Design of an algorithm based on the estimation of distributions to generate new rules in the XCS classifier system

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“Design of an algorithm based on the estimation of distributions to generate new rules in the XCS classifier system” by J. P. Rivera and R. Santana, Institute of Cybernetics. Mathematics and Physics technical report ICIMAF 2000-100, CEMAFIT 2000-78, (Havana, Cuba), June 2000.

Abstract

In classifier systems the genetic algorithms (GAs) have been usually employed as the discovery component. The theory of evolutionary algorithms has achieved important results nowadays, but classifier systems do not seem to be employing these advances in their own benefit. The aim of this paper is to analyze the effect of replacing the traditional discovery component of the XCS classifier system by another kind of population based search method, an Estimation Distribution Algorithm (EDA). The algorithm, which we have called CS-EDA required the implementation of a mutation-like effect with a selected mutation rate. To achieve a proper performance of XCS a new rule deletion method was developed. A more elaborated technique for the calculation of the predictions of the offspring was devised. Finally, to obtain a categorical comparison between both evolutionary algorithms it was necessary to define performance measures that permitted us to verify that the proposed algorithm performed better than the GA for the examples considered.

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BibTeX entry:

@techreport{Rivera_and_Santana:2000,
   author = {J. P. Rivera and R. Santana},
   title = {Design of an algorithm based on the estimation of
	distributions to generate new rules in the {XCS} classifier
	system},
   institution = {Institute of Cybernetics, Mathematics and Physics},
   number = {ICIMAF 2000-100, CEMAFIT 2000-78},
   address = {Havana, Cuba},
   month = jun,
   year = {2000},
   issn = {0138-8916}
}

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