SMCGP2: finding algorithms that approximate numerical constants using quaternions and complex numbers

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "Simon Harding and Julian F. Miller and 
                 Wolfgang Banzhaf",
  title =        "SMCGP2: finding algorithms that approximate numerical
                 constants using quaternions and complex numbers",
  booktitle =    "GECCO '11: Proceedings of the 13th annual conference
                 companion 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 =       "978-1-4503-0690-4",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming: Poster",
  pages =        "197--198",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Dublin, Ireland",
  DOI =          "doi:10.1145/2001858.2001968",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Self Modifying Cartesian Genetic Programming 2
                 (SMCGP2) 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 a number of computational problems. Here, we apply
                 the new SMCGP technique to find mathematical
                 relationships between well known mathematical constants
                 (i.e. pi, e, phi, omega etc) using a variety of
                 functions sets. Some of formulae obtained are
                 distinctly unusual and may be unknown in mathematics.",
  notes =        "Also known as \cite{2001968} Distributed on CD-ROM at

                 ACM Order Number 910112.",

Genetic Programming entries for Simon Harding Julian F Miller Wolfgang Banzhaf