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NAIS: A Calibrated Immune Inspired Algorithm to Solve Binary Constraint Satisfaction Problems

  • Marcos Zuñiga
  • María-Cristina Riff
  • Elizabeth Montero
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4628)

Abstract

We propose in this paper an artificial immune system to solve CSPs. The algorithm has been designed following the framework proposed by de Castro and Timmis. We have calibrated our algorithm using Relevance Estimation and Value Calibration (REVAC), that is a new technique, recently introduced to find the parameter values for evolutionary algorithms. The tests were carried out using random generated binary constraint satisfaction problems on the transition phase where are the hardest problems. The algorithm shown to be able to find quickly good quality solutions.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Marcos Zuñiga
    • 1
  • María-Cristina Riff
    • 2
  • Elizabeth Montero
    • 2
  1. 1.Projet ORION, INRIA Sophia-Antipolis, NiceFrance
  2. 2.Department of Computer Science, Universidad Técnica Federico Santa María, ValparaísoChile

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