Recurrent Cartesian Genetic Programming

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

  author =       "Andrew Turner and Julian Miller",
  title =        "Recurrent Cartesian Genetic Programming",
  booktitle =    "13th International Conference on Parallel Problem
                 Solving from Nature",
  year =         "2014",
  editor =       "Thomas Bartz-Beielstein and Juergen Branke and 
                 Bogdan Filipic and Jim Smith",
  publisher =    "Springer",
  isbn13 =       "978-3-319-10761-5",
  pages =        "476--486",
  series =       "Lecture Notes in Computer Science",
  address =      "Ljubljana, Slovenia",
  month =        "13-17 " # sep,
  volume =       "8672",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1007/978-3-319-10762-2_47",
  abstract =     "This paper formally introduces Recurrent Cartesian
                 Genetic Programming (RCGP), an extension to Cartesian
                 Genetic Programming (CGP) which allows recurrent
                 connections. The presence of recurrent connections
                 enables RCGP to be successfully applied to partially
                 observable tasks. It is found that RCGP significantly
                 outperforms CGP on two partially observable tasks:
                 artificial ant and sunspot prediction. The paper also
                 introduces a new parameter, recurrent connection
                 probability, which biases the number of recurrent
                 connections created via mutation. Suitable choices of
                 this parameter significantly improve the effectiveness
                 of RCGP.",
  notes =        "",

Genetic Programming entries for Andrew James Turner Julian F Miller