Reinforcement learning for a vision based mobile robot
نویسندگان
چکیده
Reinforcement learning systems improve behaviour based on scalar rewards from a critic. In this work vision based behaviours, servoing and Wandering, are learned through a Q-learning method which handles continuous states and actions. There is no requirement for camera calibration, an actuator model, or a knowledgeable teacher. Learning thmugh observing the actions of other behaviours improves learning speed. Experiments were performed on a mobile robot wing a real-time vision system.
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