Reinforcement Learning From Imperfect Corrective Actions And Proxy Rewards

Zhaohui Jiang, Xuening Feng, Paul Weng +6

In practice, reinforcement learning (RL) agents are often trained with a possibly imperfect proxy reward function, which may lead to a human-agent alignment issue (i.e., the learne…