Learning Long-Term Reward Redistribution via Randomized Return Decomposition

Zhizhou Ren, Ruihan Guo, Yuan Zhou +1

Many practical applications of reinforcement learning require agents to learn from sparse and delayed rewards. It challenges the ability of agents to attribute their actions to fut…