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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| Format: | eBook |
| Language: | English |
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Berlin, Heidelberg
Springer Berlin Heidelberg
2006, 2006
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| Edition: | 1st ed. 2006 |
| Series: | Studies in Fuzziness and Soft Computing
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| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 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