Table of contents for Unifying computing and cognition : the SP theory and its applications J. Gerard Wolff.


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1 .  Beginnings          .........        ..    . ... . ..      2
1.2  Goals andbenefits .......                   ...            3
1.3  Creating a good theory ...... .             . .           4
14   The SP theory and related research   . . . . . . . . . .  13
1.5  How  to read this book. ......            ..    .....     16
1.6  Presentation  ........                         ..         16
2  Computing, Cognition and Compression                            19
2.1  Introduction .     .   ..    ..       .   . ...            19
2.2  Aspects of information  .  . . . .    ........     ..   .  9
2.3  Coding for reduced redundancy      . . . .  . . . . . . . .  39
2.4  Searching for redundancy       . . .  .  .   . . . . . . .  55
2.5  Conclusion  ....... .      . .....                        63
3  The SP Theory                                                   67
1 1  Introduction  ...... ...........                        .  67
3.2  The overall framework  ... .              . . . ..........  67
3.3  Representation of knowledge . . ..                 . .  .  70
3A4  Multiple alignments . . .       . .  . .                  74
3.5  Evaluating multiple alignments . . . . . . . .            86
3.6  Compression techniques in SP   .   . .    . . .  . . . .  92
3.7  Calculation of probabilities  . . . . .       ..  .  . . .  93
3.8  Decompression by compression  .. . . . . .  . . . . . . . . .  97
"3.9  Outline of computer models  . . . . . . . . . . . . . . .  . .  99
130 Detailed description of SP61   ...          . . . .   . . . . . 10
3  l  Conclusion  ..      ... . . . . . . ..4. . . . . . . . . . .   ..   112
4  The SP Theory as a Theory of Computing                         113
4.1  Introduction  .   ...  .  . .. . ......    .  ....  .     113
4.2  Turing and Post systems . ..4    ......4                  114
4.3  SP and the Post canonical system .      ... .  ...  .  .  . 118
4.4  Discussion . ....                .            .    .   .124
4.5  Conclusion  .  . ...  .  ... ..   ..       .  ...  . .   .  30
5  Natural Language Processing                                  131
5.1  Introduction  .            .....            .           1 31
5.2  Ambiguities in language ..    .  ..  ....       .    .  133
5.3  Recursion in language. ..   .... 134
5.4  Syntactic dependencies in French ........ . . . .        36
5.5  English auxiliary verbs             ........       ... 142
5.6  Cross serial dependencies   .  ..............        .  151
5.7  The integration of syntax with semantics  . .        .   53
5.8  Conclusion   ........                                  . 57
6  Recognition and Retrieval                                    159
6.1  Introduction .......                                    159
6.2  Recognition, retrieval and multiple alignment .. . .  . . . . . .  160
6.3  Best-match information retrieval   . . . .  . . . . .  . . 163
6.4  Class-inclusion, part-whole and inheritance  .  . . . . . . .  165
6.5  Medical diagnoss   ..   ..    . .  . . . .               71
6.6  Conclusion  ..1-..-                                     i 8
7  Probabilistic Reasoning                                      183
7.1  Introduction               ..  ...                      183
7.2  Probabilistic reasoning and multiple alignments .  ..  .. 85
"7.3  One-step 'deductive' reasoning ..........           . . 188
7.4  Abductive reasoning  .    .........         ....... . 190
7.5  Probabilistic networks and trees .             . . . . . .91
7.6  Reasoning with 'rules' ....... ...      ........       . 198
7.7  Nonmonotonic reasoning           ............        .  200
7.8  Explaining away  ..... ..  ..       ........            202
7.9  Causai diagnosis ................        .....         214
7 0O Reasoning which is not supported by evidence . . .  . . .  . 220
7.1 Conlusion .........         ...........       ....   ..222
8  Planning and Problem Solving                                 225
8.1  Introduction  .......                              ....225
8.2  Planning                  ........                      225
8.3  Solving geometric analogy problems . . . .... .  .  .  . 232
8.4  Conclusion .    .. . .. 234
9  Unsupervised Learning                                          235
9.   Introduction  .. ..........235
9.2  SP70 .                                                    236
9.3  Evaluation of the model ..........           ..   ..250
9.4  Examples  .                       ...............252
9.5  Discussion  . .w   ,,,      w     w,.                  .  257
9.6  Conclusion  ......         .....          ..   .          263
10 Mathematics and Logic                                          265
10. Introduction    .   .......                                265
0.2 Preliminaries .....     ...    ..    ....                  266
0.3 Information compression and structures  . . .  . . . .  . . . 271
10.4 Information compression and processes .  . .   . . ..     281
10.5  Discussion  .....          ..   ..  ..   ...            . 290
o0.6 Conclusion              ... .                    .   ...  296
1 Neural Mechanisms                                              297
11.1  Introduction  .  .  .  ....    .      ...    .  .   .   . .297
11.2  Global considerations  . ..... . .....       . .   . ..  . . . . 298
1 .3 Neural realisation of the SP concepts . . . . . . . . .   300
1.4  Discussion  . ..    .. ..    .. ..  ..    . .  .... . 309
11,5 Comparison with alternative proposals  . . ...  .. ..  .  334
11.6 Conclusion                       ............341
12 SP and Cognitive Psychology                                    345
12,1 Introduction. . ..                            . .. .....  ..  345
2.,2 Recognition and categorisation . . . .  . ...  .    . . .  346
12.3  Reasoning  .......         .................              354
12.4 Associative learning ..............                    .  358
2.5 Artificial grammar learning ............. ..              .3 61
12.6 Language learning    ............... .                    365
4.7 Analogy and structure mapping  . .  ......... . . .       373
2.8 Conclusion  .............                          ...     377
13 SP in the Future                                               379
31 Introduction .   .......          ...........               379
13.2 Development of the theory . .................             379
3.3 Development of an 'SP machine' .. .                  .    390
13.4 Applications of the SP theory and machine . .  .  . . . .  . 393
13.5  Conclusion  ...  .  ..            .  ...  .   .   ....   409
14 Con6lusion                                                    411
14. Is the SP theory a good theory? . . . . . .              41
A  Finding Good Matches                                          415
A.   The hit structure  .. ....    ...   ..    ..             4  5
A.2  Probabilities      .. ..   .......... 418
A.3 Discussion of the search technique    ..                  421
A.4 Computational complexity ...                              422
B  The SP Computer Models                                        425



Library of Congress subject headings for this publication: Artificial intelligence, Cognition