The complexity of elementary algebra and geometry
Journal of Computer and System Sciences
Interval valued fuzzy sets based on normal forms
Fuzzy Sets and Systems
Distribution theory and transform analysis: an introduction to generalized functions, with applications
Readings in uncertain reasoning
Readings in uncertain reasoning
Structured local fuzzy logics in MILORD
Fuzzy logic for the management of uncertainty
Kolmogorov's theorem and multilayer neural networks
Neural Networks
Approximative versions of Kolmogorov's superposition theorem, proved constructively
Journal of Computational and Applied Mathematics
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
A first course in fuzzy logic
An introduction to Kolmogorov complexity and its applications (2nd ed.)
An introduction to Kolmogorov complexity and its applications (2nd ed.)
Kolmogorov's theorem and its impact on soft computing
The ordered weighted averaging operators
Introduction to Languages and the Theory of Computation
Introduction to Languages and the Theory of Computation
Elements of the Theory of Computation
Elements of the Theory of Computation
Data mining, rough sets and granular computing
Data mining, rough sets and granular computing
Partial query resolution for animation authoring
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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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 chapter, we provide results aimed at finding a better (ideally optimal) way of combining these approaches.