Abstract
We believe that a deeper understanding of the uses of contexts, in terms of its impact on knowledge representation structures, as reflected by a corpus of examples, is vital to the programme of formalizing contexts in Artificial Intelligence. In this paper, we examine a number of examples from the literature from the perspective of identifying general usage patterns. We identify four important varieties of contexts — Projection Contexts, Approximation Contexts, Ambiguity Contexts and Mental State Contexts. We define each type, describe sub-types, list benchmark examples of each sub-type, discuss their practical uses and the requirements they make of the underlying logic. We pay particular attention to the problem of lifting, i.e., of using information obtained from one context in another and describe how these different varieties of contexts tend to require different kinds of lifting rules.
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References
Saul Amarel. On representation of problems of reasoning about action. In Donald Michie, editor, Machine Intel. 3, pages 131–171. Edinburgh Univ. Press, 1971.
J. Barwise and J. Perry. Situations and Attitudes. MIT Press, 1983.
Massimo Beneceretti, Paolo Bouquet, and Chiara Ghidini. On the dimensions of context dependence: Partiality, approximation, and perspective. In Modeling and Using Context, pages 59–72. Springer-Verlag, Berlin, 2001.
Sasa Buvač. Quantificational logic of context. In Howard Shrobe and Ted Senator, editors, AAAI 1996, pages 600–606, Menlo Park, California, 1996. AAAI Press.
Saša Buvač. Ambiguity via formal theory of context. Available from http://www-formal.stanford.edu/buvac., 1995.
Saša Buvač and Ian Mason. Propositional logic of context. In AAAI, pages 412–419, 1993.
Tom Costello and John McCarthy. Useful counterfactuals. Linköping Electronic Articles in Computer and Information Science, 4(12), 1999.
Chiara Ghidini and Fausto Giunchiglia. Local models semantics, or contextual reasoning = locality + compatibility. Artificial Intelligence, 127(2):221–259, 2000.
Ramanathan V. Guha. Contexts: a formalization and some applications. Technical Report STAN-CS-91-1399, Stanford CS Dept., Stanford, CA, 1991.
P. Hayes and C. Menzel. A semantics for the knowledge interchange format.
Patrick J. Hayes. Contexts in context. In Sasa Buvač and Łucia Iwańska, editors, AAAI Fall Symposium on Context, pages 71–81, Menlo Park, CA, 1997. AAAI.
Douglas B. Lenat and R. V. Guha. Building Large Knowledge-based Systems: Representation and Inference in the Cyc Project. Addison-Wesley, 1990.
John McCarthy. Applications of circumscription to formalizing common sense knowledge. In Vladimir Lifschitz, editor, Formalizing Common Sense: Papers by John McCarthy, pages 198–225. Ablex Publishing Corporation, Norwood, New Jersey, 1990.
John McCarthy. Generality in artificial intelligence. In Vladimir Lifschitz, editor, Formalizing Common Sense: Papers by John McCarthy, pages 226–236. Ablex Publishing Corporation, Norwood, New Jersey, 1990.
John McCarthy. Notes on formalizing contexts. In Ruzena Bajcsy, editor, Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, pages 555–560, San Mateo, California, 1993. Morgan Kaufmann.
John McCarthy and Saša Buvač. Formalizing context (expanded notes). Available from http://www-formal.stanford.edu/buvac., 1995.
P. Pandurang Nayak. Representing multiple theories. In B. Hayes-Roth and R. Korf, editors, AAAI-94, pages 1154–1160, Menlo Park, CA, 1994.
N.J. Nilsson and M. Genesereth. Logical Foundations of Artificial Intelligence. Addison-Wesley, 1987.
W.V.O. Quine. Propositional Objects. Columbia Univ. Press, 1969.
R.M. Keller, M. Rimon, and A. Das. A knowledge based prototyping environment for construction of scientific modeling software. Automated Software Engineering, 1994.
Yoav Shoham. Varieties of context. In Vladimir Lifschitz, editor, Artificial Intelligence and Mathematical Theory of Computation, pages 393–407. Academic Press, San Diego, 1991.
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Guha, R., McCarthy, J. (2003). Varieties of Contexts. In: Blackburn, P., Ghidini, C., Turner, R.M., Giunchiglia, F. (eds) Modeling and Using Context. CONTEXT 2003. Lecture Notes in Computer Science(), vol 2680. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44958-2_14
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DOI: https://doi.org/10.1007/3-540-44958-2_14
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