Deciding Subsumption in Defeasible ELI with Typicality Models

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

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

OriginalspracheEnglisch
TitelLogics in Artificial Intelligence
Redakteure/-innenSarah Gaggl, Maria Vanina Martinez, Magdalena Ortiz, Magdalena Ortiz
Herausgeber (Verlag)Springer
Seiten531-546
Seitenumfang16
ISBN (elektronisch)978-3-031-43619-2
ISBN (Print)978-3-031-43618-5
PublikationsstatusVeröffentlicht - 2023
Peer-Review-StatusJa

Publikationsreihe

ReiheLecture Notes in Computer Science
Band14281
ISSN0302-9743

Externe IDs

Scopus 85174532037

Schlagworte

Schlagwörter

  • Defeasible Logics, Description Logics, Nonmonotonic Reasoning