Reward Self-adjusting Reinforcement Learning Using Statistical Information

Abstract

In this study, we developed a method “Statistical Q-learning” a combination of statistical learning and reinforcement learning (Q-learning), which adjusts sub reward by itself using statistical information to fasten the learning speed of Q-learning. The experiment result of learning swing action shows that Statistical Q-learning can learn many stated problems, which is difficult for conventional method to learn stably.