Analytic Solutions to Differential Equations under Graph-based Genetic Programming

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

  author =       "Tom Seaton and Gavin Brown and Julian Miller",
  title =        "Analytic Solutions to Differential Equations under
                 Graph-based Genetic Programming",
  booktitle =    "Proceedings of the 13th European Conference on Genetic
                 Programming, EuroGP 2010",
  year =         "2010",
  editor =       "Anna Isabel Esparcia-Alcazar and Aniko Ekart and 
                 Sara Silva and Stephen Dignum and A. Sima Uyar",
  volume =       "6021",
  series =       "LNCS",
  pages =        "232--243",
  address =      "Istanbul",
  month =        "7-9 " # apr,
  organisation = "EvoStar",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  isbn13 =       "978-3-642-12147-0",
  DOI =          "doi:10.1007/978-3-642-12148-7_20",
  abstract =     "Cartesian Genetic Programming (CGP) is applied to
                 solving differential equations (DE). We illustrate that
                 repeated elements in analytic solutions to DE can be
                 exploited under GP. An analysis is carried out of the
                 search space in tree and CGP frameworks, examining the
                 complexity of different DE problems. Experimental
                 results are provided against benchmark ordinary and
                 partial differential equations. A system of ordinary
                 differential equations (SODE) is solved using multiple
                 outputs from a genome. We discuss best heuristics when
                 generating DE solutions through evolutionary search.",
  notes =        "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010
                 held in conjunction with EvoCOP2010 EvoBIO2010 and

Genetic Programming entries for Tom Seaton Gavin Brown Julian F Miller