Contexts: a formalization and some applications
Contexts: a formalization and some applications
Multilanguage hierarchical logics, or: how we can do without modal logics
Artificial Intelligence
Local models semantics, or contextual reasoning = locality + compatibility
Artificial Intelligence
Type Theoretic Foundations for Context, Part 1: Contexts as Complex Type-Theoretic Objects
CONTEXT '99 Proceedings of the Second International and Interdisciplinary Conference on Modeling and Using Context
Comparing formal theories of context in AI
Artificial Intelligence
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
CONTEXT'03 Proceedings of the 4th international and interdisciplinary conference on Modeling and using context
Quantificational logic of context
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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It is a desirable feature of knowledge bases that they are able to accommodate and reason across the different perspectives that may exist on a particular theory or situation. With the aim of obtaining an adequate logic for this problem, the knowledge representation community has extensively researched into the formalization of contexts as first-class citizens. However, most of the proposed logics of context only deal with the propositional case, which for many applications is not enough, and those tackling the quantificational case face many counterintuitive restrictions. In this paper, we present a model-theoretic semantics that, based on a cognitive approach to the notions of context and meaning, succeeds in addressing the quantificational case in a flexible manner that overcomes the limitations of the previous initiatives. The expressive power of the system will be evaluated in the paper by formalizing some of the benchmark examples that can be found in the literature.