Evolving choice structures for genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Shuaiqiang Wang and Jun Ma and Jiming Liu and 
                 Xiaofei Niu",
  title =        "Evolving choice structures for genetic programming",
  journal =      "Information Processing Letters",
  year =         "2010",
  volume =       "110",
  number =       "20",
  pages =        "871--876",
  month =        "30 " # sep,
  keywords =     "genetic algorithms, genetic programming, Program
                 derivation, Evolutionary computation, Choice
  ISSN =         "0020-0190",
  URL =          "http://www.sciencedirect.com/science/article/B6V0F-50K5T29-1/2/9ef3031afe03a6d15f2f0a468fca26ec",
  DOI =          "doi:10.1016/j.ipl.2010.07.014",
  abstract =     "It is quite difficult but essential for Genetic
                 Programming (GP) to evolve the choice structures.
                 Traditional approaches usually ignore this issue. They
                 define some if-structures functions according to their
                 problems by combining if-else statement, conditional
                 criteria and elemental functions together. Obviously,
                 these if-structure functions depend on the specific
                 problems and thus have much low reusability. Based on
                 this limitation of GP, in this paper we propose a kind
                 of termination criterion in the GP process named
                 Combination Termination Criterion (CTC). By testing
                 CTC, the choice structures composed of some basic
                 functions independent to the problems can be evolved
                 successfully. Theoretical analysis and experiment
                 results show that our method can evolve the programs
                 with choice structures effectively within an acceptable
                 additional time.",
  notes =        "Also known as \cite{Wang2010871}",

Genetic Programming entries for Shuaiqiang Wang Jun Ma Jiming Liu Xiaofei Niu