Antonis Bikakis, Grigoris Antoniou
A Multi-Context System consists of a set of contexts and a set of inference rules (known as mapping or bridge rules) that enable information flow between different contexts. A context can be thought as a logical theory - a set of axioms and inference rules - that models local context knowledge. Different contexts are expected to use different languages and inference systems, and although each context may be locally consistent, global onsistency cannot be required or guaranteed. Reasoning with multiple contexts requires performing two types of reasoning; (a) ocal reasoning, based on the individual context theories; and (b) distributed reasoning, which combines the consequences of local theories using the mappings. The most critical challenges of ontextual reasoning are; (a) the heterogeneity of local context theories; and (b) the potential conflicts that may arise from the interaction of different contexts through the mappings. Our study mainly focuses on the second issue, by modeling the different contexts as peers in a P2P system, and performing some type of defeasible reasoning on the distributed peer theories.
Subjects: 3.3 Nonmonotonic Reasoning; 11. Knowledge Representation
Submitted: Apr 1, 2008