Cooperative Q-learning based on learning automata
Mao Yang, Yantao Tian, Xinyue Qi · 2009
The theory of learning automata has already been applied in reinforcement learning which is characterized by single-agent and single-stage. This paper proposed a multi-robot cooperative Q-learning algorithm based on learning automata. Each robot updates probability for action selection through the learning automata constantly, and then converts the probability to special experience. Robots can accelerate the learning process by means of sharing experiences among each other. Simulation experiments verify the effectiveness of this algorithm.