A Peer-to-Peer Approach to Genetic Programming

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

@InProceedings{laredo:2011:EuroGP,
  author =       "Juan Luis Jim\'enez Laredo and 
                 Daniel {Lombra\~na Gonz\'alez} and Francisco {Fern\'andez de Vega} and 
                 Maribel Garc\'ia Arenas and 
                 Juan Juli\'an {Merelo Guerv\'os}",
  title =        "A Peer-to-Peer Approach to Genetic Programming",
  booktitle =    "Proceedings of the 14th European Conference on Genetic
                 Programming, EuroGP 2011",
  year =         "2011",
  month =        "27-29 " # apr,
  editor =       "Sara Silva and James A. Foster and Miguel Nicolau and 
                 Mario Giacobini and Penousal Machado",
  series =       "LNCS",
  volume =       "6621",
  publisher =    "Springer Verlag",
  address =      "Turin, Italy",
  pages =        "108--117",
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-20406-7",
  DOI =          "doi:10.1007/978-3-642-20407-4_10",
  abstract =     "This paper proposes a fine-grained parallelization of
                 the Genetic Programming paradigm (GP) using the
                 Evolvable Agent model evagbp The algorithm is
                 decentralised in order to take full-advantage of a
                 massively parallel Peer-to-Peer infrastructure. In this
                 context, GP is particularly demanding due to its high
                 requirements of computational power. To assess the
                 viability of the approach, the evag model has been
                 empirically analysed in a simulated Peer-to-Peer
                 environment where experiments were conducted on two
                 well-known GP problems. Results show that the spatially
                 structured nature of the algorithm is able to yield a
                 good quality in the solutions. Additionally,
                 parallelisation improves times to solution by several
                 orders of magnitude.",
  notes =        "See also \cite{Laredo:thesis}.

                 Newscast P2P protocol from EU DREAM project. Agents are
                 lightweight computing threads. Possibly many threads
                 per node. Emigration within distributed GP population
                 integrated with stochastic establishment of directly
                 links in P2P application layer protocol.

                 Part of \cite{Silva:2011:GP} EuroGP'2011 held in
                 conjunction with EvoCOP2011 EvoBIO2011 and
                 EvoApplications2011",
}

Genetic Programming entries for Juan L J Laredo Daniel Lombrana Gonzalez Rodriguez Francisco Fernandez de Vega Maribel Garcia Arenas Juan Julian Merelo

Citations