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International Conference on Computational Intelligence

Fuzzy Days 2001: Computational Intelligence. Theory and Applications pp 471–478Cite as

Reducing Bloat in Genetic Programming

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2206))

Abstract

In this paper, several techniques will be presented to constrain the growth of solutions that are constructed by genetic programming. The most successful technique imposes a maximum size on the created individuals of the population that depends solely on the size of the best individual of the population. This method will be compared with other methods to reduce bloat, demonstrating that this method reduces bloat significantly better than the other methods.

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References

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Author information

Authors and Affiliations

  1. Expertise Center for Digital Media, Wetenschapspark 2, 3590, Diepenbeek, Belgium

    Patrick Monsieurs & Eddy Flerackers

Authors
  1. Patrick Monsieurs
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  2. Eddy Flerackers
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Editor information

Editors and Affiliations

  1. Computer Science I, University of Dortmund, 44221, Dortmund, Germany

    Bernd Reusch

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© 2001 Springer-Verlag Berlin Heidelberg

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Monsieurs, P., Flerackers, E. (2001). Reducing Bloat in Genetic Programming. In: Reusch, B. (eds) Computational Intelligence. Theory and Applications. Fuzzy Days 2001. Lecture Notes in Computer Science, vol 2206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45493-4_48

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  • DOI: https://doi.org/10.1007/3-540-45493-4_48

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42732-2

  • Online ISBN: 978-3-540-45493-9

  • eBook Packages: Springer Book Archive

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