Explicit Control of Diversity and Effective Variation Distance in Linear Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  title =        "Explicit Control of Diversity and Effective Variation
                 Distance in Linear Genetic Programming",
  author =       "Markus Brameier and Wolfgang Banzhaf",
  year =         "2002",
  month =        feb # "~25",
  citeseer-isreferencedby = "oai:CiteSeerPSU:92442;
  citeseer-references = "oai:CiteSeerPSU:266665; oai:CiteSeerPSU:271953;
                 oai:CiteSeerPSU:270103; oai:CiteSeerPSU:61421;
                 oai:CiteSeerPSU:440305; oai:CiteSeerPSU:32228;
                 oai:CiteSeerPSU:212034; oai:CiteSeerPSU:61877",
  annote =       "The Pennsylvania State University CiteSeer Archives",
  language =     "en",
  language =     "ENG",
  oai =          "oai:eldorado:0x0004162d",
  oai =          "oai:CiteSeerPSU:552561",
  rights =       "unrestricted",
  URL =          "http://eldorado.uni-dortmund.de/0x81d98002_0x0004162d",
  URL =          "http://eldorado.uni-dortmund.de:8080/bitstream/2003/5419/1/123.pdf",
  URL =          "http://citeseer.ist.psu.edu/552561.html",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/download?doi=",
  institution =  "Dortmund University",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "We investigate structural and semantic distance
                 metrics for linear genetic programs. Causal connections
                 between changes of the genotype and fitness changes
                 form a necessary condition for analyzing structural
                 differences between genetic programs and for the two
                 major objectives of this paper: (i) Distance
                 information betweenin-dividuals is used to control
                 structural diversity of population individuals actively
                 by a two-level tournament selection. (ii) Variation
                 distance of effective code is controlled for different
                 genetic operators - including an effective variant of
                 the mutation operator that works closely with the used
                 distance metric. Numerous experiments have been
                 performed for a regression problem, a classification
                 task, and a Boolean problem",
  notes =        "see also \cite{brameier:2002:EuroGP} 123.pdf crashes
                 SUSE 10.0 KDE Konqueror 3.4.2b, Nov 2006",
  size =         "25 pages",

Genetic Programming entries for Markus Brameier Wolfgang Banzhaf