Reducing Bloat and Promoting Diversity using Multi-Objective Methods

Created by W.Langdon from gp-bibliography.bib Revision:1.4009

@InProceedings{jong:2001:gecco,
  title =        "Reducing Bloat and Promoting Diversity using
                 Multi-Objective Methods",
  author =       "Edwin D. {de Jong} and Richard A. Watson and 
                 Jordan B. Pollack",
  pages =        "11--18",
  year =         "2001",
  publisher =    "Morgan Kaufmann",
  booktitle =    "Proceedings of the Genetic and Evolutionary
                 Computation Conference (GECCO-2001)",
  editor =       "Lee Spector and Erik D. Goodman and Annie Wu and 
                 W. B. Langdon and Hans-Michael Voigt and Mitsuo Gen and 
                 Sandip Sen and Marco Dorigo and Shahram Pezeshk and 
                 Max H. Garzon and Edmund Burke",
  address =      "San Francisco, California, USA",
  publisher_address = "San Francisco, CA 94104, USA",
  month =        "7-11 " # jul,
  keywords =     "genetic algorithms, genetic programming, code growth,
                 bloat, introns, diversity maintenance, evolutionary
                 multi-objective optimization, Pareto, optimality",
  ISBN =         "1-55860-774-9",
  URL =          "http://www.demo.cs.brandeis.edu/papers/rbpd_gecco01.pdf",
  URL =          "http://www.demo.cs.brandeis.edu/papers/rbpd_gecco01.ps.gz",
  URL =          "http://www.demo.cs.brandeis.edu/papers/long.html#rbpd_gecco01",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2001/d01.pdf",
  URL =          "http://citeseer.ist.psu.edu/440305.html",
  abstract =     "Two important problems in genetic programming (GP) are
                 its tendency to find unnecessarily large trees (bloat),
                 and the general evolutionary algorithms problem that
                 diversity in the population can be lost prematurely.
                 The prevention of these problems is frequently an
                 implicit goal of basic GP. We explore the potential of
                 techniques from multi-objective optimization to aid GP
                 by adding explicit objectives to avoid bloat and
                 promote diversity. The even 3, 4, and 5-parity problems
                 were solved efficiently compared to basic GP results
                 from the literature. Even though only non-dominated
                 individuals were selected and populations thus remained
                 extremely small, appropriate diversity was maintained.
                 The size of individuals visited during search
                 consistently remained small, and solutions of what we
                 believe to be the minimum size were found for the 3, 4,
                 and 5-parity problems.",
  notes =        "GECCO-2001 A joint meeting of the tenth International
                 Conference on Genetic Algorithms (ICGA-2001) and the
                 sixth Annual Genetic Programming Conference (GP-2001)
                 Part of \cite{spector:2001:GECCO}",
}

Genetic Programming entries for Edwin D de Jong Richard A Watson Jordan B Pollack

Citations