Uncertainty-Aware Selection of Online Algorithms with Simulator Ensembles.

arXiv:2609.32170v1 Announce Type: cross Abstract: The performance of online reinforcement learning depends critically on design choices, especially those that affect exploration. These choices are often selected by fitting a simulator to offline data, evaluati