THE COMPUTER REVOLUTION IN PHILOSOPHY (1978): Contents Page

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THE COMPUTER REVOLUTION IN PHILOSOPHY (1978)
Aaron Sloman

Book contents page

This page is also available in PDF format here.

CONTENTS
(Page numbers refer to printed edition)

Preface and Acknowledgements ........................... x

1. INTRODUCTION AND OVERVIEW ........................... 1
1.1. Computers as toys to stretch our minds ........................... 1
1.2. The revolution in philosophy ........................... 3
1.3. Themes from the computer revolution ........................... 6
1.4. What is Artificial Intelligence? ........................... 17
1.5. Conclusion ........................... 20

PART ONE Methodological Preliminaries

2. WHAT ARE THE AIMS OF SCIENCE? ........................... 22
Part one: overview ........................... 22
2.1.1. Introduction ........................... 22
2.1.2. First crude subdivision of aims of science ........................... 23
2.1.3. A further subdivision of the factual aims: form and content ..................... 24

Part two: interpreting the world ........................... 26
2.2.1. The interpretative aims of science sub divided ........................... 26
2.2.2. More on the interpretative and historical aims of science ...................... 29
2.2.3. Interpreting the world and changing it ........................... 30

Part three: elucidation of subgoal (a) ........................... 32
2.3.1. More on interpretative aims of science ........................... 32
2.3.2. The role of concepts and symbolisms ........................... 33
2.3.3. Non-numerical concepts and symbolisms ........................... 34
2.3.4. Unverbalised concepts ........................... 35
2.3.5. The power of explicit symbolisation ........................... 36
2.3.6. Two phases in knowledge acquisition: understanding and knowing ................ 36
2.3.7. Examples of conceptual change ........................... 37
2.3.8. Criticising conceptual systems ........................... 39

Part four: elucidating subgoal (b) ........................... 41
2.4.1. Conceivable or representable vs. really possible ........................... 41
2.4.2. Conceivability as consistent representability ........................... 41
2.4.3. Proving real possibility or impossibility ........................... 43
2.4.4. Further analysis of 'possible' is required ........................... 44

Part five: elucidating subgoal (c) ........................... 45
2.5.1. Explanations of possibilities ........................... 45
2.5.2. Examples of theories purporting to explain possibilities ....................... 46
2.5.3. Some unexplained possibilities ........................... 48
2.5.4. Formal requirements for explanations of possibilities ........................... 49
2.5.5. Criteria for comparing explanations of possibilities ........................... 51
2.5.6. Rational criticism of explanations of possibilities ........................... 53
2.5.7. Prediction and control ........................... 55
2.5.8. Unfalsifiable scientific theories ........................... 57
2.5.9. Empirical support for explanations of possibilities ........................... 58

Part six: concluding remarks ........................... 60
2.6.1. Can this view of science be proved correct? ........................... 60

3 SCIENCE AND PHILOSOPHY ........................... 63
3.1. Introduction ........................... 63
3.2. The aims of philosophy and science overlap ........................... 64
3.3. Philosophical problems of the form 'how is X possible?' ........................... 65
3.4. Similarities and differences between science and philosophy ........................... 69
3.5. Transcendental deductions ........................... 71
3.6. How methods of philosophy can merge into those of science ........................... 73
3.7. Testing theories ........................... 75
3.8. The regress of explanations ........................... 76
3.9. The role of formalisation ........................... 77
3.10. Conceptual developments in philosophy ........................... 77
3.11. The limits of possibilities ........................... 78
3.12. Philosophy and technology ........................... 80
3.13. Laws in philosophy and the human sciences ........................... 81
3.14. The contribution of artificial intelligence ........................... 82
3.15. Conclusion ........................... 82

4. WHAT IS CONCEPTUAL ANALYSIS? ........................... 84
4.1. Introduction ........................... 84
4.2. Strategies in conceptual analysis ........................... 86
4.3. The importance of conceptual analysis ........................... 99

5. ARE COMPUTERS REALLY RELEVANT? ........................... 103
5.1. What is a computer? ........................... 103
5.2. A misunderstanding about the use of computers ........................... 105
5.3. Connections with materialist or physicalist theories of mind ................... 106
5.4. On doing things the same way ........................... 108

PART TWO Mechanisms

6. SKETCH OF AN INTELLIGENT MECHANISM ........................... 112
6.1. Introduction ........................... 112
6.2. The need for flexibility and creativity ........................... 113
6.3. The role of conceptual analysis ........................... 113
6.4. Components of an intelligent system ........................... 114
6.5. Computational mechanisms need not be hierarchic ........................... 115
6.6. The structures ........................... 117
(a) the environment ........................... 117
(b) a store of factual information (beliefs and knowledge) ........................ 118
(c) a motivational store ........................... 119
(d) a store of resources for action ........................... 120
(e) a resources catalogue ........................... 121
(f) a purpose-process (action-motive) index ........................... 122
(g) temporary structures for current processes ........................... 124
(h) a central administrator program ........................... 124
(i) perception and monitoring programs ........................... 127
(j) retrospective analysis programs ........................... 132
6.7. Is such a system feasible? ........................... 134
6.8. The role of parallelism ........................... 135
6.9. Representing human possibilities ........................... 135
6.10. A picture of the system ........................... 136
6.11. Executive and deliberative sub-processes ........................... 137
6.12. Psychopathology ........................... 140


7. INTUITION AND ANALOGICAL REASONING ........................... 144
7.1. The problem ........................... 144
7.2. Fregean (applicative) vs analogical representations ........................... 145
7.3. Examples of analogical representations and reasoning ...................... 147
7.4. Reasoning about possibilities ........................... 154
7.5. Reasoning about arithmetic and non-geometrical relations ................... 155
7.6. Analogical representations in computer vision ........................... 156
7.7. In the mind or on paper? ........................... 157
7.8. What is a valid inference? ........................... 158
7.9. Generalising the concept of validity ........................... 159
7.10. What are analogical representations? ........................... 162
7.11. Are natural languages Fregean (applicative)? ........................... 167
7.12. Comparing Fregean and analogical representations ........................... 168
7.13. Conclusion ........................... 174


8. ON LEARNING ABOUT NUMBERS: SOME PROBLEMS AND SPECULATIONS ....... 177
8.1. Introduction ........................... 177
8.2. Philosophical slogans about numbers ........................... 179
8.3. Some assumptions about memory ........................... 181
8.4. Some facts to be explained ........................... 183
8.5. Knowing number words ........................... 184
8.6. Problems of very large stores ........................... 186
8.7. Knowledge of how to say number words ........................... 187
8.8. Storing associations ........................... 188
8.9. Controlling searches ........................... 190
8.10. Dealing with order relations ........................... 191
8.11. Control-structures for counting games ........................... 196
8.12. Problems of co-ordination ........................... 197
8.13. Interleaving two sequences ........................... 200
8.14. Programs as examinable structures ........................... 201
8.15. Learning to treat numbers as objects with relationships ........................... 202
8.16. Two major kinds of learning ........................... 203
8.17. Making a reverse chain explicit ........................... 205
8.18. Some properties of structures containing pointers ........................... 210
8.19. Conclusion 212


9. PERCEPTION AS A COMPUTATIONAL PROCESS ........................... 217
9.1. Introduction ........................... 217
9.2. Some computational problems of perception ........................... 218
9.3. The importance of prior knowledge in perception ........................... 219
9.4. Interpretations ........................... 223
9.5. Can physiology explain perception? ........................... 224
9.6. Can a computer do what we do? ........................... 226
9.7. The POPEYE program ........................... 228
9.8. The program's knowledge ........................... 230
9.9. Learning ........................... 233
9.10. Style and other global features ........................... 234
9.11. Perception involves multiple co-operating processes ........................... 235
9.12. The relevance to human perception ........................... 237
9.13. Limitations of such models ........................... 239


10. CONCLUSION: AI AND PHILOSOPHICAL PROBLEMS ........................... 242
10.1. Introduction ........................... 242
10.2. Problems about the nature of experience and consciousness ........................... 242
10.3. Problems about the relationships between experience and behaviour .............. 252
10.4. Problems about the nature of science and scientific theories ........................... 254
10.5. Problems about the role of prior knowledge and perception ........................... 255
10.6. Problems about the nature of mathematical knowledge ........................... 258
10.7. Problems about aesthetic experience ........................... 259
10.8. Problems about kinds of representational systems ........................... 260
10.9. Problems about rationality ........................... 261
10.10. Problems about ontology, reductionism, and phenomenalism ....................... 262
10.11. Problems about scepticism ........................... 263
10.12. The problems of universals ........................... 264
10.13. Problems about free will and determinism ........................... 266
10.14. Problems about the analysis of emotions ........................... 267
10.15. Conclusion ........................... 268
Epilogue ........................... 272
Bibliography ........................... 274
Postscript ........................... 285
Index ........................... 288

Footnotes will be found at the end of each chapter.


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Updated: 4 Jun 2007