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Iterative reinforcement learning with human feedback transforms robot gestures from stiff and unnatural to fluid and expressive, revolutionizing human-robot communication.
Infant-inspired noise can enhance exploration efficiency in deep RL, outperforming traditional uncorrelated noise strategies.
