Reinforcement Learning with Supervision from Noisy Demonstrations

Kun-Peng Ning, Sheng-Jun Huang

Reinforcement learning has achieved great success in various applications. To learn an effective policy for the agent, it usually requires a huge amount of data by interacting with…