Amortized Low-Rank Adaptation for Model-Based Reinforcement Learning.

arXiv:2609.12278v2 Announce Type: replace-cross Abstract: World models let agents plan by predicting the consequences of their actions, but changes in the environment can make them inaccurate. We study the problem of adapting a world model to an unknown test-t