Demonstrating Constraints to Diversity with a Tunably Difficulty Problem for Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{daida:2004:dctdwatdpfgp,
  title =        "Demonstrating Constraints to Diversity with a Tunably
                 Difficulty Problem for Genetic Programming",
  author =       "Jason M. Daida and Michael E. Samples and 
                 Bryan T. Hart and Jeffry Halim and Aditya Kumar",
  pages =        "1217--1224",
  booktitle =    "Proceedings of the 2004 IEEE Congress on Evolutionary
                 Computation",
  year =         "2004",
  publisher =    "IEEE Press",
  month =        "20-23 " # jun,
  address =      "Portland, Oregon",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, Theoretical
                 Foundations of Evolutionary Computation",
  URL =          "http://sitemaker.umich.edu/daida/files/CEC04highlander.pdf",
  DOI =          "doi:10.1109/CEC.2004.1331036",
  abstract =     "This paper introduces a tunably difficult problem for
                 genetic programming (GP) that probes for an upper bound
                 to the amount of heterogeneity that can be represented
                 by a single individual. Although GP's variable-length
                 representation would suggest that there is no upper
                 bound, our results indicate otherwise. The results
                 provide insight into the dynamics that occur during the
                 course of a GP run.",
  size =         "8 pages",
  notes =        "CEC 2004 - A joint meeting of the IEEE, the EPS, and
                 the IEE.",
}

Genetic Programming entries for Jason M Daida Michael E Samples Bryan Hart Jeffry Halim Aditya Kumar

Citations