图书简介

1 The science of cognition; 1.1 The last 50 years; 1.2 How we got here; 1.3 Where we are; 1.4 Questions and answers; 1.5 Nengo: An introduction; Part I. How to build a brain; 2 An introduction to brain building; 2.1 Brain parts; 2.2 A framework for building a brain; 2.2.1 Representation; 2.2.2 Transformation; 2.2.3 Dynamics; 2.2.4 The three principles; 2.3 Levels; 2.4 Nengo: Neural representation; 3 Biological cognition - Semantics; 3.1 The semantic pointer hypothesis; 3.2 What is a semantic pointer?; 3.3 Semantics: An overview; 3.4 Shallow semantics; 3.5 Deep semantics for perception; 3.6 Deep semantics for action; 3.7 The semantics of perception and action; 3.8 Nengo: Neural computations; 4 Biological cognition - Syntax; 4.1 Structured representations; 4.2 Binding without neurons; 4.3 Binding with neurons; 4.4 Manipulating structured representations; 4.5 Learning structural manipulations; 4.6 Clean-up memory and scaling; 4.7 Example: Fluid intelligence; 4.8 Deep semantics for cognition; 4.9 Nengo: Structured representations in neurons; 5 Biological cognition - Control; 5.1 The flow of information; 5.2 The basal ganglia; 5.3 Basal ganglia, cortex, and thalamus; 5.4 Example: Fixed sequences of actions; 5.5 Attention and the routing of information; 5.6 Example: Flexible sequences of actions; 5.7 Timing and control; 5.8 Example: The Tower of Hanoi; 5.9 Nengo: Question answering; 6 Biological cognition - Memory and learning; 6.1 Extending cognition through time; 6.2 Working memory; 6.3 Example: Serial list memory; 6.4 Biological learning; 6.5 Example: Learning new actions; 6.6 Example: Learning new syntactic manipulations; 6.7 Nengo: Learning; 7 The Semantic Pointer Architecture (SPA); 7.1 A summary of the SPA; 7.2 A SPA unified network; 7.3 Tasks; 7.3.1 Recognition; 7.3.2 Copy drawing; 7.3.3 Reinforcement learning; 7.3.4 Serial working memory; 7.3.5 Counting; 7.3.6 Question answering; 7.3.7 Rapid variable creation; 7.3.8 Fluid reasoning; 7.3.9 Discussion; 7.4 A unified view: Symbols and probabilities; 7.5 Nengo: Advanced modeling methods; Part II. Is that how you build a brain?; 8 Evaluating cognitive theories; 8.1 Introduction; 8.2 Core Cognitive Criteria (CCC); 8.2.1 Representational structure; 8.2.1.1 Systematicity; 8.2.1.2 Compositionality; 8.2.1.3 Productivity; 8.2.1.4 The massive binding problem; 8.2.2 Performance concerns; 8.2.2.1 Syntactic generalization; 8.2.2.2 Robustness; 8.2.2.3 Adaptability; 8.2.2.4 Memory; 8.2.2.5 Scalability; 8.2.3 Scientific merit; 8.2.3.1 Triangulation; 8.2.3.2 Compactness; 8.3 Conclusion; 8.4 Nengo Bonus: How to build a brain - A practical guide; 9 Theories of cognition; 9.1 The state of the art; 9.1.1 ACT-R; 9.1.2 Synchrony-based approaches; 9.1.3 Neural Blackboard Architecture (NBA); 9.1.4 The Integrated Connectionist/Symbolic Architecture (ICS); 9.1.5 Leabra; 9.1.6 Dynamic Field Theory (DFT); 9.2 An evaluation; 9.2.1 Representational structure; 9.2.2 Performance concerns; 9.2.3 Scientific merit; 9.2.4 Summary; 9.3 The same...; 9.4 ...but different; 9.5 The SPA versus the SOA; 10 Consequences and challenges; 10.1 Representation; 10.2 Concepts; 10.3 Inference; 10.4 Dynamics; 10.5 Challenges; 10.6 Conclusion; A Mathematical notation and overview; A.1 Vectors; A.2 Vector spaces; A.3 The dot product; A.4 Basis of a vector space; A.5 Linear transformations on vectors; A.6 Time derivatives for dynamics; B Mathematical derivations for the NEF; B.1 Representation; B.1.1 Encoding; B.1.2 Decoding; B.2 Transformation; B.3 Dynamics; C Further details on deep semantic models; C.1 The perceptual model; C.2 The motor model; D Mathematical derivations for the SPA; D.1 Binding and unbinding HRRs; D.2 Learning high-level transformations; D.3 Ordinal serial encoding model; D.4 Spike-timing dependent plasticity; D.5 Number of neurons for representing structure; E SPA model details; E.1 Tower of Hanoi; Bibliography; Index

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