Advertisement

Operator Self-adaptation in Genetic Programming

  • Min Hyeok Kim
  • Robert Ian (Bob) McKay
  • Nguyen Xuan Hoai
  • Kangil Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6621)

Abstract

We investigate the application of adaptive operator selection rates to Genetic Programming. Results confirm those from other areas of evolutionary algorithms: adaptive rate selection out-performs non-adaptive methods, and among adaptive methods, adaptive pursuit out-performs probability matching. Adaptive pursuit combined with a reward policy that rewards the overall fitness change in the elite worked best of the strategies tested, though not uniformly on all problems.

Keywords

Genetic Programming Adaptive Operator Selection Adaptive Pursuit Probability Matching Evolutionary Algorithm Tree Adjoining Grammar Grammar Guided Genetic Programming 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    De Jong, K.: Parameter setting in EAs: a 30 year perspective. In: Lobo, F.G., Lima, C.F., Michalewicz, Z. (eds.) Parameter Setting in Evolutionary Algorithms. SCI, vol. 54, pp. 1–18. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Schwefel, H.: Numerical optimization of computer models. John Wiley & Sons, Inc., New York (1981)zbMATHGoogle Scholar
  3. 3.
    Thierens, D.: An adaptive pursuit strategy for allocating operator probabilities. In: Proceedings of the 7th Genetic and Evolutionary Computation Conference, pp. 1539–1546 (2005)Google Scholar
  4. 4.
    Lobo, F., Lima, C., Michalewicz, Z.: Parameter setting in evolutionary algorithms. Springer Publishing Company, Incorporated, Heidelberg (2007)CrossRefzbMATHGoogle Scholar
  5. 5.
    Fialho, Á., Da Costa, L., Schoenauer, M., Sebag, M.: Dynamic multi-armed bandits and extreme value-based rewards for adaptive operator selection in evolutionary algorithms. In: Stützle, T. (ed.) LION 3. LNCS, vol. 5851, pp. 176–190. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  6. 6.
    Thierens, D.: Adaptive strategies for operator allocation. Parameter Setting in Evolutionary Algorithms, 77–90 (2007)Google Scholar
  7. 7.
    Goldberg, D.: Probability matching, the magnitude of reinforcement, and classifier system bidding. Machine Learning 5(4), 407–425 (1990)Google Scholar
  8. 8.
    Tuson, A., Ross, P.: Adapting operator settings in genetic algorithms. Evolutionary Computation 6(2), 161–184 (1998)CrossRefGoogle Scholar
  9. 9.
    Igel, C., Kreutz, M.: Operator adaptation in evolutionary computation and its application to structure optimization of neural networks. Neurocomputing 55, 347–361 (2003)CrossRefGoogle Scholar
  10. 10.
    Thathachar, M., Sastry, P.: A class of rapidly converging algorithms for learning automata. IEEE Transactions on Systems, Man and Cybernetics 15, 168–175 (1985)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Joshi, A.K., Levy, L.S., Takahashi, M.: Tree adjunct grammars. Journal of Computer and System Sciences 10(1), 136–163 (1975)MathSciNetCrossRefzbMATHGoogle Scholar
  12. 12.
    Hoai, N.X., McKay, R.I., Essam, D.: Some experimental results with tree adjunct grammar guided genetic programming. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A.G.B. (eds.) EuroGP 2002. LNCS, vol. 2278, pp. 228–237. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  13. 13.
    Hoai, N.X., McKay, R.I.B., Essam, D.: Representation and structural difficulty in genetic programming. IEEE Transactions on Evolutionary Computation 10(2), 157–166 (2006)CrossRefGoogle Scholar
  14. 14.
    Murphy, E., O’Neill, M., Galván-López, E., Brabazon, A.: Tree-adjunct grammatical evolution. In: 2010 IEEE Congress on Evolutionary Computation (CEC), July 1-8 (2010)Google Scholar
  15. 15.
    Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)zbMATHGoogle Scholar
  16. 16.
    Fialho, Á., Da Costa, L., Schoenauer, M., Sebag, M.: Extreme value based adaptive operator selection. In: Rudolph, G., Jansen, T., Lucas, S., Poloni, C., Beume, N. (eds.) PPSN 2008. LNCS, vol. 5199, pp. 175–184. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Min Hyeok Kim
    • 1
  • Robert Ian (Bob) McKay
    • 1
  • Nguyen Xuan Hoai
    • 2
  • Kangil Kim
    • 1
  1. 1.Seoul National UniversityKorea
  2. 2.Hanoi UniversityVietnam

Personalised recommendations