[Zurück]

M. Dao-Tran, T. Eiter, M. Fink, T. Krennwallner:
"Distributed Evaluation of Nonmonotonic Multi-Context Systems";
Journal of Artificial Intelligence Research, 52 (2015), S. 543 - 600.

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 shortcoming and present a suite of such algorithms which includes a basic algorithm DMCS, an advanced 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
system 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.

http://dx.doi.org/10.1613/jair.4574

Projektleitung Thomas Eiter:
Evaluierung von ASP Programming mit Externen Zugriffen