Evolving Recursive Functions for the Even-Parity Problem Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Man Leung Wong and Kwong Sak Leung",
  title =        "Evolving Recursive Functions for the Even-Parity
                 Problem Using Genetic Programming",
  booktitle =    "Advances in Genetic Programming 2",
  publisher =    "MIT Press",
  year =         "1996",
  editor =       "Peter J. Angeline and K. E. {Kinnear, Jr.}",
  pages =        "221--240",
  chapter =      "11",
  address =      "Cambridge, MA, USA",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-262-01158-1",
  URL =          "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6277537",
  size =         "20 pages",
  abstract =     "One of the most important and challenging areas of
                 research in evolutionary algorithms is the
                 investigation of ways to successfully apply
                 evolutionary algorithms to larger and more complicated
                 problems. In this chapter. we apply GGP (Generic
                 Genetic Programming) to evolve general recursive
                 functions for the even-n-parity problem. GGP is very
                 flexible and programs in various programming languages
                 can be acquired. Moreover. it is powerful enough to
                 handle context-sensitive information and
                 domain-dependent knowledge. This knowledge can be used
                 to accelerate the learning speed and/or improve the
                 quality of the programs induced. A number of
                 experiments have been performed to determine the impact
                 of domain-specific knowledge on the speed of

Genetic Programming entries for Man Leung Wong Kwong-Sak Leung