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Rule-Based Evolutionary Online Learning Systems

Name: Rule-Based Evolutionary Online Learning Systems
Brand: Springer, Berlin
SKU: 01651722
Price: 40696 HUF
Availability: InStock
Author: Martin V. Butz
ISBN: 9783642064777

A Principled Approach to LCS Analysis and Design

Martin V. Butz

Language

English

Book Paperback

Libristo code: 01651722

Publishers Springer, Berlin, November 2009

This book offers a comprehensive introduction to learning classifier systems (LCS) or more generally... Full description

Libristo code: 01651722

271 b

40 696 Ft

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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.