A parallel implementation of genetic programming that achieves super-linear performance

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "David Andre and John R. Koza",
  title =        "A parallel implementation of genetic programming that
                 achieves super-linear performance",
  booktitle =    "Proceedings of the International Conference on
                 Parallel and Distributed Processing Techniques and
  year =         "1996",
  editor =       "Hamid R. Arabnia",
  volume =       "III",
  pages =        "1163--1174",
  address =      "Sunnyvale",
  month =        "9-11 " # aug,
  publisher =    "CSREA",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.genetic-programming.com/jkpdf/pdpta1996.pdf",
  size =         "13 pages",
  abstract =     "This paper describes the successful parallel
                 implementation of genetic programming on a network of
                 processing nodes using the transputer architecture.
                 With this approach, researchers of genetic algorithms
                 and genetic programming can acquire computing power
                 that is intermediate between the power of currently
                 available workstations and that of supercomputers at
                 intermediate cost. This approach is illustrated by a
                 comparison of the computational effort required to
                 solve a benchmark problem. Because of the decoupled
                 character of genetic programming, our approach achieved
                 a nearly linear speed up from parallelization. In
                 addition, for the best choice of parameters tested, the
                 use of subpopulations delivered a super linear speed-up
                 in terms of the ability of the algorithm to solve the
                 problem. Several examples are also presented where the
                 parallel genetic programming system evolved solutions
                 that are competitive with human performance on the same
  notes =        "Awarded Best Paper Award PDPTA'96",

Genetic Programming entries for David Andre John Koza