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- W2137177580 abstract "In this paper, we study several adaptive learning strategies for robot agents in a Robocop game. A Q-learning based method is introduced to learning the mapping among agentpsilas actions. We apply these strategies to improve robotpsilas plan. In order to facilitate the development of shred understanding among game strategies, Pigetpsilas cognitive theory is applied to the use of cooperative learning. This paper uses a RoboCup game to explain our approach." @default.
- W2137177580 created "2016-06-24" @default.
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- W2137177580 date "2008-07-01" @default.
- W2137177580 modified "2023-10-05" @default.
- W2137177580 title "Adaptive and cooperative learning for Robocup agents" @default.
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- W2137177580 doi "https://doi.org/10.1109/icmlc.2008.4620945" @default.
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