Sensible Initialisation in Chorus

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Conor Ryan and R. Muhammad Atif Azad",
  title =        "Sensible Initialisation in Chorus",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2003",
  year =         "2003",
  editor =       "Conor Ryan and Terence Soule and Maarten Keijzer and 
                 Edward Tsang and Riccardo Poli and Ernesto Costa",
  volume =       "2610",
  series =       "LNCS",
  pages =        "394--403",
  address =      "Essex",
  publisher_address = "Berlin",
  month =        "14-16 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution: Poster",
  ISBN =         "3-540-00971-X",
  URL =          "",
  DOI =          "doi:10.1007/3-540-36599-0_37",
  abstract =     "One of the key characteristics of Evolutionary
                 Algorithms is the manner in which solutions are evolved
                 from a primordial soup. The way this soup, or initial
                 generation, is created can have major implications for
                 the eventual quality of the search, as, if there is not
                 enough diversity, the population may become stuck on a
                 local optimum.

                 This paper reports an initial investigation using a
                 position independent evolutionary algorithm, Chorus,
                 where the usual random initialisation has been compared
                 to an approach modelled on the GP ramped half and half
                 method. Three standard benchmark problems have been
                 chosen from the GP literature for this study. It is
                 shown that the new initialisation method, termed
                 sensible initialisation maintains populations with
                 higher average fitness especially earlier on in
                 evolution than with random initialisation. Only one of
                 the benchmarks fails to show an improvement in a
                 probability of success measure, and we demonstrate that
                 this is more likely a symptom of issues with that
                 benchmark than with the idea of sensible

                 Performance seems to be unaffected by the different
                 derivation tree depths used, and having a wider pool of
                 individuals, regardless of their average size, seems
                 enough to improve the performance of the system.",
  notes =        "EuroGP'2003 held in conjunction with EvoWorkshops

Genetic Programming entries for Conor Ryan R Muhammad Atif Azad