Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios
Yiren Lu,Justin Fu,George Tucker,Xinlei Pan,Eli Bronstein,Rebecca Roelofs,Benjamin Sapp,Brandyn White,Aleksandra Faust,Shimon Whiteson,Dragomir Anguelov,Sergey Levine,Yiren Lu,Justin Fu,George Tucker,Xinlei Pan,Eli Bronstein,Rebecca Roelofs,Benjamin Sapp,Brandyn White,Aleksandra Faust,Shimon Whiteson,Dragomir Anguelov,Sergey Levine
Imitation learning (IL) is a simple and powerful way to use high-quality human driving data, which can be collected at scale, to produce human-like behavior. However, policies based on imitation learning alone often fail to sufficiently account for safety and reliability concerns. In this paper, we show how imitation learning combined with reinforcement learning using simple rewards can substan-ti...
