Rule-based Inference Method for Fuzzy-Quantified and Truth-Qualified Natural Language Propositions

We propose an IF...THEN... rule-based inference method, which is necessary to construct a natural language dialog system and an expert system. The method is used to estimate a truth qualifier, tauB\´, when the input proposition is "QA are F is tau" and the IF ... THEN ... rule "IF Q\´A\´ are F\´ is tauA, THEN Q"A" are F" is tauB" is given and the inference result is "Q"A" is F" is tauB\´ " (Q, Q\´, Q": Fuzzy quantifiers, A, A\´, A": Fuzzy subjects, F, F\´, F": Fuzzy predicates, tau, tauA, tauB, tauB\´: Truth qualifiers). We propose a method, which infers a result proposition for monotone Q\´s and show concrete application examples of using the method. Furthermore, we compare the inference results under various implication functions used for obtaining a truth-value fuzzy set of the rule.