A Comparative Analysis of Dynamic Locality and Redundancy in Grammatical Evolution

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@InProceedings{Medvet:2017:EuroGP,
  author =       "Eric Medvet",
  title =        "A Comparative Analysis of Dynamic Locality and
                 Redundancy in Grammatical Evolution",
  booktitle =    "EuroGP 2017: Proceedings of the 20th European
                 Conference on Genetic Programming",
  year =         "2017",
  month =        "19-21 " # apr,
  editor =       "Mauro Castelli and James McDermott and 
                 Lukas Sekanina",
  series =       "LNCS",
  volume =       "10196",
  publisher =    "Springer Verlag",
  address =      "Amsterdam",
  pages =        "326--342",
  organisation = "species",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 Evolution: Poster",
  DOI =          "doi:10.1007/978-3-319-55696-3_21",
  abstract =     "the most salient feature of Grammatical Evolution (GE)
                 is a procedure which maps genotypes to phenotypes using
                 the grammar production rules; however, the search
                 effectiveness of GE may be affected by low locality and
                 high redundancy, which can prevent GE to comply with
                 the basic principle that offspring should inherit some
                 traits from their parents. Indeed, many studies
                 previously investigated the locality and redundancy of
                 GE as originally proposed in [1]. In this paper, we
                 extend those results by considering redundancy and
                 locality during the evolution, rather than statically,
                 hence trying to understand if and how they are
                 influenced by the selective pressure determined by the
                 fitness. Moreover, we consider not only the original GE
                 formulation, but three other variants proposed later
                 (BGE, piGE, and SGE). We experimentally find that there
                 is an interaction between locality/redundancy and other
                 evolution-related measures, namely diversity and growth
                 of individual size. In particular, the combined action
                 of the crossover operator and the genotype-phenotype
                 mapper makes SGE less redundant at the beginning of the
                 evolution, but with very high redundancy after some
                 generations, due to the low phenotype diversity.",
  notes =        "Part of \cite{Castelli:2017:GP} EuroGP'2017 held
                 inconjunction with EvoCOP2017, EvoMusArt2017 and
                 EvoApplications2017",
}

Genetic Programming entries for Eric Medvet

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