Proceedings

Managed Multi-Context Systems

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 786-790.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-138

Abstract

Multi-context systems (MCS) are a powerful framework for interlinking heterogeneous knowledge sources. They model the flow of information among different reasoning components (called contexts) in a declarative way, using so-called bridge rules, where contexts and bridge rules may be nonmonotonic. We considerably generalize MCS to managed MCS (mMCS): while the original bridge rules can only add information to contexts, our generalization allows arbitrary operations on context knowledge bases to be freely defined, e.g., deletion or revision operators. The paper motivates and introduces the generalized framework and presents several interesting instances. Furthermore, we consider inconsistency management in mMCS and complexity issues.

Gerhard Brewka, Thomas Eiter, Michael Fink, and Antonius Weinzierl. 2011. Managed Multi-Context Systems. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 786–790. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-138
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