Modeling an agrifood industrial process using cooperative coevolution Algorithms

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

@TechReport{inria-00381681,
  title =        "Modeling an agrifood industrial process using
                 cooperative coevolution Algorithms",
  author =       "Olivier Barriere and Evelyne Lutton and 
                 Pierre-Henri Wuillemin and Cedric Baudrit and Mariette Sicard and 
                 Bruno Pinaud and Nathalie Perrot",
  institution =  "INRIA",
  year =         "2009",
  number =       "inria-00381681, version 1",
  address =      "Parc Orsay, France",
  month =        "6 " # may,
  keywords =     "genetic algorithms, genetic programming, Parisian,
                 Computer Science, Artificial Intelligence, Life
                 Sciences/Food and Nutrition, Agrifood, Cheese ripening,
                 Cooperative coevolution, Parisian approach, Bayesian
                 Network",
  URL =          "http://hal.inria.fr/inria-00381681/en/",
  URL =          "http://hal.inria.fr/docs/00/38/16/81/PDF/RR2008.pdf",
  bibsource =    "OAI-PMH server at oai.archives-ouvertes.fr",
  identifier =   "HAL:inria-00381681, version 1",
  language =     "EN",
  oai =          "oai:hal.archives-ouvertes.fr:inria-00381681_v1",
  abstract =     "This report presents two experiments related to the
                 modeling of an industrial agrifood process using
                 evolutionary techniques. Experiments have been focused
                 on a specific problem which is the modeling of a
                 Camembert-cheese ripening process. Two elated complex
                 optimisation problems have been considered: -- a
                 deterministic modeling problem, the phase prediction
                 problem, for which a search for a closed form tree
                 expression has been performed using genetic programming
                 (GP), -- a Bayesian network structure estimation
                 problem, considered as a two-stage problem, i.e.
                 searching first for an approximation of an independence
                 model using EA, and then deducing, via a deterministic
                 algorithm, a Bayesian network which represents the
                 equivalence class of the independence model found at
                 the first stage. In both of these problems,
                 cooperative-coevolution techniques (also called
                 ``Parisian'' approaches) have been proved successful.
                 These approaches actually allow to represent the
                 searched solution as an aggregation of several
                 individuals (or even as a whole population), as each
                 individual only bears a part of the searched solution.
                 This scheme allows to use the artificial Darwinism
                 principles in a more economic way, and the gain in
                 terms of robustness and efficiency is important.",
  size =         "51 pages",
}

Genetic Programming entries for Olivier Barriere Evelyne Lutton Pierre-Henri Wuillemin Cedric Baudrit Mariette Sicard Bruno Pinaud Nathalie Perrot

Citations