Visualising Evolutionary Search Spaces

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@Article{McDermott:2014:sigevolution,
  author =       "James McDermott",
  title =        "Visualising Evolutionary Search Spaces",
  journal =      "SIGEvolution newsletter of the ACM Special Interest
                 Group on Genetic and Evolutionary Computation",
  year =         "2014",
  volume =       "7",
  number =       "1",
  pages =        "2--10",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1931-8499",
  acmid =        "2661736",
  publisher =    "ACM",
  URL =          "http://www.sigevolution.org/issues/SIGEVOlution0701.pdf",
  DOI =          "doi:10.1145/2661735.2661736",
  size =         "9 pages",
  abstract =     "Understanding the structure of search spaces can help
                 us to design better search algorithms, and it is
                 natural to try to understand search spaces by
                 visualising them. For typical evolutionary search
                 spaces, like the space of genetic programming trees,
                 visualising them directly is impossible, because of
                 their large dimensionality. However, we can use the
                 idea of distances on search spaces to project them into
                 two dimensions, expose their structure, and obtain
                 useful and attractive visualisations.",
}

Genetic Programming entries for James McDermott

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