Explicit Control of Diversity and Effective Variation Distance in Linear Genetic Programming

  • Markus Brameier
  • Wolfgang Banzhaf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2278)


We have investigated structural distance metrics for linear genetic programs. Causal connections between changes of the genotype and changes of the phenotype form a necessary condition for analyzing structural differences between genetic programs and for the two objectives of this paper: (i) Distance information between individuals is used to control structural diversity of population individuals actively by a two-level tournament selection. (ii) Variation distance is controlled on the effective code for different genetic operators - including a mutation operator that works closely with the applied distance metric. Numerous experiments have been performed for three benchmark problems.


Genetic Algorithm Boolean Function Cellular Automaton Cellular Automaton Genetic Operator 
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 2002

Authors and Affiliations

  • Markus Brameier
    • 1
  • Wolfgang Banzhaf
    • 1
  1. 1.Department of Computer ScienceUniversity of DortmundDortsmundGermany

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