# FRESH: Interactive Reward Shaping in High-Dimensional State Spaces using Human Feedback

Reinforcement learning has been successful in training autonomous agents to accomplish goals in complex environments. Although this has been adapted to multiple settings, including robotics and computer games, human players often find it easier to obtain higher rewards in some environments than reinforcement learning algorithms... (read more)

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