Dafo, a Multi-agent Framework for Decomposable Functions Optimization

Abstract : This paper introduces Dafo, a new multi-agent framework for evolutionary optimization relying on a competitive coevolutionary genetic algorithm, aka LCGA (Loosely Coupled Genetic Algorithm). We describe our solution, discuss of the potential advantages of using an agent based approach and present some results on a real case study: i.e. Inventory Control Parameter (ICP) optimization problem.
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Chapitre d'ouvrage
Khosla, Rajiv : Howlett, Robert : Jain, Lakhmi. Knowledge-Based Intelligent Information and Engineering Systems, Springer Berlin / Heidelberg, p 906 - 906, 2005, Lecture Notes in Computer Science, 〈10.1007/11554028_87〉
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https://hal-emse.ccsd.cnrs.fr/emse-00680394
Contributeur : Florent Breuil <>
Soumis le : lundi 19 mars 2012 - 13:31:08
Dernière modification le : mardi 22 mars 2016 - 01:16:55

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Gregoire Danoy, Pascal Bouvry, Olivier Boissier. Dafo, a Multi-agent Framework for Decomposable Functions Optimization. Khosla, Rajiv : Howlett, Robert : Jain, Lakhmi. Knowledge-Based Intelligent Information and Engineering Systems, Springer Berlin / Heidelberg, p 906 - 906, 2005, Lecture Notes in Computer Science, 〈10.1007/11554028_87〉. 〈emse-00680394〉

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