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A Fuzzy Intelligent Controller for Genetic Algorithms’ Parameters

  • Felipe Houat de Brito
  • Artur Noura Teixeira
  • Otávio Noura Teixeira
  • Roberto Célio Limão de Oliveira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4221)

Abstract

Genetic Algorithms have been successful in several practical appliances and obtained great prominence among the techniques of Evolutionary Computation. A large portion of methods and parameters adopted in its use are heuristic or random choices, which remain unchanged throughout the execution once they are set. This can lead to a certain lack of exploration of the search surface and also compromise the variability of the population. For that matter, this work introduces the implementation of an intelligent agent based on fuzzy logic, enabling dynamic monitoring and regulation of six GA parameters. The results obtained surpass the GA traditional implementation in many aspects, and open a wide new space for research and study.

Keywords

Genetic Algorithm Intelligent Agent Evolutionary Game Crossover Rate Genetic Algorithm Parameter 
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 2006

Authors and Affiliations

  • Felipe Houat de Brito
    • 1
    • 2
    • 3
  • Artur Noura Teixeira
    • 1
    • 2
    • 3
  • Otávio Noura Teixeira
    • 1
    • 2
    • 3
  • Roberto Célio Limão de Oliveira
    • 2
  1. 1.Área de Ciências Exatas e Tecnologia – ACET, Centro Universitário do Pará – CESUPABelémBrasil
  2. 2.Programa de Pós-Graduação em Engenharia Elétrica, PPGEE, Departamento de Engenharia Elétrica e Computação – DEEC, Universidade Federal do Pará – UFPABelémBrasil
  3. 3.MEC2A – Movimento Evolucionário e Cooperativo para a Construção do ArtificialCidade Velha, BelémBrasil

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