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Stable model semantics for description logic terminologies
Institute of Logic and Computation, TU Wien, Austria.
Umeå University, Faculty of Science and Technology, Department of Computing Science. Institute of Logic and Computation, TU Wien, Austria.ORCID iD: 0000-0003-0632-0294
2024 (English)In: Proceedings of the 38th AAAI conference on artificial intelligence / [ed] Michael Wooldridge; Jennifer Dy; Sriraam Natarajan, Association for the Advancement of Artificial Intelligence , 2024, Vol. 38, p. 10484-10492Conference paper, Published paper (Refereed)
Abstract [en]

This paper studies a stable model semantics for Description Logic (DL) knowledge bases (KBs) and for (possibly cyclic) terminologies, ultimately showing that terminologies under the proposed semantics can be equipped with effective reasoning algorithms. The semantics is derived using Quantified Equilibrium Logic, and-in contrast to the usual semantics of DLs based on classical logic-supports default negation and allows to combine the open-world and the closed-world assumptions in a natural way. Towards understanding the computational properties of this and related formalisms, we show a strong undecidability result that applies not only to KBs under the stable model semantics, but also to the more basic setting of minimal model reasoning. Specifically, we show that concept satisfiability in minimal models of an ALCIO KB is undecidable. We then turn our attention to (possibly cyclic) DL terminologies, where ontological axioms are limited to definitions of concept names in terms of complex concepts. This restriction still yields a very rich setting. We show that standard reasoning problems, like concept satisfiability and subsumption, are EXPTIME-complete for terminologies expressed in ALCI under the stable model semantics.

Place, publisher, year, edition, pages
Association for the Advancement of Artificial Intelligence , 2024. Vol. 38, p. 10484-10492
Series
Proceedings of the AAAI Conference on Artificial Intelligence, ISSN 2159-5399, E-ISSN 2374-3468 ; 38:9
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-223237DOI: 10.1609/aaai.v38i9.28917Scopus ID: 2-s2.0-85189359529ISBN: 1577358872 (electronic)ISBN: 9781577358879 (electronic)OAI: oai:DiVA.org:umu-223237DiVA, id: diva2:1852882
Conference
38th AAAI Conference on Artificial Intelligence, AAAI 2024, Vancouver, Canada, February 20-27, 2024
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Available from: 2024-04-19 Created: 2024-04-19 Last updated: 2024-04-19Bibliographically approved

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Šimkus, Mantas

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Total: 178 hits
CiteExportLink to record
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Citation style
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