Genetic Programming on GPGPU cards using EASEA

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@InCollection{Maitre:2013:ecgpu,
  author =       "Ogier Maitre",
  title =        "Genetic Programming on GPGPU cards using EASEA",
  booktitle =    "Massively Parallel Evolutionary Computation on
                 {GPGPUs}",
  publisher =    "Springer",
  year =         "2013",
  editor =       "Shigeyoshi Tsutsui and Pierre Collet",
  series =       "Natural Computing Series",
  chapter =      "11",
  pages =        "227--248",
  keywords =     "genetic algorithms, genetic programming, GPU",
  isbn13 =       "978-3-642-37958-1",
  URL =          "http://www.springer.com/computer/ai/book/978-3-642-37958-1",
  DOI =          "doi:10.1007/978-3-642-37959-8_11",
  abstract =     "Genetic programming is one of the most powerful
                 evolutionary paradigms because it allows us to optimise
                 not only the parameter space but also the structure of
                 a solution. The search space explored by genetic
                 programming is therefore huge and necessitates a very
                 large computing power which is exactly what GPGPUs can
                 provide. This chapter will show how Koza-like
                 tree-based genetic programming can be efficiently
                 ported onto GPGPU processors.",
}

Genetic Programming entries for Ogier Maitre

Citations