Advances in Learning Classifier Systems [electronic resource] : 4th International Workshop, IWLCS 2001 San Francisco, CA, USA, July 7–8, 2001 Revised Papers / edited by Pier Luca Lanzi, Wolfgang Stolzmann, Stewart W. Wilson.

Theory -- Biasing Exploration in an Anticipatory Learning Classifier System -- An Incremental Multiplexer Problem and Its Uses in Classifier System Research -- A Minimal Model of Communication for a Multi-agent Classifier System -- A Representation for Accuracy-Based Assessment of Classifier System Prediction Performance -- A Self-Adaptive XCS -- Two Views of Classifier Systems -- Social Simulation Using a Multi-agent Model Based on Classifier Systems: The Emergence of Vacillating Behaviour in the “El Farol” Bar Problem -- Applications -- XCS and GALE: A Comparative Study of Two Learning Classifier Systems on Data Mining -- A Preliminary Investigation of Modified XCS as a Generic Data Mining Tool -- Explorations in LCS Models of Stock Trading -- On-Line Approach for Loss Reduction in Electric Power Distribution Networks Using Learning Classifier Systems -- Compact Rulesets from XCSI -- An Algorithmic Description of ACS2.