RETRACTED: Research on decision-making strategy of soccer robot based on multi-agent reinforcement learning

Xiaoli Liu

doi:10.1177/1729881420916960

Abstract

This article studies a multi-agent reinforcement learning algorithm based on agent action prediction. In multi-agent system, the action of learning agent selection is inevitably affected by the action of other agents, so the reinforcement learning system needs to consider the joint state and joint action of multi-agent based on this. In addition, the application of this method in the cooperative strategy learning of soccer robot is studied, so that the multi-agent system can pass through the environment. To realize the division of labour and cooperation of multi-robots, the interactive learning is used to master the behaviour strategy. Combined with the characteristics of decision-making of soccer robot, this article analyses the role transformation and experience sharing of multi-agent reinforcement learning, and applies it to the local attack strategy of soccer robot, uses this algorithm to learn the action selection strategy of the main robot in the team, and uses Matlab platform for simulation verification. The experimental results prove the effectiveness of the research method, and the superiority of the proposed method is validated compared with some simple methods.

Highlights

Multi-agent system robot soccer match is a typical multi-agent system research platform, which is a field of artificial intelligence and robotics machine learning.[1,2]
A multi-agent reinforcement learning method based on agent action prediction is studied
The actions selected by each agent are determined by state information and affected by the actions performed by other agents

Summary

Introduction

Multi-agent system (a distributed system composed of multiple independent autonomous agents, which are in the same working environment, can sense the environmental information and perform their own actions) robot soccer match is a typical multi-agent system research platform, which is a field of artificial intelligence and robotics machine learning.[1,2] At present, the subject of high challenge has received extensive attention and research.[3,4,5] the process of robot soccer match is complex, dynamic and uncertain, which makes the decision-making system based on expert knowledge is lack sufficient completeness and flexibility to deal the process of the complex, dynamic and uncertain of robot football game, the reinforcement learning method does not need accurate environment model and complete expert knowledge. Keywords Soccer robot, multi-agent, reinforcement learning, decision-making strategy Meola et al.[17] studied the reinforcement learning method of multi-agent based on general and games and proved that the algorithm converges to the equilibrium point in a specific environment.

Results

Conclusion