Investigation of the Neighborhood Attraction Evolutionary Algorithm Based on Neural Gas

  • Jutta Huhse
  • Thomas Villmann
  • Andreas Zell
Part of the Advances in Soft Computing book series (AINSC, volume 19)


In this contribution we present a new approach to involve the idea of neighborhood cooperation during adaptation known from neural maps in evolutionary algorithms. Thereby we focus on application of cooperativeness according to the neural gas network and present first parameter studies for this NG-neighborhood attraction EA.


Neighborhood Function Adaptation Strength Neighborhood Cooperativeness Neighborhood Range Neighborhood Attraction 
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  1. 1.
    L. Altenberg. The evolution of evolvability in genetic programming. In K. E. Kinnear, editor, Advances in Genetic Programming, Complex Adaptive Systems, pages 47–74, Cambridge, 1994. MIT Press.Google Scholar
  2. 2.
    T. Bäck. Evolutionary Algorithms in Theory and Practice. Oxford University Press, New York - Oxford, 1996.MATHGoogle Scholar
  3. 3.
    J. Huhse, T. Villmann, P. Merz, and A. Zell. Evolution strategies with neighborhood attraction using a neural gas approach. Parallel Problem Solving from Nature,submitted, 2002.Google Scholar
  4. 4.
    J. Huhse and A. Zell. Evolutionary strategy with neighborhood attraction. In H. Bothe and R. Rojas, editors, Neural Computation 2000, pages 363–369, Zürich, 2000. ICSC Academic Press.Google Scholar
  5. 5.
    J. Huhse and A. Zell. Evolution strategy with neighborhood attraction - A robust evolution strategy. In L. Spector, E. D. Goodman, A. Wu, W. B. Langdon, H.-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk, M. H. Garzon, and E. Burke, editors, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001),pages 1026–1033, San Francisco, California, USA, 7–11 2001. San Francisco, CA 94104, USA.Google Scholar
  6. 6.
    J. Huhse and A. Zell. Investigating the influence of the neighborhood attraction factor to the evolution strategies with neighborhood attraction. In M. Verleysen, editor, Proc. Of European Symposium on Artificial Neural Networks (ESANN’2001), pages 179–184, Brussels, Belgium, 2001. D facto publications.Google Scholar
  7. 7.
    T. Kohonen. Self-Organizing Maps, volume 30 of Springer Series in Information Sciences. Springer, Berlin, Heidelberg, 1995. (Second Extended Edition 1997 ).Google Scholar
  8. 8.
    T. Martinetz and K. Schulten. Topology representing networks. Neural Networks, 7 (3): 507–522, 1994.CrossRefGoogle Scholar
  9. 9.
    Z. Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag Berlin Heidelberg New York, third, revised and extended edition, 1996.Google Scholar
  10. 10.
    H.-P. Schwefel. Numerical Optimization of Computer Models. Wiley and Sons, 1981.Google Scholar
  11. 11.
    T. Villmann. Evolutionary algorithms and neural networks in hybrid systems. In Proc. Of European Symposium on Artificial Neural Networks (ESANN’2001),pages 137–152, Brussels, Belgium, 2001. D facto publications.Google Scholar
  12. 12.
    T. Villmann. Evolutionary algorithms with subpopulations using a neural network like migration scheme and its application to real world problems. Integrated Computer- Aided Engineering, 9 (1): 25–36, 2002.Google Scholar
  13. 13.
    T. Villmann, R. Haupt, K. Hering, and H. Schulze. Parallel evolutionary algorithms with som-like migration. In A. Dobnikar, N. Steele, D. W. Pearson, and R. Albrecht, editors, Artificial Neural Networks and Genetic Algorithms (Proc. Of ICANNGA’99), pages 274–279, Wien–New York, 1999. Springer-Verlag.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jutta Huhse
    • 1
  • Thomas Villmann
    • 2
  • Andreas Zell
    • 1
  1. 1.Inst. of Computer ScienceUniversity TübingenTübingenGermany
  2. 2.Clinic for Psychotherapy and Psychosomatic MedicineUniversity LeipzigLeipzigGermany

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