Medial Crossovers for Genetic Programming

  • Krzysztof Krawiec
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7244)

Abstract

We propose a class of crossover operators for genetic programming that aim at making offspring programs semantically intermediate (medial) with respect to parent programs by modifying short fragments of code (subprograms). The approach is applicable to problems that define fitness as a distance between program output and the desired output. Based on that metric, we define two measures of semantic ‘mediality’, which we employ to design two crossover operators: one aimed at making the semantic of offsprings geometric with respect to the semantic of parents, and the other aimed at making them equidistant to parents’ semantics. The operators act only on randomly selected fragments of parents’ code, which makes them computationally efficient. When compared experimentally with four other crossover operators, both operators lead to success ratio at least as good as for the non-semantic crossovers, and the operator based on equidistance proves superior to all others.

Keywords

Genetic programming Program semantic Semantic crossover 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Krzysztof Krawiec
    • 1
  1. 1.Institute of Computing SciencePoznan University of TechnologyPoznańPoland

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