Barlatier Patrick, Richard Dapoigny
The context paradigm emerges from different areas of Artificial Intelligence. However, while significative formalizations have been proposed, contexts are either mapped on independent micro-theories or considered as different concurrent viewpoints with mappings between contexts to export/import knowledge. These logical formalisms focus on the semantic level and do not take into account dynamic low-level information such as those available from sensors. This information is a key element of contexts in pervasive computing environments. In this paper, we introduce a formal framework where the knowledge representation of context bridges the gap between semantic high-level and low-level knowledge. The logical reasoning based on intuitionistic type theory and the Curry-Howard isomorphism is able to incorporate expert knowledge as well as technical resources such as task properties. Based on our context model, we also present the foundations of a Context-Aware architecture (Softweaver) for building of context-aware services.
Subjects: 11. Knowledge Representation; 3. Automated Reasoning
Submitted: Feb 10, 2007