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New Generation Computing

, Volume 23, Issue 2, pp 129–142 | Cite as

Reference chromosome to overcome user fatigue in IEC

  • Yago Saez
  • Pedro Isasi
  • Javier Segovia
  • Julio C. Hernandez
Special Issue

Abstract

Evolutionary Computation encompasses computational models that follow a biological evolution metaphor. The success of these techniques is based on the maintenance of the genetic diversity, for which it is necessary to work with large populations. However, it is not always possible to deal with such large populations, for instance, when the adequacy values must be estimated by a human being (Interactive Evolutionary Computation, IEC). This work introduces a new algorithm which is able to perform very well with a very low number of individuals (micropopulations) which speeds up the convergence and it is solving problems with complex evaluation functions. The new algorithm is compared with the canonical genetic algorithm in order to validate its efficiency. Two experimental frameworks have been chosen: table and logotype designs. An objective evaluation measures has been proposed to avoid user interaction in the experiments. In both cases the results show the efficiency of the new algorithm in terms of quality of solutions and convergence speed, two key issues in decreasing user fatigue.

Keywords

Interactive Evolutionary Computation Genetic Algorithm Micropopulations Chromosome Appearance Probability Matrix Fatigue Design Table Logotype 

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Copyright information

© Ohmsha, Ltd. and Springer 2005

Authors and Affiliations

  • Yago Saez
    • 1
  • Pedro Isasi
    • 1
  • Javier Segovia
    • 1
  • Julio C. Hernandez
    • 1
  1. 1.Universidad CARLOS III de Madrid y UPMMadridSpain

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