Learning Classifier Systems
From Foundations to Applications
Editors: Lanzi, Pier L., Stolzmann, Wolfgang, Wilson, Stewart W. (Eds.)
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- About this book
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Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book provides a unique survey of the current state of the art of LCS and highlights some of the most promising research directions. The first part presents various views of leading people on what learning classifier systems are. The second part is devoted to advanced topics of current interest, including alternative representations, methods for evaluating rule utility, and extensions to existing classifier system models. The final part is dedicated to promising applications in areas like data mining, medical data analysis, economic trading agents, aircraft maneuvering, and autonomous robotics. An appendix comprising 467 entries provides a comprehensive LCS bibliography.
- Table of contents (17 chapters)
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What Is a Learning Classifier System?
Pages 3-32
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A Roadmap to the Last Decade of Learning Classifier System Research (From 1989 to 1999)
Pages 33-61
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State of XCS Classifier System Research
Pages 63-81
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An Introduction to Learning Fuzzy Classifier Systems
Pages 83-104
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Fuzzy and Crisp Representations of Real-Valued Input for Learning Classifier Systems
Pages 107-124
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Table of contents (17 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Learning Classifier Systems
- Book Subtitle
- From Foundations to Applications
- Editors
-
- Pier L. Lanzi
- Wolfgang Stolzmann
- Stewart W. Wilson
- Series Title
- Lecture Notes in Artificial Intelligence
- Series Volume
- 1813
- Copyright
- 2000
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- eBook ISBN
- 978-3-540-45027-6
- DOI
- 10.1007/3-540-45027-0
- Softcover ISBN
- 978-3-540-67729-1
- Edition Number
- 1
- Number of Pages
- X, 354
- Topics
