Reinforcement Learning

Meta-Reward-Net: Implicitly Differentiable Reward Learning for Preference-based Reinforcement Learning
Setting up a well-designed reward function has been challenging for many reinforcement learning applications. Preference-based …
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Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning
Achieving human-level dexterity is an important open problem in robotics. However, tasks of dexterous hand manipulation even at the …
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End-to-End Affordance Learning for Robotic Manipulation
Learning to manipulate 3D objects in an interactive environment has been a challenging problem in Reinforcement Learning (RL). In …
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