Mutual Q-learning

Mutual learning is an emerging technique for improving performance in machine learning models by allowing functions to learn from each other. In this paper, we present an updated version of Q-learning, improved with the application of mutual learning techniques. We apply this algorithm to a traditional reinforcement learning control problem and compare our performance with that of a standard Q-learning approach. We show that these approaches lead to a significant improvement in performance.