Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
ISMVL '97 Proceedings of the 27th International Symposium on Multiple-Valued Logic
Unified full implication algorithms of fuzzy reasoning
Information Sciences: an International Journal
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Triangular norms (t-norms) have been applied to many areas of artificial intelligence. Residual implications (R-implications) induced by t-norms have become important tools in both theoretical and applied researches of nonclassical logics and approximate reasoning. This paper discusses axiomatic characterizations of t-norms and R-implications. The correspondences between properties of t-norms and R-implications are investigated. Some important conclusions are proved first time. Some mistakes in the related literature are corrected, and the proof procedures of some results are simplified.