Quantitative Analysis of Locally Geometric Semantic Crossover

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Krzysztof Krawiec and Tomasz Pawlak",
  title =        "Quantitative Analysis of Locally Geometric Semantic
  booktitle =    "Parallel Problem Solving from Nature - PPSN XII",
  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 =        "397--406",
  address =      "Taormina, Italy",
  month =        sep # " 1-5",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, semantic
                 crossover, homology",
  isbn13 =       "978-3-642-32936-4",
  URL =          "http://dx.doi.org/10.1007/978-3-642-32937-1_40",
  DOI =          "doi:10.1007/978-3-642-32937-1_40",
  abstract =     "We investigate the properties of locally geometric
                 semantic crossover (LGX), a genetic programming search
                 operator that is approximately semantically geometric
                 on the level of homologous code fragments. For a pair
                 of corresponding loci in the parents, LGX finds a
                 semantically intermediate procedure from a library
                 prepared prior to evolutionary run, and creates an
                 offspring by using such procedure as replacement code.
                 LGX proves superior when compared to standard subtree
                 crossover and other control methods in terms of search
                 convergence, test-set performance, and time required to
                 find a high-quality solution. This paper focuses in
                 particular the impact of homology and program semantic
                 on LGX performance.",
  notes =        "PPSN-XII",

Genetic Programming entries for Krzysztof Krawiec Tomasz Pawlak