Reinforcement Learning from Hierarchical Critics

8 Feb 2019Zehong CaoChin-Teng Lin

In this study, we investigate the use of global information to speed up the learning process and increase the cumulative rewards of reinforcement learning (RL) in competition tasks. Within the actor-critic RL, we introduce multiple cooperative critics from two levels of the hierarchy and propose a reinforcement learning from hierarchical critics (RLHC) algorithm... (read more)

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