This paper is about the fusion of multiple knowledge sources represented using default logic. More precisely, the focus
is on solving the problem that occurs when the standard-logic knowledge parts of the sources are contradictory, as default
theories trivialize in this case. To overcome this problem, several candidate policies are discussed. Among them, it is
shown that replacing each formula belonging to minimally unsatisfiable subformulas by a corresponding supernormal
default exhibits appealing features.
In this paper, a new family of approaches to fuse inconsistent knowledge sources is introduced in a standard logical setting. They combine two preference criteria to arbitrate between conflicting information: the minimization of falsified formulas and the minimization of the number of the different atoms that are involved in those formulas. Although these criteria exhibit a syntactical flavor, the approaches are semantically-defined.
In this paper, the general logic-based framework for knowledge and beliefs fusion proposed by Konieczny, Lang and Marquis is investigated. It is shown that contrary to one of its main objectives, it fails to handle the fusion of some inconsistent knowledge bases. Accordingly, it is revisited in order to overcome this drawback.
In this paper, a new approach to logic-based knowledge fusion is proposed. It is based on the use of (a form of) semaphores to solve conflicting information. It is shown that a traditional use of semaphores is not relevant in the case of an iterated fusion process. Accordingly, an adequate technique is thus proposed that allows multiple fusion steps to be performed. Technical properties of this new technique are then investigated.
In this paper, the problem of fusing logic-based technical specification -or model-based diagnosis- knowledge components of a physical device or process, is investigated. It is shown that most standard logic approaches to beliefs fusion are not relevant in this context since some rules should be merged even in the case of a consistent fusion. Accordingly, we discuss the various types of formulas that should be merged during a fusion process, in order to avoid necessary conditions for the absence of failure to become sufficient conditions. This transformation is then described formally. It can be performed as an efficient preprocessing step on the knowledge components to be fused. Finally, a series of subsumption tests are proposed, preventing conditions of absence of failure from being overridden by subsumption.
In this paper, a series of knowledge fusion operators are motivated and analyzed. They are defined in a semantic way, although syntactical facets of knowledge are taken into account. More precisely, they rely on a rank-ordering of interpretations that is based on the number of formulas that the interpretations falsify. It is briefly discussed how these operators could be refined, by taking into account various distribution policies of the falsified information among the knowledge sources, syntactical properties of formulas to be fused and forms of integrity constraints preference among literals.
In this paper, new operators for fusing logical knowledge-bases (Kbs) are proposed. They are defined in such a way that they can handle Kbs that must be interpreted under forms of the closed- world assumption. Such assumptions implicitly augment the Kbs with some additional information that could not be deduced using the standard logical deductive apparatus. More precisely, we extend previous recent works about the logical fusion of knowledge to handle such Kbs. We focus on the model-theoretic definition of fusion operators to show their limits. In particular, the basic logical concept of model appears too coarse-grained. We solve this problem and propose new operators that cover a whole family of fusion approaches in the presence of variants of the closed-world assumption.