Cooperative multi-agent deep reinforcement learning for reliable and energy-efficient mobile access via multi-UAV control
This paper addresses a novel multi-agent deep reinforcement learning (MADRL)-based
positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration (ie, UAVs …
positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration (ie, UAVs …
Cooperative Multi-UAV Positioning for Aerial Internet Service Management: A Multi-Agent Deep Reinforcement Learning Approach
This paper proposes a novel multi-agent deep reinforcement learning (MADRL)-based
positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration in mobile …
positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration in mobile …
QoE-driven adaptive deployment strategy of multi-UAV networks based on hybrid deep reinforcement learning
Y Zhou, X Ma, S Hu, D Zhou… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) serve as aerial base stations to provide controlled
wireless connections for ground users. Due to their constraints on both mobility and energy …
wireless connections for ground users. Due to their constraints on both mobility and energy …
Coordinated multi-agent deep reinforcement learning for energy-aware UAV-based big-data platforms
This paper proposes a novel coordinated multi-agent deep reinforcement learning (MADRL)
algorithm for energy sharing among multiple unmanned aerial vehicles (UAVs) in order to …
algorithm for energy sharing among multiple unmanned aerial vehicles (UAVs) in order to …
Trajectory design and access control for air–ground coordinated communications system with multiagent deep reinforcement learning
Unmanned-aerial-vehicle (UAV)-assisted communications has attracted increasing attention
recently. This article investigates air–ground coordinated communications system, in which …
recently. This article investigates air–ground coordinated communications system, in which …
Distributed energy-efficient multi-UAV navigation for long-term communication coverage by deep reinforcement learning
In this paper, we aim to design a fully-distributed control solution to navigate a group of
unmanned aerial vehicles (UAVs), as the mobile Base Stations (BSs) to fly around a target …
unmanned aerial vehicles (UAVs), as the mobile Base Stations (BSs) to fly around a target …
UAV-enabled Collaborative Beamforming via Multi-Agent Deep Reinforcement Learning
In this paper, we investigate an unmanned aerial vehicle (UAV)-assistant air-to-ground
communication system, where multiple UAVs form a UAV-enabled virtual antenna array …
communication system, where multiple UAVs form a UAV-enabled virtual antenna array …
Decentralized trajectory and power control based on multi-agent deep reinforcement learning in UAV networks
Unmanned aerial vehicles (UAVs) are capable of enhancing the coverage of existing
cellular networks by acting as aerial base stations (ABSs). Due to the limited on-board …
cellular networks by acting as aerial base stations (ABSs). Due to the limited on-board …
Multiagent deep reinforcement learning for wireless-powered UAV networks
Unmanned aerial vehicles (UAVs) have attracted much attention lately and are being used
in a multitude of applications. But the duration of being in the sky remains to be an issue due …
in a multitude of applications. But the duration of being in the sky remains to be an issue due …
Multi-agent deep reinforcement learning for efficient passenger delivery in urban air mobility
It has been considered that urban air mobility (UAM), also known as drone-taxi or electrical
vertical takeoff and landing (eVTOL), will play a key role in future transportation. By putting …
vertical takeoff and landing (eVTOL), will play a key role in future transportation. By putting …