Abstract
The evaluation of logic programs with access to external knowledge sources requires to interleave external computation and model building. Deciding where and how to stop with one task and proceed with the next is a difficult problem, and existing approaches have severe scalability limitations in many real-world application scenarios. We introduce a new approach for organizing the evaluation of logic programs with external knowledge sources and describe a configurable framework for dividing the non-ground program into overlapping possibly smaller parts called evaluation units. These units will then be processed by interleaving external evaluations and model building according to an evaluation and a model graph, and by combining intermediate results. Experiments with our prototype implementation show a significant improvement of this technique compared to existing approaches. Interestingly, even for ordinary logic programs (with no external access), our decomposition approach speeds up existing state of the art ASP solvers in some cases, showing its potential for wider usage.
This research has been supported by the Austrian Science Fund (FWF) project P20841 and the Vienna Science and Technology Fund (WWTF) project ICT08-020.
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Eiter, T., Fink, M., Ianni, G., Krennwallner, T., Schüller, P. (2011). Pushing Efficient Evaluation of HEX Programs by Modular Decomposition. In: Delgrande, J.P., Faber, W. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2011. Lecture Notes in Computer Science(), vol 6645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20895-9_10
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