Syntactic Labelled Tableaux for Lukasiewicz Fuzzy ALC
Author(s): Kulacka A, Pattinson D, Schröder L
Title edited volumes: IJCAI International Joint Conference on Artificial Intelligence
Publishing place: Palo Alto
Publication year: 2013
Conference Proceedings Title: Proc. 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
Pages range: 962-969
Event: 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
Event location: Beijing
Start date of the event: 03/08/2013
End date of the event: 09/08/2013
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.
FAU Authors / FAU Editors How to cite
APA: Kulacka, A., Pattinson, D., & Schröder, L. (2013). Syntactic Labelled Tableaux for Lukasiewicz Fuzzy ALC. In Proc. 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 (pp. 962-969). Palo Alto: IJCAI/AAAI.
MLA: Kulacka, Agnieszka, Dirk Pattinson, and Lutz Schröder. "Syntactic Labelled Tableaux for Lukasiewicz Fuzzy ALC." Proceedings of the 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013, Beijing Palo Alto: IJCAI/AAAI, 2013. 962-969.