Behavioral Diversity and a Probabilistically Optimal GP Ensemble

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@Article{imamura:2003:GPEM,
  author =       "Kosuke Imamura and Terence Soule and 
                 Robert B. Heckendorn and James A. Foster",
  title =        "Behavioral Diversity and a Probabilistically Optimal
                 {GP} Ensemble",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2003",
  volume =       "4",
  number =       "3",
  pages =        "235--253",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming, N-version
                 programming, classification, ensemble, diversity",
  ISSN =         "1389-2576",
  doi =          "doi:10.1023/A:1025124423708",
  abstract =     "We propose N-version Genetic Programming (NVGP) as an
                 ensemble method to enhance accuracy and reduce
                 performance fluctuation of programs produced by genetic
                 programming. Diversity is essential for forming
                 successful ensembles. NVGP quantifies behavioural
                 diversity of ensemble members and defines NVGP optimal
                 as an ensemble that has independent fault occurrences
                 among its members. We observed significant accuracy
                 improvement by NVGP optimal ensembles when applied to a
                 DNA segment classification problem.",
  notes =        "Article ID: 5141123

                 CJMP CJMPI p243 five different types of crossover
                 NVGP",
}

Genetic Programming entries for Kosuke Imamura Terence Soule Robert B Heckendorn James A Foster