Combining Ontologies with Correspondences and Link Relations: The E-SHIQ Representation Framework
This addresses the problem of integrating modular knowledge in distributed AI systems, but it is incremental as it builds on existing Description Logics frameworks.
The paper tackles the challenge of combining ontologies from autonomous peers in distributed settings by proposing the E-SHIQ representation framework, which allows peers to maintain subjectivity while reasoning collaboratively with a distributed tableau, and discusses the efficiency of its implementation.
Combining knowledge and beliefs of autonomous peers in distributed settings, is a ma- jor challenge. In this paper we consider peers that combine ontologies and reason jointly with their coupled knowledge. Ontologies are within the SHIQ fragment of Description Logics. Although there are several representation frameworks for modular Description Log- ics, each one makes crucial assumptions concerning the subjectivity of peers' knowledge, the relation between the domains over which ontologies are interpreted, the expressivity of the constructors used for combining knowledge, and the way peers share their knowledge. However in settings where autonomous peers can evolve and extend their knowledge and beliefs independently from others, these assumptions may not hold. In this article, we moti- vate the need for a representation framework that allows peers to combine their knowledge in various ways, maintaining the subjectivity of their own knowledge and beliefs, and that reason collaboratively, constructing a tableau that is distributed among them, jointly. The paper presents the proposed E-SHIQ representation framework, the implementation of the E-SHIQ distributed tableau reasoner, and discusses the efficiency of this reasoner.