DISTRIBUTED EVALUATION OF NONMONOTONIC MULTI-CONTEXT SYSTEMS

Multi-Context Systems (MCSs) are a formalism for systems consisting of knowledge bases (possibly heterogeneous and non-monotonic) that are interlinked via bridge rules, where the global system semantics emerges from the local semantics of the knowledge bases (also called “contexts”) in an equilibrium. While MCSs and related formalisms are inherently targeted for distributed settings, no truly distributed algorithms for their evaluation were available. We address this short-coming and present a suite of such algorithms which includes a basic algorithm DMCS, an ad-vanced version DMCSOPT that exploits topology-based optimizations, and a streaming algorithm DMCS-STREAMING that computes equilibria in packages of bounded size. The algorithms behave quite differently in several respects, as experienced in thorough experimental evaluation of a sys-tem prototype. From the experimental results, we derive a guideline for choosing the appropriate algorithm and running mode in particular situations, determined by the parameter settings