2020
RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning
NeurIPS 2020poster
Offline methods for reinforcement learning have a potential to help bridge the gap between reinforcement learning research and real-world applications. They make it possible to learn policies from offline datasets, thus overcoming concerns associated with online data collection in the real-world, in…