New entropy model for extraction of structural information from XCS population

Won Kyung Park, Jae C. Oh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

We show that when XCS is applied to complex real-valued problems, the XCS populations contain structural information. This information exists in the underlying classifier space as the degree of uncertainty associated to the problem space. Therefore, we can use structural information to improve the overall system performance. We take an information theoretic approach, introducing a new entropy model for XCS to extract the structural information from dynamically forming substructures. Using this entropy model, we can collectively emphasize or de-emphasize the effect of an individual input. For a complex problem domain, we chose the speaker identification (SID) problem. The SID problem challenges XCS with a complex problem space that may force the learning classifier system to evolve large and highly overlapping population. The entropy model improved the system performance up to 5-10% in large-set SID problems. Furthermore, the entropy model has the ability to assist the population initialization in the beginning of the learning process by assuring a certain level of overall diversity.

Original languageEnglish (US)
Title of host publicationProceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Pages1283-1290
Number of pages8
DOIs
StatePublished - Dec 31 2009
Event11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 - Montreal, QC, Canada
Duration: Jul 8 2009Jul 12 2009

Publication series

NameProceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009

Other

Other11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
CountryCanada
CityMontreal, QC
Period7/8/097/12/09

Keywords

  • Information theory
  • Learning classifier systems
  • Speaker identification

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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  • Cite this

    Park, W. K., & Oh, J. C. (2009). New entropy model for extraction of structural information from XCS population. In Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 (pp. 1283-1290). (Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009). https://doi.org/10.1145/1569901.1570073