Anticorrelation Measures in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Robert McKay and Hussein Abbass",
  title =        "Anticorrelation Measures in Genetic Programming",
  booktitle =    "Australasia-Japan Workshop on Intelligent and
                 Evolutionary Systems",
  pages =        "45--51",
  year =         "2001",
  editor =       "Nikola Kasabov and Peter Whigham",
  address =      "University of Otago, Dunedin, New Zealand",
  month =        "19-21st " # nov,
  keywords =     "genetic algorithms, genetic programming, committee
                 learning, fitness sharing, anti-correlation, population
  URL =          "",
  URL =          "",
  size =         "7 pages",
  abstract =     "We compare three diversity-preserving mechanisms,
                 implicit fitness sharing, negative correlation
                 learning, and a new form, root-quartic negative
                 correlation learning, on a standard genetic programming
                 problem, the 6multiplexer. On this problem,
                 root-quartic negative correlation learning
                 significantly outperforms standard negative correlation
                 learning, and marginally outperforms implicit fitness
                 sharing. We analyse the difference between standard and
                 root-quartic negative correlation learning, and provide
                 a partial explanation for the improved performance.",
  notes =        "6-MUX DCTG-GP broken Nov 2012

                 Perhaps also McKay, R I and Abbass H.A.
                 {"}Anti-correlation: A Diversity Promoting Mechanisms
                 in Ensemble Learning{"}. The Australian Journal of
                 Intelligent Information Processing Systems 7(3/4),
                 2001, Pp 139 - 149 \cite{McKay:2001:AJIIPS_2}.",

Genetic Programming entries for R I (Bob) McKay Hussein A Abbass