MT-CGP: mixed type cartesian genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Harding:2012:GECCO,
  author =       "Simon Harding and Vincent Graziano and 
                 Juergen Leitner and Juergen Schmidhuber",
  title =        "MT-CGP: mixed type cartesian genetic programming",
  booktitle =    "GECCO '12: Proceedings of the fourteenth international
                 conference on Genetic and evolutionary computation
                 conference",
  year =         "2012",
  editor =       "Terry Soule and Anne Auger and Jason Moore and 
                 David Pelta and Christine Solnon and Mike Preuss and 
                 Alan Dorin and Yew-Soon Ong and Christian Blum and 
                 Dario Landa Silva and Frank Neumann and Tina Yu and 
                 Aniko Ekart and Will Browne and Tim Kovacs and 
                 Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and 
                 Giovanni Squillero and Nicolas Bredeche and 
                 Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and 
                 Martin Pelikan and Silja Meyer-Nienberg and 
                 Christian Igel and Greg Hornby and Rene Doursat and 
                 Steve Gustafson and Gustavo Olague and Shin Yoo and 
                 John Clark and Gabriela Ochoa and Gisele Pappa and 
                 Fernando Lobo and Daniel Tauritz and Jurgen Branke and 
                 Kalyanmoy Deb",
  isbn13 =       "978-1-4503-1177-9",
  pages =        "751--758",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Philadelphia, Pennsylvania, USA",
  DOI =          "doi:10.1145/2330163.2330268",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "The majority of genetic programming implementations
                 build expressions that only use a single data type.
                 This is in contrast to human engineered programs that
                 typically make use of multiple data types, as this
                 provides the ability to express solutions in a more
                 natural fashion. In this paper, we present a version of
                 Cartesian Genetic Programming that handles multiple
                 data types. We demonstrate that this allows evolution
                 to quickly find competitive, compact, and human
                 readable solutions on multiple classification tasks.",
  notes =        "Also known as \cite{2330268} GECCO-2012 A joint
                 meeting of the twenty first international conference on
                 genetic algorithms (ICGA-2012) and the seventeenth
                 annual genetic programming conference (GP-2012)",
}

Genetic Programming entries for Simon Harding Vincent Graziano Juergen Leitner Jurgen Schmidhuber

Citations