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

Xun Shen, Liu Guo-dong

Year
2011
Citations
2

Abstract

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.

Keywords

VanguardReinforcement learningComputer scienceOffensiveArtificial intelligenceField (mathematics)Competition (biology)RobotHuman–computer interactionOperations research

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