Adjusting parameters of a fuzzy classifier using RL

What is it about?

A fuzzy rule based classification system is a special type of fuzzy modeling where its output is a discrete crisp value. The main challenging issue in designing fuzzy classifiers is constructing fuzzy rule base. This paper proposes a new fuzzy classifier based on reinforcement learning.

Featured Image

Why is it important?

The single winner reasoning method was improved. The proposed algorithm adjusts the parameters of another group of rules which affects the classification result indirectly. The experimental results show that the proposed approach outperforms other approaches like conventional reward and punishment scheme and multi-layer perceptron network in the terms of quality of classification and precision.