Privacy stochastic games in distributed constraint reasoning

Julien Savaux, Julien Vion, Sylvain Piechowiak, René Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Shakre Elmane, Marius Silaghi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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 languageEnglish
Pages (from-to)691-715
Number of pages25
JournalAnnals of Mathematics and Artificial Intelligence
Issue number7
Publication statusPublished - Jul 1 2020

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Applied Mathematics


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