Krzysztof Krawiec


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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.

@INPROCEEDINGS { krawiec:2012:EuroGP,
    AUTHOR = { Krzysztof Krawiec },
    TITLE = { Medial Crossovers for Genetic Programming },
    BOOKTITLE = { Genetic Programming },
    YEAR = { 2012 },
    EDITOR = { Alberto Moraglio and Sara Silva and Krzysztof Krawiec and Penousal Machado and Carlos Cotta },
    VOLUME = { 7244 },
    SERIES = { Lecture Notes in Computer Science },
    PAGES = { 61--72 },
    ADDRESS = { Malaga, Spain },
    MONTH = { 11-13 April },
    PUBLISHER = { Springer },
    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. },
    ISBN = { 978-3-642-29138-8 },
    KEYWORDS = { Genetic programming, Program semantic, Semantic crossover },
    LOCATION = { Heidelberg },
    NOTES = { Proceedings of the 15th European Conference on Genetic Programming, EuroGP 2012 },
    ORGANISATION = { EvoStar },
}


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