... the proposed EAAT method and DS-based fuzzy reward function. Section 5 describes EAAT usage in three experiments. Section 6 describes experimental setup, training configurations and results. Finally, Section 7 concludes the paper. Deep reinforcement learning Sparse reward Compound actions...

... propose a distributed multi-agent deep reinforcement learning ( MADRL ) framework that leverages the autonomous decision-making capability of deep reinforcement learning to achieve distributed continuous action control of UAVs, thereby enabling efficient autonomous deployment. Design/methodology...

...Jinbao Fang; Qiyu Sun; Yukun Chen; Yang Tang Purpose This work aims to combine the cloud robotics technologies with deep reinforcement learning to build a distributed training architecture and accelerate the learning procedure of autonomous systems. Especially, a distributed training architecture...