[Zurück]

S. Bairakdar, M. Dao-Tran, T. Eiter, M. Fink, T. Krennwallner:
"Decomposition of Distributed Nonmonotonic Multi-Context Systems";
Vortrag: 12th European Conference on Logics in Artificial Intelligence (JELIA 2010), Helsinki, Finland; 13.09.2010 - 15.09.2010; in: "12th European Conference on Logics in Artificial Intelligence", T. Janhunen, I. Niemelä (Hrg.); Springer, 6341 (2010), S. 24 - 37.

Multi-Context Systems (MCS) are formalisms that enable the inter-linkage 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.

Answer Set Programming, Nonmonotonic Reasoning, Multi-Context System, Decentralized Model Computation

http://dx.doi.org/10.1007/978-3-642-15675-5_5

Projektleitung Thomas Eiter:
Modulare HEX-Programme

Projektleitung Thomas Eiter:
Net2¿A Network for Enabling Networked Knowledge

Projektleitung Michael Fink:
Inconsistency Management for Knowledge-Integration Systems