Syntactic Labelled Tableaux for Lukasiewicz Fuzzy ALC

Kulacka A, Pattinson D, Schröder L (2013)


Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2013

Publisher: IJCAI/AAAI

Edited Volumes: IJCAI International Joint Conference on Artificial Intelligence

City/Town: Palo Alto

Pages Range: 962-969

Conference Proceedings Title: Proc. 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

Event location: Beijing CN

Open Access Link: http://ijcai.org/Proceedings/13/Papers/147.pdf

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.

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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). Beijing, CN: 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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