On Efficient Representation of Expert Knowledge by Fuzzy Logic: Towards an Optimal Combination of Granularity and Higher-Order Approaches

Authors

Hung T. Nguyen
Vladik Kreinovich, The University of Texas at El PasoFollow

Publication Date

4-2002

Comments

UTEP-CS-01-24b.

Published in: Ajith Abraham, Lakhmi Jain, and Janusz Kacprzyk (eds.), Recent Advances in Intelligent Paradigms and Applications, Springer-Verlag, 2002, pp. 107-132.

Abstract

A natural approach to designing an intelligent system is to incorporate expert knowledge into this system. One of the main approaches to translating this knowledge into computer-understandable terms is the approach of fuzzy logic. It has led to many successful applications, but in several aspects, the resulting computer representation is somewhat different from the original expert meaning. Two related approaches have been used to make fuzzy logic more adequate in representing expert reasoning: granularity and higher-order approaches. Each approach is successful in some applications where the other approach did not succeed so well; it is therefore desirable to combine these two approaches. This idea of combining the two approaches is very natural, but so far, it has led to few successful practical applications. In this paper, we provide results aimed at finding a better (ideally optimal) way of combining these approaches.