Multiagent cooperation learning based on an evolutional algorithm
Wei Han · Journal of Shandong University · 2010
Reinforcement learning is not applicable concerning large state-actions,since that its convergence speed increases exponentially with the number of dimensions of state-action space.In many situations,this problem partially can be solved by utilizing a cooperation relationship among agents.An evolutional algorithm was put forward,which could rapidly find the effective updating of state-action pairs by the evolutionary operators such as reproduction as well as die out.Simulations proved that the algorithm performs was better than present multiagent cooperation learning algorithms.