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)


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.


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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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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