Policy Learning Using Weak Supervision

Jingkang Wang, Hongyi Guo, Zhaowei Zhu +1

Most existing policy learning solutions require the learning agents to receive high-quality supervision signals such as well-designed rewards in reinforcement learning (RL) or high…