Skip to Main content Skip to Navigation
Journal articles

Privacy stochastic games in distributed constraint reasoning.

Abstract : In this work, we approach the issue of privacy in distributed constraint reasoning by studying how agents compromise solution quality for preserving privacy, using utility and game theory. We propose a utilitarian definition of privacy in the context of distributed constraint reasoning, detail its different implications, and present a model and solvers, as well as their properties. We then show how important steps in a distributed constraint optimization with privacy requirements can be modeled as a planning problem, and more specifically as a stochastic game. We present experiments validating the interest of our approach, according to several criteria.
Document type :
Journal articles
Complete list of metadata

https://hal-uphf.archives-ouvertes.fr/hal-03396820
Contributor : Mylène Delrue Connect in order to contact the contributor
Submitted on : Friday, October 22, 2021 - 5:44:35 PM
Last modification on : Wednesday, November 3, 2021 - 6:13:38 AM

Identifiers

Collections

Citation

Julien Savaux, Julien Vion, Sylvain Piechowiak, René Mandiau, Toshihiro Matsui, et al.. Privacy stochastic games in distributed constraint reasoning.. Annals of Mathematics and Artificial Intelligence, Springer Verlag, 2020, 88 (7), pp.691-715. ⟨10.1007/s10472-019-09628-8⟩. ⟨hal-03396820⟩

Share

Metrics

Record views

11