A multi-agent reinforcement learning method based on voting to solve the collaboration problem of team members is presented.The method translates the collaboration problem into learning strategies by defining joint actions which called the strategies and then can simplify the problem.Through dividing of the playground

the location can be measured by a lot of numbered regions and then can effectively reduce the state-space dimensions to speed up the pace of learning.By distinguishing the environment states and taking the collaboration status into account

that causing the reduction of the state-action space

the learning speed can be further improved.Using a voting process that combines the decisions of the agents can realize the collaboration.At last

experimental results show the effectiveness and correctness of the method.