Syntactic labelled tableaux for Łukasiewicz fuzzy ALC

Authors:
Agnieszka Kułacka;Dirk Pattinson;Lutz Schröder
Affiliations:
Imperial College London;Imperial College London, The Australian National University;Friedrich-Alexander Universität, Erlangen-Nürnberg
Venue:
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Year:
2013

Citing 12
Cited 0

Fuzzy logic of Lukasiewicz logic: a clarification

Fuzzy Sets and Systems
Complexity of Terminological Reasoning Revisited

LPAR '99 Proceedings of the 6th International Conference on Logic Programming and Automated Reasoning
Managing uncertainty and vagueness in description logics for the Semantic Web

Web Semantics: Science, Services and Agents on the World Wide Web
Proof Theory for Fuzzy Logics

Proof Theory for Fuzzy Logics
Reasoning within fuzzy description logics

Journal of Artificial Intelligence Research
Reasoning with very expressive fuzzy description logics

Journal of Artificial Intelligence Research
Making fuzzy description logic more general

Fuzzy Sets and Systems
Reasoning with the finitely many-valued Łukasiewicz fuzzy Description Logic SROIQ

Information Sciences: an International Journal
On the failure of the finite model property in some Fuzzy Description Logics

Fuzzy Sets and Systems
Finite-valued Lukasiewicz modal logic Is PSPACE-complete

IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Description logics and fuzzy probability

IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
On the (un)decidability of fuzzy description logics under Łukasiewicz t-norm

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Fuzzy description logics (DLs) serve as a tool to handle vagueness in real-world knowledge. There is particular interest in logics implementing Łukasiewicz semantics, which has a number of favourable properties. Current decision procedures for Łukasiewicz fuzzy DLs work by reduction to exponentially large mixed integer programming problems. Here, we present a decision method that stays closer to logical syntax, a labelled tableau algorithm for Łukasiewicz Fuzzy ALC that calls only on (pure) linear programming, and this only to decide atomic clashes. The algorithm realizes the best known complexity bound, NEXPTIME. Our language features a novel style of fuzzy ABoxes that work with comparisons of truth degrees rather than explicit numerical bounds.