Alternatives in Automatic Function Definition: A Comparison Of Performance

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InCollection{kinnear:kinnear,
  author =       "Kenneth E. {Kinnear, Jr.}",
  institution =  "Adaptive Computing Technology",
  title =        "Alternatives in Automatic Function Definition: A
                 Comparison Of Performance",
  booktitle =    "Advances in Genetic Programming",
  publisher =    "MIT Press",
  editor =       "Kenneth E. {Kinnear, Jr.}",
  year =         "1994",
  pages =        "119--141",
  chapter =      "6",
  keywords =     "genetic algorithms, genetic programming, Hoist
                 (shrink) mutation, ADF, MA, GLib",
  URL =          "http://www.amazon.co.uk/Advances-Genetic-Programming-Complex-Adaptive/dp/0262111888",
  URL =          "http://cognet.mit.edu/sites/default/files/books/9780262277181/pdfs/9780262277181_chap6.pdf",
  size =         "23 pages",
  abstract =     "Two approaches to the automatic definition of
                 functions are compared, Koza's Automatically Defined
                 Functions (ADF) and Angeline and Pollack's Module
                 Acquisition (MA). Their effect on the likelihood of
                 evolving a correct solution to the even-4-parity
                 problem is contrasted, with the use of ADFs causing a
                 significant improvement and MA having no apparent
                 effect. Through a variety of experiments the
                 differences in these approaches are explored.
                 Ultimately it is concluded that the ADF approach
                 creates a particular form of structural regularity that
                 strongly increases the likelihood of evolving a correct
                 solution to the even-4-parity problem - a form of
                 structural regularity not present in the MA approach. A
                 similar type of structural regularity can be created by
                 a new genetic operator called modular crossover,
                 created from the primitives used in the MA approach.",
  size =         "22 pages",
}

Genetic Programming entries for Kenneth E Kinnear Jr

Citations