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Advances in Learning Classifier Systems : Third International Workshop, Iwlcs 2000, Paris, France, September 15-16, 2000. Revised Papers - Pier Luca Lanzi

Advances in Learning Classifier Systems

Third International Workshop, Iwlcs 2000, Paris, France, September 15-16, 2000. Revised Papers

By: Pier Luca Lanzi (Editor), Wolfgang Stolzmann (Editor), Stewart W. Wilson (Editor)

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Published: 29th August 2001
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Learning classi er systems are rule-based systems that exploit evolutionary c- putation and reinforcement learning to solve di cult problems. They were - troduced in 1978 by John H. Holland, the father of genetic algorithms, and since then they have been applied to domains as diverse as autonomous robotics, trading agents, and data mining. At the Second International Workshop on Learning Classi er Systems (IWLCS 99), held July 13, 1999, in Orlando, Florida, active researchers reported on the then current state of learning classi er system research and highlighted some of the most promising research directions. The most interesting contri- tions to the meeting are included in the book Learning Classi er Systems: From Foundations to Applications, published as LNAI 1813 by Springer-Verlag. The following year, the Third International Workshop on Learning Classi er Systems (IWLCS 2000), held September 15{16 in Paris, gave participants the opportunity to discuss further advances in learning classi er systems. We have included in this volume revised and extended versions of thirteen of the papers presented at the workshop.

Theory
An Artificial Economy of Post Production Systemsp. 3
Simple Markov Models of the Genetic Algorithm in Classifier Systems: Accuracy-Based Fitnessp. 21
Simple Markov Models of the Genetic Algorithm in Classifier Systems: Multi-step Tasksp. 29
Probability-Enhanced Predictions in the Anticipatory Classifier Systemp. 37
YACS: Combining Dynamic Programming with Generalization in Classifier Systemsp. 52
A Self-Adaptive Classifier Systemp. 70
What Makes a Problem Hard for XCS?p. 80
Applications
Applying a Learning Classifier System to Mining Explanatory and Predictive Models from a Large Clinical Databasep. 103
Strength and Money: An LCS Approach to Increasing Returnsp. 114
Using Classifier Systems as Adaptive Expert Systems for Controlp. 138
Mining Oblique Data with XCSp. 158
Advanced Architectures
A Study on the Evolution of Learning Classifier Systemsp. 177
Learning Classifier Systems Meet Multiagent Environmentsp. 192
The Bibliography
A Bigger Learning Classifier Systems Bibliographyp. 213
Appendix
An Algorithmic Description of XCSp. 253
Author Indexp. 273
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9783540424376
ISBN-10: 3540424377
Series: Lecture Notes in Computer Science
Audience: General
Format: Paperback
Language: English
Number Of Pages: 280
Published: 29th August 2001
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Country of Publication: DE
Dimensions (cm): 23.39 x 15.6  x 1.52
Weight (kg): 0.41