Distilling the salient features of natural systems: Commentary on ``On the mapping of genotype to phenotype in evolutionary algorithms'' by Whigham, Dick and Maclaurin

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@Article{O'Neill:2017:GPEM,
  author =       "Michael O'Neill and Miguel Nicolau",
  title =        "Distilling the salient features of natural systems:
                 Commentary on ``On the mapping of genotype to phenotype
                 in evolutionary algorithms'' by {Whigham, Dick and
                 Maclaurin}",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2017",
  volume =       "18",
  number =       "3",
  pages =        "379--383",
  month =        sep,
  note =         "Special Peer Commentary on Mapping of Genotype to
                 Phenotype in Evolutionary Algorithms",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 Evolution",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-017-9293-0",
  size =         "5 pages",
  abstract =     "Here we comment on the article, ``On the mapping of
                 genotype to phenotype in evolutionary algorithms'', by
                 Peter A. Whigham, Grant Dick, and James Maclaurin
                 \cite{Whigham:2017:GPEM}. The authors present a
                 critical view on the use of genotype to phenotype
                 mapping in Evolutionary Algorithms, and how the use of
                 this analogy can be detrimental for problem solving.
                 They examine a grammar-based approach to Genetic
                 Programming (GP), Grammatical Evolution (GE), and
                 highlight properties of GE which are detrimental to
                 effective evolutionary search. Rather than use loose
                 analogies and methaphors, we suggest that a focus
                 should be (and has been in GE and other approaches to
                 GP) on addressing one of the most significant open
                 issues in our field, i.e., What are the sufficient set
                 of features in natural, genetic, evolutionary and
                 developmental systems, which can translate into the
                 most effective computational approaches for program
                 synthesis?",
  notes =        "Introduction in \cite{Spector:2017:GPEM}

                 An author's reply to this comment is available at
                 http://dx.doi.org/10.1007/s10710-017-9289-9
                 \cite{Whigham:2017:GPEM2}.

                 This comment refers to the article available at:
                 http://dx.doi.org/10.1007/s10710-017-9288-x
                 \cite{Whigham:2017:GPEM}.",
}

Genetic Programming entries for Michael O'Neill Miguel Nicolau

Citations