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

摘要

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.