Krzysztof Krawiec


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Traditional Genetic Programming (GP) searches the space of functions/programs by using search operators that manipulate their syntactic representation (e.g., parse trees), regardless of their semantic. Recently, semantically aware search operators have been shown to outperform purely syntactic operators. In this work, using a formal geometric view on search operators and representations, we bring the semantic approach to its extreme consequences and introduce a novel form of GP - Semantic GP (SGP) - that searches directly the space of the underlying semantic of the programs. This perspective provides new insights on the relation between syntax, semantic, search operators and fitness landscape, and allows for the principled formal design of semantic search operators for different classes of problems. We derive specific forms of SGP for a number of classic GP domains and report preliminary experimental results. Furthermore, we show that the search of SGP is equivalent to the search of a traditional Genetic Algorithm on the One-Max problem. #2011ThrashMoraglioKrawiecJohnsonBib

@INPROCEEDINGS { 2011ThrashMoraglioKrawiecJohnson,
    AUTHOR = { Alberto Moraglio and Krzysztof Krawiec and Colin Johnson },
    TITLE = { Geometric Semantic Genetic Programming },
    BOOKTITLE = { 5th workshop on Theory of Randomized Search Heuristics },
    YEAR = { 2011 },
    ADDRESS = { July 8-9, Copenhagen, Denmark },
    ABSTRACT = { Traditional Genetic Programming (GP) searches the space of functions/programs by using search operators that manipulate their syntactic representation (e.g., parse trees), regardless of their semantic. Recently, semantically aware search operators have been shown to outperform purely syntactic operators. In this work, using a formal geometric view on search operators and representations, we bring the semantic approach to its extreme consequences and introduce a novel form of GP - Semantic GP (SGP) - that searches directly the space of the underlying semantic of the programs. This perspective provides new insights on the relation between syntax, semantic, search operators and fitness landscape, and allows for the principled formal design of semantic search operators for different classes of problems. We derive specific forms of SGP for a number of classic GP domains and report preliminary experimental results. Furthermore, we show that the search of SGP is equivalent to the search of a traditional Genetic Algorithm on the One-Max problem. },
    URL = { http://www.thrash-workshop.org/slides/moraglio.pdf },
}


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