Unveiling the properties of structured grammatical evolution

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@Article{Lourenco:2016:GPEM,
  author =       "Nuno Lourenco and Francisco B. Pereira and 
                 Ernesto Costa",
  title =        "Unveiling the properties of structured grammatical
                 evolution",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2016",
  volume =       "17",
  number =       "3",
  pages =        "251--289",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, locality, Redundancy, Representation",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-015-9262-4",
  size =         "39 pages",
  abstract =     "Structured grammatical evolution (SGE) is a new
                 genotypic representation for grammatical evolution
                 (GE). It comprises a hierarchical organization of the
                 genes, where each locus is explicitly linked to a
                 non-terminal of the grammar being used. This one-to-one
                 correspondence ensures that the modification of a gene
                 does not affect the derivation options of other
                 non-terminals. We present a comprehensive set of
                 optimization results obtained with problems from three
                 different categories: symbolic regression, path
                 finding, and predictive modelling. In most of the
                 situations SGE outperforms standard GE, confirming the
                 effectiveness of the new representation. To understand
                 the reasons for SGE enhanced performance, we scrutinize
                 its main features. We rely on a set of static measures
                 to model the interactions between the representation
                 and variation operators and assess how they influence
                 the interplay between the genotype-phenotype spaces.
                 The study reveals that the structured organization of
                 SGE promotes an increased locality and is less
                 redundant than standard GE, thus fostering an effective
                 exploration of the search space.",
}

Genetic Programming entries for Nuno Lourenco Francisco Jose Baptista Pereira Ernesto Costa

Citations