Distributional Reinforcement Learning with Sample-set Bellman Update
Weijian Zhang,Jianshu Wang,Yang Yu,Weijian Zhang,Jianshu Wang,Yang Yu
Distributional Reinforcement Learning (DRL) not only endeavors to optimize expected returns, but also strives to accurately characterize the full distribution of these returns, a key aspect in enhancing risk-aware decision-making. Previous DRL implementations often inappropriately treat statistical estimations as concrete samples, which undermines the integrity of learning. While several studies h...
