Evolving distributed algorithms with genetic programming: election

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

  author =       "Thomas Weise and Michael Zapf",
  title =        "Evolving distributed algorithms with genetic
                 programming: election",
  booktitle =    "GEC '09: Proceedings of the first ACM/SIGEVO Summit on
                 Genetic and Evolutionary Computation",
  year =         "2009",
  editor =       "Lihong Xu and Erik D. Goodman and Guoliang Chen and 
                 Darrell Whitley and Yongsheng Ding",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  pages =        "577--584",
  address =      "Shanghai, China",
  organisation = "SigEvo",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=",
  URL =          "http://www.it-weise.de/documents/files/WZ2009EDAWGPE.pdf",
  DOI =          "doi:10.1145/1543834.1543913",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        jun # " 12-14",
  isbn13 =       "978-1-60558-326-6",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "In this paper, we present a detailed analysis of the
                 application of Genetic Programming to the evolution of
                 distributed algorithms. This research field has many
                 facets which make it especially difficult. These
                 aspects are discussed and countermeasures are provided.
                 Six different Genetic Programming approaches (SGP,
                 eSGP, LGP, RBGP, eRBGP, and Fraglets) are applied to
                 the election problem as case study using these
                 countermeasures. The results of the experiments are
                 analysed statistically and discussed thoroughly.",
  notes =        "Also known as \cite{DBLP:conf/gecco/WeiseZ09} part of

Genetic Programming entries for Thomas Weise Michael Zapf