Task scheduling with use of classifier systems

  • Franciszek Seredyński
Novel Techniques and Applications of Evolutionary algorithms
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1305)


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.


Genetic Algorithm Payoff Function Classifier System System Graph Multiprocessor System 
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 1997

Authors and Affiliations

  • Franciszek Seredyński
    • 1
  1. 1.Institute of Computer SciencePolish Academy of SciencesWarsawPoland

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