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Linkage Learning, Rule Representation, and the χ-Ary Extended Compact Classifier System

  • Xavier Llorà
  • Kumara Sastry
  • Cláudio F. Lima
  • Fernando G. Lobo
  • David E. Goldberg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4998)

Abstract

This paper reviews a competent Pittsburgh LCS that automatically mines important substructures of the underlying problems and takes problems that were intractable with first-generation Pittsburgh LCS and renders them tractable. Specifically, we propose a χ-ary extended compact classifier system (χeCCS) which uses (1) a competent genetic algorithm (GA) in the form of χ-ary extended compact genetic algorithm, and (2) a niching method in the form restricted tournament replacement, to evolve a set of maximally accurate and maximally general rules. Besides showing that linkage exist on the multiplexer problem, and that χeCCS scales exponentially with the number of address bits (building block size) and quadratically with the problem size, this paper also explores non-traditional rule encodings. Gene expression encodings, such as the Karva language, can also be used to build χeCCS probabilistic models. However, results show that the traditional ternary encoding 0,1,# presents a better scalability than the gene expression inspired ones for problems requiring binary conditions.

Keywords

Gene Expression Programming Expression Tree Rule Representation Niching Method Multiplexer Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Xavier Llorà
    • 1
  • Kumara Sastry
    • 2
  • Cláudio F. Lima
    • 3
  • Fernando G. Lobo
    • 3
  • David E. Goldberg
    • 2
  1. 1.National Center for Supercomputer ApplicationsUniversity of Illinois at Urbana-ChampaignUSA
  2. 2.Illinois Genetic Algorithms LaboratoryUniversity of Illinois at Urbana-ChampaignUSA
  3. 3.Informatics Laboratory (UALG-ILAB), Dept. of Electronics and Computer Science EngineeringUniversity of AlgarveFaroPortugal

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