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Comparing Energetic and Immunological Selection in Agent-Based Evolutionary Optimization

  • Aleksander Byrski
  • Marek Kisiel-Dorohinicki
Part of the Advances in Soft Computing book series (AINSC, volume 35)

Abstract

In the paper the idea of an immunological selection mechanism for the agent-based evolutionary computation is presented. General considerations are illustrated by the particular system dedicated to function optimization. Selected experimental results allow for the comparison of the performance of immune-inpired selection mechanisms and classical energetic ones.

Keywords

Selection Mechanism Soft Computing Rosenbrock Function Step Step Intelligent Information Processing 
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 2006

Authors and Affiliations

  • Aleksander Byrski
    • 1
  • Marek Kisiel-Dorohinicki
    • 1
  1. 1.Department of Computer ScienceAGH University of Science and TechnologyKrakówPoland

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