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03308nam a22005535i 4500 |
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|a 9783540312314
|9 978-3-540-31231-4
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|a 10.1007/b104669
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|a 004.0151
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|a Butz, Martin V.
|e author.
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|a Rule-Based Evolutionary Online Learning Systems
|h [electronic resource] :
|b A Principled Approach to LCS Analysis and Design /
|c by Martin V. Butz.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2006.
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| 300 |
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|a XXI, 259 p.
|b online resource.
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|a text
|b txt
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|a computer
|b c
|2 rdamedia
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|a online resource
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|a text file
|b PDF
|2 rda
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|a Studies in Fuzziness and Soft Computing,
|x 1434-9922 ;
|v 191
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|a Prerequisites -- Simple Learning Classifier Systems -- The XCS Classifier System -- How XCS Works: Ensuring Effective Evolutionary Pressures -- When XCS Works: Towards Computational Complexity -- Effective XCS Search: Building Block Processing -- XCS in Binary Classification Problems -- XCS in Multi-Valued Problems -- XCS in Reinforcement Learning Problems -- Facetwise LCS Design -- Towards Cognitive Learning Classifier Systems -- Summary and Conclusions.
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|a 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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|a Computer science.
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|a Neurosciences.
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|a Computers.
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|a Artificial intelligence.
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|a Applied mathematics.
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|a Engineering mathematics.
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|a Computer Science.
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|a Theory of Computation.
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|a Appl.Mathematics/Computational Methods of Engineering.
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|a Artificial Intelligence (incl. Robotics).
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|a Neurosciences.
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|a Applications of Mathematics.
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| 710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783540253792
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| 830 |
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|a Studies in Fuzziness and Soft Computing,
|x 1434-9922 ;
|v 191
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| 856 |
4 |
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|u http://dx.doi.org/10.1007/b104669
|z Full Text via HEAL-Link
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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