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Préserver la confidentialité pour l'algorithme Generalized Distributed Breakout

Abstract : Privacy has traditionally been a major motivation of distributed problem solving. In this paper, we focus on privacy issues when solving Distributed Constraint Optimization Problems (DCOPs). Recently, Okamoto, Zivan et Nahon promoted the Generalized Distributed Breakout Algorithm (GDBA) as a very efficient heuristic strategy to find good solutions to DCOPs. We study how GDBA behaves when solving Utilitarian DCOPs, where utilitarian agents want to reach an agreement while reducing the privacy loss. We show that GDBA can be improved to allow for extensive handling of constraint privacy, and reduce domain privacy loss by a factor 2~3 with no significant impact on the quality of the solution
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Contributor : Mylène Delrue Connect in order to contact the contributor
Submitted on : Wednesday, January 12, 2022 - 11:53:54 AM
Last modification on : Wednesday, January 19, 2022 - 8:44:08 AM


  • HAL Id : hal-03522784, version 1



Julien Vion, René Mandiau, Sylvain Piechowiak, Marius Silaghi. Préserver la confidentialité pour l'algorithme Generalized Distributed Breakout. Actes des 15e Journées Francophones de Programmation par Contraintes (JFPC 2019), Jun 2019, Albi, France. pp.7-16. ⟨hal-03522784⟩



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