Reactive Multi-Context Systems: Heterogeneous Reasoning in Dynamic Environments

TL;DR

Reactive multi-context systems (rMCSs) extend existing multi-context frameworks to effectively handle dynamic, stream-based reasoning with heterogeneous knowledge sources, addressing inconsistencies and non-determinism in evolving environments.

Contribution

This paper introduces rMCSs, a novel framework for reactive reasoning in dynamic environments, generalizing and extending prior static multi-context systems for stream reasoning.

Findings

rMCSs effectively handle stream reasoning problems

Inconsistencies in heterogeneous data integration can be managed

Alternative semantics reduce non-determinism and improve computation

Abstract

Managed multi-context systems (mMCSs) allow for the integration of heterogeneous knowledge sources in a modular and very general way. They were, however, mainly designed for static scenarios and are therefore not well-suited for dynamic environments in which continuous reasoning over such heterogeneous knowledge with constantly arriving streams of data is necessary. In this paper, we introduce reactive multi-context systems (rMCSs), a framework for reactive reasoning in the presence of heterogeneous knowledge sources and data streams. We show that rMCSs are indeed well-suited for this purpose by illustrating how several typical problems arising in the context of stream reasoning can be handled using them, by showing how inconsistencies possibly occurring in the integration of multiple knowledge sources can be handled, and by arguing that the potential non-determinism of rMCSs can be avoided if needed using an alternative, more skeptical well-founded semantics instead with beneficial computational properties. We also investigate the computational complexity of various reasoning problems related to rMCSs. Finally, we discuss related work, and show that rMCSs do not only generalize mMCSs to dynamic settings, but also capture/extend relevant approaches w.r.t. dynamics in knowledge representation and stream reasoning.