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STIR$^2$: Reward Relabelling for combined Reinforcement and Imitation Learning on sparse-reward tasks
Our method is based on a reward bonus given to demonstrations and successful episodes (via relabeling), encouraging expert imitation and self-imitation.
Learning from demonstrations with SACR2: Soft Actor-Critic with Reward Relabeling
We also present a new method for sparse-reward tasks, based on a reward bonus given to demonstrations and successful episodes.
Towards a Sample Efficient Reinforcement Learning Pipeline for Vision Based Robotics
The pipeline is divided into two parts: the first one is to capture the relevant information from the RGB video with a Computer Vision algorithm.
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