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Rule-Based Evolutionary Online Learning Systems A Principled Approach to LCS Analysis and Design /
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 backgrou...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2006.
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| Edición: | 1st ed. 2006. |
| Colección: | Studies in Fuzziness and Soft Computing,
191 |
| Temas: | |
| Acceso en línea: | Texto Completo |
| Sumario: | 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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| Descripción Física: | XXI, 259 p. online resource. |
| ISBN: | 9783540312314 |
| ISSN: | 1860-0808 ; |