基于Q学习Robocup前锋的射门训练  

Robocup vanguard’s goal-scoring ability based on Q-learning

作　　者：申迅[1] 刘国栋[1] 

机构地区：[1]江南大学通信与控制工程学院,江苏无锡214000

出　　处：《计算机工程与应用》2011年第18期53-55,共3页Computer Engineering and Applications

摘　　要：3D仿真机器人是当今人工智能领域里一个极富挑战性的高技术密集型项目。在Robocup 3D比赛中,由于现今球队的人数较少,一个球队的进攻能力往往取决于前锋的个人能力,因此增强前锋的射门能力就显得十分重要。Q学习是一种重要的强化学习方法,将Q学习用到Robocup仿真环境中,使智能体通过在线学习获得射门技巧,并且通过实际比赛证明了算法的有效性。3D simulation of robot soccer is one of the modern challenging high-tech-intensive projects in artificial intelligence field.Due to the small number of players in one team in the competition,the offensive capability of a team often depends on the vanguard ’s personal abilities,and it is extremely necessary to enhance ability of vanguard’s shot ability.Q-learning is an important method of reinforcement learning.This paper uses Q-learning in simulation environment,so that agent can learn shot skills through the online learning,and it has proved the effectiveness of the algorithm through the actual game.

关 键 词：ROBOCUP Q学习 智能体 射门 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]