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.
| Original language | English |
|---|---|
| Journal | Annals of Mathematics and Artificial Intelligence |
| DOIs | |
| Publication status | Published - Jan 1 2019 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Applied Mathematics
Cite this
Privacy stochastic games in distributed constraint reasoning. / Savaux, Julien; Vion, Julien; Piechowiak, Sylvain; Mandiau, René; Matsui, Toshihiro; Hirayama, Katsutoshi; Yokoo, Makoto; Elmane, Shakre; Silaghi, Marius.
In: Annals of Mathematics and Artificial Intelligence, 01.01.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Privacy stochastic games in distributed constraint reasoning
AU - Savaux, Julien
AU - Vion, Julien
AU - Piechowiak, Sylvain
AU - Mandiau, René
AU - Matsui, Toshihiro
AU - Hirayama, Katsutoshi
AU - Yokoo, Makoto
AU - Elmane, Shakre
AU - Silaghi, Marius
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=85064348715&partnerID=8YFLogxK
U2 - 10.1007/s10472-019-09628-8
DO - 10.1007/s10472-019-09628-8
M3 - Article
AN - SCOPUS:85064348715
JO - Annals of Mathematics and Artificial Intelligence
JF - Annals of Mathematics and Artificial Intelligence
SN - 1012-2443
ER -