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An Incremental and Non-generational Coevolutionary Algorithm

  • Ramón Alfonso Palacios-Durazo
  • Manuel Valenzuela-Rendón
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2723)

Keywords

Genetic Algorithm Genetic Programming Multiobjective Optimization Parasite Population Genetic Algo 
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.

References

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    John Holland. Escaping brittleness: The possibilities of general-purpose learning algorithms applied to parallel rule-based systems. Machine Learning: An Artificial Intelligence Approach, 2, 1986.Google Scholar
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    Christopher D. Rosin and Richard K. Belew. Methods for competitive co-evolution: Finding opponents worth beating. In Larry Eshelman, editor, Proceedings of the Sixth International Conference on Genetic Algorithms, pages 373–380, San Francisco, CA, 1995. Morgan Kaufmann.Google Scholar
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    Manuel Valenzuela-Rendón. Two Analysis Tools to Describe the Operation of Classifier Systems. PhD thesis, The University of Alabama, Tuscaloosa, Alabama, 1989.Google Scholar
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    Manuel Valenzuela-Rendón and E. Uresti-Charre. A nongenerational genetic algorithm for multiobjective optimization. In Proceedings of the Seventh International Conference on Genetic Algorithms, pages 658–665. Morgan Kaufmann, 1997.Google Scholar
  5. 5.
    Richard A. Watson and Jordan B. Pollack. Coevolutionary dynamics in a minimal substrate. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), pages 702–709, San Francisco, California, USA, 7–11 2001. Morgan Kaufmann.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Ramón Alfonso Palacios-Durazo
    • 1
  • Manuel Valenzuela-Rendón
    • 2
  1. 1.Lumina SoftwareMonterrey N.L.Mexico
  2. 2.Monterrey Centro de Sistemas InteligentesITESMMonterrey, N.L.Mexico

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