Postscript Product DescriptionIn a computational explanation of thought, Baum argues that the complexity of mind is the outcome of evolution, which has built thought processes that act unlike the standard algorithms of computer science. The underlying mind is a complex program that corresponds to the underlying structure of the world and is essentially programmed by DNA, and we learn more rapidly than computer scientists have so far been able to explain because DNA has programmed the mind to deal only with meaningful possibilities.
"Baum (Eric B.) - What is Thought?"
Source: Baum (Eric B.) - What is Thought?
Contents
- Introduction – 1
- 1.1 Meaning, Understanding, and Thought - 2
- 1.2 A Road Map - 5
- The Mind Is a Computer Program - 33
- 2.1 Evolution as Computation - 47
- 2.2 The Program of Life - 52
- The Turing Test, the Chinese Room, and What Computers Can't Do - 67
- 3.1 The Turing Test - 69
- 3.2 Semantics vs. Syntax - 75
- Occam's Razor and Understanding - 79
- 4.1 Neural Nets and Other Curves - 80
- 4.2 Minimum Description Length - 93
- 4.3 Bayesian Statistics - 95
- 4.4 Summary - 102
- Optimization - 107
- 5.1 Hill Climbing - 109
- 5.2 The Fitness Landscape - 109
- 5.3 What Good Solutions Look Like - 111
- 5.4 Back-Propagation - 116
- 5.5 Why Hill Climbing Works - 118
- 5.6 Biological Evolution and Genetic Algorithms - 120
- 5.7 Summary - 125
- Appendix: Other Potential Problems with the Search for a Turing Machine Input - 126
- Remarks on Occam's Razor - 129
- 6.1 Why the Inner Workings of Understanding Are Opaque - 129
- 6.2 Are Compact Representations Really Necessary? - 135
- Appendix: The VC Lower Bound - 142
- Reinforcement Learning - 145
- 7.1 Reinforcement Learning by Memorizing the State-Space - 146
- 7.2 Generalization by Building a Compact Evaluation Function - 149
- 7.3 Why Value Iteration Is Fundamentally Suspect - 153
- 7.4 Why Neural Nets Are Too Weak a Representation - 155
- 7.5 Reaction vs. Reflection - 157
- 7.6 Evolutionary Programming, or Policy Iteration - 159
- Exploiting Structure - 165
- 8.1 What Are Objects? - 168
- 8.2 A Concrete Example: Blocks World - 174
- 8.3 Games - 187
- 8.4 Why Hand-Coded Al Programs Are Clueless - 206
- 8.5 Another Way AI Has Discarded Structure - 208
- 8.6 Platonism vs. Reality - 211
- Appendix: Plan Compilation - 212
- Modules and Metaphors - 215
- 9.1 Evidence for a Modular Mind - 215
- 9.2 The Metaphoric Nature of Thought - 220
- 9.3 The Metaphoric Nature of Thought Reflects Compressed Code - 225
- 9.4 New Thought and Metaphor on the Fly - 228
- 9.5 Why a Modular Structure? - 230
- Evolutionary Programming - 233
- 10.1 An Economic Model - 240
- 10.2 The Hayek Machine - 250
- 10.3 Discussion - 266
- Intractability - 271
- 11.1 Hardness - 271
- 11.2 Polynomial Time Mapping - 281
- 11.3 So, How Do People Do It? - 286
- 11.4 Constraint Propagation - 293
- The Evolution of Learning - 303
- 12.1 Learning and Development - 308
- 12.2 Inductive Bias - 316
- 12.3 Evolution and Inductive Bias - 319
- 12.4 Evolution's Own Inductive Bias - 320
- 12.5 The Inductive Bias Evolution Discovers - 323
- 12.6 The Inductive Bias Built by Evolution into Creatures - 325
- 12.7 Gene Expression and the Program of Mind - 329
- 12.8 The Interaction of Learning during Life and Evolution - 331
- 12.9 Culture: An Even More Powerful Interaction - 335
- 12.10 A Case Study: Language Learning as an Example of Programmed Inductive Bias - 337
- 12.11 Grammar Learning and the Baldwin Effect - 343
- 12.12 Summary - 346
- Language and the Evolution of Thought - 349
- 13.1 The Evolution of Behavior from Simple to Complex Creatures - 351
- 13.2 Review of the Model - 360
- 13.3 What Is Language? - 365
- 13.4 Gavagai - 367
- 13.5 Grammar and Thought - 370
- 13.6 Nature vs. Nurture: Language and the Divergence between Apes and Modern Humankind - 374
- 13.7 The Evolution of Language - 378
- 13.8 Summary - 382
- The Evolution of Consciousness - 385
- 14.1 Wanting - 387
- 14.2 The Self - 403
- 14.3 Awareness - 408
- 14.4 Qualia - 424
- 14.5 Free Will - 426
- 14.6 Epilogue - 436
- What Is Thought? – 437
Text Colour Conventions (see disclaimer)- Blue: Text by me; © Theo Todman, 2025
- Mauve: Text by correspondent(s) or other author(s); © the author(s)