Geometric Semantic Genetic Programming

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@InProceedings{conf/ppsn/MoraglioKJ12,
  author =       "Alberto Moraglio and Krzysztof Krawiec and 
                 Colin G. Johnson",
  title =        "Geometric Semantic Genetic Programming",
  booktitle =    "Parallel Problem Solving from Nature, PPSN XII (part
                 1)",
  year =         "2012",
  editor =       "Carlos A. {Coello Coello} and Vincenzo Cutello and 
                 Kalyanmoy Deb and Stephanie Forrest and 
                 Giuseppe Nicosia and Mario Pavone",
  volume =       "7491",
  series =       "Lecture Notes in Computer Science",
  pages =        "21--31",
  address =      "Taormina, Italy",
  month =        sep # " 1-5",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-32936-4",
  DOI =          "doi:10.1007/978-3-642-32937-1_3",
  size =         "11 pages",
  abstract =     "Traditional Genetic Programming (GP) searches the
                 space of functions/programs by using search operators
                 that manipulate their syntactic representation,
                 regardless of their actual semantics/behaviour.
                 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, Geometric Semantic GP (GSGP), that searches
                 directly the space of the underlying semantics of the
                 programs. This perspective provides new insights on the
                 relation between program syntax and semantics, search
                 operators and fitness landscape, and allows for
                 principled formal design of semantic search operators
                 for different classes of problems. We derive specific
                 forms of GSGP for a number of classic GP domains and
                 experimentally demonstrate their superiority to
                 conventional operators.",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  affiliation =  "School of Computer Science, University of Birmingham,
                 UK",
}

Genetic Programming entries for Alberto Moraglio Krzysztof Krawiec Colin G Johnson

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