Learning to navigate using a lazy map


In this paper we present a novel framework that allows a mobile robot to represent the environment and learn a task. The representation is a ‘lazy map’ in which observation are stored. Reinforcement learning is used to enable a human teacher to train the robot using rewards and punishments. 


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