Modularity and Position Independence in EDA-GP

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

@InProceedings{Shan:2004:aspgp,
  author =       "Yin Shan and Robert I. McKay and Daryl Essam and 
                 Jianying Liu",
  title =        "Modularity and Position Independence in EDA-GP",
  booktitle =    "Proceedings of The Second Asian-Pacific Workshop on
                 Genetic Programming",
  year =         "2004",
  editor =       "R I Mckay and Sung-Bae Cho",
  address =      "Cairns, Australia",
  month =        "6-7 " # dec,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://sc.snu.ac.kr/PAPERS/interval4.pdf",
  size =         "15 pages",
  abstract =     "There has been growing interest in Estimation of
                 Distribution Algorithms (EDA). Conventional EDA mainly
                 use a linear string representation, resembling an
                 individual of Genetic Algorithms (GA). Because of the
                 flexibility of GP style tree encoding, a limited number
                 of researchers have started addressing estimation of
                 distribution of GP-style tree form solutions. For
                 simplicity, we refer to this kind of research as
                 EDA-GP, As in conventional EDA, the focus of EDA-GP at
                 this stage has to be finding an appropriate model. In
                 (Shan et al., 2004), we proposed a number of criteria
                 for an appropriate model for EDA-GP. While our focus is
                 on EDA-GP, we note that these criteria are important
                 not only for EDA-GP research, but may provide clues for
                 general problem solving with tree form solutions. In
                 this research, we empirically examine two criteria,
                 namely modularity and position dependence. In this
                 research, we empirically confirm their importance.
                 Furthermore, we also validate that PRODIGY (Shan et
                 al., 2004), the framework we propose for EDA-GP, is
                 capable of handling it.",
  notes =        "http://sc.snu.ac.kr/~aspgp/aspgp04/programme.html",
}

Genetic Programming entries for Yin Shan R I (Bob) McKay Daryl Essam Jianying Liu

Citations