Program Evolution by Integrating EDP and GP

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Kohsuke Yanai and Hitoshi Iba",
  title =        "Program Evolution by Integrating EDP and GP",
  booktitle =    "Genetic and Evolutionary Computation -- GECCO-2004,
                 Part I",
  year =         "2004",
  editor =       "Kalyanmoy Deb and Riccardo Poli and 
                 Wolfgang Banzhaf and Hans-Georg Beyer and Edmund Burke and 
                 Paul Darwen and Dipankar Dasgupta and Dario Floreano and 
                 James Foster and Mark Harman and Owen Holland and 
                 Pier Luca Lanzi and Lee Spector and Andrea Tettamanzi and 
                 Dirk Thierens and Andy Tyrrell",
  series =       "Lecture Notes in Computer Science",
  pages =        "774--785",
  address =      "Seattle, WA, USA",
  publisher_address = "Heidelberg",
  month =        "26-30 " # jun,
  organisation = "ISGEC",
  publisher =    "Springer-Verlag",
  volume =       "3102",
  ISBN =         "3-540-22344-4",
  ISSN =         "0302-9743",
  DOI =          "doi:10.1007/b98643",
  URL =          "",
  size =         "12",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "This paper discusses the performance of a hybrid
                 system which consists of EDP and GP. EDP, Estimation of
                 Distribution Programming, is the program evolution
                 method based on the probabilistic model, where the
                 probability distribution of a program is estimated by
                 using a Bayesian network, and a population evolves
                 repeating estimation of distribution and program
                 generation without crossover and mutation. Applying the
                 hybrid system of EDP and GP to various problems, we
                 discovered some important tendencies in the behavior of
                 this hybrid system. The hybrid system was not only
                 superior to pure GP in a search performance but also
                 had interesting features in program evolution. More
                 tests revealed how and when EDP and GP compensate for
                 each other. We show some experimental results of
                 program evolution by the hybrid system and discuss the
                 characteristics of both EDP and GP.",
  notes =        "GECCO-2004 A joint meeting of the thirteenth
                 international conference on genetic algorithms
                 (ICGA-2004) and the ninth annual genetic programming
                 conference (GP-2004)",

Genetic Programming entries for Kohsuke Yanai Hitoshi Iba