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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 L. Lanzi, Wolfgang Stolzmann, Stewart W. Wilson.

Medverkande: Materialtyp: TextSerie: Utgivningsuppgift: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2002Utgåva: 1st ed. 2002Beskrivning: VIII, 236 p. online resourceInnehållstyp:
  • text
Medietyp:
  • computer
Bärartyp:
  • online resource
ISBN:
  • 9783540481041
Ämnen: DDK-klassifikation:
  • 006.3 23
Onlineresurser:
Innehåll:
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 2El Farol3 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.
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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 2El Farol3 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.

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