Foundations of Learning Classifier Systems
Author:   Larry Bull ,  Tim Kovacs
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   Softcover reprint of hardcover 1st ed. 2005
Volume:   183
ISBN:  

9783642064135


Pages:   336
Publication Date:   25 November 2010
Format:   Paperback
Availability:   Out of print, replaced by POD   Availability explained
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Foundations of Learning Classifier Systems


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Author:   Larry Bull ,  Tim Kovacs
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of hardcover 1st ed. 2005
Volume:   183
Dimensions:   Width: 15.50cm , Height: 1.80cm , Length: 23.50cm
Weight:   0.528kg
ISBN:  

9783642064135


ISBN 10:   3642064132
Pages:   336
Publication Date:   25 November 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD   Availability explained
We will order this item for you from a manufatured on demand supplier.

Table of Contents

Section 1 – Rule Discovery. Population Dynamics of Genetic Algorithms. Approximating Value Functions in Classifier Systems. Two Simple Learning Classifier Systems. Computational Complexity of the XCS Classifier System. An Analysis of Continuous-Valued Representations for Learning Classifier Systems.- Section 2 – Credit Assignment. Reinforcement Learning: a Brief Overview. A Mathematical Framework for Studying Learning Classifier Systems. Rule Fitness and Pathology in Learning Classifier Systems. Learning Classifier Systems: A Reinforcement Learning Perspective. Learning Classifier Systems with Convergence and Generalization.- Section 3 – Problem Characterization. On the Classification of Maze Problems. What Makes a Problem Hard?

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