Sub-machine-code Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3332

@InCollection{poli:1999:aigp3,
  author =       "Riccardo Poli and William B. Langdon",
  title =        "Sub-machine-code Genetic Programming",
  booktitle =    "Advances in Genetic Programming 3",
  publisher =    "MIT Press",
  year =         "1999",
  editor =       "Lee Spector and William B. Langdon and 
                 Una-May O'Reilly and Peter J. Angeline",
  chapter =      "13",
  pages =        "301--323",
  address =      "Cambridge, MA, USA",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-262-19423-6",
  URL =          "http://cswww.essex.ac.uk/staff/rpoli/papers/Poli-AIGP3-1999.pdf",
  URL =          "http://www.cs.bham.ac.uk/~wbl/aigp3/ch13.pdf",
  URL =          "http://citeseer.ist.psu.edu/332925.html",
  abstract =     "Introduction Genetic Programming (GP) [Koza, 1992;
                 Koza, 1994; Banzhaf et al., 1998] is usually seen as
                 quite demanding from the computation load and memory
                 use point of view. So, over the years a number of ideas
                 on how to improve GP performance have been proposed in
                 the literature. We recall the main speedup techniques
                 published to date in Section 13.2. Some of these
                 techniques are now used in many GP implementations.
                 Thanks to this and to the fact that the power of our
                 workstations is increasing exponentially (today's CPUs
                 are now more than 10 times faster than those used in
                 early GP work), nowadays we can run 50 generations a
                 typical GP benchmark problem with a population of 500
                 individuals in perhaps ten seconds on a normal
                 workstation. Nonetheless, the demand for more and more
                 efficient implementations has not stopped. This is
                 because extensive experimental GP studies (like
                 [Langdon and Poli, 1998] or [Luke and Spector, 1998])
                 and complex applications (like [Poli, 1996]",
  notes =        "AiGP3. Machine code level parallelism. Includes
                 code.",
}

Genetic Programming entries for Riccardo Poli William B Langdon

Citations by GP GP evolved google citation