Overcoming Knowledge Barriers: Online Imitation Learning from Visual Observation with Pretrained World Models
Published in TMLR, 2025
We identify two knowledge barriers for pretrained-model-based Imitation Learning from Observation and propose AIME-NoB to overcome these barriers, which showcases supreme performance on common benchmarks.
Recommended citation: Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl, Overcoming Knowledge Barriers: Online Imitation Learning from Visual Observation with Pretrained World Models, TMLR, 2025 https://openreview.net/forum?id=BaRD2Nfj41