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Sylvain Piechowiak
Researcher at University of Valenciennes and Hainaut-Cambresis
Publications - 60
Citations - 588
Sylvain Piechowiak is an academic researcher from University of Valenciennes and Hainaut-Cambresis. The author has contributed to research in topics: Constraint satisfaction problem & Bayesian network. The author has an hindex of 12, co-authored 60 publications receiving 530 citations. Previous affiliations of Sylvain Piechowiak include Centre national de la recherche scientifique & university of lille.
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A behavioral multi-agent model for road traffic simulation
TL;DR: This article proposes a multi-agent behavioral model based on the opportunistic individual behaviors that describe the norm violation and the anticipatory individual abilities of simulated drivers that allow critical situations to be detected that has been validated for different traffic scenarios.
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An explication of uncertain evidence in Bayesian networks: likelihood evidence and probabilistic evidence
TL;DR: A systematized presentation and a terminology for observations in a Bayesian network focusing on the three main concepts of uncertain evidence, namely likelihood evidence and fixed and not-fixed probabilistic evidence, using a review of previous literature.
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Anticipation based on constraint processing in a multi-agent context
TL;DR: This article proposes to use constraint processing to formalize preventive anticipation in the context of multi-agent coordination, particularly preventive anticipation which consists of anticipating undesirable future situations in order to avoid them.
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Human-reliability analysis of cooperative redundancy to support diagnosis
TL;DR: A human reliability analysis method of cooperative redundancy on which a diagnosis function is realized jointly by interacting human and automated controllers and takes into account two types of constraints: constraints based on human behavior and constraints regarding the system being diagnosed.
Proceedings Article
Dealing with Multi-Agent Coordination by Anticipation: Application to the Traffic Simulation at Junctions.
TL;DR: This article details the proposition of a model actions selection by anticipation within the framework of a traffic simulation application and shows its relevance for critical situations such as traffic jam in crossroad.