Deciding Subsumption in Defeasible ELI⊥ with Typicality Models
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Beitragende
Abstract
Some reasoning methods for Defeasible Description Logics (DDLs) suffer from quantification neglect (QN) as they omit un-defeated information for quantified objects. Reasoning in defeasible EL⊥ based on so-called typicality models (TMs), which extend canonical models of classical EL⊥, can alleviate QN. The DDL ELI⊥ extends EL⊥ by inverse roles, i.e., a limited form of value restriction. Extending TMs to inverse roles is challenging due to their interaction with existential restrictions. In this paper, we develop TMs for ELI⊥ for 4 different semantics reliant on rational and relevant closure. Our computation methods for those TMs are effective decision procedures for subsumption in defeasible ELI⊥ and the stronger forms of TMs can mitigate QN.
Details
Originalsprache | Englisch |
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Titel | Logics in Artificial Intelligence |
Redakteure/-innen | Sarah Gaggl, Maria Vanina Martinez, Magdalena Ortiz, Magdalena Ortiz |
Herausgeber (Verlag) | Springer |
Seiten | 531-546 |
Seitenumfang | 16 |
ISBN (elektronisch) | 978-3-031-43619-2 |
ISBN (Print) | 978-3-031-43618-5 |
Publikationsstatus | Veröffentlicht - 2023 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | Lecture Notes in Computer Science |
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Band | 14281 |
ISSN | 0302-9743 |
Externe IDs
Scopus | 85174532037 |
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Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Defeasible Logics, Description Logics, Nonmonotonic Reasoning