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.
Product code: 9783540253792
| ISBN |
9783540253792 |
| No. Of Pages |
259 |
| Dimensions (HxWxD in mm) |
H297xW210 |
| Series |
Studies in Fuzziness and Soft Computing |
| Edition |
2006 ed. |
| Publisher |
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG |