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Machine Learning

, Volume 9, Issue 1, pp 9–21 | Cite as

Dynamic Parameter Encoding for Genetic Algorithms

  • Nicol N. Schraudolph
  • Richard K. Belew
Article
  • 652 Downloads

Abstract

The common use of static binary place-value codes for real-valued parameters of the phenotype in Holland's genetic algorithm (GA) forces either the sacrifice of representational precision for efficiency of search or vice versa. Dynamic Parameter Encoding (DPE) is a mechanism that avoids this dilemma by using convergence statistics derived from the GA population to adaptively control the mapping from fixed-length binary genes to real values. DPE is shown to be empirically effective and amenable to analysis; we explore the problem of premature convergence in GAs through two convergence models.

Adaptive encoding real-valued parameters ARGOT premature convergence genetic hitchhiking 

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Copyright information

© Kluwer Academic Publishers 1992

Authors and Affiliations

  • Nicol N. Schraudolph
    • 1
  • Richard K. Belew
    • 1
  1. 1.Computer Science & Engineering DepartmentUniversity of CaliforniaSan Diego, La Jolla

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