Mixed Reinforcement Learning with Additive Stochastic Uncertainty

Yao Mu, Shengbo Eben Li, Chang Liu +4

Reinforcement learning (RL) methods often rely on massive exploration data to search optimal policies, and suffer from poor sampling efficiency. This paper presents a mixed reinfor…