Algorithm Selection for Paracoherent Answer Set Computation
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Abstract
Answer Set Programming (ASP) is a well-established AI formalism rooted in nonmonotonic reasoning. Paracoherent semantics for ASP have been proposed to derive useful conclusions also in the absence of answer sets caused by cyclic default negation. Recently, several different algorithms have been proposed to implement them, but no algorithm is always preferable to the others in all instances. In this paper, we apply algorithm selection techniques to devise a more efficient paracoherent answer set solver combining existing algorithms. The effectiveness of the approach is demonstrated empirically running our system on existing benchmarks.
Notes
Acknowledgments
This work has been supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skodowska-Curie grant agreement No. 690974 for the project “MIREL: MIning and REasoning with Legal texts”.
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