DocumentCode
387527
Title
A fuzzy logic with similarity
Author
Wang, Jia-Bing ; Xu, Zheng-Quan ; Wang, Neng-Chao
Author_Institution
Sch. of Comput., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume
3
fYear
2002
fDate
2002
Firstpage
1178
Abstract
Fuzzy set and fuzzy logic are an important and practical mathematical tool for the processing of uncertain and vague information. The similarity relation is a basic notion in fuzzy set and has been applied to almost every field where uncertainty and vagueness are concerned. In this paper, a fuzzy logic with similarity is proposed, and the solution and paramodulation-based fuzzy reasoning are discussed. In order to effectively deal with similarity in reasoning procedure, the inference rule paramodulation is extended to fuzzy reasoning. It is shown that the resolution and paramodulation are complete and sound for fuzzy predicate calculus, i.e., on one hand, if a set of clauses is S-unsatisfiable, then there is a refutation using the resolution and/or paramodulation from the set; on the other hand, if every clause in a set of clauses is something more than a "half-truth" and the most unreliable clause has a truth-value A, then it is guaranteed that all the logical consequence obtained by repeatedly applying the resolution and/or paramodulation will have truth-value no less than A.
Keywords
fuzzy logic; fuzzy set theory; inference mechanisms; uncertainty handling; fuzzy logic; fuzzy reasoning; fuzzy set theory; inference rule; paramodulation; similarity relation; truth-value; uncertainty handling; vagueness; Artificial intelligence; Calculus; Concurrent computing; Fuzzy logic; Fuzzy reasoning; Fuzzy sets; Machine learning; Parallel processing; Terminology; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN
0-7803-7508-4
Type
conf
DOI
10.1109/ICMLC.2002.1167386
Filename
1167386
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