Theories and uses of context in knowledge representation and reasoning

This paper discusses the uses of context in knowledge representation and reasoning (KRR). We propose to partition the theories of context brought forward in KRR into two main classes, which we call divide-and-conquer and compose-and-conquer. We argue that this partition provides a possible explanation of why in KRR context is used to solve different types of problems, or to address the same problems from very different perspectives. The problems we use to illustrate this point are the problem of generality, the formalization of propositional attitudes, and knowledge and data integration.

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