Abstract
A characteristic approach of approximate reasoning is the partial matching of observations to prototypes. This analysis is cast in the framework of fuzzy set theory and brings another dimension to the fuzzy matching criterion; this dimension is the measure of uncertainty through the concept of subjective entropy. While a similarity measure, in the matching process, activates relevant prototypes, the entropy formalism derived provides a measure of uncertainty in the partial matching to each prototype. The novel approach formalizes an entropy weights activation of prototypes for fuzzy partial matching. A methodology is developed for matching of observation to a set of prototypes making use of a suitable aggregation done with a framework of fuzzy integrals. A method of dealing with compound hypothesis is also developed.< >