Learning Multi-Task Transferable Rewards via Variational Inverse Reinforcement Learning
Se-Wook Yoo,Seung-Woo Seo,Se-Wook Yoo,Seung-Woo Seo
Many robotic tasks are composed of a lot of temporally correlated sub-tasks in a highly complex environment. It is important to discover situational intentions and proper actions by deliberating on temporal abstractions to solve problems effectively. To understand the intention separated from changing task dynamics, we extend an empowerment-based regularization technique to situations with multipl...
