Robo Cup regional cooperative strategy based on multi-Agent Q-learning
Zhao Faju · Computer Engineering and Applications Journal · 2014
Because many multi-Agent cooperative problems can hardly be solved in Robo Cup, this paper investigates a regional cooperative multi-Agent Q-learning method. Through subdividing the stadium area and rewards of agents, the agents' collaboration ability can be strengthened. As a result, the team's offensive and defensive abilities are enhanced.At the same time, the agents can spend less time learning via restricting the using range of the algorithm. Consequently,the real-time of the game can be ensured. Finally, the experiment on the platform of the simulation 2D proves that the effect of this method is much better than that of the previous one, and it fully complies with the design of the original goal.