Conference contribution
(Original article)


Syntactic Labelled Tableaux for Lukasiewicz Fuzzy ALC


Publication Details
Author(s): Kulacka A, Pattinson D, Schröder L
Title edited volumes: IJCAI International Joint Conference on Artificial Intelligence
Publisher: IJCAI/AAAI
Publishing place: Palo Alto
Publication year: 2013
Conference Proceedings Title: Proc. 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
Pages range: 962-969
ISSN: 1045-0823

Event details
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
Language: English

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.



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.

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