Circuits of the mind
著者
書誌事項
Circuits of the mind
Oxford University Press, 1994
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注記
Bibliography: p. 219-229
Includes index
内容説明・目次
内容説明
In this groundbreaking work, computer scientists Leslie G. Valiant details a promising new computational approach to studying the intricate workings of the brain.
Focusing on the brain's enigmatic ability to quickly access a massive store of accumulated information during reasoning processes, the author asks how such feats are possible given the extreme constraints imposed by the brain's finite number of neurons, their limited speed of communication, and their restricted interconnectivity. Valiant proposes a "neuroidal model" that serves as a vehicle to explore these fascinating questions.
This model provides a concrete computational language and a unified framework in which diverse cognitve phenomena such as memory, learning, and reasoning, can be systematically analysed.
Requiring no specialist knowledge this book offers students and researchers in computer science and the cognitive sciences an exciting new approach to brain science.
目次
1: The Approach. 2: Biological Constraints. 2.1: Introduction. 2.2: The Neocortex. 2.3: Pyramidal Neurons. 3: Computational Laws. 3.1: Introduction. 3.2: Three Sources of Complexity. 4: Cognitive Functions. 4.1: Introduction. 4.2: Boolean Functions. 4.3: Learning. 4.4: The Nature of Concepts. 4.5: Experimental Psychology. 5: The Neuroidal Model. 5.1: Programmable Models. 5.2: Neuroids. 5.3: Timing. 6: Knowledge Representations. 6.1: Positive Knowledge Representations. 6.2: Vicinal Algorithms. 6.3: Frontier Properties and Storing New Items. 6.4: Frontier Properties and Associations. 6.5: Hashing. 7: Unsupervised Memorization. 7.1: An Algorithm. 8: Superivsed Memorization. 8.1: Introduction. 8.2: A Simple Algorithm. 8.3: A Second Algorithm. 9: Supervised Inductive Learning. 9.1: Introduction. 9.2: Pac Learning. 9.3: Learning Conjunctions. 9.4: Learning Disjunctions. 9.5: Learning Linear Threshold Functions. 10: Correlational Learning. 10.1: An Algorithm. 10.2: Computing with Numerical Values. 11: Objects and Relational Expressions. 11.1: Multiple Object Scenes. 11.2: Relations. 11.3: Timed Conjunctions. 11.4: Memorizing Expressions Containing Relations. 11.5: Memorizing New Relations. 11.6: Discussion. 12: Systems Questions. 12.1: Introduction. 12.2: General Organizational Principles. 12.3: Compatibility of Mechanisms. 13: Reasoning. 13.1: Introduction. 13.2: Relfex Reasoning. 13.3: Simple Reflex Reasoning. 13.4: Compound Reflex Reasoning. 13.5: Nonmonotonic Phenomena. 14: More Detailed Neural Models. 14.1: Implementing Vicinal Algorithms. 14.2: A Laminar Model. 14.3: A Columnar Model. 14.4: Sparser Random Graphs. 14.5: Another Columnar Model. 15: Afterword. Notes. Exercises. References. Index of Notation. Index
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