Federated Reinforcement Learning Acceleration Method for Precise Control of Multiple Devices

Federated Reinforcement Learning Acceleration Method for Precise Control of Multiple Devices

Nowadays, Reinforcement Learning (RL) is applied to various real-world tasks and attracts much attention in the fields of games, robotics, and autonomous driving. It is very challenging and devices overwhelming to directly apply RL to real-world environments. Due to the reality gap simulated environ...

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Bibliographic Details
Main Authors:	Hyun-Kyo Lim, Ju-Bong Kim, Ihsan Ullah, Joo-Seong Heo, Youn-Hee Han
Format:	Article
Language:	English
Published:	IEEE 2021-01-01
Series:	IEEE Access
Subjects:	Federated reinforcement learning multi-agent transfer learning gradient sharing
Online Access:	https://ieeexplore.ieee.org/document/9439484/

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