Abstract
Multi-Context Systems (MCS) are formalisms that enable the interlinkage of single knowledge bases, called contexts, via bridge rules. Recently, a fully distributed algorithm for evaluating heterogeneous, nonmonotonic MCS was described in [7]. In this paper, we continue this line of work and present a decomposition technique for MCS which analyzes the topology of an MCS. It applies pruning techniques to get economically small representations of context dependencies. Orthogonal to this, we characterize minimal interfaces for information exchange between contexts, such that data transmissions can be minimized. We then present a novel evaluation algorithm that operates on a query plan which is compiled with topology pruning and interface minimization. The effectiveness of the optimization techniques is demonstrated by a prototype implementation, which uses an off-the-shelf SAT solver and shows encouraging experimental results.
This research has been supported by the Austrian Science Fund (FWF) project P20841 and by the Vienna Science and Technology Fund (WWTF) project ICT 08-020.
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Bairakdar, S.ED., Dao-Tran, M., Eiter, T., Fink, M., Krennwallner, T. (2010). Decomposition of Distributed Nonmonotonic Multi-Context Systems . In: Janhunen, T., Niemelä, I. (eds) Logics in Artificial Intelligence. JELIA 2010. Lecture Notes in Computer Science(), vol 6341. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15675-5_5
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DOI: https://doi.org/10.1007/978-3-642-15675-5_5
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