Abstract
We propose an algorithm based on satisfiability problem (SAT) solving for determining the contension inconsistency degree in propositional knowledge bases. In addition, we present a revised version of an algorithm based on answer set programming (ASP), which serves the same purpose. In an experimental analysis, we compare the two algorithms to each other, as well as to a naive baseline method. Our results demonstrate that both the SAT and the ASP approach expectedly outperform the baseline algorithm. Further, the revised ASP method is not only superior to the SAT approach, but also to its predecessors from the literature. Hence, it poses a new state of the art.
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For any function \(\varphi :X\mapsto Y\) and \(y \in Y\) we define \(\varphi ^{-1}(y) = \{x\in X \mid f(x) = y\}\).
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Download: https://e.feu.de/srs-dataset.
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Overview of inconsistency values: https://e.feu.de/sum2022-tables.
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Download: https://e.feu.de/ml-dataset.
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Kuhlmann, I., Gessler, A., Laszlo, V., Thimm, M. (2022). A Comparison of ASP-Based and SAT-Based Algorithms for the Contension Inconsistency Measure. In: Dupin de Saint-Cyr, F., Öztürk-Escoffier, M., Potyka, N. (eds) Scalable Uncertainty Management. SUM 2022. Lecture Notes in Computer Science(), vol 13562. Springer, Cham. https://doi.org/10.1007/978-3-031-18843-5_10
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