Mutation as a diversity enhancing mechanism in genetic programming

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

@InProceedings{Jackson:2011:GECCO,
  author =       "David Jackson",
  title =        "Mutation as a diversity enhancing mechanism in genetic
                 programming",
  booktitle =    "GECCO '11: Proceedings of the 13th annual conference
                 on Genetic and evolutionary computation",
  year =         "2011",
  editor =       "Natalio Krasnogor and Pier Luca Lanzi and 
                 Andries Engelbrecht and David Pelta and Carlos Gershenson and 
                 Giovanni Squillero and Alex Freitas and 
                 Marylyn Ritchie and Mike Preuss and Christian Gagne and 
                 Yew Soon Ong and Guenther Raidl and Marcus Gallager and 
                 Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and 
                 Nikolaus Hansen and Silja Meyer-Nieberg and 
                 Jim Smith and Gus Eiben and Ester Bernado-Mansilla and 
                 Will Browne and Lee Spector and Tina Yu and Jeff Clune and 
                 Greg Hornby and Man-Leung Wong and Pierre Collet and 
                 Steve Gustafson and Jean-Paul Watson and 
                 Moshe Sipper and Simon Poulding and Gabriela Ochoa and 
                 Marc Schoenauer and Carsten Witt and Anne Auger",
  isbn13 =       "978-1-4503-0557-0",
  pages =        "1371--1378",
  keywords =     "genetic algorithms, genetic programming",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Dublin, Ireland",
  DOI =          "doi:10.1145/2001576.2001761",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "In various evolutionary computing algorithms, mutation
                 operators are employed as a means of preserving
                 diversity of populations. In genetic programming (GP),
                 by contrast, mutation tends to be viewed as offering
                 little benefit, to the extent that it is often not
                 implemented in GP systems. We investigate the role of
                 mutation in GP, and attempt to answer questions
                 regarding its effectiveness as a means for enhancing
                 diversity, and the consequent effects of any such
                 diversity promotion on the solution finding performance
                 of the algorithm. We find that mutation can be
                 beneficial for GP, but subject to the proviso that it
                 be tailored to enhance particular forms of diversity.",
  notes =        "Santa Fe Ant, 600 steps, diversity of path. Mux,
                 4-even-parity, polynomial (diversity = 32 floats).

                 Also known as \cite{2001761} GECCO-2011 A joint meeting
                 of the twentieth international conference on genetic
                 algorithms (ICGA-2011) and the sixteenth annual genetic
                 programming conference (GP-2011)",
}

Genetic Programming entries for David Jackson

Citations