Fighting Program Bloat with the Fractal Complexity Measure

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

  author =       "Vili Podgorelec and Peter Kokol",
  title =        "Fighting Program Bloat with the Fractal Complexity
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2000",
  year =         "2000",
  editor =       "Riccardo Poli and Wolfgang Banzhaf and 
                 William B. Langdon and Julian F. Miller and Peter Nordin and 
                 Terence C. Fogarty",
  volume =       "1802",
  series =       "LNCS",
  pages =        "326--337",
  address =      "Edinburgh",
  publisher_address = "Berlin",
  month =        "15-16 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming: Poster",
  ISBN =         "3-540-67339-3",
  URL =          "",
  DOI =          "doi:10.1007/978-3-540-46239-2_25",
  size =         "12 pages",
  abstract =     "The problem of evolving decision programs to be used
                 for medical diagnosis prediction brought us to the
                 problem, well know to the genetic programming (GP)
                 community: the tendency of programs to grow in length
                 too fast. While searching for a solution we found out
                 that an appropriately defined fractal complexity
                 measure can differentiate between random and non-random
                 computer programs by measuring the fractal structure of
                 the computer programs. Knowing this fact, we introduced
                 the fractal measure alpha in the evaluation and
                 selection phase of the evolutionary process of decision
                 program induction, which resulted in a significant
                 program bloat reduction.",
  notes =        "EuroGP'2000, part of \cite{poli:2000:GP}",

Genetic Programming entries for Vili Podgorelec Peter Kokol