Quantitative Analyses of Behaviour: Neural Network Models of Conditioning and Action v. 11 download

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Quantitative Analyses of Behaviour: Neural Network Models of Conditioning and Action v. 11 download

Quantitative Analyses of Behaviour: Neural Network Models of Conditioning and Action v. 11 by Michael L. Commons

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Author: Michael L. Commons
Number of Pages: 376 pages
Published Date: 01 Apr 1991
Publisher: Lawrence Erlbaum Associates Inc
Publication Country: Mahwah, United States
Language: English
Type: PDF
ISBN: 9780805808438
Download Link: Quantitative Analyses of Behaviour Neural Network Models of Conditioning and Action v. 11
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The result of a conference held at Harvard University, this volume presents some of the exciting interdisciplinary developments that are clarifying how animals and people learn to behave adaptively in a rapidly changing environment. The text focuses on aspects of how recognition learning, reinforcement learning, and motor learning interact to generate adaptive goal-oriented behaviors that can satisfy internal needs -- an important topic for understanding brain function as well as for designing new types of autonomous robots. Because a dynamic analysis of system interactions is needed to understand these challenging phenomena -- and neural network models provide a natural framework for representing and analyzing such interactions -- all the articles either develop neural network models or provide biological constraints for guiding and testing their design. The result of a conference held at Harvard University, this volume presents some of the exciting interdisciplinary developments that clarify how animals and people learn to behave adaptively in a rapidly changing environment. The contributors focus on aspects of how recognition learning, reinforcement learning, and motor learning interact to generate adaptive goal-oriented behaviors that can satisfy internal needs -- an area of inquiry as important for understanding brain function as it is for designing new types of autonomous robots. Because a dynamic analysis of system interactions is needed to understand these challenging phenomena -- and neural network models provide a natural framework for representing and analyzing such interactions -- all the articles either develop neural network models or provide biological constraints for guiding and testing their design.

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