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Investigation of the Performance of Different Mapping Orders for GE on the Max Problem

  • David Fagan
  • Miguel Nicolau
  • Erik Hemberg
  • Michael O’Neill
  • Anthony Brabazon
  • Sean McGarraghy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6621)

Abstract

We present an analysis of how the genotype-phenotype map in Grammatical Evolution (GE) can effect performance on the Max Problem. Earlier studies have demonstrated a performance decrease for Position Independent Grammatical Evolution (πGE) in this problem domain. In πGE the genotype-phenotype map is changed so that the evolutionary algorithm controls not only what the next expansion will be but also the choice of what position in the derivation tree is expanded next. In this study we extend previous work and investigate whether the ability to change the order of expansion is responsible for the performance decrease or if the problem is simply that a certain order of expansion in the genotype-phenotype map is responsible. We conclude that the reduction of performance in the Max problem domain by πGE is rooted in the way the genotype-phenotype map and the genetic operators used with this mapping interact.

Keywords

Genetic Programming Mapping Order Derivation Tree Symbolic Regression Performance Decrease 
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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References

  1. 1.
    Banzhaf, W.: Genotype-phenotype-mapping and neutral variation – A case study in genetic programming. In: Davidor, Y., Männer, R., Schwefel, H.-P. (eds.) PPSN 1994. LNCS, vol. 866. Springer, Heidelberg (1994)Google Scholar
  2. 2.
    Brameier, M.F., Banzhaf, W.: Linear Genetic Programming. Springer, Heidelberg (2007)zbMATHGoogle Scholar
  3. 3.
    Dempsey, I., O’Neill, M., Brabazon, A.: Foundations in Grammatical Evolution for Dynamic Environments. SCI. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  4. 4.
    Fagan, D., O’Neill, M., Galván-López, E., Brabazon, A., McGarraghy, S.: An Analysis of Genotype-Phenotype Maps in Grammatical Evolution. In: Esparcia-Alcázar, A.I., Ekárt, A., Silva, S., Dignum, S., Uyar, A.Ş. (eds.) EuroGP 2010. LNCS, vol. 6021, pp. 62–73. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  5. 5.
    Fernandez-Villacanas Martin, J.-L., Shackleton, M.: Investigation of the importance of the genotype-phenotype mapping in information retrieval. Future Generation Computer Systems 19(1) (2003)Google Scholar
  6. 6.
    Gathercole, C., Ross, P.: An adverse interaction between crossover and restricted tree depth in genetic programming. In: Proceedings of the First Annual Conference on Genetic Programming, pp. 291–296. MIT Press, Cambridge (1996)Google Scholar
  7. 7.
    Harding, S., Miller, J.F., Banzhaf, W.: Evolution, development and learning using self-modifying cartesian genetic programming. In: GECCO 2009: Proc. of the 11th Annual Conference on Genetic and Evolutionary Computation. ACM, New York (2009)Google Scholar
  8. 8.
    Hemberg, E., McPhee, N., O’Neill, M., Brabazon, A.: Pre-, in- and postfix grammars for symbolic regression in grammatical evolution. In: IEEE Workshop and Summer School on Evolutionary Computing (2008)Google Scholar
  9. 9.
    Byrne, J., O’Neill, M., McDermott, J., Brabazon, A.: An analysis of the behaviour of mutation in grammatical evolution. In: Esparcia-Alcázar, A.I., Ekárt, A., Silva, S., Dignum, S., Uyar, A.Ş. (eds.) EuroGP 2010. LNCS, vol. 6021, pp. 14–25. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  10. 10.
    Kell, D.B.: Genotype-phenotype mapping: genes as computer programs. Trends in Genetics 18(11) (2002)Google Scholar
  11. 11.
    Keller, R.E., Banzhaf, W.: Genetic programming using genotype-phenotype mapping from linear genomes into linear phenotypes. In: Genetic Programming 1996: Proc. of the First Annual Conference. MIT Press, Cambridge (1996)Google Scholar
  12. 12.
    Keller, R.E., Banzhaf, W.: Evolution of genetic code on a hard problem. In: Proc. of the Genetic and Evolutionary Computation Conference (GECCO 2001). Morgan Kaufmann, San Francisco (2001)Google Scholar
  13. 13.
    Koza, J.R., Keane, M.A., Streeter, M.J., Mydlowec, W., Yu, J., Lanza, G.: Genetic Programming IV: Routine Human-Competitive Machine Intelligence. Kluwer Academic Publishers, Dordrecht (2003)zbMATHGoogle Scholar
  14. 14.
    Langdon, W., Poli, R.: An analysis of the MAX problem in genetic programming. In: Genetic Programming (1997)Google Scholar
  15. 15.
    Margetts, S., Jones, A.J.: An adaptive mapping for developmental genetic programming. In: Miller, J., Tomassini, M., Lanzi, P.L., Ryan, C., Tetamanzi, A.G.B., Langdon, W.B. (eds.) EuroGP 2001. LNCS, vol. 2038, p. 97. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  16. 16.
    Miller, J.F., Thomson, P.: Cartesian genetic programming. In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J., Nordin, P., Fogarty, T.C. (eds.) EuroGP 2000. LNCS, vol. 1802, pp. 121–132. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  17. 17.
    O’Neill, M.: Automatic Programming in an Arbitrary Language: Evolving Programs with Grammatical Evolution. PhD thesis, University Of Limerick (2001)Google Scholar
  18. 18.
    O’Neill, M., Brabazon, A., Nicolau, M., Garraghy, S.M., Keenan, P.: πgrammatical evolution. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol. 3103, pp. 617–629. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  19. 19.
    O’Neill, M., Hemberg, E., Gilligan, C., Bartley, E., McDermott, J., Brabazon, A.: GEVA: Grammatical evolution in java. SIGEVOlution 3(2) (2008)Google Scholar
  20. 20.
    O’Neill, M., Ryan, C.: Grammatical Evolution: Evolutionary Automatic Programming in a Arbitrary Language. In: Genetic Programming. Kluwer Academic Publishers, Dordrecht (2003)Google Scholar
  21. 21.
    O’neill, M., Ryan, C., Keijzer, M., Cattolico, M.: Crossover in grammatical evolution. Genetic Programming and Evolvable Machines 4(1), 67–93 (2003)CrossRefzbMATHGoogle Scholar
  22. 22.
    Poli, R., Langdon, W.B., McPhee, N.F.: A field guide to genetic programming (2008), Published via http://lulu.com and freely available at http://www.gp-field-guide.org.uk (With contributions by J. R. Koza)
  23. 23.
    Stephens, C.R.: Effect of mutation and recombination on the genotype-phenotype map. In: Proc. of the Genetic and Evolutionary Computation Conference, vol. 2. Morgan Kaufmann, San Francisco (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • David Fagan
    • 1
  • Miguel Nicolau
    • 1
  • Erik Hemberg
    • 1
  • Michael O’Neill
    • 1
  • Anthony Brabazon
    • 1
  • Sean McGarraghy
    • 1
  1. 1.Natural Computing Research & Applications GroupUniversity College DublinIreland

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