Grammar-Based Genetic Programming with Bayesian Network

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

@InProceedings{Wong:2014:CEC,
  title =        "Grammar-Based Genetic Programming with {Bayesian}
                 Network",
  author =       "Pak-Kan Wong and Leung-Yau Lo and Man-Leung Wong and 
                 Kwong-Sak Leung",
  pages =        "739--746",
  booktitle =    "Proceedings of the 2014 IEEE Congress on Evolutionary
                 Computation",
  year =         "2014",
  month =        "6-11 " # jul,
  editor =       "Carlos A. {Coello Coello}",
  address =      "Beijing, China",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 Algorithms with Statistical and Machine Learning
                 Techniques, Estimation of distribution algorithms",
  DOI =          "doi:10.1109/CEC.2014.6900423",
  abstract =     "Grammar-Based Genetic Programming (GBGP) improves the
                 search performance of Genetic Programming (GP) by
                 formalising constraints and domain specific knowledge
                 in grammar. The building blocks (i.e. the functions and
                 the terminals) in a program can be dependent. Random
                 crossover and mutation destroy the dependence with a
                 high probability, hence breeding a poor program from
                 good programs. Understanding on the syntactic and
                 semantic in the grammar plays an important role to
                 boost the efficiency of GP by reducing the number of
                 poor breeding. Therefore, approaches have been proposed
                 by introducing context sensitive ingredients encoded in
                 probabilistic models. In this paper, we propose
                 Grammar-Based Genetic Programming with Bayesian Network
                 (BGBGP) which learns the dependence by attaching a
                 Bayesian network to each derivation rule and
                 demonstrates its effectiveness in two benchmark
                 problems.",
  notes =        "WCCI2014",
}

Genetic Programming entries for Pak-Kan Wong "Peter" Leung-Yau Lo Man Leung Wong Kwong-Sak Leung

Citations