Signature-Based Abduction with Fresh Individuals and Complex Concepts for Description Logics

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Abstract

Given a knowledge base and an observation as a set of facts, ABox abduction aims at computing a hypothesis that, when added to the knowledge base, is sufficient to entail the observation. In signature-based ABox abduction, the hypothesis is further required to use only names from a given set. This form of abduction has applications such as diagnosis, KB repair, or explaining missing entailments. It is possible that hypotheses for a given observation only exist if we admit the use of fresh individuals and/or complex concepts built from the given signature, something most approaches so far do not support or only support with restrictions. In this paper, we investigate the computational complexity of this form of abduction-allowing either fresh individuals, complex concepts, or both-for various description logics, and give size bounds on the hypotheses if they exist.
Original languageEnglish
Title of host publicationProceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021)
EditorsZhi-Hua Zhou
PublisherInternational Joint Conferences on Artificial Intelligence
Pages1929-1935
Number of pages7
ISBN (Electronic)9780999241196
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event30th International Joint Conference on Artificial Intelligence, IJCAI 2021 - Virtual, Online, Canada
Duration: 19 Aug 202127 Aug 2021

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference30th International Joint Conference on Artificial Intelligence, IJCAI 2021
Country/TerritoryCanada
CityVirtual, Online
Period19/08/2127/08/21

Funding

Patrick Koopmann is supported by DFG grant 389793660 of TRR 248 (see https://www.perspicuous-computing.science/).

FundersFunder number
Deutsche ForschungsgemeinschaftTRR 248, 389793660

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