Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Hormoz Shahrzad and Babak Hodjat",
  title =        "Tackling the {Boolean} Multiplexer Function Using a
                 Highly Distributed Genetic Programming System",
  booktitle =    "Genetic Programming Theory and Practice XII",
  year =         "2014",
  editor =       "Rick Riolo and William P. Worzel and Mark Kotanchek",
  series =       "Genetic and Evolutionary Computation",
  pages =        "167--179",
  address =      "Ann Arbor, USA",
  month =        "8-10 " # may,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-16029-0",
  DOI =          "doi:10.1007/978-3-319-16030-6_10",
  abstract =     "We demonstrate the effectiveness and power of the
                 distributed GP platform, EC-Star, by comparing the
                 computational power needed for solving an
                 11-multiplexer function, both on a single machine using
                 a full-fitness evaluation method, as well as using
                 distributed, age-layered, partial-fitness evaluations
                 and a Pitts-style representation. We study the impact
                 of age-layering and show how the system scales with
                 distribution and tends towards smaller solutions. We
                 also consider the effect of pool size and the choice of
                 fitness function on convergence and total
  notes =        "http://cscs.umich.edu/gptp-workshops/

                 Part of \cite{Riolo:2014:GPTP} published after the
                 workshop in 2015",

Genetic Programming entries for Hormoz Shahrzad Babak Hodjat