
The generalized modus ponens deals with the problem of inference in an imprecise setting. The paper explores four of the most often encountered possibilities, in the case where a single rule is considered at a time. The behavior of two deduction systems sufficient for practical use is investigated in the situation where the dependency between antecedent and consequent variables is described by a collection of rules. It is shown that one can get a meaningful approximation of what is produced by the generalized modus ponens technique. This paper suggests one more step to computational tractability of the fuzzy set theory framework.
implication functions, t-norms, deduction rules, Applied Mathematics, approximate reasoning systems, Theoretical Computer Science, imprecision, Fuzzy sets and logic (in connection with information, communication, or circuits theory), Artificial Intelligence, fuzzy logic, generalized modus ponens, uncertainty, trapezoidal possibility distributions, Software
implication functions, t-norms, deduction rules, Applied Mathematics, approximate reasoning systems, Theoretical Computer Science, imprecision, Fuzzy sets and logic (in connection with information, communication, or circuits theory), Artificial Intelligence, fuzzy logic, generalized modus ponens, uncertainty, trapezoidal possibility distributions, Software
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