Circuits of the Mind

Inbunden, Engelska, 1995

AvLeslie G. Valiant

1 459 kr

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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.

Produktinformation

Utgivningsdatum1995-01-26
Mått159 x 242 x 22 mm
Vikt629 g
FormatInbunden
SpråkEngelska
Antal sidor256
FörlagOUP USA
ISBN9780195089264

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Biovetenskap inom Naturvetenskap och teknik

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

"The book is written in a clear style, with a sufficient number of figures illustrating the algorithms. . .This new insight into complex problems of the brain, as well as the proposed methodology, makes the book highly readable and interesting." --Computing Reviews"The author shows that the proposed neuroidal model supports the cognitive activities he identifies. It provides a good structure to explore the functions of the mind still further." -- IEEE Spectrum"Although there are many books today dealing with a simple neuronal model based on the weighted sum principle, this one rises above these others in providing an explanation of cognitive functions." --Choice