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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Butz, Martin V. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Colección:Studies in Fuzziness and Soft Computing, 191
Temas:
Computer science.
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Neurosciences.
Mathematics.
Theory of Computation.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Neuroscience.
Applications of Mathematics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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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