Learning Dense Rewards for Contact-Rich Manipulation Tasks

Zheng Wu, Wenzhao Lian, Vaibhav Unhelkar +2

Rewards play a crucial role in reinforcement learning. To arrive at the desired policy, the design of a suitable reward function often requires significant domain expertise as well…