The compositional rule of inference under the composition max-product

Abstract

Approximate reasoning is used in Fuzzy Inference Systems to handle imprecise knowledge. It aims to be close as possible to human reasoning. The main approach of approximate reasoning is the compositional rule of inference, which generates different methods by varying its parameters: a t-norm and an implication. In most cases, combinations of t-norms and implications do not fit human intuitions. Based on these methods, we suggest the use of the product t-norm in the compositional rule of inference. We combine this t-norm with different known implications. We then study these combinations and check if they give reasonable consequences.