An Analogical Inference Representation with Certainty Factor
Hata Yutaka, K. Yamato · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics · 1994
This paper proposes a scheme of approximate reasoning with analogical inference for purpose of flexible inference. In this method, we use truth value t ∈ [0,1] based on possibility and assign a truth value called certainty factor (cf) ∈ [0,1] to the implication A → B. This inference conclusion is derived as a product of the truth value T (A) of the fact A and certainty factor cf. We also introduce a scheme of analogical inference based on the concept "similar causes lead similar results". This analogical inference can be done by using a degree of equivalence as a similarity between statements. Moreover we describe the new combination rule of conclusions. It derives the supremum and the infimum of a conclusion and determines a meaningful value by using those bounds. Finally, it is clarified that our scheme can derive the inference result that is suited for our intuition.