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Foundations of Learning Classifier Systems / Edition 1
     

Foundations of Learning Classifier Systems / Edition 1

by Larry Bull
 

ISBN-10: 3540250735

ISBN-13: 9783540250739

Pub. Date: 09/26/2005

Publisher: Springer Berlin Heidelberg

This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computation) tailored for a classifier systems audience and written by

Overview

This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computation) tailored for a classifier systems audience and written by acknowledged authorities in their area - as well as a relevant historical original work by John Holland.

Product Details

ISBN-13:
9783540250739
Publisher:
Springer Berlin Heidelberg
Publication date:
09/26/2005
Series:
Studies in Fuzziness and Soft Computing Series , #183
Edition description:
2005
Pages:
336
Product dimensions:
9.21(w) x 6.14(h) x 0.81(d)

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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