Huiling Qin

Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations

2022 · arXiv (Cornell University)

We study the problem of offline Imitation Learning (IL) where an agent aims to learn an optimal expert behavior policy without additional online environment interactions. Instead, the agent is provided with a supplementary offline dataset …