Fusion de bases propositionnelles : une méthode basée sur les R-ensembles

La prise de décision collective conduit à l'interaction de plusieurs agents afin d'élaborer une décision commune cohérente. D'un point de vue informatique, ce problème peut se ramener à celui de la fusion de différentes sources d'informations. Dans le domaine de la représentation des connaissances pour l'intelligence artificielle, plusieurs approches ont été proposées pour la fusion de bases de croyances propositionnelles, cependant, la plupart d'entre elles l'ont été sur un plan sémantique et sont peu utilisables en pratique. Ce papier propose une nouvelle approche syntaxique pour la fusion de bases de croyances, appelée Fusion par Rensembles (ou RSF). La notion de R-ensemble, initialement définie dans le contexte de la révision de croyances, est étendue à la fusion et la plupart des opérations classiques de fusion sont capturées syntaxiquement par RSF. Afin d'implanter efficacement RSF, ce papier montre comment RSF peut être codé en un programme logique avec sémantique des modèles stables, puis présente une adaptation du système Smodels permettant de calculer efficacement les R-ensembles. Finalement, une étude expérimentale préliminaire montre que la mise en œuvre utilisant la programmation logique avec sémantique des modèles stables semble prometteuse pour réaliser la fusion de bases de croyances sur des applications réelles. Collective decision making leads to interaction between agents in order to elaborate a consistent common decision. From a data-processing point of view, this problem can be brought back to the merging of different sources of information. In knowledge representation for artificial intelligence, several approaches have been proposed for propositional bases fusion, however, most of them are de- paper proposes a new syntactic approach of belief bases fusion, called Removed Sets Fusion (RSF). The notion of removed-set, initially defined in the context of belief revision is extended to fusion and most of the classical fusion operations are syntactically captured by RSF. In order to efficiently implement RSF, the paper shows how RSF can be encoded into a logic program with answer set semantics, then presents an adaptation of the smodels system devoted to efficiently compute the removed sets in order to perform RSF. Finally a preliminary experimental study shows that the answer set programming approach seems promising for performing belief bases fusion on real scale applications

A Semantic Characterization for ASP Base Revision

International audienceThe paper deals with base revision for Answer Set Programming (ASP). Base revision in classical logic is done by the removal of formulas. Exploiting the non-monotonicity of ASP allows one to propose other revision strategies, namely addition strategy or removal and/or addition strategy. These strategies allow one to define families of rule-based revision operators. The paper presents a semantic characterization of these families of revision operators in terms of answer sets. This semantic characterization allows for equivalently considering the evolution of syntactic logic programs and the evolution of their semantic content. It then studies the logical properties of the proposed operators and gives complexity results

A Syntactic Possibilistic Belief Change Operator: Theory and empirical study

International audienceWe propose a syntactic possibilistic belief-change operator, which operates on a belief base of necessity-valued formulas. Such a base may be regarded as a finite and compact encoding of a possibility distribution over a possibly infinite set of interpretations. The proposed operator is designed so that it behaves like a semantic possibilistic belief-change operator for BDI agents recently proposed in the literature. The equivalence of the semantic and syntactic operators is then proved. Experimental results are presented. The aim of these experiments is to demonstrate that the cost of belief revision (expressed in terms of the number of entailment checks required) as well as the size of the belief base do not explode as the number of new pieces of information (formulas) supplied increases

AGM 25 years: twenty-five years of research in belief change

The 1985 paper by Carlos Alchourrón (1931–1996), Peter Gärdenfors, and David Makinson (AGM), “On the Logic of Theory Change: Partial Meet Contraction and Revision Functions” was the starting-point of a large and rapidly growing literature that employs formal models in the investigation of changes in belief states and databases. In this review, the first twenty five years of this development are summarized. The topics covered include equivalent characterizations of AGM operations, extended representations of the belief states, change operators not included in the original framework, iterated change, applications of the model, its connections with other formal frameworks, computatibility of AGM operations, and criticism of the model.info:eu-repo/semantics/publishedVersio