Rule-Based Evolutionary Online Learning Systems

A Principled Approach to LCS Analysis and Design

  • Martin V. Butz

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 191)

Table of contents

  1. Front Matter
    Pages I-XXI
  2. Martin V. Butz
    Pages 1-7
  3. Martin V. Butz
    Pages 9-30
  4. Martin V. Butz
    Pages 31-50
  5. Martin V. Butz
    Pages 51-64
  6. Martin V. Butz
    Pages 147-156
  7. Martin V. Butz
    Pages 157-179
  8. Martin V. Butz
    Pages 181-195
  9. Martin V. Butz
    Pages 197-206
  10. Martin V. Butz
    Pages 207-217
  11. Martin V. Butz
    Pages 219-225
  12. Back Matter
    Pages 227-266

About this book

Introduction

This book offers a comprehensive introduction to learning classifier systems (LCS) – or more generally, rule-based evolutionary online learning systems. LCSs learn interactively – much like a neural network – but with an increased adaptivity and flexibility. This book provides the necessary background knowledge on problem types, genetic algorithms, and reinforcement learning as well as a principled, modular analysis approach to understand, analyze, and design LCSs. The analysis is exemplarily carried through on the XCS classifier system – the currently most prominent system in LCS research. Several enhancements are introduced to XCS and evaluated. An application suite is provided including classification, reinforcement learning and data-mining problems. Reconsidering John Holland’s original vision, the book finally discusses the current potentials of LCSs for successful applications in cognitive science and related areas.

Keywords

Artificial Intelligence / Machine Learning Cognitive Science Genetic Algorithms Genetics-Based Machine Learning Learning Classifier Systems Online Learning Reinforcement Learning algorithm algorithms calculus classification complexity data mining learning

Authors and affiliations

  • Martin V. Butz
    • 1
  1. 1.Department of Cognitive PsychologyUniversity of WürzburgWürzburgGermany

Bibliographic information

  • DOI https://doi.org/10.1007/b104669
  • Copyright Information Springer-Verlag 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-25379-2
  • Online ISBN 978-3-540-31231-4
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • About this book
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