MDL-Based Fitness Functions for Learning Parsimonious Programs

Created by W.Langdon from gp-bibliography.bib Revision:1.4020

  author =       "Byoung-Tak Zhang and Heinz M{\"u}hlenbein",
  title =        "MDL-Based Fitness Functions for Learning Parsimonious
  booktitle =    "Working Notes for the AAAI Symposium on Genetic
  year =         "1995",
  editor =       "E. V. Siegel and J. R. Koza",
  pages =        "122--126",
  address =      "MIT, Cambridge, MA, USA",
  publisher_address = "445 Burgess Drive, Menlo Park, CA 94025, USA",
  month =        "10--12 " # nov,
  publisher =    "AAAI",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  URL =          "",
  size =         "5 pages",
  abstract =     "In this paper we use a Bayesian model-comparison
                 method to develop a framework in which a class of
                 fitness measures is introduced for dealing with
                 problems of parsimony based on the minimum description
                 length (MDL) principle (Rissanen 1986). We then
                 describe an adaptive technique for putting this fitness
                 function into practice.",
  notes =        "AAAI-95f GP. Part of \cite{siegel:1995:aaai-fgp} {\em
                 Telephone:} 415-328-3123 {\em Fax:} 415-321-4457 {\em
                 email} {\em URL:}",

Genetic Programming entries for Byoung-Tak Zhang Heinz Muhlenbein