Cartesian Genetic Programming on the GPU

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InCollection{Harding:2013:ecgpu,
  author =       "Simon Harding and Julian F. Miller",
  title =        "Cartesian Genetic Programming on the GPU",
  booktitle =    "Massively Parallel Evolutionary Computation on
                 {GPGPUs}",
  publisher =    "Springer",
  year =         "2013",
  editor =       "Shigeyoshi Tsutsui and Pierre Collet",
  series =       "Natural Computing Series",
  chapter =      "12",
  pages =        "249--266",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 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_12",
  abstract =     "Cartesian Genetic Programming is a form of Genetic
                 Programming based on evolving graph structures. It has
                 a fixed genotype length and a genotype phenotype
                 mapping that introduces neutrality into the
                 representation. It has been used for many applications
                 and was one of the first Genetic Programming techniques
                 to be implemented on the GPU. In this chapter, we
                 describe the representation in detail and discuss
                 various GPU implementations of it. Later in the
                 chapter, we discuss a recent implementation based on
                 the GPU.net framework.",
}

Genetic Programming entries for Simon Harding Julian F Miller

Citations