Multi-Agent Reinforcement Learning-Based Resource Allocation Scheme for UAV-Assisted Internet of Remote Things Systems
Multi-layered communication networks including satellites and unmanned aerial vehicles
(UAVs) with remote sensing capability are expected to be an essential part of next …
(UAVs) with remote sensing capability are expected to be an essential part of next …
Intelligent resource allocation in UAV-enabled mobile edge computing networks
Unmanned aerial vehicles (UAVs) have been considered as effective flying base stations
(FBSs) to provide on-demand wireless communications. Equipped with computation …
(FBSs) to provide on-demand wireless communications. Equipped with computation …
Energy-efficient multi-uav network using multi-agent deep reinforcement learning
With the explosive growth in mobile data traffic, unmanned aerial vehicles (UAVs) has
received much attention in recent years. While UAV offers a number of benefits, the …
received much attention in recent years. While UAV offers a number of benefits, the …
Energy Consumption Modeling and Optimization of UAV-Assisted MEC Networks Using Deep Reinforcement Learning
Unmanned aerial vehicle (UAV)-assisted multiaccess edge computing (MEC) technology
has garnered significant attention and has been successfully implemented in specific …
has garnered significant attention and has been successfully implemented in specific …
Optimization for master-UAV-powered auxiliary-aerial-IRS-assisted IoT networks: An option-based multi-agent hierarchical deep reinforcement learning approach
This article investigates a master unmanned aerial vehicle (MUAV)-powered Internet of
Things (IoT) network, in which we propose using a rechargeable auxiliary UAV (AUAV) …
Things (IoT) network, in which we propose using a rechargeable auxiliary UAV (AUAV) …
Communication-Assisted Multi-Agent Reinforcement Learning Improves Task-Offloading in UAV-Aided Edge-Computing Networks
Equipping unmanned aerial vehicles (UAVs) with computing servers allows the ground-
users to offload complex tasks to the UAVs, but the trajectory optimization of UAVs is critical …
users to offload complex tasks to the UAVs, but the trajectory optimization of UAVs is critical …
Resource allocation for multi-UAV assisted IoT networks: A deep reinforcement learning approach
YY Munaye, RT Juang, HP Lin… - … on Pervasive Artificial …, 2020 - ieeexplore.ieee.org
The wireless communication system for the massively heterogeneous Internet of Things
(IoT) network hinders the allocation of resources. For this study, an unmanned aerial vehicle …
(IoT) network hinders the allocation of resources. For this study, an unmanned aerial vehicle …
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 …
Blocklength Allocation and Power Control in UAV-Assisted URLLC System via Multi-agent Deep Reinforcement Learning
X Li, X Zhang, J Li, F Luo, Y Huang, X Zhang - International Journal of …, 2024 - Springer
Integration of unmanned aerial vehicles (UAVs) with ultra-reliable and low-latency
communication (URLLC) systems can improve the real-time communication performance for …
communication (URLLC) systems can improve the real-time communication performance for …
Asynchronous Federated Learning for Resource Allocation in Software Defined Internet of UAVs
KI Qureshi, L Wang, X Xiong… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The use of Unmanned Aerial Vehicles (UAVs) as flying base stations to support various
tasks, such as data collection, machine learning (ML) model training, and wireless …
tasks, such as data collection, machine learning (ML) model training, and wireless …