Neutral genetic drift: an investigation using Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Turner:2015:GPEMa,
  author =       "Andrew James Turner and Julian Francis Miller",
  title =        "Neutral genetic drift: an investigation using
                 Cartesian Genetic Programming",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2015",
  volume =       "16",
  number =       "4",
  pages =        "531--558",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming, Neutral genetic drift, Genetic
                 redundancy",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-015-9244-6",
  size =         "28 pages",
  abstract =     "Neutral genetic drift is an evolutionary mechanism
                 which can strongly aid the escape from local optima.
                 This makes neutral genetic drift an increasingly
                 important property of Evolutionary Computational
                 methods as more challenging applications are
                 approached. Cartesian Genetic Programming (CGP) is a
                 Genetic Programming technique which contains explicit,
                 as well as the more common implicit, genetic
                 redundancy. As explicit genetic redundancy is easily
                 identified and manipulated it represents a useful tool
                 for investigating neutral genetic drift. The
                 contributions of this paper are as follows. Firstly the
                 paper presents a substantial evaluation of the role and
                 benefits of neutral genetic drift in CGP. Here it is
                 shown that the benefits of explicit genetic redundancy
                 are additive to the benefits of implicit genetic
                 redundancy. This is significant as it indicates that
                 that levels of implicit genetic redundancy present in
                 other Evolutionary Computational methods may be
                 insufficient to fully use neutral genetic drift. It is
                 also shown than the identification and manipulation of
                 explicit genetic redundancy is far easier than for
                 implicit genetic redundancy. This is significant as it
                 makes the investigations here possible and leads to new
                 possibilities for allowing more effective use of
                 neutral genetic drift. This is the case not only for
                 CGP, but many other Evolutionary Computational methods
                 which contain explicit genetic redundancy. Finally, it
                 is also shown that neutral genetic drift has additional
                 benefits other than aiding the escape from local
                 optima",
}

Genetic Programming entries for Andrew James Turner Julian F Miller

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