Doing Genetic Algorithms the Genetic Programming Way

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  author =       "Conor Ryan and Miguel Nicolau",
  title =        "Doing Genetic Algorithms the Genetic Programming Way",
  booktitle =    "Genetic Programming Theory and Practice",
  publisher =    "Kluwer",
  year =         "2003",
  editor =       "Rick L. Riolo and Bill Worzel",
  chapter =      "12",
  pages =        "189--204",
  keywords =     "genetic algorithms, genetic programming, gauge",
  ISBN =         "1-4020-7581-2",
  URL =          "",
  DOI =          "doi:10.1007/978-1-4419-8983-3_12",
  abstract =     "This paper describes the GAuGE system, Genetic
                 Algorithms using Grammatical Evolution, which uses
                 Grammatical Evolution to perform as a position
                 independent Genetic Algorithm. Gauge has already been
                 successfully applied to domains such as bit level,
                 sorting and regression problems, and our experience
                 suggests that it evolves individuals with a similar
                 dynamic to Genetic Programming. That is, there is a
                 hierarchy of dependency within the individual, and, as
                 evolution progresses, those parts at the top of the
                 hierarchy become fixed across a population. We look at
                 the manner in which the population evolves the
                 representation at the same time as optimising the
                 problem, and demonstrate there is a definite emergence
                 of representation.",
  notes =        "Part of \cite{RioloWorzel:2003}",
  size =         "16 pages",

Genetic Programming entries for Conor Ryan Miguel Nicolau