Satisfiability and Query Answering in Description Logics with Global and Local Cardinality Constraints
From International Center for Computational Logic
Satisfiability and Query Answering in Description Logics with Global and Local Cardinality Constraints
Franz BaaderFranz Baader, Bartosz BednarczykBartosz Bednarczyk, Sebastian RudolphSebastian Rudolph
Franz Baader, Bartosz Bednarczyk, Sebastian Rudolph
Satisfiability and Query Answering in Description Logics with Global and Local Cardinality Constraints
Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), June 2020
Satisfiability and Query Answering in Description Logics with Global and Local Cardinality Constraints
Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), June 2020
- KurzfassungAbstract
We introduce and investigate the expressive description logic (DL) ALCSCC++,in which the global and local cardinality constraints introduced in previous papers can be mixed. We prove that the added expressivity does not increase the complexity of satisfiability checking and other standard inference problems. However,
reasoning in ALCSCC++ becomes undecidable if inverse roles are added or conjunctive query entailment is considered. We prove that decidability of querying can be regained if global and local constraints are not mixed and the global constraints are appropriately restricted. In this setting, query entailment can be shown to be EXPTIME-complete and hence not harder than reasoning in ALC. - Projekt:Project: DeciGUT
- Forschungsgruppe:Research Group: Automatentheorie, Computational Logic
Autoren am ICCLICCL Authors
Prof. Dr.-Ing. Franz Baader
- APB 3021
- +49 (0) 351 463-39160
Prof. Dr. Sebastian Rudolph
- APB 2035
- +49 351 463 38516
@inproceedings{BBR2020,
author = {Franz Baader and Bartosz Bednarczyk and Sebastian Rudolph},
title = {Satisfiability and Query Answering in Description Logics with
Global and Local Cardinality Constraints},
booktitle = {Proceedings of the 24th European Conference on Artificial
Intelligence (ECAI 2020)},
year = {2020},
month = {June}
}