摘要: The authors present an approach that uses Q-learning on individual robotic agents for coordinating a mission-tasked team of robots in a complex scenario. To reduce the size of the state space, actions are grouped into sets of rela... 展开
作者 | Martinson, E. Arkin, R. C. | ||
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原报告号 | ADA442291 | 总页数 | 9 |
报告类别/文献类型 | AD / NTIS科技报告 | ||
关键词 | Software engineering Control systems Teams(Personnel) Learning machines Roles(Behavior) Robots Missions Computerized simulation Learning Antitank mines Visual perception Performance(Engineering) Decision making Knowledge based systems Mine clearance Robotics |