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- W2082020216 abstract "This paper presents a study on biped walking and balance control by reinforcement learning. The robot learns how to walk without prior knowledge of explicit dynamics model by a reinforcement learning approach. The Q-learning sharpens up the robot's walking gaits so as that improve the stability of each gait and reduce the number of the posture patterns in a gait cycle. In this paper, the learning agent employs an intuitive evaluation knowledge to help the biped robot with a basic walking skill learn to improve its behavior in terms of restricting ZMP to a certain region on each foot." @default.
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- W2082020216 date "2013-01-01" @default.
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- W2082020216 title "The Study on the Learning of Walking Gaits for Biped Robots" @default.
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- W2082020216 doi "https://doi.org/10.3182/20130410-3-cn-2034.00126" @default.
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