Multilanguage hierarchical logics, or: how we can do without modal logics
Artificial Intelligence
Logic programming with social features1
Theory and Practice of Logic Programming
On Reductive Semantics of Aggregates in Answer Set Programming
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Equilibria in heterogeneous nonmonotonic multi-context systems
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Answer sets for logic programs with arbitrary abstract constraint atoms
Journal of Artificial Intelligence Research
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Conflict-driven answer set solving
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Characterizations of stable model semantics for logic programs with arbitrary constraint atoms
Theory and Practice of Logic Programming
Reasoning with imperfect context and preference information in multi-context systems
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Decomposition of distributed nonmonotonic multi-context systems
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
Answer sets for propositional theories
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
Comparing inconsistency resolutions in multi-context systems
ESSLLI'10 Proceedings of the 2010 international conference on New Directions in Logic, Language and Computation
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Multi-Context Systems (MCSs) are a powerful framework for representing the information exchange between heterogeneous (possibly nonmonotonic) knowledge-bases. Significant recent advancements include implementations for realizing MCSs, e.g., by a distributed evaluation algorithm and corresponding optimizations. However, certain enhanced modeling concepts like aggregates and the use of variables in bridge rules, which allow for more succinct representations and ease system design, have been disregarded so far. We fill this gap introducing open bridge rules with variables and aggregate expressions, extending the semantics ofMCSs correspondingly. The semantic treatment of aggregates allows for alternative definitions when so-called grounded equilibria of an MCS are considered. We discuss options in relation to wellknown aggregate semantics in answer-set programming. Moreover, we develop an implementation by elaborating on the DMCS algorithm, and report initial experimental results.