Complexity Compression and Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Nordin:1995:cce,
  author =       "Peter Nordin and Wolfgang Banzhaf",
  title =        "Complexity Compression and Evolution",
  booktitle =    "Genetic Algorithms: Proceedings of the Sixth
                 International Conference (ICGA95)",
  year =         "1995",
  editor =       "Larry J. Eshelman",
  pages =        "310--317",
  address =      "Pittsburgh, PA, USA",
  publisher_address = "San Francisco, CA, USA",
  month =        "15-19 " # jul,
  publisher =    "Morgan Kaufmann",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-55860-370-0",
  URL =          "ftp://lumpi.informatik.uni-dortmund.de/pub/biocomp/papers/icga95-1.ps.gz",
  URL =          "http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.2133",
  size =         "8 pages",
  abstract =     "Compression of information is an important concept in
                 the theory of learning. We argue for the hypothesis
                 that there is an inherent compression pressure towards
                 short, elegant and general solutions in a genetic
                 programming system and other variable length
                 evolutionary algorithms. This pressure becomes visible
                 if the size or complexity of solutions are measured
                 without non-effective code segments called introns. The
                 built in parsimony pressure effects complex fitness
                 functions crossover probability, generality, maximum
                 depth or length of solutions, explicit parsimony,
                 granularity of fitness function, initialization depth
                 or length, and modularization. Some of these effects
                 are positive and some are negative. In this work we
                 provide a basis for an analysis of these effects and
                 suggestions to overcome the negative implications in
                 order to obtain the balance needed for successful
                 evolution. An empirical investigation that supports our
                 hypothesis is also presented.",
}

Genetic Programming entries for Peter Nordin Wolfgang Banzhaf

Citations