Title
Distributed Evaluation of Nonmonotonic Multi-context Systems.
Abstract
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.
Year
DOI
Venue
2015
10.1613/jair.4574
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
Field
DocType
Volume
Suite,Computer science,Theoretical computer science,Artificial intelligence,Distributed computing,Streaming algorithm,Exploit,Distributed algorithm,Formalism (philosophy),Rotation formalisms in three dimensions,Machine learning,Semantics,Bounded function
Journal
52
Issue
ISSN
Citations 
1
1076-9757
5
PageRank 
References 
Authors
0.41
32
4
Name
Order
Citations
PageRank
Minh Dao-Tran139520.39
Thomas Eiter27238532.10
Michael Fink3114562.43
Thomas Krennwallner446829.14