In the last decade the concept of context has been extensivelyexploited in many research areas, e.g., distributed artificialintelligence, multi agent systems, distributed databases, informationintegration, cognitive science, and epistemology. Three alternative approaches to the formalization of the notion ofcontext have been proposed: Giunchiglia and Serafini's Multi LanguageSystems (ML systems), McCarthy's modal logics of contexts, andGabbay's Labelled Deductive Systems.Previous papers have argued in favor of ML systems with respect to theother approaches. Our aim in this paper is to support these arguments froma theoretical perspective. We provide a very general definition of ML systems, which covers allthe ML systems used in the literature, and we develop a proof theoryfor an important subclass of them: the MR systems. We prove variousimportant results; among other things, we prove a normal form theorem,the sub-formula property, and the decidability of an importantinstance of the class of the MR systems. The paper concludes with a detailed comparison among the alternativeapproaches
Keywords contextual reasoning  distributed information-oriented theories  modal logics  multi context systems  normal form  proof theory
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Reprint years 2004
DOI 10.1023/A:1019967901393
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References found in this work BETA

Belief, Awareness, and Limited Reasoning.Ronald Fagin & Joseph Y. Halpern - 1987 - Artificial Intelligence 34 (1):39-76.
Formalizing Context (Expanded Notes).John McCarthy & Sasa Buvac - 1998 - CSLI Lecture Notes 81:13-50.
Objective and Cognitive Context.Carlo Penco - 1999 - In P. Brezillon & P. Bouquet (eds.), Lecture Notes in Artificial Intelligence. Springer.

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A Decidable Multi-Modal Logic of Context.Rolf Nossum - 2003 - Journal of Applied Logic 1 (1-2):119-133.

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