
bright, self-directed child. Obtain the catalog at better toy stores.
$50 and up, far up.
John Nagle
------------------------------
Date: 6 Dec 87 17:39:24 GMT
From: gleicher@cs.duke.edu (Michael Gleicher)
Subject: Re: Robotic "kits" for kids
When I was about that age I had a lot of fishertechnic stuff. It was neat
because you could build things that really worked, with exectric motors and
gear drives and stuff.
A lot of the stuff I had were strange gear boxes, strain gauages,
differentials, or other things an 11 year old kid would understand. My dad (a
mechanical engineers) liked these toys as much as I did.
A few years back at a computer show (I think it was the Trenton Computer Fair)
I saw some rather impressive demonstrations of robots build with the stuff.
The small electric motors were easy to interface with computers.
Unfortunately, these constructions were build out of a LOT of parts (and these
things are EXPENSIVE!!! they were expensive 10 years ago, I'd hate to see what
they cost now) and were very complex (they were designed and built by
engineers, not by kids).
I don't think if you buy your kids a whole bunch of fishertechnic stuff they
will be building robots. But they will be building other things, and probably
having as much fun with it. It is my personal philosophy (I am NOT a
psychologist) that things like this help develop not only an interest in
mechanical things, but also develop skills like mathematical ability, logical
reasoning, design, planning and the like. Once these things are developed,
you're ready to build robots.
One last comment: Fishertechnic pieces are EXPENSIVE (or at least were). There
might be cheaper alternatives (what ever happened to old fashioned erector
sets? (with the metal pieces and minature bolts). these might be even better
for building mini-robots).
Mike
Michael Lee Gleicher (-: If it looks like I'm wandering
Duke University (-: around like I'm lost . . .
E-Mail: gleicher@cs.duke.edu)(or uucp (-:
Or P.O.B. 5899 D.S., Durham, NC 27706 (-: It's because I am!
------------------------------
Date: 6 Dec 87 18:17:11 GMT
From: Robert Stanley <roberts%cognos%math.waterloo.edu@RELAY.CS.NET>
Reply-to: Robert Stanley
<roberts%cognos%math.waterloo.edu@RELAY.CS.NET>
Subject: Re: ES tools for Mac
To the moderator:
My apologies for sending this to your group, but I am unable to persuade my
mailer that cive.ri.cmu.edu is a viable address on this unsupported Sunday
afternoon. It then struck me that perhaps this information might be of
interest to the group after all; I'll leave you to make that decision. When
support arrives on Monday, I'll get this mailed directly to Mary.Lou.Maher.
In article <8712010829.AA13510@ucbvax.Berkeley.EDU>
Mary.Lou.Maher@CIVE.RI.CMU.EDU writes:
>I have to give a tutorial and workshop on Expert Systems at an engineering
>conference and would like to use the Mac since it has relatively little
>start up time. I am interested in simple rule based tools and object
>oriented tools that run on a Mac. Simplicity is more important
>than sophistication. Can anyone help? Mary Lou Maher maher@cive.ri.cmu.edu
There are a number of possibilities, depending on how much you wish to achieve,
how big a Macintosh you have available, and how much you want to spend. You
might also benefit from repeating your posting in comp.sys.mac, which is a very
lively group featuring some knowledgeable players.
With respect to Object-Oriented programming:
* Probably the most interesting (and cheapest) approach is to use HyperCard,
which comes free with all new Macs, and costs $49 (US) otherwise. This
has a true object-oriented language named HyperTalk very well integrated
into its environment. Drawback: needs minimum 128K ROMs, 1 Megabyte RAM,
and is difficult to put to work without a hard disk. The language is
somewhat muddled, but quite powerful and *very* easy to use.
Consult your local Apple dealer.
* Other object-oriented possibilities include SmallTalk, available cheaply
from APDA, and *much* more expensively from Parc Place Systems (I am not
sure that they have brought their Mac product to market yet); the language
NEON (a sort of cross between SmallTalk and FORTH) from Kriya Systems; and
MacScheme, if you want to step right down to the nitty-gritty level.
Consult a month's worth of the Mac news-stand publications.
With respect to shells and rule-based programming:
* The hands-down winner in this field is NEXPERT Object from Neuron Data, but
it is expensive, and runs best in large environments. This is a real tool,
aimed at implementing real solutions to real problems, but I suspect that
it needs quite some practice to master. On a Mac II with colour it runs
rings around the VAX GPX II version.
Neuron Data: 444 High Street, Palo Alto, CA 94301 (415) 321-4488
* At the other end of the scale, there is a micky-mouse implementation of
OPS/5 for the Mac, but it only allows around 50 rules! I am sorry, but
I have no reference to hand.
To the best of my knowledge, there has been little or no attempt on the part of
any of the innumerable shell-builders in the IBM-PC world to port their
products to the Mac. This has left the Mac world pretty much devoid of simple
tools in this class.
Further possibilities:
* LPA Associates have an acceptable implementation of Micro-Prolog for the
Mac, which would give you access to tools such as APES (Augmented Prolog
for Expert Systems).
* Advanced AI Systems produce AAIS-Prolog, which appears to be currently the
best Prolog implementation for the Mac. By no means perfect, but
definitely practical.
I hope these suggestions will go part way towards solving your problem. If you
need more detailed references, e-mail me or telephone (we are on EST).
Robert_S
--
R.A. Stanley Cognos Incorporated S-mail: P.O. Box 9707
Voice: (613) 738-1440 (Research: there are 2!) 3755 Riverside Drive
FAX: (613) 738-0002 Compuserve: 76174,3024 Ottawa, Ontario
uucp: decvax!utzoo!dciem!nrcaer!cognos!roberts CANADA K1G 3Z4
------------------------------
Date: 5 Dec 87 07:45:46 GMT
From: glacier!jbn@labrea.stanford.edu (John B. Nagle)
Subject: Neural nets are science
I've been implementing Rumelhart's learning technique, and
observing how fast it learns, what factors affect the learning rate,
and how my results compare with his. Suddenly it struck me - I'm
repeating someone else's experiment, and comparing my data with his.
It's rare in this field to be able to repeat the experiments of
another and actually compare numerical results. In this area, we
can do it. We can conduct repeatable experiments and objectively
validate the work of others. This is real science. Instead of
arguing, we converge on accepted, repeatable results. The
scientific method works here.
It's interesting that in the area of AI where things seem most complex,
chaotic, and noisy, one can do good experimental science. This field
may move forward rapidly.
John Nagle
------------------------------
End of AIList Digest
********************
∂10-Dec-87 0112 LAWS@KL.SRI.COM AIList V5 #281 - Common Lisp Portability, Chess
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Dec 87 01:12:16 PST
Date: Wed 9 Dec 1987 23:17-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #281 - Common Lisp Portability, Chess
To: AIList@SRI.COM
AIList Digest Thursday, 10 Dec 1987 Volume 5 : Issue 281
Today's Topics:
AI Tools - Common Lisp Portability,
Games - Computer Chess Rankings
----------------------------------------------------------------------
Date: 8 Dec 87 17:52:26 GMT
From: orstcs!ruffwork@rutgers.edu (Ritchey Ruff)
Subject: Common Lisp lacks portability (105 lines)
Would you use a language that can arbitrarily ignore some of your
code ??? Especially if different implementations ignored different
statements in the same code ??? Even if it didn't TELL you what
it was ignoring when ???
I have a bone to pick with Steele about something he left out of
the Common Lisp definition. The above is *EXACTLY* what Common
Lisp *DOES* !!! In the sections about the
strong typing, "Common Lisp:The Language" says the compiler
or interpreter can ignore many declarations. It should also
state that there be a standard way to find out WHAT the compiler/
interpreter is ignoring (or using). Something like a compiler flag
(":declares-ignored t/nil") or a global flag (*IGNORED-WARNINGS*) to
force common lisp to show what it is ignoring.
Why, you ask??? First, principle (I kind of like that ;-):
when you put in strong typing statements (like "(the integer foo)")
do you REALLY want them ignored in different ways, at different times,
by different Common Lisps - and not even know which is ignoring
what when ???
Second, I've just spent weeks tracking bugs caused by
compilers/interpreters ignoring different parts of my declarations. Simply
because an interpreter/compiler can IGNORE strong typing (like
"(the integer foo)"), optimizer statements (like safety=3),
and declarations (like "(declare (integer foo))") I found that
code that ran ok on one version of Common Lisp would not even
compile under another, run but go into a break on another, and
run to completion but give wrong results on another !!!!
For example - lots of people use Bill Shelters' excellent SLOOP
looping macro package (thanks for all that work you put into an
excellent package, Bill!). Its great, but because it tries to
optimize (by default it expands with declarations that give
type info on looping vars, etc.) it turns out to be non-portable.
Here is a totally non-portable piece of code -
(DEFUN TST (N M)
(SLOOP FOR I FROM N TO M COLLECT I))
This is quite simple, right? When it expands N, M, and I get
declared of type integer, and the iteration var gets checked by
the "THE" statement each time it's incremented to see that it
remains of type integer. Below are results from several different
Common Lisps (all this was done with safety=3) ---
----------------------------------------
FranzExtendedCommonLisp> (tst 1 5)
(1 2 3 4 5)
FranzExtendedCommonLisp> (tst 1.0 5.0)
Continuable Error: Object 2.0 is not of type FIXNUM.
If continued with :continue, Prompt for a new object.
[1c] <cl> ↑D
FranzExtendedCommonLisp> (compile 'tst)
TST
FranzExtendedCommonLisp> (tst 1.0 5.0)
(1.0 2.0 3.0 4.0 5.0)
FranzExtendedCommonLisp> (tst 1 5.0)
(1 2 3 4 5)
----------------------------------------
KyotoCommonLisp> (tst 1 5)
(1 2 3 4 5)
KyotoCommonLisp> (tst 1.0 5.0)
Error: 2.0 is not of type FIXNUM.
Error signaled by THE.
Broken at THE. Type :H for Help.
KyotoCommonLisp>> :q
KyotoCommonLisp> (compile 'tst)
End Pass1.
End Pass2.
TST
KyotoCommonLisp> (tst 1.0 5.0)
(0)
KyotoCommonLisp> (tst 1 5.0)
NIL
----------------------------------------
AllegroCommonLisp> (tst 1 5)
(1 2 3 4 5)
AllegroCommonLisp> (tst 1.0 5.0)
(1.0 2.0 3.0 4.0 5.0)
AllegroCommonLisp> (compile 'tst)
TST
AllegroCommonLisp> (tst 1.0 5.0)
(1.0 2.0 3.0 4.0 5.0)
AllegroCommonLisp> (tst 1 5.0)
(1 2 3 4 5)
----------------------------------------
So we have 3 different "Common Lisps" (and the quotes are intentional)
that give radically different results for the SAME code !!! EVEN the
interpreter (Help me, Spock ;-) !!! If the compiler and interpreter
gave warnings when they ignored code the reason for the bugs that this type
of behavior can cause would be so much easier to track down.
When you have your code debugged and are looking for raw speed,
a global flag could be set to stop displaying warnings of this type.
MORAL OF THE STORY --- IF YOU WANT TRULY PORTABLE COMMON LISP CODE
THAT WORKS THE SAME INTERPRETED AS COMPILED, *DO* *NOT* PUT
STRONG TYPING OR OPTIMIZER STATEMENTS ANYWHERE IN YOUR CODE !!!
IF *ANYTHING* *CAN* IGNORE A STATEMENT, *NEVER* USE THAT STATEMENT !!!
I've gone on too long, but I think I've made my point.
Thanks for the bandwidth,
--Ritchey Ruff ruffwork@cs.orst.edu -or-
"I haven't lost my mind, ruffwork%oregon-state@relay-cs-net -or-
its' backed up on tape somewhere..." { hp-pcd | tektronix }!orstcs!ruffwork
------------------------------
Date: Fri, 04 Dec 87 10:33:58 PST
From: Stuart Cracraft <cracraft@venera.isi.edu>
Subject: computers vs. humans
Ken,
This might be of interest to the AI readership. I'll leave the
decision up to you...
*** C.R.A. Rates Commercial Chess Machines at American Open ***
by Stuart Cracraft (copyright (C) 1987, 1988)
At the American Open, held during the Thanksgiving holidays, three chess
machines were certified. Certification involved having each machine play
48 rated games against strong human opposition. The result is a rating for
the machine.
The three manufacturers who submitted machines for certification are as
follows.
Fidelity submitted a machine that is still somewhat of a mystery.
[Editorial comment: C.R.A. policy should be amended to require full
disclosure by the manufacturer. --Stuart] Fidelity representatives refused
to reveal information about the micro-chip(s) inside the machine,
memory-size, and search-speed. (Rumor has it that this was a 16mhz 68020
with a minimum of 128K memory for transposition table. Rumor also has it
that this would be prohibitively expensive to market.)
Mephisto came with the much-acclaimed Mephisto "Dallas" program in the
commercial Mephisto Mondial unit (available exactly as it was in the
certification, from U.S.C.F. for about $400) the winner of the 1986
world-micro championship (when running on a 28mhz 68020 which is available
from Mephisto commercially only at 14mhz). At certification time, it was
running at 12 mhz on a 68000.
Novag came with the "Super-Expert" a follow-on to the Novag Expert.
Super-Expert ran at 6mhz and contained a 6502 processor.
Due to variations and fluctuations in the ratings of the machine's
opponents and the actual certification rating process itself (a
complicated procedure), no final rating-per-machine was calculated, though
estimates are available. Please remember that these are estimates only
and that the actual, final, certified rating will be available shortly.
Please also note that unless the machine is commercially available exactly
as it existed at certification time, the certified rating is not available
for advertisment purposes nor can the manufacturer place the C.R.A.
rating seal on any other machine.
So, with that disclaimer aside, here are the results of the tournament,
and at the very end are the estimates ratings for each manufacturer's
entry. Results consist of six-games per round, organized in tabular
format. A 0 means a loss for machine, .5 means a draw, and 1 means
a win for the machine. The ratings are of the human opponent
the machine played.
Round 1 2 3 4 5 6 7 8
-------------------------------------------------------------------
Fidelity (16mhz 68020? with 128K+ memory for transposition? by the Spracklens)
2300-0 2185-0 2139-.5 2067-1 2256-0 2144-.5 2116-0 2274-1
2283-0 2204-0 2175-0 1778-1 2244-0 2115-1 2105-1 2103-0
2209-.5 2244-0 2260-1 2226-1 2351-0 2119-1 2161-1 2434-1
2129-1 1969-.5 2163-0 2183-0 2067-1 2073-1 2055-0 2002-1
1966-1 2175-0 2168-0 2122-.5 2134-0 2191-1 2181-1 2106-.5
1944-1 2106-1 1963-1 1954-1 1970-1 1987-1 1890-1 1866-1
Mephisto (12mhz 68000 with "Dallas" program by Richard Lang)
2286-0 2189-0 2137-0 2242-1 2243-.5 2250-0 2183-0 1871-1
2267-0 2179-.5 2000-1 2069-1 2140-.5 2227-0 2123-.5 2058-.5
2145-1 2216-0 2145-1 1929-1 2358-0 2074-1 2171-0 2172-.5
2139-0 2174-1 2109-1 2167-.5 2175-0 1966-1 2127-0 2006-1
2298-0 2119-1 1953-.5 2156-1 2117-.5 1958-1 2145-1 2053-1
1924-0 1875-1 2182-0 1962-1 1947-.5 2109-1 2216-0 2030-1
Novag (6 mhz 6502 with "Super-Expert" program by David Kittinger)
2294-.5 2262-.5 2261-.5 2320-.5 2250-0 2213-1 2217-0 2235-0
2274-0 2209-0 1958-0 1966-.5 2115-0 2000-0 2145-1 1992-1
2264-1 2389-0 2257-0 2219-0 2249-0 2068-1 2206-.5 2233-1
2144-0 2122-1 2114-0 2074-0 2053-1 2160-1 2092-1 2000-1
2137-0 2106-0 2156-1 2069-0 2050-.5 2089-1 2010-1 2167-0
1854-1 1950-1 1922-1 1941-.5 1989-0 1952-1 1814-1 2157-1
Estimated ratings:
Fidelity Experimental (not currently commercially available):
USCF 2190-2200
Mephisto Mondial 68000 XL (just becoming available commercially):
USCF 2150-2160
Novag Super-Expert (just becoming available commercially):
An estimated rating for this machine is complicated by
the fact that the first 30-games of the certification
were played with a selective-search feature, and the last
18-games were played with the feature disabled (done with C.R.A.
permission.) C.R.A. agency extended an invitation to Novag to use the
latter 18 games as the first 18 games of a new certification
(requiring 30 more games be played).
The overall concensus is that a commercial master will first become
available in one year or less. Certainly, the prestige associated with
being the manufacturer of such a product, especially if attractively
priced, would be immense. There is clearly a race to be the first
manufacturuer to do so.
Stuart
------------------------------
End of AIList Digest
********************
∂10-Dec-87 0311 LAWS@KL.SRI.COM AIList V5 #282 - Semantic Nets, Mac Lisp and Prolog, Science, Law
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 10 Dec 87 03:10:49 PST
Date: Wed 9 Dec 1987 23:22-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #282 - Semantic Nets, Mac Lisp and Prolog, Science, Law
To: AIList@SRI.COM
AIList Digest Thursday, 10 Dec 1987 Volume 5 : Issue 282
Today's Topics:
Queries - OPS83 Execution Profiling & Expert System References &
Epistemic Logic Examples & Planning Papers &
UNISYS Master Apprentice Program,
AI Tools - Semantic Nets & Mac Lisp and Prolog,
Philosophy - Neural Nets as Science,
Law - Can You Sue an Expert System?
----------------------------------------------------------------------
Date: 7 Dec 87 19:48:52 GMT
From: "David C. Bond" <dcbond%watvlsi.waterloo.edu@RELAY.CS.NET>
Subject: OPS83 execution profiling
At the University of Waterloo, a computer architecture called CUPID has
been developed to rapidly perform the match phase of OPS5. CUPID is
a multiprocessor which executes a distributed RETE algorithm and
returns match information to the host machine.
I am investigating the changes required to allow CUPID to evaluate
OPS83 programs. The main difference between these two languages is
OPS83's use of simple procedures in the left hand sides of rules. The
processors currently used in CUPID are simple and were designed to
quickly compare fixed fields in a pair of tokens. "Left hand
procedures" can perform numerical calculations and comparisons of
arbitrary data structures. These operations require a more
sophisticated processor than those currently used in CUPID. Two
possibilities exist: make the processors more complex so they can
perform these operations, or off-load these operations to a subhost
(e.g. 680x0 processor). The latter alternative is the simpler but I
don't know what the impact on performance will be.
What I would like to find out is:
1. generally how many of these procedures are in an OPS83 program
2. what are their general execution characteristics (i.e. execution
time).
3. how many times are they called. Note: I mean how many
times they are evaluated, *NOT* how many times rules containing
procedures in their left hand sides fire.
4. how other researchers who have proposed multi-processors for
evaluating the RETE algorithm handle "left hand procedures".
Any data on these four items would be very appreciated.
Thanks in advance,
------------------------------
Date: Mon, 07 Dec 87 16:45 EST
From: WURST%UCONNVM.BITNET@WISCVM.WISC.EDU
Subject: Expert System references...
I am a graduate student in Computer Science, and I am planning
to do an independent study project next semester in Expert Systems.
My project, as it stands now, will be to build a simple expert system
for use in a microbiology lab. I plan to write the system twice,
once in LISP, and once in PROLOG, and then compare the relative
merits of each language for expert systems.
Can anyone suggest some references to get me started? This
will be my first expert system, and I am interested in literature
on how to go about building one. I would like to see information
on designing expert systems in general, how to go about getting
the information from the domain expert, and any information on
building expert systems in LISP and PROLOG in particular. Any
help you can give me would be greatly appreciated.
----------
Karl R. Wurst
Computer Science and Engineering
University of Connecticut
BITNET: WURST@UCONNVM
'Things fall apart. It's scientific' - David Byrne
------------------------------
Date: Wed, 9 Dec 87 13:58:21 PST
From: mcvax!casun.kaist.ac.kr!skhan@uunet.UU.NET (Sangki Han)
Subject: Epistemic Logic Examples
Hi! I and my collegue have designed and implemented a theorem prover
for the epistemic logic based on Konolige's deduction model.
We want to get various meaningful or famous examples to test our prover.
Especially, it would be better if the example concerns both the knowledge
and belief of multiple agents since we want to handle that kind of situations.
Thanks in advance.
Sangki Han
------------------------------
Date: Wed, 9 Dec 87 08:54:16 PST
From: marcel%meridian@ADS.ARPA (Marcel Schoppers)
Subject: two rare papers wanted
I have been looking for the following two papers for several years, and have
been unable to get copies. I can't wait any longer -- my thesis needs them.
If you have one or both of them, *please* send me a message. So as to avoid
duplicate labor I'll let you know if someone else is already helping me out.
The articles are
Warren, DHD. "Generating conditional plans and programs" Proc
AISB Summer Conference, Edinburgh (1976), 344ff.
Sacerdoti, ED "Plan generation and execution for robotics" Rhode
Island Wshop on Robotics Research (Apr 1980).
marcel@ADS.ARPA
------------------------------
Date: 8 Dec 87 14:22 -0600
From: Imants Krumins <krumins%asd.arc.cdn%ubc.csnet@RELAY.CS.NET>
Subject: UNISYS Master Apprentice Program
I have been asked to develop a proposal for development of an expert
system under the UNISYS Master Apprentice Program (MAP).
For those unfamiliar with MAP, it is basically a program in which UNISYS
provides training and expert consulting with the goal of introducing the
client corporation to expert systems through the development of a
prototype system to "solve" an appropriate practical problem faced by
the client. The trainee will presumably have gained sufficient
expertise during MAP to complete the development of the prototype to a
production system.
My backgound/knowledge in this field consists primarily of reading this
newsgroup and a very limited amount of literature as well as low level
fooling with LISP programming. I would appreciate hearing from anyone in
the group with direct or indirect experience with MAP or expert systems
technology at UNISYS in general. Is the MAP a good way to get involved
in expert systems development? Are the MAP products of any practical
use? What backgound reading would be useful as a preparation? Any info
regarding the quality of the MAP, personnel, hardware, software, etc.
would be very useful.
I will summarize to the net if there is sufficient interest.
Imants Krumins (krumins@asd.arc.cdn)
Resource Technologies Department
Alberta Research Council
PO Box 8330, Postal Station F
Edmonton, Alberta
Canada T6H 5X2
403/450-5263
------------------------------
Date: Mon, 7 Dec 87 09:03:46 EST
From: rapaport@cs.Buffalo.EDU (William J. Rapaport)
Subject: kannan's inquiry re sem nets
I couldn't contact Kannan by email (daemon problems); so here's a
reply about sem nets:
The SNePS semantic network processing system might be what you want.
See:
Shapiro, Stuart C. (1979), ``The SNePS Semantic Network Processing System,''
in N. V. Findler (ed.),
.ul
Associative Networks
(New York: Academic Press, 1979): 179-203.
and
Shapiro, Stuart C., & Rapaport, William J. (1987),
``SNePS Considered as a Fully Intensional Propositional Semantic Network,''
in G. McCalla & N. Cercone (eds.),
.ul
The Knowledge Frontier: Essays in the Representation of Knowledge
(New York: Springer-Verlag): 262-315;
earlier version preprinted as Technical Report No. 85-15
(Buffalo: SUNY Buffalo Dept. of Computer Science, 1985);
shorter version appeared in
.ul
Proc. 5th Nat'l. Conf. on Artificial Intelligence (AAAI-86; Philadelphia)
(Los Altos, CA: Morgan Kaufmann), Vol. 1, pp. 278-83.
------------------------------
Date: Mon 7 Dec 87 09:17:32-PST
From: George S. Cole <GCOLE@Sushi.Stanford.EDU>
Subject: Re: AIList V5 #280 - Robot Kits, Mac ES Tools, Scientific
Method
Re: Expert System Shells for the Mac: Tools to Build the Tool
The paucity of shells for the Macintosh is puzzling. There are three
language environments which can be used to build such a shell currently on
the market: (1) AAIS Prolog; (2) Expertelligence's ExperCommonLisp, and
(3) Allegro Common LISP from Coral Software.
AAIS Prolog is the least expensive of the three -- but contains the
least support for moving beyond the language. The price is below $200 (as
part of a class purchase, we were able to buy it for $70 a copy). Tying new
resources into the system will require some Mac-hacking.
ExperCommonLisp comes in two varieties: plain (~$200) and chocolate
(~$800). It is an extension to LISP that allows object-oriented programming,
but lacks type-casting features. The debugger works on the compiled code
rather than the interpreted code, which can be puzzling. The expensive version
is supposed to produce stand-alone applications (but I have only used the
language).
Allegro Common LISP falls into the mid-range (~$490). It is also an
extension to Common LISP that allows object-oriented programming, contains
the full type-casting power, and is a better implementation by far. However,
it demands 2 megabytes (5 for us cautious types) and does not yet have the
"stand-alone application" power, though this is promised for the future.
George S. Cole, Esq. GCole@sushi.stanford.edu
793 Nash Av.
Menlo Park, CA 94025 (415) 322-7760
------------------------------
Date: Mon, 7 Dec 87 09:08:55 EST
From: Jim Hendler <hendler@brillig.umd.edu>
Subject: Re: Neural Nets are science
I'd like to congratulate John Nagle on his sense of humor. Without
arguing about his premise I'd like to point out that by his argument
everytime I make a phone call I am doing science by comparing my results
with Alexander Graham Bells. Building something and exploring how it
works is not even close to the scientific methodology. Experimentation
requires small little things like hypotheses and analytic methods. I hope
Mr. Nagle can succeed at developing a scientific approach to neural nets,
but comparing results??? Not even close.
------------------------------
Date: 7 Dec 87 16:54:08 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: Can you sue an expert system?
In article <1788@cup.portal.com> Barry_A_Stevens@cup.portal.com writes:
>
>Consider, and please comment on, this scenario.
>
> * * * * * * * * * * *
>
>A well-respected, well-established expert systems(ES) company constructs
>an expert financial advisory system. The firm employs the top ES
>applications specialists in the country. The system is constructed with
>help from the top domain experts in the financial services industry. It
>is exhaustively tested, including verification of rules, verification of
>reasoning, and further analyses to establish the system's overall value.
>All results are excellent, and the system is offered for sale.
>
Anyone who is willing to accept these premises at face value may be more
interested in investing in the bridge I have between Manhattan and Brooklyn
than in expert systems. The sort of "ideal" product envisaged here is
certainly beyond the grasp of current development technology and may remain
so for quite some time. The most important omission from this scenario is
the assumption that any sort of disclaimer has been attached to the product.
I have encountered a variety of advertisements for human financial consultants;
and, as a rule, there is always some disclaimer about risk present. The
idea that their would be a machine-based product which would be risk-free
borders on ludicrous. If a customer was hooked by such a claim, most likely
the only place he would be able to complain would be to the Better Business
Bureau.
>
>By now, you know the outcome. On the Friday morning before Black Monday,
>the expert system tells Joe to "sell everything he has and go into the
>stock market." ESs can usually explain their actions, and Joe asks for
>an explanation. The ES replies "because ... it's only been going UP for
>the past five years and there are NO PROBLEMS IN SIGHT."
>
Would Joe have accepted such an explanation from a human advisor? If so,
he has gotten what he deserved. (I happened to be discussing an analogous
case with my lawyer-neighbor. Our scenario involved medical systems and
malpractice, but the theme is basically the same.)
This raises another question: Assuming Joe is no dummy (and that he can
afford good human advice), why would he be intersted in an machine advisor?
I would argue that the area in which machines tend to have it over humans
is that of quantitative risk assessment. Thus, the machine is more likely
to synthesize and justify concrete quantitative predictive models than is
a human expert, whose skills are fundamentally qualitative. Thus, the best
Joe could hope for would be such a model. INTERPRETING the model would
remain his responsibility (although that interpretation may be linked to
the machines justification of the model, itself).
I would conclude that this scenario is far too simplistic for the real world.
I suggest that Mr. Stevens debug it a bit. Then we might be able to have a
more realistic debate on the matter.
------------------------------
End of AIList Digest
********************
∂15-Dec-87 0133 LAWS@KL.SRI.COM AIList V5 #283 - Smalltalk, Lisp Portability, AI Liability
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 15 Dec 87 01:33:07 PST
Date: Mon 14 Dec 1987 22:24-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #283 - Smalltalk, Lisp Portability, AI Liability
To: AIList@SRI.COM
AIList Digest Tuesday, 15 Dec 1987 Volume 5 : Issue 283
Today's Topics:
Queries - Statistics on AI Programmers & KR References &
Cognitive Science Programs,
AI Tools - Smalltalk for the MAC & RACTER & LISP vs. PROLOG &
Common Lisp Portability,
Law - Expert System Liability,
Philosophy - The Role of Biological Models in AI
----------------------------------------------------------------------
Date: 13 Dec 87 13:30:14 GMT
From: caip.rutgers.edu!anar@rutgers.edu (Anar Shah)
Subject: Statistics on AI programmers requested
I am looking for articles/statistics on the availability of AI
programmers - the demand vs the supply. Any information on this
subject will be a great help.
Anar Shah
------------------------------
Date: 11 Dec 87 11:54:08 GMT
From: mcvax!lifia!gb@uunet.UU.NET (Guilherme Bittencourt)
Reply-to: mcvax!lifia!gb@uunet.UU.NET (Guilherme Bittencourt)
Subject: References wanted
I am very interested in recent publications concerning
Knowledge Representation tutorials or surveys, and papers
comparing different techniques of Knowledge Representation.
If someone knows about or has published such papers, I'd be
very pleased if she/he could contact me, or send me her/his papers
and/or any pointer to such publications.
Besides being useful for my research these papers will be
included to the second version of a bibliography on Expert and
Knowledge-Based Systems. The first version is just out as an
internal lab. report and is available (until the requests do not
oversize our supply !)
Thank you for your help.
Guilherme
--
Guilherme BITTENCOURT +-----+ gb@lifia.imag.fr
L.I.F.I.A. | <0> |
46, Avenue Felix Viallet +-----+
38031 GRENOBLE Cedex (33) 76574668
------------------------------
Date: 10 Dec 87 20:55:11 GMT
From: clyde!watmath!utgpu!jarvis.csri.toronto.edu!utai!tjhorton@rutger
s.edu (Timothy J. Horton)
Subject: Cognitive Science programs (once and for all)
Do you have info about cognitive science programs?
ie. interdisciplinary programs based on several of
computersci / psychology / neurosci / linguistics / even philosophy / etc
Please drop me a few lines or pointers to info. I will summarize and post.
I have read of a Cognitive Science Society. Do they have a published list
of programs somewhere? If so, where?
From what I understand, perhaps not accurately (please clarify):
MIT:
department of Brain and Cognitive Science
Brown:
department of Linguistics and Cognitive Science
Stanford:
Graduate Program in Cognitive Science
Psychology (organizing dept), Linguistics, Computer Science, Philosophy
UCSD:
interdisciplinary PhD in Cognitive Science exists
undergraduate program in Cog Sci currently offered by psychology
strengths in psychology, connectionism (though fading?), neurosci, linguistics
a real dept of Cognitive Science is in the works, perhaps for 88/89
UC Berkley:
Cognitive Science Program
focus on linguistics
Michigan:
defunct Program in Communications Sciences
Toronto:
Undergraduate Major in Cognitive Science and Artificial Intelligence
Princeton:
program of some sort?
Edinburgh:
department of Cognitive Science (formerly School of Epistemics)
focus on linguistics
Sussex:
School of Cognitive Science
--
Timothy J Horton (416) 979-3109 tjhorton@ai.toronto.edu (CSnet,UUCP,Bitnet)
Dept of Computer Science tjhorton@ai.toronto (other Bitnet)
University of Toronto, tjhorton@ai.toronto.cdn (EAN X.400)
Toronto, Canada M5S 1A4 {seismo,watmath}!ai.toronto.edu!tjhorton
------------------------------
Date: 11 Dec 87 14:22:10 GMT
From: sunybcs!rapaport@ames.arpa (William J. Rapaport)
Subject: Re: Cognitive Science programs (once and for all)
In article <4186@utai.UUCP> tjhorton@ai.toronto.edu (Timothy J. Horton) writes:
>Do you have info about cognitive science programs?
State University of New York at Buffalo has several active cognitive science
programs. What follows is a slightly outdated on-line information
sheet on two of them. The newest is the SUNY Buffalo Graduate Studies
and Research Initiative in Cognitive and Linguistic Sciences, whose
Steering Committee is currently planning the establishment of a Cog and
Ling Sci Center and running a colloquium series. For more information,
please contact me. In addition, let me know if you wish to be on my
on-line mailing list for colloquium announcements.
William J. Rapaport
Assistant Professor of Computer Science
Co-Director, Graduate Group in Cognitive Science
Interim Director, GSRI in Cognitive and Linguistic Sciences
Dept. of Computer Science||internet: rapaport@cs.buffalo.edu
SUNY Buffalo ||bitnet: rapaport@sunybcs.bitnet
Buffalo, NY 14260 ||uucp: {ames,boulder,decvax,rutgers}!sunybcs!rapaport
(716) 636-3193, 3180 ||
[Write to the author if you need the full message. -- KIL]
------------------------------
Date: Fri, 11 Dec 87 11:45 EDT
From: TAM%MCOIARC.BITNET@WISCVM.WISC.EDU
Subject: Smalltalk for the MAC
In response to Robert Stanley's mention of Smalltalk for the MAC:
The Smalltalk version available from APDA is a very poor implementation.
I found that it frequently overwrite the whole screen when using
standard graphics. Parc Place Systems has a version now for the MAC II
(which I have recently ordered), for the MAC SE, and the MAC Plus.
These versions are standard Smalltalk-80 (Parc Place is a division of
Xerox Corp).
The manual shipped with Apples Smalltalk is very bad. You must be
very effient with SMalltalk-80 before using it.
Smalltalk from Apple cost $75.00. Smalltalk-80 from Parc Place
is $1000 for the MAC SE and Plus, and $1295.00 for the MAC II, but
Parc Place offers a 90% educational discount making all the systems
practically the same price.
My opinion is get the real thing and buy Parc Place's Smalltalk.
------------------------------
Date: 13 Dec 87 01:00:41 GMT
From: cbmvax!swatsun!hirai@uunet.uu.net (Eiji "A.G." Hirai)
Subject: Re: Request for RACTER
In article <8712041829.AA19308@ucbvax.Berkeley.EDU> ST502042@BROWNVM.BITNET
(Michael Nosal) writes:
> ...
>m on the subject, if anyone knows of other 'Eliza-like' AI programs out there,
>please let me know.
GNU Emacs has a bery primitive Eliza-like (un-AI like) lisp program
called 'doctor'. Also check out 'flames' too, which reponds to your
efforts at communicating with it through flames. Very sociable. :-)
> Michael Nosal (please respond to this account if possible)
-a.g. hirai
--
Eiji "A.G." Hirai @ Swarthmore College, Swarthmore PA 19081 | Tel. 215-543-9855
UUCP: {rutgers, ihnp4, cbosgd}!bpa!swatsun!hirai | "All Cretans are liars."
Bitnet: vu-vlsi!swatsun!hirai@psuvax1.bitnet | -Epimenides
Internet: bpa!swatsun!hirai@rutgers.edu | of Cnossus, Crete
------------------------------
Date: 14 Dec 87 17:56:27 GMT
From: umix!umich!eecs.umich.edu!dwt@uunet.UU.NET (David West)
Reply-to: umix!umich!eecs.umich.edu!dwt@uunet.UU.NET (David West)
Subject: Re: Expert System references...
In article <8712100816.AA09612@ucbvax.Berkeley.EDU> WURST@UCONNVM.BITNET writes:
>
> I am a graduate student in Computer Science [...]
> I plan to write the system twice,
> once in LISP, and once in PROLOG, and then compare the relative
> merits of each language for expert systems.
> Can anyone suggest some references to get me started?
Unless you are already proficient in both languages, what you are likely to
end up comparing is your relative understanding of the two languages. For
this reason I think that your first reference to read should be Richard
O'Keefe's article "Prolog and LISP Compared?" in SIGPLAN Notices, about 1984.
This is a critique of an article by someone else in which the someone else
fell into precisely the above-mentioned trap.
(That title and date are approximate, but close.)
David West dwt@zippy.eecs.umich.edu
------------------------------
Date: 10 Dec 87 08:43:22 est
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Common Lisp lacks portability (105 lines)
It seems to me that your complaint is not about Steele & the
rest of the committee's unwillingness to overconstrain the
language in what is still a relatively unexplored area, but
rather with implementors who chose to interpret the verb
`ignore' in the sense of ``the compiler or interpreter can
pretend it aint there'' instead of ``the compiler doesn't have
to generate special code for it''. Sort of like the difference
between (declare (ignore x)) and (ignore x), if you catch my
drift. In any case, since you have obviously thought some
about this problem perhaps you could suggest which of the three
examples you gave were the `right' ones and what the spec should
have been said, keeping in mind the purpose of the definition
described so succinctly in the first three pages of CLtL.
Walter Hamscher
------------------------------
Date: Thu, 10 Dec 87 14:11:42 EST
From: "Christopher M. Maeda" <MAEDA@AI.AI.MIT.EDU>
Subject: AIList V5 #281 - Common Lisp Portability, Chess
Reply to Ritchey Ruff on type declarations:
I don't see why you are mad at Steele for saying that compilers and
interpreters can ignore declarations. For example, if you type the
following definition,
(defun foo (x)
(declare (type x integer))
...)
and you always pass integers as arguments to foo, what difference does
it make (aside from performance) if the lisp system does full type
checking or just assumes it's an integer?
From reading your message, I think it is the buggy SLOOP macro
that you should be flaming at. You said you typed the folowing
definition:
(defun tst (m n)
(sloop for i from m to n
collecting i))
Why in the world would sloop declare m and n to be of type integer
when there is no such information from the programmer? That, and the
fact that you gave tst floating point arguments when you knew they
were declared as fixnums, is what is causing your problems.
Chris Maeda
------------------------------
Date: Thu 10 Dec 87 10:27:39-PST
From: George S. Cole <GCOLE@Sushi.Stanford.EDU>
Subject: Expert System Liability
I have researched this area and a paper is forthcoming -- as soon as the
USC Computer/Law Journal editorial staff are ready -- on "Tort Liability for
Artificial Intelligence and Expert Systems". The trite answer is yes, there can
be a suit and EVERYBODY INVOLVED will be named -- because the plaintiff's
lawyer will realize that the law does not clearly know who is liable (including
the plaintiff).
A short answer is to cite the Restatement of Torts, 2nd, Section 552:
"Information Negligently Supplied for the Guidance of Others:
one who, in the course of his business, profession, or employment, or in
any other transaction in which he has a pecuniary interest, supplies false
information for the guidance of others in their business transactions, is
subject to liability for pecuniary loss caused to them by their justifiable
reliance upon the information, if he fails to exercise reasonable care or
competence in obtaining or communicating the information".
This section was cited without success in Black, Jackson and Simmons Insurance
Brokerage, Inc. v. IBM, 440 N.E. 2d 282, 109 Ill. App. 132 (1982). The phrase
"in the course of his business" was strictly construed to prevent liability
under this cause of action (there were others, including warranty) as the
court noted that the defendant had sold both hardware and software to allow
the firm to process information. But in Independant School District No. 454,
Fairmont, Minnesota v. Statistical Tabulating Corporation, 359 F. Supp. 1095
(N.D. Ill, 1973) the court permitted a negligence action to be brought against
the third-party statistical bureau whose miscalculations had led to the
under-insurance of a school which had then burned down. The court stated:
"[O]ne may be liable to another for providing inaccurate information which
was relied upon and caused economic loss, although there was no direct
contractual relationship between the parties...The duty to do work reasonably
and in a workmanlike manner has always been imposed by law..." Factors the
court suggested to consider included (1) the existence, if any, of a guarantee
of correctness; (2) the defendant's knowledge that the plaintiff would rely
upon the information; (3) the restriction of potential liability to a small
group; (4) the absence of proof of any correction once found being delivered
to the plaintiff; (5) the undesirability of requiring an innocent party to
carry the burden of another's professional mistakes; and (6) the promotion
of cautionary techniques among the potential defendants for the protection
of all potential plaintiffs.
Did the ES indeed make a mistake? Suppose Joe has said he plans to
invest for 15 years -- too short for real estate, too long for bonds, and
in that light the "Black Monday" might be seen as a temporary aberration.
(I.e. Joe caused the harm by selling out at the bottom rather than holding
on for the 15 years as planned.)
Can the experts hide behind the company? Those who are professionals
(which is a legal phrase for "holders of a semi-monopoly") probably cannot be
fully shielded; the rest may have to seek indemnity from their corporation.
It will depend in part on their employment contract, or lack thereof.
Can the knowledge engineers be found liable if their mistake led to
this? What sort of mistake? A standard programming flaw is not the same as
a design flaw. What if the mistake lies at the boundary -- who is responsible
for realizing that the computer has to have rules for assessing "market
psychology" that will quantitatively assess the subtle dynamics of what
the current "feel" for the market is? Did the domain experts learn that the
computer was going to do more than crunch numbers?
This is both a nascent and a complex legal area. My hope is that a
number of the AI and ES companies realize the potential exposure and that the
evolution of the law can be influenced by their behavior -- and begin to
plan defensively. It is a bit more expensive initially, affecting immediate
profits; but it can provide tremendous savings both for the firm and for the
industry over the longer run.
George S. Cole, Esq.
793 Nash Av.
Menlo Park, CA 94025
GCole@Sushi.stanford.edu (until it goes away)
------------------------------
Date: 10 Dec 87 02:57:50 GMT
From: ece-csc!ncrcae!gollum!rolandi@mcnc.org (rolandi)
Subject: the role of biological models in ai
Marty!
Sorry about our previous misunderstanding. But regarding your reply ...
> You know perfectly well that, as a technology
> matures, it stops modeling its techniques on "natural processors" and
> develops artificial substitutes that were previously unknown. You
> don't fly by flapping wings, your car doesn't propel itself with legs,
> and your air conditioner sweats as a result of cooling, not the other
> way around. We first learn from natural processors, and then we
> progress by inventing artificial processors.
You make a good point here but, in a way, your examples labor against the
interest of your argument. According to some AI theorists, (see Schank,
R.C., (1984) The Cognitive Computer. Reading, Mass.: Addison-Wesley)
AI is "an investigation into human understanding through which we learn
...about the complexities of our own intelligence." Thus, at least for
some AI researchers, the automation of intelligent behavior is secondary
to the expansion and formalization of our self-understanding. This is
assumed to be the result of creating computational "accounts" of (typically
intellectual) behavior. Researchers write programs which display the
performance characteristics of humans within some given domain. The
efficacy of a program is a function of the similarity of its performance
to the human performance after which it was modeled. Thus AI programs are
(often) created in order to "explain" the processes that they model.
Although one of your examples provides an instance of a machine that employs
principles derived from studying natural flight, (airplanes) I don't
think many people would argue that the airplane was invented in order to
"explain" flight. Of your other examples, I do not think that the workings
of an automobile have ever been thought to provide insights into the nature
of human locomotion. Nor do I believe that the "sweat" of an air conditioner
is in any meaningful way related to perspiration in humans.
-w.rolandi
ncrcae!gollum!rolandi
Look Boss, DisClaim! DisClaim!
------------------------------
End of AIList Digest
********************
∂18-Dec-87 0154 LAWS@KL.SRI.COM AIList V5 #284 - RACTER, Mac ES Tools, KR References, CogSci
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 18 Dec 87 01:54:08 PST
Date: Thu 17 Dec 1987 23:53-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #284 - RACTER, Mac ES Tools, KR References, CogSci
To: AIList@SRI.COM
AIList Digest Friday, 18 Dec 1987 Volume 5 : Issue 284
Today's Topics:
Query - OPS5 for Atari ST,
Software - RACTER,
AI Tools - Mac ES Tools,
References - Knowledge Representation Techniques,
Cognitive Science - Princeton & UCSD
----------------------------------------------------------------------
Date: Wed, 16 Dec 87 12:25:13 +0100
From: mcvax!lasso!ralph@uunet.UU.NET (Ralph P. Sobek)
Subject: OPS5 for Atari ST
I'm looking for information concerning OPS5 on an Atari ST. Its existence
was mentioned in Vol.4, No. 203 of AIList Digest. Does anybody have any
more information? Is it Public Domain? Price? Does it require Lisp, and if so
which one? Where can I get it? How does it compare to the other versions
that float around the net? Is there any room left in the ST once OPS5 is
loaded?
Thanx in advance.
Ralph P. Sobek
UUCP: mcvax!inria!lasso!ralph or ralph@lasso.UUCP
Internet: lasso!ralph@{inria.inria.fr or uunet.UU.NET} or
ralph@lasso.laas.fr
ARPA: sobek@shadow.Berkeley.EDU (automatic forwarding)
BITNET: SOBEK@FRMOP11
------------------------------
Date: 16 Dec 87 20:50:17 GMT
From: jbn@glacier.stanford.edu (John B. Nagle)
Reply-to: glacier!jbn@kestrel.arpa (John B. Nagle)
Subject: Re: Request for RACTER
RACTER is available as a commercial product. Try a computer store
with a good selection of games.
John Nagle
------------------------------
Date: 15 Dec 87 00:42:32 GMT
From: Robert Stanley <roberts%cognos%math.waterloo.edu@RELAY.CS.NET>
Reply-to: Robert Stanley
<roberts%cognos%math.waterloo.edu@RELAY.CS.NET>
Subject: Re: Request for RACTER
In article <8712041829.AA19308@ucbvax.Berkeley.EDU>
ST502042@BROWNVM.BITNET.UUCP writes:
>Howdy!
>I am interested in locating the (in)famous 'AI' program RACTER.
There is a commercial version of Racter available for the Apple Macintosh,
published by Mindscape. I do not have their address to hand, but they are
a major player in the Mac games market (Deja Vu, Balance of Power, etc.) and
so should be fairly easy to track down via a computer store or magazine.
Racter is in no way ai, but it can be fairly amusing.
Robert_S
--
R.A. Stanley Cognos Incorporated S-mail: P.O. Box 9707
Voice: (613) 738-1440 (Research: there are 2!) 3755 Riverside Drive
FAX: (613) 738-0002 Compuserve: 76174,3024 Ottawa, Ontario
uucp: decvax!utzoo!dciem!nrcaer!cognos!roberts CANADA K1G 3Z4
------------------------------
Date: 16 Dec 87 23:04:49 GMT
From: Will Clinger <willc%tekchips.tek.com@RELAY.CS.NET>
Reply-to: willc@tekchips.UUCP (Will Clinger)
Subject: Mac ES Tools
In article <12356608461.22.GCOLE@Sushi.Stanford.EDU>
GCOLE@SUSHI.STANFORD.EDU (George S. Cole) writes:
> The paucity of shells for the Macintosh is puzzling. There are three
>language environments which can be used to build such a shell currently on
>the market: (1) AAIS Prolog; (2) Expertelligence's ExperCommonLisp, and
>(3) Allegro Common LISP from Coral Software.
I'm curious as to why MacScheme+Toolsmith from Semantic Microsystems isn't
in this list. (For that matter, I wonder why things like MPW C aren't in
the list, but I can at least imagine a reason for excluding them.)
William Clinger
------------------------------
Date: Tue, 15 Dec 87 09:22:50 EST
From: Bruce Nevin <bnevin@cch.bbn.com>
Subject: ref. comparing KR techniques
In AIList Digest 5.283 (11 Dec 87) Guilherme Bittencourt
<mcvax!lifia!gb@uunet.UU.NET> asks for
". . . papers comparing different techniques of Knowledge Representation."
Try:
Gregory, Dik, Philosophy and practice in knowledge
representation. In Joseph Zeidner (ed.), _Human Productivity
Enhancement_, Vol. I, NY: Praeger (1986).
I assume you are familiar with the papers in the Brachman & Levesque
_Readings in KR_.
------------------------------
Date: 15 Dec 87 13:48:28 GMT
From: sunybcs!rapaport@ames.arpa (William J. Rapaport)
Subject: Re: References wanted
In article <3237@lifia.UUCP> gb@lifia.UUCP (Guilherme Bittencourt) writes:
>
> I am very interested in recent publications concerning
>Knowledge Representation tutorials or surveys, and papers
>comparing different techniques of Knowledge Representation.
A new collection of essays, based on the ca. 1983 IEEE Computer special
issue on KR, has just been published:
G. McCalla & N. Cercone (eds.),
The Knowledge Frontier: Essays in the Representation of Knowledge
(New York: Springer-Verlag).
William J. Rapaport
Assistant Professor
Dept. of Computer Science||internet: rapaport@cs.buffalo.edu
SUNY Buffalo ||bitnet: rapaport@sunybcs.bitnet
Buffalo, NY 14260 ||uucp: {ames,boulder,decvax,rutgers}!sunybcs!rapaport
(716) 636-3193, 3180 ||
------------------------------
Date: Thu, 17 Dec 09:51:31 1987
From: rjb%research.att.com@RELAY.CS.NET
Subject: Reply to request for references on Knowledge Representation
In reply to article <3237@lifia.UUCP> [gb@lifia.UUCP (Guilherme Bittencourt)]:
Dear Guilherme,
Among the best survey articles there are is one by Hector Levesque in the
Annual Review of Computer Science, Vol. 1, 1986. This is published by
Annual Reviews, Inc., of Palo Alto, California. Hector's article is
entitled "Knowledge Representation and Reasoning." Ray Reiter has an
article on "Nonmonotonic Reasoning," to appear in the next volume of
the same series.
You might also refer to our Readings in Knowledge Representation book
(Morgan Kaufmann, 1985); it includes a brief introduction to the
field, and a number of important articles highlighting, among other
things, different techniques of KR.
The section on KR in the AI Handbook is always a reasonable place to
start, as well.
Finally, I have just completed a brief (20-page) survey/tutorial
article for the AT&T Technical Journal, entitled "The Basics of
Knowledge Representation and Reasoning." I can send you a copy if you
would like.
- Ron Brachman
------------------------------
Date: Wed, 16 Dec 87 14:28:10 PST
From: Marie Bienkowski <bienk@spam.istc.sri.com>
Subject: Cognitive Science Program at Princeton
CC: bjr@mind.princeton.edu tjhorton@rutgers.edu
Princeton University has an excellent Cognitive Science
program, although there is no department by that name.
They have active research programs on automated tutoring,
vocabulary acquisition, reasoning, belief revision,
connectionism (with Bellcore), computational linguistics,
cognitive anthropology, and probably more that I've missed.
The main sponsoring departments are Psychology, Philosophy
and Linguistics.
A good person to contact is bjr@mind.princeton.edu,
who is, in real life, a professor in the Psychology Dept.
His p-mail address is:
Brian Reiser
Cognitive Science Laboratory
221 Nassau St.
Princeton, NJ 08542
Marie Bienkowski
------------------------------
Date: Tue, 15 Dec 87 10:31:52 pst
From: norman%ics@sdcsvax.ucsd.edu (Donald A. Norman)
Subject: Cognitive Science programs (once and for all)
Yes, there is a Cognitive Science Society. It hosts an annual
conference (the next one will be in Montreal). It publishes the
journal "Cognitive Science." You can find out about it by writing
the secretary treasurer:
Kurt Vanlehn
Department of Psychology
Carnegie-Mellon University
Pittsburgh, PA 15213
vanlehn@a.psy.cmu.edu
At UCSD, we are indeed in the process of establishing a Department of
Cognitive Science. We are now hiring, but formal classes will not
start until the Fall of 1989. We will have both an undergraduate and
a PhD program. We now have an Interdisciplinary PhD program:
students enter some department, X, and join the interdisciplinary
program after completing the first year requirements of X. They then
receive a "PhD in X and Congitive Sicnefce." We have about 20
students now and have given out about 3 PhDs.
(One of these is now in Computer Science at Toronto: Mike Mozer)
The strengths are in the computational understanding of cognition,
with strong emphasis in psychology, AI, linguisitics, neuroscience,
philosophy, and social cognition. PDP (connectionism) is one of the
strengths at UCSD, and the approach permeates all of the different
areas of Cognitive Science, even among those of us who do not directly
do work on weights, algorithms, or connectionist architectures: the
strength grows by the hour).
Don Norman
Donald A. Norman
Institute for Cognitive Science C-015
University of California, San Diego
La Jolla, California 92093
INTERNET: norman%ics@sdcsvax.ucsd.edu INTERNET: danorman@ucsd.edu
BITNET: danorman@ucsd.bitnet
ARPA: norman@nprdc.arpa UNIX:{decvax,ucbvax,ihnp4}!sdcsvax!ics!norman
------------------------------
End of AIList Digest
********************
∂18-Dec-87 0342 LAWS@KL.SRI.COM AIList V5 #285 - Probability, Simulation, DAEDALUS, Methodology
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 18 Dec 87 03:41:53 PST
Date: Thu 17 Dec 1987 23:59-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #285 - Probability, Simulation, DAEDALUS, Methodology
To: AIList@SRI.COM
AIList Digest Friday, 18 Dec 1987 Volume 5 : Issue 285
Today's Topics:
Query & Puzzle - Probability Bounds,
Announcements - Simulation List & Issue of DAEDALUS on AI,
Philosophy - The Role of Biological Models in AI
----------------------------------------------------------------------
Date: 11 Dec 87 14:10:21 GMT
From: mcvax!ukc!its63b!hwcs!tom@uunet.uu.net (Tom Kane)
Subject: Probability Bounds from Bayes Theory: (A Problem).
I am sending this letter out to the network to ask for solutions to a
particular problem of Bayesian Inference. Below is the text of the
problem, and at the end is the mathematical statement of the information
given. Simply, I am asking the questions:
1) Can you find bounds on the final result. If so, how?
2) If not, why is it not possible to do so?
What is missing in the specification of the problem?
3) If you get nowhere with this problem, would you be able to solve it
if you were given the information: p(pv|t or l)=0.9?
I am interested in the problem of providing probability bounds for events
specified in a Bayesian setting when not all the necessary conditional
probabilities are provided in setting up the problem.
PROBLEM
~~~~~~~
(A problem relevant to the handling of Uncertainty in Expert Systems.)
We want to know the probability of a patient having both lung cancer and
tuberculosis based on the fact that this person has had a positive reading
in a chest X-ray. We are given the following pieces of information:
1. The probability that a person with lung cancer will have a positive
chest X-ray is 0.9.
2. The probability that a person with tuberculosis will have a positive
chest X-ray is 0.95.
3. The probability that a person with neither lung cancer nor tuberculosis
will have a positive chest X-ray is 0.07.
4. In the town of interest, 4 percent of the population have lung cancer,
and three percent have tuberculosis.
EVENTS
~~~~~~
l = lung cancer; t = tuberculosis; pv = positive chest X-ray
SETUP
~~~~~
In the statement of the problem below:-
~l means 'not l'.
~l, ~t means 'not l and not t'.
t or l means 't or l'
where 'not', 'and' , and 'or' are logical operators.
so that: p(~l, ~t) means probability( not l and not t).
Also,
p(pv|l) means the conditional probability of event pv, given event l.
PRIORS
~~~~~~
p(l) = 0.04; p(t) = 0.03; p(~l, ~t) = 0.95
CONDITIONALS
~~~~~~~~~~~~
p(pv|l) = 0.9; p(pv|t) = 0.95; p(pv| ~t,~l) = 0.07
(You are not given p(pv| t or l) )
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Please mail all solutions or comments to me, and I will let interested parties
know what the results are.
(I will specially treasure attempts which don't use independence assumptions.)
Thanks in advance to anyone who will spend time on this problem...
Regards,
Tom Kane.
------------------------------
Date: Thu, 17 Dec 87 09:30:06 EST
From: Paul Fishwick <fishwick@fish.cis.ufl.edu>
Subject: New Simulation List
------------------------------------------
****** NOTICE: NEW MAILING LIST **********
------------------------------------------
on
S I M U L A T I O N
GENERAL:
There has not been a news group on the topic of simulation, so I have
decided to start one. Actually, it is a mailing list and if it grows
into a popular forum then we can formally apply to have it made a
news "group" (which apparently requires votes,etc.).
TOPICS:
All topics connected with simulation are welcome (no flaming please!).
Some sample topics are listed:
real time simulation methods
flight simulation
parallel architectures for simulation analysis and modeling
simulation and training
distributed simulation
artificial intelligence and simulation
automatic generation and analysis of models
analog vs. digital methods, hybrids
continuous, discrete, and combined methods
qualitative modeling
application specific questions
theory of simulation and systems
queries and comments about available simulation software
announcements of simulation-related talks and seminars
graphics and image processing in simulation
HOW TO JOIN:
To participate in the mailing list you need to know two net addresses:
simulation@fish.cis.ufl.edu - for sending topical mail messages
simulation-request@fish.cis.ufl.edu - for subscribing/unsubscribing
to the list (administration)
METHOD:
At first, we will operate on an automatic mode (unedited list): All
mail sent to 'simulation' will be forwarded automatically to everyone
else on the list. My SUN is strictly acting as a mail handler. As
interesting topics come up and more people chip in, then I will try
my hand at moderating the list to form a digest which will be shipped
periodically. I'm sure that most net readers subscribe to both kinds
of these mailing lists already. So let's go!
Paul Fishwick
University of Florida
------------------------------
Date: Mon, 14 Dec 87 15:22:40 EST
From: amcad!billb@husc6.harvard.edu
Subject: New Issue of DAEDALUS on AI
In response to numerous queries re. forthcoming issue of DAEDALUS on AI,
we would like to provide Table of Contents for this 320-page volume and
information on how to get a copy.
Contents include essays by the following:
Seymour Papert - "One AI or Many?"
Hubert L. Dreyfus & Stuart E. Dreyfus - "Making a Mind Versus Modeling
a Brain: AI Back at a Branchpoint"
Robert Sokolowski - "Natural and Artificial Intelligence"
Pamela McCorduck - "Artificial Intelligence: An Apercu"
Jack D. Cowan & David H. Sharp - "Neural Nets and AI"
Jacob T. Schwartz - "The New Connectionism: Developing Relationships
Between Neuroscience and AI"
George N. Reeke Jr. & Gerald M. Edelman - "Real Brains and AI"
W. Daniel Hillis - "Intelligence as an Emergent Behavior; or,
The Songs of Eden"
David L. Waltz - "The Prospects for Building Truly Intelligent
Machines"
Anya Hurlbert & Tomasio Poggio - "Making Machines (and AI) See"
Sherry Turkle - "AI and Psychoanalysis: A New Alliance"
Hilary Putnam - "Much Ado About Not Very Much"
Daniel C. Dennett - "When Philosophers Encounter AI"
John McCarthy - "Mathematical Logic and AI"
Copies of this volume of DAEDALUS are available @ $5 each ($1 additional for
surface mail delivery outside the U.S.) by writing to:
DAEDALUS Business Office
P.O. Box 515
Canton, MA. 02021 U.S.A.
Email orders can be sent, along with credit card billing number to:
daedalus%amcad.uucp@husc6.harvard.edu
or
harvard!husc6!amcad!daedalus
Holiday greetings,
Guild Nichols
DAEDALUS
------------------------------
Date: 15 Dec 87 03:06:02 GMT
From: marque!gryphon!sarima@csd1.milw.wisc.edu (Stan Friesen)
Subject: Re: the role of biological models in ai
In article <23@gollum.Columbia.NCR.COM> rolandi@gollum.UUCP () writes:
>
> According to some AI theorists, (see Schank,
>R.C., (1984) The Cognitive Computer. Reading, Mass.: Addison-Wesley)
>AI is "an investigation into human understanding through which we learn
>...about the complexities of our own intelligence." Thus, at least for
>some AI researchers, the automation of intelligent behavior is secondary
>to the expansion and formalization of our self-understanding. This is
>assumed to be the result of creating computational "accounts" of (typically
>intellectual) behavior. Researchers write programs which display the
>performance characteristics of humans within some given domain. The
>efficacy of a program is a function of the similarity of its performance
>to the human performance after which it was modeled. Thus AI programs are
>(often) created in order to "explain" the processes that they model.
>
My problem with this class of AI research is that I question it
validity/usefulness. Why should there be only *one* algorithm for a
particular 'behavior'? What evidence do we have that the algorithms that
we are writing into our programs are in fact related in any way th the
ones used by the human brain? Mere parallel behavior is NOT sufficient
evidence to claim increased understanding of a human behavior, some
evidence from neurology and psychology is necessary to at least
demonstrate applicibility. In particular, I find most current AI
algorithms to be far too analytical to be realistic models of human,
or even animal, cognition.
------------------------------
End of AIList Digest
********************
∂19-Dec-87 0157 LAWS@KL.SRI.COM AIList V5 #286 - Seminars, Conferences
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 19 Dec 87 01:57:26 PST
Date: Fri 18 Dec 1987 23:55-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #286 - Seminars, Conferences
To: AIList@SRI.COM
AIList Digest Saturday, 19 Dec 1987 Volume 5 : Issue 286
Today's Topics:
Seminars - Practical Reasoning and Unstructured Work (BBN) &
Distributing Deductions to Multiple Processors (SRI) &
Matrix Proof Methods for First Order Logics (SRI),
Conferences - Request for AAAI-88 Workshop Proposals &
AAAAIC88 Aerospace Applications of AI &
Computers and Law &
3rd CAD/CAM Robotics and Factories of the Future
----------------------------------------------------------------------
Date: Wed 9 Dec 87 08:33:12-EST
From: Dori Wells <DWELLS@G.BBN.COM>
Subject: Seminar - Practical Reasoning and Unstructured Work (BBN)
BBN Science Development Program
Language And Cognition Seminar
ISSUES IN THE STUDY OF PRACTICAL REASONING:
DESIGNING COMPUTER SUPPORT FOR
"UNSTRUCTURED WORK"
Constance Perin
Sloan School of Management
BBN Laboratories Inc.
10 Moulton Street
Large Conference Room, 2nd Floor
10:00 a.m., Wednesday, December 9, 1987
Abstract: To develop computer applications that are relevant to
nonroutine, relatively unstructured work processes requires
descriptions of them in terms of the rational, irrational, and
nonrational thought they employ. Deriving structures from the
particularities of these tasks and from the relationships among tasks
is one representational problem which needs to be addressed in
designing computer support for such tasks. Another is how to
acknowledge the influence of contexts on tasks. A third problem is
how to decrease the probability of miscommunication and increase that
of shared interpretations in complex organizations. The perspectives
of discourse analysis, semantic analysis, and figurative language
analysis seem to be appropriate to this set of questions. In this
talk, I will discuss how these types of observation and analysis might
be employed in designing research methods appropriate to knowledge
acquisition for tasks in unstructured work domains.
------------------------------
Date: Thu, 10 Dec 87 15:38:13 PST
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Distributing Deductions to Multiple Processors
(SRI)
DISTRIBUTING BACKWARD-CHAINING DEDUCTIONS TO MULTIPLE PROCESSORS
Vineet Singh (VSINGH@SPAR-20.ARPA)
Schlumberger Palo Alto Research
11:00 AM, MONDAY, December 14
SRI International, Building E, Room EJ228
This talk presents a parallel execution model called PM for
backward-chaining deduction with horn clauses. The target class of
multiprocessors for this work has the following properties: (1) there
are a finite number of MIMD processors; (2) each processor has a
finite amount of local memory; (3) there is no global memory; (4)
processors can communicate only by sending messages to each other; (5)
message delay is a function of the amount of data in the message and
the distance between source and destination; (6) each processor can
perform backward-chaining deductions based on the subset of the
program that it contains. For this multiprocessor class, PM can
exploit the most parallelism among existing execution models that use
data-driven control. In particular, PM can exploit or-parallelism,
and-parallelism, and pipelining.
One problem area that PM addresses is the design of a resource
allocator to map the parallel processes to hardware resources for
processing, storage, and communication. The allocation strategy
proposed is for use at compile-time (as opposed to run-time) and is
application-independent and multiprocessor-independent. This strategy
works subject to two restrictions. First, the type of
backward-chaining deduction is restricted. In particular, no
recursive clauses are allowed, unit clauses must be ground, and
certain probabilistic uniformity and independence assumptions must
apply. Second, a partitioning of the database is assumed to be given.
The allocator consists of an initial allocation phase followed by a
local minimization phase. In the initial allocation phase, database
partitions are allocated to processors one at a time using a greedy
algorithm. The local minimization phase consists of a sequence of
cost-reducing reallocations of partitions to neighboring processors.
Considerable speedups are obtained by using this allocation strategy.
These speedups compare favorably with an unreachable upper bound and
speedups obtained using random allocations.
------------------------------
Date: Wed, 16 Dec 87 13:09:25 PST
From: Amy Lansky <lansky@venice.ai.sri.com>
Subject: Seminar - Matrix Proof Methods for First Order Logics (SRI)
MATRIX PROOF METHODS FOR FIRST ORDER LOGICS
Lincoln A. Wallen (LW@SALLY.UTEXAS.EDU)
Dept. of Computer Sciences, Univ. of Texas at Austin
11:00 AM, MONDAY, December 21
SRI International, Building E, Room EJ228
We present matrix-based proof methods for classical, modal, and
intuitionistic first order logics. The methods are designed to
facilitate automated proof search and, as such, represent a
comprehensive extension of resolution-style techniques to modal and
intuitionistic logics. We emphasise how the matrix methods arise from
an analysis of the structure of Gentzen sequent calculi. This
suggests a general method for obtaining efficient proof systems for
other logics of interest to Computing Science and Artificial
Intelligence.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Fri, 18 Dec 87 08:46:53 EST
From: Joseph L. Katz. <katz@mitre-bedford.ARPA>
Subject: Conference - Request for AAAI-88 Workshop Proposals
AAAI-88 Workshops:
Request for Proposals
The AAAI-88 Program Committee invites proposals for the Workshop Program of
the Seventh National Conference on Artificial Intelligence (AAAI-88), to be
held at Saint Paul, Minn. from August 21, 1988 to August 26, 1988. Gathering
in an informal setting, workshop participants will have the opportunity to
meet and discuss issues with a selected focus---providing for active exchange
among researchers and practioners on topics of mutual interest. Members from
all segments of the AI community are encouraged to submit workshop proposals
for review.
To encourage interaction and a broad exchange of ideas, the workshops will be
kept small---preferably under 35 participants. Attendance should be limited
to active participants only. The format of workshop presentations will be
determined by the organizers of the workshop, but ample time must be allotted
for general discussion. Workshops can range in length from two hours to two
days, but most workshops will last a half day or a full day.
Proposals for workshops should be between 1 and 2 pages in length, and
should contain:
1/ a brief description the workshop identifying specific issues that will be
focused on.
2/ a discussion of why the workshop would be of interest at this time,
3/ the names and addresses of the organizing committee, preferably 3 or 4
people not all at the same site,
4/ a list of several potential participants, and
5/ a proposed schedule.
Workshop proposals should be submitted as soon as possible, but no later
than 1 February 1988. Proposals will be reviewed as they are received and
resources allocated as workshops are approved. Organizers will be notified
of the committee's decision no later than 15 February 1988.
Workshop organizers will be responsible for:
1/ producing a Call for Participation in the workshop, which will be mailed
to AAAI members by AAAI,
2/ reviewing requests to participate in the workshop, and determining the
workshop participants,
3/ scheduling the activities of the workshop, and
4/ preparing a review of the workshop, which will be printed in the AI
Magazine.
AAAI will provide logistical support, will provide a meeting place for
the workshop, and, in conjunction with the organizers, will determine the
date and time of the workshop.
Please submit your workshop proposals, and enquiries concerning workshops,
to:
Joseph Katz
MITRE Corporation
MS L203
Burlington Road
Bedford, MA 01730
(617) 271 5200
or
Katz@Mitre-Bedford.ARPA
------------------------------
Date: 7 Dec 87 10:01:00 EDT
From: "ETD2::WILSONJ" <wilsonj%etd2.decnet@afwal-aaa.arpa>
Reply-to: "ETD2::WILSONJ" <wilsonj%etd2.decnet@afwal-aaa.arpa>
Subject: Conference - AAAAIC88 Aerospace Applications of AI
AAAIC88 CALL FOR PAPERS
AEROSPACE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE 1988
With Neural Networks Aerospace Applications
Special Interest Sessions
Stouffer's Hotel, Dayton, OH, October 25-27, 1988
Particulars - Tutorials will be held on 24 Oct 88. Workshops will be held on
28 Oct 88. There will be exhibits by AI companies and related industries as
well as product familiarization sessions. There will be up to 18 technical
sessions in 5 half-day periods, luncheon speakers and a banquet.
The 4th Aerospace Applications of Artificial Intelligence Conference will
investigate a wide range of topics with heavy emphasis this year on neural
network applications in aerospace. Topic areas for which timely, original,
technical papers are solicited include:
Integrating Neural Networks and Knowledge Processing with Neural Nets
Expert Systems Robotics
Neural Networks and Signal Processing Data Fusion/Sensor Fusion
Machine Learning, Cognition & the Combinatorial Optimization for
Cockpit Scheduling and Resource Control
Machine Vision & Avionics Applications Natural Language Recognition and
Neural Networks and Man-Machine Synthesis
Interface Issues Self-Organization in Avionics
Neural Network Development Tools Applied Adaptive-Resonance
Applied Biological Models Cooperative and Competitive Network
Parallel Processing & Neural Networks Dynamics in Aerospace
Automatic Target Recognition Learning Theory and Techniques
Back Propagation with Momentum, Simulation and Implementation of
Shared Weights or Recurrent Neural Networks
Network Architectures Technology - Microchips, Optics, etc.
Expert System Development Tools Applications of Expert Systems in
Aerospace Scheduling Manufacturing
Operational and Maintenance Issues Design Automation
Using Expert Systems Data Management
Real Time Expert Systems Acquisition Management
Knowledge Base Simulation Verification and Validation of ES
Advanced Problem Solving Techniques Diagnostics and Fault Isolation
ABSTRACT DEADLINE : 26 Feb 88
Authors are invited to submit abstracts of 500 words in any of the above topic
areas. Please avoid acronyms or abbreviations in the title of the paper. A
short biographical sketch of the author(s) to include citizenship, mailing
address and telephone number must be included with the abstract. Final
manuscripts for papers are due 19 Aug 88.
James R. Johnson
Send abstracts to: AFWAL/AAOR
WPAFB, OH 45433
Sponsored by Dayton SIGART and the Association of Computing Machinery.
------------------------------
Date: Fri 18 Dec 87 19:34:50-PST
From: ELIOT@ECLA.USC.EDU
Subject: Conference - Computers and Law
CONFERENCE NOTICE
International Conference on Computers and Law
Dates: February 8-10, 1988
Location: The Miramar Sheraton Hotel, Santa Monica, Ca.
Purpose:
This Conference will bring together legal experts, computer
users, computer product developers, buyers/sellers of computers,
and related interested parties in order to explore common legal
and business problems related to all areas of computing.
Topics:
Emerging Technologies such as Artificial Intelligence and Expert
Systems, Protection and Litigation of Intellectual Property
Rights, Independent Contractor Relationships, Information Systems
Crimes, Malpractice Potential and Prevention, Computers and
Criminal Justice, and additonal topics.
Sponsors:
IFIP Technical Committee on Computers and Society, Law and
Technology Section of the Los Angeles County Bar Association,
Computer Law Section of the San Francisco Bar Association, High
Technology Exchange Inc., Irell & Manella Attorneys at Law,
Laventhol & Horwath Management Consultants, Pactific Bell, and
Peter Norton Computing Inc.
Conference Fees:
Cost is $395.00 until January 8, 1988, and $495.00 thereafter.
Send registration fee made out to "ICCL88" either by check or
money order to Michael Krieger (address below). Attendees are
responsible for obtaining their own hotel reservations, contact
the Miramar Sheraton Hotel at (213) 394-3731, mention the
Conference rates of $110/night for single and $125/night for a
double.
Additional Information:
For additional information and a Conference brochure, contact the
Conference Chair:
Michael M. Krieger
c/o ICCL88
P.O. Box 24619
Los Angeles, Ca. 90024.
Krieger may be reached by phone at (213) 208-2461.
Electronic Mail:
As a courtesy to the Conference, Dr. Eliot of the University of
Southern California has agreed to assist interested attendees via
electronic mail at ELIOT@ECLA.USC.EDU on the Arpanet. He can
help answer limited questions about the Conference.
------------------------------
Date: 16 Dec 87 18:14:18 GMT
From: siemens!liu@princeton.edu (Peiya Liu)
Subject: Conference - 3rd CAD/CAM Robotics and Factories of the Future
Call for Papers
Third International Conference on CAD/CAM Automation
Robotics and Factories of the Future
Southfield Hilton, Southfield, MI
August 14-17, 1988
The main objective of this conference is to bring together researchers
and practitioners from government, industries, and academia interested
in the multidisciplinary and interorganizational productivity aspects
of advanced manufacturing systems utilizing CAD/CAM, CAE, CIM, Parametric
Technology, AI, Robotics, Factory of Future, AGV technology, etc.,
and to address productivity enhancement issues of other hybrid automated
systems that combine machine skills and human intelligence in areas
of application both manufacturing (aerospace, automotive, civil,
electrical, mechanical, industrial, computer, chemical, etc.) and
non-manufacturing (such as forestry, mining, service and leisure,
process industry, medicine and rehabilitation).
Papers are invited for the section on AI in Manufacturing and Robotics
of The Third International Conference on CAD/CAM Automation, Robotics and
Factories of the Future(CAR & FOF). Topics of interest include, but are
not limited to, the following artificial intellgience areas:
Manufacturing Workcell Diagnosis, Process Planning, Robot Motion Planning,
Scheduling, Knowledge Representation of Workcells, Sensor-based Programming,
Vision, and Object Representation.
Deadline: Three copies of an extended abstract should be sent to the section
organizer at the address given below. Each copy of the extended
abstract should contain the title of the paper, full name(s) and
addresses of all authors, objectives, methods and significance of
the reported results. The closing date for receipt of abstracts is
February 1, 1988. Authors will be notified of acceptance by
March 15, 1988. Camera-ready manuscript will be due by April 15, 1988.
The section organizer: Dr. Peiya Liu, Siemens Research and Technology Labs,
105 College Road East, Princeton, NJ 08540. Csnet: liu@siemens.com,
Tel:(609)734-3349. The conference general chairman: Dr. Biren Prasad,
Electronic Data Systems, EDS Pinehurst #201, 1400 North Woodward Ave,
Bloomfield Hills, Michigan 48013, USA. General information inquires may be
directed to (313)645-4714.
Publication: Manuscripts of full length papers accepted and presented
at the conference will be reviewed and published in the Conference Proceedings
by Springer-Verlag, Berlin. Selected papers could be reviewed and published
in one of the relevant journals: Journal of Intelligent Systems and Machines
(IMPACT); International Journal of Vehicle Design: Int. Journal of
Technology Management: Int. Journal of Materials and Product Technology;
Advances in Engineering Software; Engineering Analysis; Microsoftware
for Engineers; Int. Journal of Robotics and Computer Integrated Manufacturing;
and Int. Journal of Computer Applications in Technology.
------------------------------
End of AIList Digest
********************
∂19-Dec-87 0352 LAWS@KL.SRI.COM AIList V5 #287 - Conferences
Received: from KL.SRI.COM by SAIL.STANFORD.EDU with TCP; 19 Dec 87 03:52:02 PST
Date: Sat 19 Dec 1987 00:04-PST
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI.COM>
Reply-to: AIList@SRI.COM
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025
Phone: (415) 859-6467
Subject: AIList V5 #287 - Conferences
To: AIList@SRI.COM
AIList Digest Saturday, 19 Dec 1987 Volume 5 : Issue 287
Today's Topics:
Conferences - ICEBOL3 Symbolic and Logical Computing &
Principles of Knowledge Representation and Reasoning &
ICSC'88 AI: Theory and Applications &
Visual Form and Motion Perception
----------------------------------------------------------------------
Date: Tue, 08 Dec 87 09:23:45 -0800
From: Richard Nelson <nelson@Q2.ICS.UCI.EDU>
Subject: Conference - ICEBOL3 Symbolic and Logical Computing
Here's an announcement for a conference with a twist: it includes
symbolic languages such as Icon and SNOBOL4.
cheers
Richard
------- Forwarded Message
Date: 7 Dec 87 12:03 CDT
From: ERIC%SDNET.BITNET@WISCVM.WISC.EDU
To: NELSON@Q2.ICS.UCI.EDU
Subject: BITNET mail follows
ICEBOL3
April 21-22, 1988 Dakota State College
Madison, SD 57042
ICEBOL3, the International Conference on Symbolic and
Logical Computing, is designed for teachers, scholars, and
programmers who want to meet to exchange ideas about
non-numeric computing. In addition to a focus on SNOBOL,
SPITBOL, and Icon, ICEBOL3 will feature introductory and
technical presentations on other dangerously powerful
computer languages such as Prolog and LISP, as well as on
applications of BASIC, Pascal, and FORTRAN for processing
strings of characters. Topics of discussion will include
artificial intelligence, expert systems, desk-top
publishing, and a wide range of analyses of texts in English
and other natural languages. Parallel tracks of concurrent
sessions are planned: some for experienced computer users
and others for interested novices. Both mainframe and
microcomputer applications will be discussed.
ICEBOL's coffee breaks, social hours, lunches, and
banquet will provide a series of opportunities for
participants to meet and informally exchange information.
Sessions will be scheduled for "birds of a feather" to
discuss common interests (for example, BASIC users group,
implementations of SNOBOL, computer generated poetry).
Call For Papers
Abstracts (minimum of 250 words) or full texts of
papers to be read at ICEBOL3 are invited on any application
of non-numeric programming. Planned sessions include the
following:
artificial intelligence
expert systems
natural language processing
analysis of literary texts (including bibliography,
concordance, and index preparation)
linguistic and lexical analysis (including parsing and
machine translation)
preparation of text for electronic publishing
computer assisted instruction
grammar and style checkers
music analysis.
Papers must be in English and should not exceed twenty
minutes reading time. Abstracts and papers should be
received by January 15, 1988. Notification of acceptance
will follow promptly. Papers will be published in ICEBOL3
Proceedings.
Presentations at previous ICEBOL conferences were made
by Susan Hockey (Oxford), Ralph Griswold (Arizona), James
Gimpel (Lehigh), Mark Emmer (Catspaw, Inc.), Robert Dewar
(New York University), and many others. Copies of ICEBOL 86
Proceedings are available.
ICEBOL3 is sponsored by
The Division of Liberal Arts
and
The Business and Education Institute
of
DAKOTA STATE COLLEGE
Madison, South Dakota
For Further Information
All correspondence including abstracts and papers as
well as requests for registration materials should be sent
to:
Eric Johnson
ICEBOL Director
114 Beadle Hall
Dakota State College
Madison, SD 57042 U.S.A.
(605) 256-5270
Inquiries, abstracts, and correspondence may also be
sent via electronic mail to:
ERIC @ SDNET (BITNET)
------- End of Forwarded Message
------------------------------
Date: Thu, 10 Dec 14:29:20 1987
From: rjb%research.att.com@RELAY.CS.NET
Subject: Conference - Principles of Knowledge Representation and
Reasoning
CALL FOR PAPERS
FIRST INTERNATIONAL CONFERENCE ON
PRINCIPLES OF KNOWLEDGE REPRESENTATION AND REASONING
Royal York Hotel
Toronto, Ontario, CANADA
May 15-18, 1989
Sponsored by the Canadian Society for Computational Studies of Intelligence,
with support from AAAI, IJCAI, the Canadian Institute for Advanced
Research, and the Information Technology Research Centre of Ontario,
in cooperation with AISB and ACM SIGART (pending approval)
The idea of explicit representations of knowledge, manipulated by
general-purpose inference algorithms, underlies much of the work in
artificial intelligence, from natural language to expert systems. A growing
number of researchers are interested in the principles governing systems
based on this idea. This conference will bring together these researchers in
a more intimate setting than that of the general AI conferences. In
particular, all authors will be expected to appear and give presentations of
adequate length to present substantial results. Accepted papers will be
collected in a conference proceedings, to be published by Morgan Kaufmann
Publishers, Inc.
The conference will focus on principles of commonsense reasoning and
representation, as distinct from concerns of engineering and details of
implementation. Thus of direct interest are logical specifications of
reasoning behaviors, comparative analyses of competing algorithms and
theories, and analyses of the correctness and/or the computational complexity
of reasoning algorithms. Papers that attempt to move away from or refute the
knowledge-based paradigm in a principled way are also welcome, so long as
appropriate connections are made to the central body of work in the field.
Submissions are encouraged in at least the following topic areas:
Analogical Reasoning Qualitative Reasoning
Commonsense Reasoning Temporal Reasoning
Deductive Reasoning Planning
Diagnostic and Knowledge Representation Formalisms
Abductive Reasoning Theories of the Commonsense World
Evidential Reasoning Theories of Knowledge and Belief
Inductive Reasoning Belief Management and Revision
Nonmonotonic Reasoning Formal Task and Domain Specifications
REVIEW OF PAPERS
The Program Committee will review extended abstracts (not complete papers).
Each submission will be read by at least two members of the Committee and
judged on clarity, significance, and originality. An important criterion for
acceptance of a paper is that it clearly contribute to principles of
representation and reasoning that are likely to influence current and future
AI practice.
Extended abstracts should contain enough information to enable the Program
Committee to identify the principal contribution of the research and its
importance. It should also be clear from the extended abstract how the work
compares to related work in the field. References to relevant literature must
be included.
Submitted papers must never have been published. Submissions must also be
substantively different from papers currently under review and must not be
submitted elsewhere before the author notification date (December 15, 1988).
SUBMISSION OF PAPERS
Submitted abstracts must be at most eight (8) double-spaced pages. All
abstracts must be submitted on 8-1/2" x 11" paper (or alternatively, a4),
and typed in 12-point font (pica on standard typewriter). Dot matrix
printout is not acceptable.
Each submission should include the names and complete addresses of all
authors. Also, authors should indicate under the title which of the
topic ares listed above best describes their paper (if none is
appropriate, please give a set of keywords that best describe the
topic of the paper).
Abstracts must be received no later than November 1, 1988, at the address
listed immediately below. Authors will be notified of the Program Committee's
decision by December 15, 1988. Final camera-ready copies of the full papers
will be due a short time later, on February 15, 1989. Final papers will be at
most twelve (12) double-column pages in the conference proceedings.
Send five (5) copies of extended abstracts [one copy is acceptable from
countries where access to copiers is limited] to
Ron Brachman and Hector Levesque, Program Co-chairs
First International Conference on Principles of
Knowledge Representation and Reasoning
c/o AT&T Bell Laboratories
600 Mountain Avenue, Room 3C-439
Murray Hill, NJ 07974
USA
Inquiries of a general nature can be addressed to the Conference Chair:
Raymond Reiter, Conference Chair
First International Conference on Principles of
Knowledge Representation and Reasoning
c/o Department of Computer Science
University of Toronto
10 Kings College Road
Toronto, Ontario M5S 1A4
CANADA
electronic mail: reiter@ai.toronto.edu
IMPORTANT DATES
Submission deadline: November 1, 1988
Author notification date: December 15, 1988
Camera-ready copy due
to publisher: February 15, 1989
Conference: May 15-18, 1989
PROGRAM COMMITTEE
James Allen (University of Rochester)
Giuseppe Attardi (Delphi SpA, Italy)
Woody Bledsoe (MCC/University of Texas)
Alan Bundy (Edinburgh University)
Eugene Charniak (Brown University)
Veronica Dahl (Simon Fraser University)
Koichi Furukawa (ICOT)
Johan de Kleer (Xerox PARC)
Herve Gallaire (European Computer Industry Research Center, Munich)
Michael Genesereth (Stanford University)
Michael Georgeff (SRI International)
Pat Hayes (Xerox PARC)
Geoff Hinton (University of Toronto)
Bob Kowalski (Imperial College)
Vladimir Lifschitz (Stanford University)
Alan Mackworth (University of British Columbia)
Drew McDermott (Yale University)
Tom Mitchell (Carnegie-Mellon University)
Robert Moore (SRI International)
Judea Pearl (UCLA)
Stan Rosenschein (SRI International)
Stuart Shapiro (SUNY at Buffalo)
Yoav Shoham (Stanford University)
William Woods (Applied Expert Systems)
------------------------------
Date: 10 Dec 87 23:23:35 GMT
From: munnari!mulga.oz.au!isaac@uunet.UU.NET (Isaac Balbin)
Subject: Conference - ICSC'88 AI: Theory and Applications
Call for Papers
International Computer Science Conference '88
Hong Kong, December 19-21, 1988
Artificial Intelligence: Theory and Applications
Sponsored by
THE COMPUTER SOCIETY OF THE IEEE, HONG KONG CHAPTER
International Computer Science Conference '88 is to be the first international
conference in Hong Kong devoted to computer science. The purpose of the
conference is to bring together people from academia and industry of the East
and of the West, who are interested in problems related to computer science.
The main focus of this conference will be on the Theory and Applications of
Artificial Intelligence. Our expectation is that this conference will provide a
forum for the sharing of research advances and practical experiences among
those working in computer science.
Topics of interest include, but are not limited to:
AI Architectures Expert Systems Knowledge Engineering
Logic Programming Machine Learning Natural Languages
Neural Networks Pattern Recognition Robotics
CAD/CAM Chinese Computing Distributed Systems
Information Systems Office Automation Software Engineering
Paper Submissions
Submit four copies of the paper by June 15, 1988 to either of the Program
Co-Chairmen:
Dr. Jean-Louis Lassez Dr. Francis Y.L. Chin
Room H1-A12 Centre of Computer Studies and
IBM Thomas J. Watson Applications
Research Center University of Hong Kong
P.O. Box 218 Pokfulam Road
Yorktown Heights NY Hong Kong
10598 (For papers from Pan-Pacific region
U.S.A. only)
e-mail: JLL@ibm.com e-mail: hkucs!chin@uunet.uu.net
The first page of the paper should contain the author's name, affiliation,
address, electronic address if available, phone number, 100 word abstract, and
key words or phrases. Papers should be no longer than 5000 words (about 20
double-spaced pages). A submission letter that contains a commitment to present
the paper at the conference if accepted should accompany the paper.
Tutorials
The day after the conference will be devoted to tutorials. Proposals for
tutorials on Artificial Intelligence topics, especially advanced topics, are
welcome. Send proposals by June 15, 1988 to the Program Co-Chairmen.
Conference Timetable and Information
Papers due: June 15, 1988
Tutorial proposals due: June 15, 1988
Acceptance letters sent: September 1, 1988
Camera-ready copy due: October 1, 1988
International Program Committee:
J-P Adam (Paris T.Y. Chen (Melbourne & W.F. Clocksin
Scientific Center) HKU) (Cambridge)
A. Despain (Berkeley) J. Gallier Qingshi Gao
M. Georgeff (SRI) (Pennsylvania) (Academia Sinica)
R.C.T. Lee (National D. Hanson (Princeton) R. Hasegawa (ICOT)
Tsin Hua) M. Maher (IBM) Z. Manna (Stanford &
F. Mizoguchi (Science U. Montanari (Pisa) Weizmann)
U. of Tokyo) P.C. Poole (Melbourne) K. Mukai (ICOT)
H.N. Phien (AIT) C.K. Yuen (Singapore) D.S.L. Tung (CUHK)
Organizing Committee Local Arrangements Publicity Chairman:
Chairman: Chairman:
Mr. Wanbil Lee
Dr. K.W. Ng Dr. K.P. Chow Department of
Department of Computer Centre of Computer Computer Studies
Science Studies and Applications City Polytechnic of
The Chinese University University of Hong Kong Hong Kong
of Hong Kong Pokfulam Road Argyle Center
Shatin, N.T. Hong Kong Kowloon, Hong Kong
Hong Kong e-mail:
hkucs!icsc@uunet.uu.net
In Cooperation With:
Center for Computing Studies and Services, Hong Kong Baptist College
Centre of Computer Studies and Applications, University of Hong Kong
Department of Computer Science, The Chinese University of Hong Kong
Department of Computer Studies, City Polytechnic of Hong Kong
Department of Computing Studies, Hong Kong Polytechnic
------------------------------
Date: Mon, 7 Dec 87 09:59:52 EST
From: ennio@bucasb.bu.edu (Ennio Mingolla)
Subject: Conference - Visual Form and Motion Perception
**************************************************************************
***** UPDATED Meeting Announcement: (Please Post) *****
VISUAL FORM AND MOTION PERCEPTION:
PSYCHOPHYSICS, COMPUTATION, AND NEURAL NETWORKS
Friday and Saturday, March 4 and 5, 1988
Conference Auditorium, George Sherman Union, Boston University
775 Commonwealth Avenue, Boston, Massachusetts
This meeting has been dedicated to the memory of the late
KVETOSLAV PRAZDNY, who was to have been a speaker, and
whose tragic death has deprived the field of visual
perception of one of its most talented investigators.
Confirmed speakers and tentative titles are:
S. ANSTIS, York University. (To be announced)
L. AREND, Eye Research Institute. Lightness and color in complex scenes
I. BIEDERMAN, University of Minnesota. Invariant primitives for visual
image understanding
P. CAVANAGH, University of Montreal. Motion: The long and the short of it
J. DAUGMAN, Harvard University. Image segmentation by networks for signal
orthogonalization
S. GROSSBERG, Boston University. Filling in the forms: Monocular and binocular
constraints on surface lightness perception
J. LAPPIN, Vanderbilt University. The optical information for perceiving
metric structure from motion
E. MINGOLLA, Boston University. Recent results in emergent visual segmentations
V. RAMACHANDRAN, UCSD. The utilitarian theory of perception: Interactions
between motion, form, color, and texture
A. REEVES, Northeastern University. Fundamental mechanisms of color vision
W. RICHARDS, MIT. Encoding shape by curvature
R. SAVOY, Rowland Institute. Traditional form and motion stimuli presented to
isolated cone classes
G. SPERLING, New York University. Non-Fourier motion perception
J. TODD, Brandeis University. Perception of smoothly curved surfaces
S. ZUCKER, McGill University. From orientation selection to optical flow
This meeting is sponsored by the Boston Consortium for Behavioral and
Neural Studies, a group of researchers supported by the Air Force Office
of Scientific Research Life Sciences Program. A Howard Johnson's Motor
Lodge is located at 575 Commonwealth Avenue, and a limited number of rooms
at a reduced conference rate can be reserved until February 10, 1988 by
those attending the meeting. Total conference registration will be
limited by available meeting space, so early registration is advised.
Registration and hotel accomodations for the meeting are being
handled by:
UNIGLOBE--Vision Meeting Telephone:
40 Washington Street (800) 521-5144
Wellesley Hills, MA 02181 (617) 235-7500
A meeting registration and hotel reservation form is attached to this
announcement. For further information about travel or accomodation
arrangements, contact UNIGLOBE at the above address or telephone numbers.
[Contact the sender if you need the registration form. -- KIL]
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End of AIList Digest
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