Local and Distributed Defeasible Reasoning in Multi-Context Systems

Abstract

Multi-Context Systems (MCS) are logical formalizations of distributed context theories connected through a set of mapping rules, which enable information flow between different contexts. Reasoning in MCS introduces many challenges that arise from the heterogeneity of contexts with respect to the language and inference system that they use, and from the potential conflicts that may arise from the interaction of context theories through the mappings. This study proposes a P2P rule-based reasoning model for MCS, which handles (a) incomplete or inconsistent local context information, by representing contexts as local theories of Defeasible Logic and performing local defeasible reasoning, and (b) global inconsistencies that result from the integration of local contexts, by representing mappings as defeasible rules and performing some type of distributed defeasible reasoning. It also provides a distributed algorithm for query evaluation, analyzes its formal properties, and illustrates its use in a Semantic Web use case scenario.