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Cooperative coevolution for agrifood process modeling

Olivier Barrière 1, * Evelyne Lutton 2 Pierre-Henri Wuillemin 3 Cédric Baudrit 4 Mariette Sicard 4 Nathalie Perrot 4
* Corresponding author
2 AVIZ - Analysis and Visualization
LRI - Laboratoire de Recherche en Informatique, Inria Saclay - Ile de France
3 DECISION
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : On the contrary to classical schemes of evolutionary optimisations algorithms, single population Cooperative Co-evolution techniques (CCEAs, also called "Parisian" approaches) make it possible to represent the evolved solution as an aggregation of several individuals (or even as a whole population). In other words, each individual represents only a part of the solution. This scheme allows simulating the principles of Darwinian evolution in a more economic way, which results in gain in robustness and efficiency. The counterpart however is a more complex design phase. In this chapter, we detail the design of efficient CCEAs schemes on two applications related to the modeling of an industrial agri-food process. The experiments correspond to complex optimisations encountered in the modeling of a Camembert-cheese ripening process. Two problems are considered: A deterministic modeling problem, phase prediction, for which a search for a closed form tree expression is performed using genetic programming (GP). A Bayesian network structure estimation problem. The novelty of the proposed approach is based on the use of a two step process based on an intermediate representation called independence model. The search for an independence model is formulated as a complex optimisation problem, for which the CCEA scheme is particularly well suited. A Bayesian network is finally deduced using a deterministic algorithm, as a representative of the equivalence class figured by the independence model.
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Olivier Barrière, Evelyne Lutton, Pierre-Henri Wuillemin, Cédric Baudrit, Mariette Sicard, et al.. Cooperative coevolution for agrifood process modeling. EVOLVE 2011 International Workshop, May 2011, Bourglinster, Luxembourg. pp.247-287, ⟨10.1007/978-3-642-32726-1_7⟩. ⟨hal-02746946⟩

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