Syntactic labelled tableaux for Łukasiewicz fuzzy ALC

Agnieszka Kułacka; Dirk Pattinson; Lutz Schröder

Syntactic labelled tableaux for Łukasiewicz fuzzy ALC

Agnieszka Kułacka, Dirk Pattinson, Lutz Schröder

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

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.

Original language	English
Title of host publication	IJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence
Pages	962-968
Number of pages	7
Publication status	Published - 2013
Event	23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 - Beijing, China Duration: 3 Aug 2013 → 9 Aug 2013

Publication series

Name	IJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)	1045-0823

Conference

Conference	23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
Country/Territory	China
City	Beijing
Period	3/08/13 → 9/08/13

Cite this

@inproceedings{abd6f6c3e358492daf35dd26f47426e2,

title = "Syntactic labelled tableaux for {\L}ukasiewicz fuzzy ALC",

abstract = "Fuzzy description logics (DLs) serve as a tool to handle vagueness in real-world knowledge. There is particular interest in logics implementing {\L}ukasiewicz semantics, which has a number of favourable properties. Current decision procedures for {\L}ukasiewicz 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 {\L}ukasiewicz 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.",

author = "Agnieszka Ku{\l}acka and Dirk Pattinson and Lutz Schr{\"o}der",

year = "2013",

language = "English",

isbn = "9781577356332",

series = "IJCAI International Joint Conference on Artificial Intelligence",

pages = "962--968",

booktitle = "IJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence",

note = "23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 ; Conference date: 03-08-2013 Through 09-08-2013",

}

Kułacka, A, Pattinson, D & Schröder, L 2013, Syntactic labelled tableaux for Łukasiewicz fuzzy ALC. in IJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence. IJCAI International Joint Conference on Artificial Intelligence, pp. 962-968, 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013, Beijing, China, 3/08/13.

Syntactic labelled tableaux for Łukasiewicz fuzzy ALC. / Kułacka, Agnieszka; Pattinson, Dirk; Schröder, Lutz.
IJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence. 2013. p. 962-968 (IJCAI International Joint Conference on Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Syntactic labelled tableaux for Łukasiewicz fuzzy ALC

AU - Kułacka, Agnieszka

AU - Pattinson, Dirk

AU - Schröder, Lutz

PY - 2013

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N2 - 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.

AB - 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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M3 - Conference contribution

SN - 9781577356332

T3 - IJCAI International Joint Conference on Artificial Intelligence

SP - 962

EP - 968

BT - IJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence

T2 - 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

Y2 - 3 August 2013 through 9 August 2013

ER -

Syntactic labelled tableaux for Łukasiewicz fuzzy ALC

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