Using Contexts to Prove and Share Situations

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

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