Abstract
Fuzzy rules are conditional pieces of knowledge which can either express constraints on the set of values which are left possible for a variable, given the values of other variables, or accumulate tuples of feasible values. The first type are implicative rules, while the second are based on conjunctions. Consequences of this view on inference and interpolation between sparse rules are presented.
Cite
CITATION STYLE
Dubois, D., Prade, H., & Ughetto, L. (2002). A new perspective on reasoning with fuzzy rules. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2275, pp. 1–11). Springer Verlag. https://doi.org/10.1007/3-540-45631-7_1
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