Evolution, Learning and Cognition

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World Scientific, 1988 - Science - 411 pages
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This review volume represents the first attempt to provide a comprehensive overview of this exciting and rapidly evolving development. The book comprises specially commissioned articles by leading researchers in the areas of neural networks and connectionist systems, classifier systems, adaptive network systems, genetic algorithm, cellular automata, artificial immune systems, evolutionary genetics, cognitive science, optical computing, combinatorial optimization, and cybernetics.
 

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Contents

Connectionist Learning through Gradient Following R J Williams
3
Efficient Stochastic Gradient Learning Algorithm for Neural
27
Information Storage in Fully Connected Networks
51
Neuronic Equations and their Solutions E R Caianiello
91
The Dynamics of Searches Directed by Genetic Algorithms
111
Probabilistic Neural Networks J W Clark
129
Some Quantitative Issues in the Theory of Perception A Zee
183
Speech Perception and Production by a SelfOrganizing Neural Network
217
Learning to Predict the Secondary Structure of Globular Proteins
257
Exploiting Chaos to Predict the Future and Reduce Noise
277
Contents
279
Scaling of Error Estimates
296
Experimental Data Analysis
314
Adaptive Dynamics
322
How Neural Nets Work A Lapedes R Farber
331
Copyright

A Neural Network Model for Visual Pattern
233

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