In this paper we give an overview on multi-context systems (MCS) with a special focus on their recent nonmonotonic extensions. MCS provide a flexible, principled account of integrating heterogeneous knowledge sources. By a knowledge source we mean a knowledge base formulated in any of the typical knowledge representation languages, including classical logic, description logics, modal or temporal logics, but also nonmonotonic formalisms like logic programs under answer set semantics or default logic. We will motivate the need for such systems, describe what has been achieved in this area, but we also discuss work in progress and introduce generalizations of the existing framework which we consider useful. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Brewka, G., Eiter, T., & Fink, M. (2011). Nonmonotonic multi-context systems: A flexible approach for integrating heterogeneous knowledge sources. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6565 LNAI, 233–258. https://doi.org/10.1007/978-3-642-20832-4_16
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