How XCS Evolves Accurate Classifiers

MV Butz, T Kovacs, PL Lanzi, SW Wilson

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)


Due to the accuracy based fitness approach, the ultimate goal for XCS is the evolution of a compact, complete, and accurate payoff mapping of an environment. This paper investigates what causes the XCS classifier system to evolve accurate classifiers. The investigation leads to two challenges for XCS, the covering challenge and the schema challenge. Both challenges are revealed theoretically and experimentally. Furthermore, the paper provides suggestions for overcoming the challenges as well as investigates environmental properties that can help XCS to overcome the challenges autonomously. Along those lines, a deeper insight into how to set the initial parameter values in XCS is provided.
Translated title of the contributionHow XCS Evolves Accurate Classifiers
Original languageEnglish
Title of host publicationUnknown
EditorsLee Spector et al.
PublisherMorgan Kaufmann
Pages927 - 934
Number of pages7
Publication statusPublished - Jul 2001

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001)


Dive into the research topics of 'How XCS Evolves Accurate Classifiers'. Together they form a unique fingerprint.

Cite this