Abstract
The objective of this paper is to develop a first order logic of contexts. Dealing with contexts in an explicit way has been initially proposed by J. McCarthy [16] as a means for handling generality in knowledge representation. For instance, knowledge may be distributed among multiple knowledge bases where each base represents a specific domain with its own vocabulary. To overcome this problem, contextual logics aim at defining mechanisms for explicitly stating the assumptions (i.e. the context) underlying a theory and also mechanisms for linking different contexts, such as lifting axioms for connecting one context to another one. However, integrating knowledge supposes the definition of inter-contextual links, based not only on relationships between contextual assertions, but also on relationships built upon contexts. In this paper, we introduce a quantificational modal-based logic of contexts where contexts are represented as explicit terms and may be quantified: we show how this framework is useful for defining first order properties over contexts.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
V. Akman. The use of situation theory in context modeling. Computational Intelligence, 1997.
P. Bonzon. A reflective proof system for reasoning in context. In Proceedings of the 15th National Conference on Artificial Intelligence (AAAI’97), Providence, Rhodes Island, 1997.
S. Buvač. Quantificational Logic of Contexts. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, 1996.
S. Buvač, V. Buvač, and I. A. Mason. Meta-Mathematics of Contexts. Fundamenta Informaticae, 23(3):263–301, 1995.
A. Cimatti and L. Serafini. MultiAgent Reasoning With Belief Contexts II: Elaboration Tolerance. In Proceedings of the first International Conference on Multi-Agent Systems (ICMAS-95), June 12-14, 1995. San Francisco, CA, USA, pages 57–64. AAAI Press / The MIT Press, 1995.
R. Fagin, J. Halpern, Y. Moses, and M. Vardi. Reasoning about Knowledge. MIT Press, 1995.
A. Farquhar, A. Dappert, R. Fikes, and W. Pratt. Integrating information sources using context logic. In AAAI-95 Spring Symposium on Information Gathering from Distributed Heterogeneous Environments, 1995.
D. Gabbay and R. Nossum. Structured contexts with fibred semantics. In Proceedings of the International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT-97), Rio de Janeiro, Brazil, February 4-6, pages 46–56, 1997.
C. Ghidini and L. Serafini. A context-based logic for distributed knowledge representation and reasoning. In P. Bouquet, L. Serafini, P. Brézillon, M. Benerecetti, and F. Castellani, editors, Proceedings of the Second International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT’99), Trento, Italy, September 1999, number 1688 in Lecture Notes In Computer Science, pages 159–172. Springer-Verlag, 1999.
F. Giunchiglia, L. Serafini, E. Giunchiglia, and M. Frixione. Non-Omniscient Belief as Context-Based Reasoning. In Proceedings IJCAI-93, 13th International Joint Conference on Artificial Intelligence. Chambéry, France, 1993.
C. Goh, S. Madnik, and M. Siegel. Ontologies, contexts and mediation: Representing and reasoning about semantic conflicts in heterogeneous and autonomous systems. Technical Report 2848, Sloan School of Management, 1996. also CISL Working Paper 95-04.
R.V. Guha. Contexts: A Formalization and Some Applications. PhD thesis, Stanford University, 1991.
F. Massacci. A Bridge Between Modal Logics and Contextual Reasoning. In IJCAI-95 International Workshop on Modeling Context in Knowledge Representation and Reasoning, 1995.
F. Massacci. Superficial tableaux for contextual reasoning. In S. Buvač, editor, Proc. of the AAAI-95 Fall Symposium on ”Formalizing Context”, number FS-95-02 in AAAI Tech. Reports Series, pages 60-66. AAAI Press/The MIT Press, 1995.
F. Massacci. Contextual reasoning is NP-complete. In W. Clancey and D. Weld, editors, Proceedings of the 13th National Conference on Artificial Intelligence (AAAI-96), pages 621–626. AAAI Press/The MIT Press, 1996.
J. McCarthy. Notes on formalizing context. In Proceeding of the thirteen International Joint Conference on Artificial Intelligence, IJCAI’93, Chambéry, France. Morgan Kaufmann Publishers, 1993.
J. McCarthy and S. Buvač. Formalizing Context: Expanded Notes. Technical Report STAN-CS-TN-94-13, Computer Science Dpt.-Stanford University, 1994.
P. Nayak. Representing Multiple Theories. In Proceedings of the Twelfth National Conference on Artificial Intelligence, pages 1154–1160, Cambridge, MA-USA, 1994. AAAI Press/MIT Press.
L. Perrussel. Contextual Reasoning. In H. Prade, editor, Proceedings of the 13th European Conference on Artificial Intelligence (ECAI’ 98), August 23–28, 1998, Brighton UK, pages 366–367. John Wiley & Sons, Ltd, 1998.
L. Perrussel. Un outillage Logique pour l’Ingénierie des Exigences Multi-Points de Vue. PhD thesis, Université Toulouse 3, Toulouse, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Perrussel, L. (2002). First-Order Contextual Reasoning. In: Bittencourt, G., Ramalho, G.L. (eds) Advances in Artificial Intelligence. SBIA 2002. Lecture Notes in Computer Science(), vol 2507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36127-8_2
Download citation
DOI: https://doi.org/10.1007/3-540-36127-8_2
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00124-9
Online ISBN: 978-3-540-36127-5
eBook Packages: Springer Book Archive