Modeling an agrifood industrial process using cooperative coevolution Algorithms
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @TechReport{inria-00381681,
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title = "Modeling an agrifood industrial process using
cooperative coevolution Algorithms",
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author = "Olivier Barriere and Evelyne Lutton and
Pierre-Henri Wuillemin and Cedric Baudrit and Mariette Sicard and
Bruno Pinaud and Nathalie Perrot",
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institution = "INRIA",
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year = "2009",
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number = "inria-00381681, version 1",
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address = "Parc Orsay, France",
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month = "6 " # may,
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keywords = "genetic algorithms, genetic programming, Parisian,
Computer Science, Artificial Intelligence, Life
Sciences/Food and Nutrition, Agrifood, Cheese ripening,
Cooperative coevolution, Parisian approach, Bayesian
Network",
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URL = "http://hal.inria.fr/inria-00381681/en/",
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URL = "http://hal.inria.fr/docs/00/38/16/81/PDF/RR2008.pdf",
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bibsource = "OAI-PMH server at oai.archives-ouvertes.fr",
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identifier = "HAL:inria-00381681, version 1",
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language = "EN",
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oai = "oai:hal.archives-ouvertes.fr:inria-00381681_v1",
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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.",
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size = "51 pages",
- }
Genetic Programming entries for
Olivier Barriere
Evelyne Lutton
Pierre-Henri Wuillemin
Cedric Baudrit
Mariette Sicard
Bruno Pinaud
Nathalie Perrot
Citations