Efficient paraconsistent reasoning with ontologies and rules

Tobias Kaminski, Matthias Knorr, João Leite

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Citations (Scopus)


Description Logic (DL) based ontologies and nonmonotonic 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.

Original languageEnglish
Title of host publicationProceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015)
PublisherInternational Joint Conferences on Artificial Intelligence
Number of pages8
ISBN (Electronic)978-157735738-4
Publication statusPublished - 2015
Event24th International Joint Conference on Artificial Intelligence, IJCAI 2015 - Buenos Aires, Argentina
Duration: 25 Jul 201531 Jul 2015


Conference24th International Joint Conference on Artificial Intelligence, IJCAI 2015
CityBuenos Aires


  • Data description
  • Semantics


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