2009
DOI: 10.1016/j.apal.2009.05.014
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First-order t-norm based fuzzy logics with truth-constants: Distinguished semantics and completeness properties

Abstract: Dedicated to Franco Montagna in the occasion of his 60th birthday. MSC: 03B50 03B52 06B99Keywords: Algebraic logic Mathematical fuzzy logic First-order predicate non-classical logics Residuated lattices T-norm based fuzzy logics Truth-constants a b s t r a c t This paper aims at being a systematic investigation of different completeness properties of first-order predicate logics with truth-constants based on a large class of left-continuous tnorms (mainly continuous and weak nilpotent minimum t-norms). We cons… Show more

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Cited by 44 publications
(18 citation statements)
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“…First, we prove the weak completeness of RGL * . A different but similar proof can be found in [9,Theorem 4.7]. Proof.…”
Section: Completeness With Respect To the Strong Entailmentmentioning
confidence: 88%
“…First, we prove the weak completeness of RGL * . A different but similar proof can be found in [9,Theorem 4.7]. Proof.…”
Section: Completeness With Respect To the Strong Entailmentmentioning
confidence: 88%
“…Nevertheless, several other extensions have been subjected to investigations in the last few years. To name just a few examples, states and connection with probability theory as studied for NM in [7]; connections with others non-classical logics, for instance Nelson's constructive logic, are dealt with in [18]; alternative, temporal semantics, are explored in [13]; extensions with truth constants, as well as the first-order case have been subjected to investigations [12,[26][27][28][29], too. The paper [31] classifies all the subvarieties of nilpotent minimum algebras.…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, there are only inference rules by which we can deduce the formulas with truth value 1 from the formulas with truth value 1. The most of fuzzy logics on [0, 1] discussed up to now is of this type [7][8][9][10], which have been designed to formalize the logical background for fuzzy sets. In addition, some important fuzzy logics developed by Wang et al [11][12][13][14][15][16][17] are also based on traditional syntax.…”
Section: Introductionmentioning
confidence: 99%