Arrow Research search

Author name cluster

Eric Grégoire

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers
1 author row

Possible papers

3

AAAI Conference 2015 Conference Paper

On Computing Maximal Subsets of Clauses that Must Be Satisfiable with Possibly Mutually-Contradictory Assumptive Contexts

  • Philippe Besnard
  • Eric Grégoire
  • Jean-Marie Lagniez

An original method for the extraction of one maximal subset of a set of Boolean clauses that must be satisfiable with possibly mutually contradictory assumptive contexts is motivated and experimented. Noticeably, it performs a direct computation and avoids the enumeration of all subsets that are satisfiable with at least one of the contexts. The method applies for subsets that are maximal with respect to inclusion or cardinality.

AAAI Conference 2014 Conference Paper

An Experimentally Efficient Method for (MSS,CoMSS) Partitioning

  • Eric Grégoire
  • Jean-Marie Lagniez
  • Bertrand Mazure

The concepts of MSS (Maximal Satisfiable Subset) and CoMSS (also called Minimal Correction Subset) play a key role in many A. I. approaches and techniques. In this paper, a novel algorithm for partitioning a Boolean CNF formula into one MSS and the corresponding CoMSS is introduced. Extensive empirical evaluation shows that it is more robust and more efficient on most instances than currently available techniques.

KER Journal 2000 Journal Article

Validation and verification of knowledge-based systems: report on EUROVAV99

  • Frans Coenen
  • Trevor Bench-Capon
  • Robin Boswell
  • JULIETTE DIBIE-BARTHÉLEMY
  • BARRY EAGLESTONE
  • RIK GERRITS
  • Eric Grégoire
  • ANTONI LIGE¸ZA

Knowledge-Based (KB) technology is being applied to complex problem solving and safety and business critical tasks in many application domains. Concerns have naturally arisen as to the dependability of Knowledge-Based Systems (KBS). As with any software, attention to quality and safety must be paid throughout development of a KBS, and rigorous Verification and Validation (V&V) techniques must be employed. Research in V&V of KBSs has emerged as a distinct field only in the last decade, and is intended to address issues associated with quality and safety aspects of KBSs, and to provide such applications with the same degree of dependability as conventional applications. In recent years, V&V of KBSs has been the topic of annual workshops associated with the main AI conferences, such as AAAI, IJCAI and ECAI.