Deriving genetic programming fitness properties by static analysis

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

@InProceedings{johnson:2002:EuroGP,
  title =        "Deriving genetic programming fitness properties by
                 static analysis",
  author =       "Colin G. Johnson",
  editor =       "James A. Foster and Evelyne Lutton and 
                 Julian Miller and Conor Ryan and Andrea G. B. Tettamanzi",
  booktitle =    "Genetic Programming, Proceedings of the 5th European
                 Conference, EuroGP 2002",
  volume =       "2278",
  series =       "LNCS",
  pages =        "298--307",
  publisher =    "Springer-Verlag",
  address =      "Kinsale, Ireland",
  publisher_address = "Berlin",
  month =        "3-5 " # apr,
  year =         "2002",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  ISBN =         "3-540-43378-3",
  URL =          "http://www.cs.kent.ac.uk/pubs/2002/1351/content.ps",
  URL =          "http://www.cs.ukc.ac.uk/pubs/2002/1351",
  DOI =          "doi:10.1007/3-540-45984-7_29",
  abstract =     "The aim of this paper is to introduce the idea of
                 using static analysis of computer programs as a way of
                 measuring fitness in genetic programming. Such
                 techniques extract information about the programs
                 without explicitly running them, and in particular they
                 infer properties which hold across the whole of the
                 input space of a program. This can be applied to
                 measure fitness, and has a number of advantages over
                 measuring fitness by running members of the population
                 on test cases. The most important advantage is that if
                 a solution is found then it is possible to formally
                 trust that solution to be correct across all inputs.
                 This paper introduces these ideas, discusses various
                 ways in which they could be applied, discusses the type
                 of problems for which they are appropriate, and ends by
                 giving a simple test example and some questions for
                 future research.",
  notes =        "EuroGP'2002, part of \cite{lutton:2002:GP}",
}

Genetic Programming entries for Colin G Johnson

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