CRIL in short


Lens Computer Science Research Lab (CRIL UMR 8188) is a joint laboratory between Université d’Artois and CNRS, grouping together 50 members, including researchers, lecturers, PhD students, postdocs and administrative or technical staff.

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Artificial Intelligence Research and Applications

mots clés du CRIL

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Jean-Marie Lagniez (CRIL, CNRS - Université d’Artois)


Srdjan Vesic (CRIL, CNRS - Université d’Artois)

In this paper, we place ourselves in the Ontology Based Data Access (OBDA) setting and investigate reasoning with inconsistent existential rules knowledge bases. We use the notion of inconsistency measures on sets of facts to rank and filter repairs. We propose a generic framework to answer queries by using the best repairs and study productivity and properties of such a framework.

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Temporary Engineer and Research positions available

In the context of “CPER DATA”, CRIL is looking for a research engineer and a researcher. The positions are advertised on

Research Engineer (12 months)
Researcher (12 months)

Seminar Collective Singleton-based Consistency for Qualitative Constraint Networks: Theory and Practice

Michael Sioutis (Örebro University)

Partial singleton weak path-consistency is essential for tackling challenging fundamental reasoning problems
associated with qualitative constraints networks. Briefly put, partial singleton weak path-consistency
ensures that each base relation of each of the constraints of a qualitative constraint network can define a
singleton relation in its corresponding partially weakly path-consistent subnetwork. In this talk, we propose
a stronger local consistency that couples partial singleton weak path-consistency with the idea of collectively
deleting certain unfeasible base relations by exploiting singleton checks. We then propose an algorithm for
enforcing this new consistency and a lazy variant of that algorithm for approximating the new consistency, both of which outperform the respective algorithm for enforcing partial singleton weak path-consistency in a given qualitative constraint network . With respect to the lazy algorithmic variant in particular, we show that it runs up to 5 times faster than our original exhaustive algorithm whilst exhibiting very similar pruning capability.
We formally prove certain properties of our new local consistency and our algorithms, and motivate their usefulness through demonstrative examples and a thorough experimental evaluation with random qualitative constraint networks of the Interval Algebra and the Region Connection Calculus from the phase transition region of two different generation models. Finally, we provide evidence of the crucial role of the new consistency in tackling the minimal labeling problem of a qualitative constraint network, which is the problem of finding the strongest implied constraints of that network.

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Daniel Le Berre awarded CNRS Innovation medal

Daniel Le Berre has been awarded on Wednesday October 10, 2018, the CNRS innovation medal, handed in by Higher Education, Research and Innovation minister Frédérique Vidal and CNRS CEO Antoine Petit, for the development of the Sat4j open source library and its integration in the open platform Eclipse.

Awarded by the CNRS since 2011, this prize rewards researchers for their outstanding work in the technological, therapeutic or social fields..

The other laureates of this medal this year are Valérie Castellani and Thierry Chartier.

CNRS press release
Presentation of the medalists in CNRS news

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