Control-Inspired Machine Learning Algorithm: Fuzzy Logic Optimization

Abstract

Fuzzy logic in simple words is a set of “if-then” rules. These rules describe the system behavior. These rules can be changed according to the required output. Fuzzy logic is a computational paradigm that generalizes classical two-valued logic for reasoning under uncertainty. In order to achieve this, the notation of membership in a set needs to become a matter of degree. This is the essence of fuzzy sets. By doing this one accomplishes two things: ease of describing human knowledge involving vague concepts and enhanced ability to develop a cost-effective solution to real-world problem. Fuzzy logic is a kind of multi-valued logic, which is a model-less approach and is a clever disguise of the Probability Theory. The most famous types of the membership functions are the triangle, trapezoidal, and Gaussian membership function.