Abstract
Integrating knowledge from various sources is a recurring problem in Artificial Intelligence, often addressed by multi-context systems (MCSs). Existing MCSs however have limited support for the open-world semantics of knowledge bases (KBs) expressed in knowledge representation languages based on first-order logic. To address this problem we introduce knowledge base networks (KBNs), which consist of open-world KBs linked by non-monotonic bridge rules under a stable model semantics. Basic entailment in KBNs is decidable whenever it is in the individual KBs. This is due to a fundamental representation theorem, which allows us to derive complexity results, and also gives a perspective for implementation. In particular, for networks of KBs in well-known Description Logics (DLs), reasoning is reducible to reasoning in nonmonotonic dl-programs. As a by product, we obtain an embedding of a core fragment of Motik and Rosati’s hybrid MKNF KBs, which amount to a special case of KBNs, to dl-programs. We also show that reasoning in networks of ontologies in lightweight DLs is not harder than in answer set programming.
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Notes
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- 2.
This was the setting of the initial version of [20]. A so-called generalized atom, i.e. a complex formula, can be replaced by a standard atom whenever it is expressible in the considered DL.
- 3.
If \(\approx \) is present in \(\mathcal {O}\), then its axiomatization must be added to P to preserve the correspondence. This is a general way to simulate equality under the SNA.
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Acknowledgments
This work was supported by the Austrian Science Fund projects P25207 and P24090, and the Vienna Science and Technology Fund project ICT12-15.
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Eiter, T., Šimkus, M. (2015). Linking Open-World Knowledge Bases Using Nonmonotonic Rules. In: Calimeri, F., Ianni, G., Truszczynski, M. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2015. Lecture Notes in Computer Science(), vol 9345. Springer, Cham. https://doi.org/10.1007/978-3-319-23264-5_25
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