Incorporating expert knowledge in object-oriented genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Michael Richard Medland and Kyle Robert Harrison and 
                 Beatrice Ombuki-Berman",
  title =        "Incorporating expert knowledge in object-oriented
                 genetic programming",
  booktitle =    "GECCO Comp '14: Proceedings of the 2014 conference
                 companion on Genetic and evolutionary computation
  year =         "2014",
  editor =       "Christian Igel and Dirk V. Arnold and 
                 Christian Gagne and Elena Popovici and Anne Auger and 
                 Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and 
                 Kalyanmoy Deb and Benjamin Doerr and James Foster and 
                 Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and 
                 Hitoshi Iba and Christian Jacob and Thomas Jansen and 
                 Yaochu Jin and Marouane Kessentini and 
                 Joshua D. Knowles and William B. Langdon and Pedro Larranaga and 
                 Sean Luke and Gabriel Luque and John A. W. McCall and 
                 Marco A. {Montes de Oca} and Alison Motsinger-Reif and 
                 Yew Soon Ong and Michael Palmer and 
                 Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and 
                 Guenther Ruhe and Tom Schaul and Thomas Schmickl and 
                 Bernhard Sendhoff and Kenneth O. Stanley and 
                 Thomas Stuetzle and Dirk Thierens and Julian Togelius and 
                 Carsten Witt and Christine Zarges",
  isbn13 =       "978-1-4503-2881-4",
  keywords =     "genetic algorithms, genetic programming: Poster",
  pages =        "145--146",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Vancouver, BC, Canada",
  URL =          "",
  DOI =          "doi:10.1145/2598394.2598494",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Genetic programming (GP) has proved to be successful
                 at generating programs which solve a wide variety of
                 problems. Object-oriented GP (OOGP) extends traditional
                 GP by allowing the simultaneous evolution of multiple
                 program trees, and thus multiple functions. OOGP has
                 been shown to be capable of evolving more complex
                 structures than traditional GP. However, OOGP does not
                 facilitate the incorporation of expert knowledge within
                 the resulting evolved type. This paper proposes an
                 alternative OOGP methodology which does incorporate
                 expert knowledge by the use of a user-supplied
                 partially-implemented type definition, i.e. an abstract
  notes =        "Also known as \cite{2598494} Distributed at

Genetic Programming entries for Michael Medland Kyle Robert Harrison Beatrice Ombuki-Berman