Exploration in Model-based Reinforcement Learning with Randomized Reward

Lingxiao Wang, Ping Li

Model-based Reinforcement Learning (MBRL) has been widely adapted due to its sample efficiency. However, existing worst-case regret analysis typically requires optimistic planning,…