A Selective Federated Reinforcement Learning Strategy for Autonomous Driving-Reference-Cited by-同舟云学术

A Selective Federated Reinforcement Learning Strategy for Autonomous Driving

Author:

Fu Yuchuan¹^ORCID,Li Changle¹^ORCID,Yu F. Richard²^ORCID,Luan Tom H.³^ORCID,Zhang Yao⁴

Affiliation:

1. State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, China

2. Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada

3. School of Cyber Engineering, Xidian University, Xi’an, China

4. School of Computer Science, Northwestern Polytechnical University, Xian, China

Funder

National Natural Science Foundation of China

Youth Innovation Team of Shaanxi Universities

Young Talent fund of Association for Science and Technology in Xi’an

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

Reference36 articles.

1. Federated learning in mobile edge networks: A comprehensive survey;lim;arXiv 1909 11875,2019

2. Continuous control with deep reinforcement learning;lillicrap;arXiv 1509 02971,2015

5. Deep gradient compression: Reducing the communication bandwidth for distributed training;lin;arXiv 1712 01887,2017

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