The inexact information system is based on linguistic terms which have values lying in the interval [0,1]. Imprecision has advantages, because fuzzy sets avoid the rigidity of conventional mathematical reasoning and computer programming. Fuzzy quantifiers are made explicit by means of fuzzy logic. Many systems, for example, complex biological processes, cannot be programmed in a precise way. With fuzzy sets the implicit quantifiers can be easily translated into machine usable form. This paper discusses a method for the description of fuzzy quantifiers in formal languages. A comparison between approximate reasoning and the method of linear interpolation is made. Inexact information in biological and medical expert systems, and the reliability inferences based on it, are also discussed.

Linguistic approach, fuzzy implication, fuzzy quantifier, fuzzy number, approximate reasoning, information system.