2020
Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation
NeurIPS 2020poster
Offline Reinforcement Learning (RL) is a promising approach for learning optimal policies in environments where direct exploration is expensive or unfeasible. However, the adoption of such policies in practice is often challenging, as they are hard to interpret within the application context, and la…