SMCGP2: self modifying cartesian genetic programming in two dimensions

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Simon Harding and Julian F. Miller and 
                 Wolfgang Banzhaf",
  title =        "SMCGP2: self modifying cartesian genetic programming
                 in two dimensions",
  booktitle =    "GECCO '11: Proceedings of the 13th annual conference
                 on Genetic and evolutionary computation",
  year =         "2011",
  editor =       "Natalio Krasnogor and Pier Luca Lanzi and 
                 Andries Engelbrecht and David Pelta and Carlos Gershenson and 
                 Giovanni Squillero and Alex Freitas and 
                 Marylyn Ritchie and Mike Preuss and Christian Gagne and 
                 Yew Soon Ong and Guenther Raidl and Marcus Gallager and 
                 Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and 
                 Nikolaus Hansen and Silja Meyer-Nieberg and 
                 Jim Smith and Gus Eiben and Ester Bernado-Mansilla and 
                 Will Browne and Lee Spector and Tina Yu and Jeff Clune and 
                 Greg Hornby and Man-Leung Wong and Pierre Collet and 
                 Steve Gustafson and Jean-Paul Watson and 
                 Moshe Sipper and Simon Poulding and Gabriela Ochoa and 
                 Marc Schoenauer and Carsten Witt and Anne Auger",
  isbn13 =       "978-1-4503-0557-0",
  pages =        "1491--1498",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming, developmental systems",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Dublin, Ireland",
  URL =          "",
  DOI =          "doi:10.1145/2001576.2001777",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  size =         "8 pages",
  abstract =     "Self Modifying Cartesian Genetic Programming is a
                 general purpose, graph-based, developmental form of
                 Cartesian Genetic Programming. Using a combination of
                 computational functions and special functions that can
                 modify the phenotype at runtime, it has been employed
                 to find general solutions to certain Boolean circuits
                 and mathematical problems. In the present work, a new
                 version, of SMCGP is proposed and demonstrated.
                 Compared to the original SMCGP both the representation
                 and the function set have been simplified. However, the
                 new representation is also two-dimensional and it
                 allows evolution and development to have more ways to
                 solve a given problem. Under most situations we show
                 that the new method makes the evolution of solutions to
                 even parity and binary addition faster than with
                 previous version of SMCGP.",
  notes =        "hill climbing. General solution to parity.

                 Also known as \cite{2001777} GECCO-2011 A joint meeting
                 of the twentieth international conference on genetic
                 algorithms (ICGA-2011) and the sixteenth annual genetic
                 programming conference (GP-2011)",

Genetic Programming entries for Simon Harding Julian F Miller Wolfgang Banzhaf