Q Value Reinforcement Learning Algorithm Based on Multi Agent System

Q-learning algorithm of multi-agent system is studied in this paper. In order to improve the learning efficiency and convergence speed of the Q algorithm which is a typical learning algorithm of multi agent system, this paper proposes an improved reinforcement learning algorithm of multi agent system based on the existing design experience and surrounding environment information. The Q learning algorithm is effectively extended to the multi agent systems by information sharing among multiple agents in the improved algorithm. The effectiveness of the proposed algorithm is verified by simulation.