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Task scheduling with use of classifier systems

  • Novel Techniques and Applications of Evolutionary algorithms
  • Conference paper
  • First Online:
Evolutionary Computing (AISB EC 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1305))

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Abstract

A new approach to develop parallel and distributed algorithms for scheduling tasks in parallel computers with use of learning machines is proposed. Coevolutionary multi-agent systems with game theoretical model of interaction between agents serve as a theoretical framework for the approach. Genetic-algorithms based learning machines called classifier systems are used as players in a game. Experimental study of such a system shows its self-organizing features and the ability of emergent behavior. Following this approach a parallel and distributed scheduler is described. Results of the experimental study of the scheduler are presented.

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Authors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237, Warsaw, Poland

    Franciszek Seredyński

Authors
  1. Franciszek Seredyński
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Editor information

David Corne Jonathan L. Shapiro

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© 1997 Springer-Verlag Berlin Heidelberg

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Seredyński, F. (1997). Task scheduling with use of classifier systems. In: Corne, D., Shapiro, J.L. (eds) Evolutionary Computing. AISB EC 1997. Lecture Notes in Computer Science, vol 1305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027182

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  • DOI: https://doi.org/10.1007/BFb0027182

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63476-8

  • Online ISBN: 978-3-540-69578-3

  • eBook Packages: Springer Book Archive

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