Multi-Agent Deep Reinforcement Learning Based Trajectory Planning for
Multi-UAV Assisted Mobile Edge Computing

Multi-Agent Deep Reinforcement Learning Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing

23 September 2020

Liang Wang

Papers citing "Multi-Agent Deep Reinforcement Learning Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing"

6 / 6 papers shown

Title
Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics Yahao Ding Zhaohui Yang Viet Quoc Pham Zhaoyang Zhang M. Shikh-Bahaei 21 31 0 03 Jan 2023
Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Survey Harrison Kurunathan Hailong Huang Kai Li Wei Ni E. Hossain 13 70 0 07 Nov 2022
Multiscale Adaptive Scheduling and Path-Planning for Power-Constrained UAV-Relays via SMDPs Bharath Keshavamurthy Nicolò Michelusi 14 1 0 16 Sep 2022
Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing Wei Xu Zhaohui Yang Derrick Wing Kwan Ng Marco Levorato Yonina C. Eldar Mérouane Debbah 24 398 0 01 Jun 2022
Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence Pengjin Wei Kun Guo Ye Li Jue Wang W. Feng Shi Jin Ning Ge Ying-Chang Liang 21 45 0 27 Jan 2022
Deep Reinforcement Learning-Based Long-Range Autonomous Valet Parking for Smart Cities Muhammad Khalid Liang Wang Kezhi Wang Cunhua Pan N. Aslam Yue Cao 11 10 0 23 Sep 2021