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Genetic algorithms and the immune system

  • 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

Using genetic algorithm techniques we introduce a model to examine the hypothesis that antibody and T cell receptor genes evolved so as to encode the information needed to recognize schemas that characterize common pathogens. We have implemented the algorithm on the Connection Machine for 16,384 64-bit antigens and 512 64-bit antibodies.

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4 References

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, University of New Mexico, 87131, Albuquerque, N.M., USA

    Stephanie Forrest

  2. Theoretical Division, Los Alamos National Laboratory, 87545, Los Alamos, N.M., USA

    Alan S. Perelson

Authors
  1. Stephanie Forrest
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  2. Alan S. Perelson
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Editor information

Hans-Paul Schwefel Reinhard Männer

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© 1991 Springer-Verlag Berlin Heidelberg

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Forrest, S., Perelson, A.S. (1991). Genetic algorithms and the immune system. 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/BFb0029771

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  • DOI: https://doi.org/10.1007/BFb0029771

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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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