DQ-GAT: Towards Safe and Efficient Autonomous Driving With Deep Q-Learning and Graph Attention Networks-Reference-Cited by-同舟云学术

DQ-GAT: Towards Safe and Efficient Autonomous Driving With Deep Q-Learning and Graph Attention Networks

Author:

Cai Peide¹^ORCID,Wang Hengli¹^ORCID,Sun Yuxiang²^ORCID,Liu Ming³^ORCID

Affiliation:

1. Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, SAR, China

2. Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China

3. Thrust of Robotics and Autonomous Systems, The Hong Kong University of Science and Technology (Guangzhou), Nansha, Guangzhou, Guangdong, China

Funder

Zhongshan Science and Technology Bureau

Foshan-HKUST

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

Reference46 articles.

1. Noisy networks for exploration;fortunato;Proc Int Conf Learn Represent,2018

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