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A classifier system with integrated genetic operators

  • Classifier Systems And Immune Networks
  • Conference paper
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Parallel Problem Solving from Nature (PPSN 1990)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 496))

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Abstract

This text presents a classifier system (CS), which is able to adapt to an environment by adjusting the activation probabilities of the rules and changing the rules itself. The operators for changing the rules are incorporated into the CS, thus allowing for an adaption of the rates of change on-line during the search process for better rules. An age is attached to the rules. Removal of rules from the rule set is done according to the age.

Experiments show that this approach to adapting the rule set by means of internal genetic operators (GO) is superior to exogenous genetic operators.

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References

  1. John J. Grefenstette. Multilevel credit assignment in a genetic learning system. In John J. Grefenstette, editor, Genetic Algorithms and their Applications: Proceedings of the Second International Conference on Genetic Algorithms, pages 202–209, Lawrence Erlbaum Associates, 1987.

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  3. John J. Holland. Adaption in natural and artificial systems. University of Michigan, 1975.

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  4. Andreas Schachtner. Problemlösen mittels einer broadcast language, 1989. Thesis, German.

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  5. J. David Schaffer and Amy Morishima. An adaptive crossover distribution mechanism for genetic algorithms. In John J. Grefenstette, editor, Genetic Algorithms and their Applications: Proceedings of the Second International Conference on Genetic Algorithms, pages 36–40, Lawrence Erlbaum Associates, 1987.

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Authors and Affiliations

  1. Department of Computer Science, University of Dortmund, Germany

    Andreas Schachtner

Authors
  1. Andreas Schachtner
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Editor information

Hans-Paul Schwefel Reinhard Männer

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© 1991 Springer-Verlag Berlin Heidelberg

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Schachtner, A. (1991). A classifier system with integrated genetic operators. In: Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature. PPSN 1990. Lecture Notes in Computer Science, vol 496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029773

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  • DOI: https://doi.org/10.1007/BFb0029773

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54148-6

  • Online ISBN: 978-3-540-70652-6

  • eBook Packages: Springer Book Archive

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