Learning Classifier Systems From Foundations to Applications /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Lanzi, Pier L. (Editor, http://id.loc.gov/vocabulary/relators/edt), Stolzmann, Wolfgang (Editor, http://id.loc.gov/vocabulary/relators/edt), Wilson, Stewart W. (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2000.
• Edition: 1st ed. 2000.
• Series: Lecture Notes in Artificial Intelligence ; 1813
• Subjects: Artificial intelligence.; Mathematical logic.; Computers.; Artificial Intelligence.; Mathematical Logic and Formal Languages.; Computation by Abstract Devices.

Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book p...

Table of Contents:

• Basics
• What Is a Learning Classifier System?
• A Roadmap to the Last Decade of Learning Classifier System Research (From 1989 to 1999)
• State of XCS Classifier System Research
• An Introduction to Learning Fuzzy Classifier Systems
• Advanced Topics
• Fuzzy and Crisp Representations of Real-Valued Input for Learning Classifier Systems
• Do We Really Need to Estimate Rule Utilities in Classifier Systems?
• Strength or Accuracy? Fitness Calculation in Learning Classifier Systems
• Non-homogeneous Classifier Systems in a Macro-evolution Process
• An Introduction to Anticipatory Classifier Systems
• A Corporate XCS
• Get Real! XCS with Continuous-Valued Inputs
• Applications
• XCS and the Monk's Problems
• Learning Classifier Systems Applied to Knowledge Discovery in Clinical Research Databases
• An Adaptive Agent Based Economic Model
• The Fighter Aircraft LCS: A Case of Different LCS Goals and Techniques
• Latent Learning and Action Planning in Robots with Anticipatory Classifier Systems
• The Bibliography
• A Learning Classifier Systems Bibliography.