ENGLISH

Rule-Based Evolutionary Online Learning Systems: A Principled Approach to LCS Analysis and Design

By Dr. Martin V. Butz (auth.)

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
2006
ISBN
9783540253792, 3-540-25379-3
DOI
10.1007/b104669
Open Library ID
OL9055468M
Language
english
Format
PDF
Filesize
5 MB (5472025 bytes)
Series
Studies in Fuzziness and Soft Computing 191
Edition
1
Pages
259\278
Topic
Education
Library
mexmat
Time added
2009-07-20 03:45:11
Appl.Mathematics/Computational Methods of Engineer

Description

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.

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