Work

Symmetry-Augmented Multi-Agent Reinforcement Learning for Scalable UAV Trajectory Design and User Scheduling

Year: 2024

Type: article

Source: IEEE Transactions on Mobile Computing

DOI: 10.1109/tmc.2024.3437679

Authors: Xuanhan Zhou, Jun Xiong, Haitao Zhao, Chao Yan, Jibo Wei

Institutions: National University of Defense Technology, Nanjing University of Aeronautics and Astronautics

Language: English

Topic: UAV Applications and Optimization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: closed

Funders: National Natural Science Foundation of China, Natural Science Foundation of Hunan Province

Awards: G1058793228, G2605822748, G3813970528, G4185544572, G8540275219, G9000332396

OpenAlex ID: W4401452427

FWCI: 2.448

Cites: 41

Cited by: 14

Related to: 10