Publication Date
5-1-2021
Abstract
In the traditional fuzzy logic, we can use "and"-operations (also known as t-norms) to estimate the expert's degree of confidence in a composite statement A&B based on his/her degrees of confidence d(A) and d(B) in the corresponding basic statements A and B. But what if we want to estimate the degree of confidence in A&B&C in situations when, in addition to the degrees of estimate d(A), d(B), and d(C) of the basic statements, we also know the expert's degrees of confidence in the pairs d(A&B), d(A&C), and d(B&C)? Traditional ``and''-operations can provide such an estimate -- but only by ignoring some of the available information. In this paper, we show that, by going beyond the traditional "and"-operations, we can find a natural estimate that takes all available information into account -- and thus, hopefully, leads to a more accurate estimate.
Original file
Comments
Technical Report: UTEP-CS-21-18a
To appear in Procedings of the 3rd International Conference on Intelligent and Fuzzy Systems INFUS'2021, Izmir, Turkey, August 24-26, 2021.