Effect of pure error-based fitness in XCS

Authors:
Martin V. Butz;David E. Goldberg;Pier Luca Lanzi
Affiliations:
Department of Cognitive Psychology, University of Würzburg, Würzburg, Germany;Illinois Genetic Algorithms Laboratory, University of Illinois at Urbana-Champaign, Urbana, Illinois;Illinois Genetic Algorithms Laboratory, University of Illinois at Urbana-Champaign, Urbana, Illinois and Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milano, Italy
Venue:
IWLCS'03-05 Proceedings of the 2003-2005 international conference on Learning classifier systems
Year:
2007

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Abstract

The accuracy-based fitness approach in XCS is one of the most significant changes in comparison with original learning classifier systems. Nonetheless, neither the scaled accuracy function, nor the importance of the relative fitness approach has been investigated in detail. The recent introduction of tournament selection to XCS has shown to make the system more independent from parameter settings and scaling issues. The question remains if relative accuracy itself is actually necessary in XCS or if the evolutionary process could be based directly on error. This study investigates advantages and disadvantages of pure error-based fitness vs. relative accuracy-based fitness in XCS.