Abstract
Explicit representation of context and contextual knowledge is critical to intelligent agents. In this paper, we discuss our view of context and context-sensitive reasoning, based on several years of work on representing and using contextual knowledge. We describe our approach to context-sensitive reasoning, called context-mediated behavior (CMB), and discuss our experience related to reasoning in context in AI programs and our ongoing and future work in the area.
This material is based upon work supported by the National Science Foundation under Grant Nos. BES-9696044 and IIS-9613646 and under contracts N0001-14-96-1-5009 and N0001-14-98-1-0648 from the U.S. Office of Naval Research. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
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Turner, R.M. (1999). A Model of Explicit Context Representation and Use for Intelligent Agents. In: Bouquet, P., Benerecetti, M., Serafini, L., Brézillon, P., Castellani, F. (eds) Modeling and Using Context. CONTEXT 1999. Lecture Notes in Computer Science(), vol 1688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48315-2_29
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DOI: https://doi.org/10.1007/3-540-48315-2_29
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