A Context-Based Mechanization of Multi-Agent Reasoning

Abstract

Belief contexts [Giunchiglia, 1993; Giunchiglia and Serafini, 1994; Giunchiglia et al., 1993] are a formalism for the representation of propositional attitudes. Their basic feature is modularity: knowledge can be distributed in different, separated modules, called contexts; the interactions between them, i.e. the transfer of knowledge between contexts, can be formally defined according to the application. For instance, the beliefs of an agent can be represented with one or more contexts, distinct from the contexts representing beliefs of other agents; different contexts can be used to represent the beliefs of an agent in different situations. Interaction between contexts can express the effect of communication between agents, and the evolution of their beliefs (e.g. learning, belief revision).KeywordsBelief RevisionCommon BeliefPropositional AttitudeNatural DeductionQuotation MarkThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.