Semantic Methods in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  title =        "Semantic Methods in Genetic Programming",
  year =         "2014",
  editor =       "Colin Johnson and Krzysztof Krawiec and 
                 Alberto Moraglio and Michael O'Neill",
  address =      "Ljubljana, Slovenia",
  month =        "13 " # sep,
  note =         "Workshop at Parallel Problem Solving from Nature 2014
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  abstract =     "Genetic programming (GP), the application of
                 evolutionary computing techniques to the creation of
                 computer programs, has been a key topic in
                 computational intelligence in the last couple of
                 decades. In the last few years a rising topic in GP has
                 been the use of semantic methods. The aim of this is to
                 provide a way of exploring the input-output behaviour
                 of programs, which is ultimately what matters for
                 problem solving. This contrasts with much previous work
                 in GP, where operators transform the program code and
                 the effect on program behaviour is indirect. This new
                 approach has produced substantially better results on a
                 number of problems, both benchmark problems and
                 real-world applications in areas such as pharmacy; and,
                 has been grounded in a body of theory, which also
                 informs algorithm design. All aspects of research
                 related to Semantic Methods in Genetic Programming will
                 be considered, including both theoretical and empirical
  notes =        "Special issue in Genetic Programming and Evolvable
                 Machines March 2016, Volume 17, Issue 1,

                 SMGP 2014",

Genetic Programming entries for Colin G Johnson Krzysztof Krawiec Alberto Moraglio Michael O'Neill