Crossover and mutation operators for grammar-guided genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{journals/soco/CouchetMRR07,
  author =       "Jorge Couchet and Daniel Manrique and Juan Rios and 
                 Alfonso Rodriguez-Paton",
  title =        "Crossover and mutation operators for grammar-guided
                 genetic programming",
  journal =      "Soft Computing",
  year =         "2007",
  volume =       "11",
  number =       "10",
  pages =        "943--955",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming,
                 Grammar-guided genetic programming, Crossover,
                 Mutation, Breast cancer prognosis",
  DOI =          "doi:10.1007/s00500-006-0144-9",
  abstract =     "This paper proposes a new grammar-guided genetic
                 programming (GGGP) system by introducing two original
                 genetic operators: crossover and mutation, which most
                 influence the evolution process. The first, the
                 so-called grammar-based crossover operator, strikes a
                 good balance between search space exploration and
                 exploitation capabilities and, therefore, enhances GGGP
                 system performance. And the second is a grammar-based
                 mutation operator, based on the crossover, which has
                 been designed to generate individuals that match the
                 syntactical constraints of the context-free grammar
                 that defines the programs to be handled. The use of
                 these operators together in the same GGGP system
                 assures a higher convergence speed and less likelihood
                 of getting trapped in local optima than other related
                 approaches. These features are shown throughout the
                 comparison of the results achieved by the proposed
                 system with other important crossover and mutation
                 methods in two experiments: a laboratory problem and
                 the real-world task of breast cancer prognosis.",
  notes =        "p945 'ambiguous' context free grammars. p950 PCT2 SSGA
                 75percent crossover 5percent mutation. p952 315 breast
                 lesions X-ray images characteristics by human: size
                 (apparent diameter mm), morphology (5 values), margins
                 (5 values), density (4 values). Biopsy as ground truth,
                 Comparison with two human experts. Evolved rule: if
                 margins=spiculated and morphology=irregular then
                 prognosis=malignant.

                 p953 benefit of ambiguous grammar (not given).",
  bibdate =      "2008-03-11",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/soco/soco11.html#CouchetMRR07",
}

Genetic Programming entries for Jorge Couchet Tarantelli Daniel Manrique Gamo Juan Rios Carrion Alfonso Rodriguez-Paton Aradas

Citations