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Efficient Paraconsistent Reasoning with Ontologies and Rules

Tobias Kaminski, Matthias Knorr, João Leite

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Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Special Track on Knowledge Representation and Reasoning. Pages 3098-3104.

Abstract

Description Logic (DL) based ontologies and non-monotonic rules provide complementary features whose combination is crucial in many applications. In hybrid knowledge bases (KBs), which combine both formalisms, for large real-world applications, often integrating knowledge originating from different sources, inconsistencies can easily occur. These commonly trivialize standard reasoning and prevent us from drawing any meaningful conclusions. When restoring consistency by changing the KB is not possible, paraconsistent reasoning offers an alternative by allowing us to obtain meaningful conclusions from its consistent part. In this paper, we address the problem of efficiently obtaining meaningful conclusions from (possibly inconsistent) hybrid KBs. To this end, we define two paraconsistent semantics for hybrid KBs which, beyond their differentiating properties, are faithful to well-known paraconsistent semantics as well as the non-paraconsistent logic they extend, and tractable if reasoning in the DL component is.

Tobias Kaminski, Matthias Knorr, and João Leite. 2015. Efficient Paraconsistent Reasoning with Ontologies and Rules. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 3098–3104. https://ijcai.org/proceedings/2015/437
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