Characterizing Diversity in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Bart Wyns and Peter {De Bruyne} and Luc Boullart",
  title =        "Characterizing Diversity in Genetic Programming",
  editor =       "Pierre Collet and Marco Tomassini and Marc Ebner and 
                 Steven Gustafson and Anik\'o Ek\'art",
  booktitle =    "Proceedings of the 9th European Conference on Genetic
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "3905",
  year =         "2006",
  address =      "Budapest, Hungary",
  month =        "10 - 12 " # apr,
  organisation = "EvoNet",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-33143-3",
  pages =        "250--259",
  DOI =          "doi:10.1007/11729976_22",
  bibsource =    "DBLP,",
  abstract =     "In many evolutionary algorithms candidate solutions
                 run the risk of getting stuck in local optima after a
                 few generations of optimisation. In this paper two
                 improved approaches to measure population diversity are
                 proposed and validated using two traditional test
                 problems in genetic programming literature. Code growth
                 gave rise to improve pseudo-isomorph measures by
                 eliminating non-functional code using an expression
                 simplifier. Also, Rosca's entropy to measure
                 behavioural diversity is updated to cope with problems
                 producing a more continuous fitness value. Results show
                 a relevant improvement with regard to the original
                 diversity measures.",
  notes =        "Part of \cite{collet:2006:GP} EuroGP'2006 held in
                 conjunction with EvoCOP2006 and EvoWorkshops2006",

Genetic Programming entries for Bart Wyns Peter De Bruyne Luc Boullart