2020
PLAS: Latent Action Space for Offline Reinforcement Learning
CoRL 2020
The goal of offline reinforcement learning is to learn a policy from a fixed dataset, without further interactions with the environment. This setting will be an increasingly more important paradigm for real-world applications of reinforcement learning such as robotics, in which data collection is sl