Abstract
In this paper we propose to re-read the past work on formalizing context as the search for a logic of the relationships between partial, approximate, and perspectival theories of the world. The idea is the following. We start from a very abstract analysis of a context dependent representation into three basic elements. We briefly show that all the mechanisms of contextual reasoning that have been studied in the past fall into three abstract forms: expand/contract, push/pop, and shifting. Moreover we argue that each of the three forms of reasoning actually captures an operation on a different dimension of variation of a context dependent representation, partiality, approximation, and perspective. We show how these ideas are formalized in the framework of MultiContext Systems, and briefly illustrate some applications.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
G. Attardi and M. Simi. A formalisation of viewpoints. Fundamenta Informaticae, 23(2–4):149–174, 1995.
M. Benerecetti, P. Bouquet, and C. Ghidini. Formalizing Belief Reports-The Approach and a Case Study. In Proc. of the 8th International Conference on Artificial Intelligence, Methodology, Systems, and Applications, volume 1480 of LNAI, Springer, 1998.
M. Benerecetti, P. Bouquet, and C. Ghidini. Contextual Reasoning Distilled. Journal of Theoretical and Experimental Artificial Intelligence, 12(3):279–305, 2000.
P. Bouquet and F. Giunchiglia. Reasoning about Theory Adequacy. A New Solution to the Qualification Problem. Fundamenta Informaticae, 23(2–4):247–262, 1995.
S. Buvač and I. A. Mason. Propositional logic of context. Proc. of the 11th National Conference on Artificial Intelligence, pages 412–419, 1993.
A. Cimatti and L. Serafini. Multi-Agent Reasoning with Belief Contexts: the Approach and a Case Study. In Intelligent Agents: Proceedings of ATAL’94, number 890 in LNCS. Springer, 1995.
J. Dinsmore. Partitioned Representations. Kluwer Academic Publishers, 1991.
G. Fauconnier. Mental Spaces: aspects of meaning construction in natural language. MIT Press, 1985.
C. Ghidini and F. Giunchiglia. Local Models Semantics, or Contextual Reasoning = Locality + Compatibility. Artificial Intelligence, To Appear.
C. Ghidini and L. Serafini. Distributed First Order Logics. In Frontiers Of Combining Systems 2, Studies in Logic and Computation. Research Studies Press, 1998.
C. Ghidini and L. Serafini. Information Integration for Electronic Commerce. In Proceedings of the Workshop on Agent Mediated Electronic Trading (AMET’98), volume 1571 of LNAI. Springer Verlag, 1998.
F. Giunchiglia. Contextual reasoning. Epistemologia, special issue on I Linguaggi e le Macchine, XVI:345–364, 1993.
F. Giunchiglia and P. Bouquet. Introduction to contextual reasoning. An Artificial Intelligence perspective. In Perspectives on Cognitive Science. NBU Press, Sofia, 1997.
F. Giunchiglia and L. Serafini. Multilanguage hierarchical logics (or: how we can do without modal logics). Artificial Intelligence, 65:29–70, 1994.
F. Giunchiglia, L. Serafini, E. Giunchiglia, and M. Frixione. Non-Omniscient Belief as Context-Based Reasoning. In Proc. of the 13th International Joint Conference on Artificial Intelligence, pages 548–554, Chambery, France, 1993.
R.V. Guha. Contexts: a Formalization and some Applications. Technical Report ACT-CYC-423-91, MCC, Austin, Texas, 1991.
J.E. Laird, A. Newell, and P.S. Rosenbloom. Soar: An architecture for general intelligence. Artificial Intelligence, 33(3):1–4 64, 1987.
D. Lewis. Index, Context, and Content. In S. Kranger and S. Ohman, editors, Philosophy and Grammar, pages 79–100. D. Reidel Publishing Company, 1980.
J. McCarthy. Overcoming an Unexpected Obstacle. Unpublished, 1991.
J. McCarthy. Notes on Formalizing Context. In Proc. of the 13th International Joint Conference on Artificial Intelligence, 1993.
Dan Sperber and Deirdre Wilson. Relevance. Communication and Cognition. Basil Blackwell, 1986.
R.W. Weyhrauch. Prolegomena to a Theory of Mechanized Formal Reasoning. Artificial Intelligence, 13(1):133–176, 1980.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Benerecetti, M., Bouquet, P., Ghidini, C. (2001). On the Dimensions of Context Dependence: Partiality, Approximation, and Perspective. In: Akman, V., Bouquet, P., Thomason, R., Young, R. (eds) Modeling and Using Context. CONTEXT 2001. Lecture Notes in Computer Science(), vol 2116. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44607-9_5
Download citation
DOI: https://doi.org/10.1007/3-540-44607-9_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42379-9
Online ISBN: 978-3-540-44607-1
eBook Packages: Springer Book Archive