Evolution of Force-Generating Equations for PSO using GP

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

  author =       "Cecilia {Di Chio} and Riccardo Poli and 
                 William B. Langdon",
  title =        "Evolution of Force-Generating Equations for PSO using
  booktitle =    "AI*IA Workshop on Evolutionary Computation,
                 Evoluzionistico GSICE05",
  year =         "2005",
  editor =       "Sara Manzoni and Matteo Palmonari and Fabio Sartori",
  address =      "University of Milan Bicocca, Italy",
  month =        "20 " # sep,
  keywords =     "genetic algorithms, genetic programming, XPS",
  ISBN =         "88-900910-0-2",
  URL =          "http://www.cs.essex.ac.uk/staff/poli/papers/gsice2005.pdf",
  size =         "10 pages",
  abstract =     "We extend our previous research on evolving the
                 physical forces which control particle swarms by
                 considering additional ingredients, such as the
                 velocity of the neighbourhood best and time, and
                 different neighbourhood topologies, namely the global
                 and local ones. We test the evolved extended PSOs
                 (XPSOs) on various classes of benchmark problems.

                 We show that evolutionary computation, and in
                 particular genetic programming (GP), can automatically
                 generate new PSO algorithms that outperform standard
                 PSOs designed by people as well as some previously
                 evolved ones.",
  notes =        "http://www.ce.unipr.it/people/cagnoni/gsice2005/gsice-eng.pdf
                 Workshop proceedings on CD-ROM only. Workshop held
                 in-conjunction with the IX Congress of the Italian
                 Association for Artificial Intelligence. In

                 Winner of Best Paper Award",

Genetic Programming entries for Cecilia Di Chio Riccardo Poli William B Langdon