Author(s)

Alex Tserkovny

Dassault Systemes, Boston, MA, USA.

In this article, we present a systemic approach toward a fuzzy logic based formalization of an approximate reasoning methodology in a fuzzy resolution, where we derive a truth value of A from both values of B → A and B by some mechanism. For this purpose, we utilize a t-norm fuzzy logic, in which an implication operator is a root of both graduated conjunction and disjunction operators. Furthermore by using an inverse approximate reasoning, we conclude the truth value of A from both values of B → A and B, applying an altogether different mechanism. A current research is utilizing an approximate reasoning methodology, which is based on a similarity relation for a fuzzification, while similarity measure is utilized in fuzzy inference mechanism. This approach is applied to both generalized modus-ponens/modus-tollens syllogisms and is well-illustrated with artificial examples.

Fuzzy Logic, Deduction, Fuzzy Resolvent, Implication, Disjunction, Conjunction, Antecedent, Consequent, Modus-Ponens, Modus-Tollens, Fuzzy Conditional Inference Rule

Tserkovny, A. (2017) A Fuzzy Logic Based Resolution Principal for Approximate Reasoning. Journal of Software Engineering and Applications, 10, 793-823. doi: 10.4236/jsea.2017.1010045.