Adaptive action fusion method for mobile robot

摘要

A method to reinforce learning based on prior knowledge was proposed,combining the traditional rule control method with the reinforcement learning method.The action fusion mechanism preserves the partially known rules and utilizes the reinforcement learning to accomplish modification of rules.At the same time,the partially known rules give guidance to the learner,which may guarantee the correct learning direction and speed up the convergence.The combination pattern of the two methods is presented,with the architecture and the parameter setting of the learner.The method was used for adaptive action fusion of a mobile robot in a pursuit-evasion game,and its efficiency was shown by simulation results.The results prove that this method converges in less time and has a good learning result.