Deep multiagent reinforcement learning: Challenges and directions
This paper surveys the field of deep multiagent reinforcement learning (RL). The
combination of deep neural networks with RL has gained increased traction in recent years …
combination of deep neural networks with RL has gained increased traction in recent years …
Global-and-local attention-based reinforcement learning for cooperative behaviour control of multiple UAVs
Due to the strong adaptability and high flexibility, unmanned aerial vehicles (UAVs) have
been extensively studied and widely applied in both civil and military applications. Although …
been extensively studied and widely applied in both civil and military applications. Although …
AoI-aware resource allocation for platoon-based C-V2X networks via multi-agent multi-task reinforcement learning
This paper investigates the problem of age of information (AoI) aware radio resource
management for a platooning system. Multiple autonomous platoons exploit the cellular …
management for a platooning system. Multiple autonomous platoons exploit the cellular …
Multi-Agent Reinforcement Learning-Based Trading Decision-Making in Platooning-Assisted Vehicular Networks
Utilizing the stable underlying and cloud-native functions of vehicle platoons allows for
flexible resource provisioning in environments with limited infrastructure, particularly for …
flexible resource provisioning in environments with limited infrastructure, particularly for …
Deep reinforcement learning for autonomous SideLink radio resource management in platoon-based C-V2X networks: An overview
Dynamic and autonomous SideLink (SL) Radio Resource Management (RRM) is essential
for platoon-based cellular vehicular networks. However, this task is challenging due to …
for platoon-based cellular vehicular networks. However, this task is challenging due to …
Accmer: Accelerating multi-agent experience replay with cache locality-aware prioritization
Multi-Agent Experience Replay (MER) is a key component of off-policy reinforcement
learning (RL) algorithms. By remembering and reusing experiences from the past …
learning (RL) algorithms. By remembering and reusing experiences from the past …
Enhancing Multi-UAV Reconnaissance and Search Through Double Critic DDPG With Belief Probability Maps
B Zhang, X Lin, Y Zhu, J Tian… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) have recently attracted significant attention due to their
potential applications in reconnaissance and search. This paper aims to investigate the …
potential applications in reconnaissance and search. This paper aims to investigate the …
Ai-based secure NOMA and cognitive radio-enabled green communications: Channel state information and battery value uncertainties
S Sheikhzadeh, M Pourghasemian… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In this paper, the security-aware robust resource allocation in energy harvesting cognitive
radio networks is considered with cooperation between two transmitters while there are …
radio networks is considered with cooperation between two transmitters while there are …
AoI-driven fresh situation awareness by UAV swarm: Collaborative DRL-based energy-efficient trajectory control and data processing
In many delay-sensitive monitoring and surveillance applications, unmanned aerial vehicles
(UAVs) can act as edge servers in the air to coordinate with base stations (BSs) for in-situ …
(UAVs) can act as edge servers in the air to coordinate with base stations (BSs) for in-situ …
Building a connected communication network for UAV clusters using DE-MADDPG
Z Zhu, N Xie, K Zong, L Chen - Symmetry, 2021 - mdpi.com
Clusters of unmanned aerial vehicles (UAVs) are often used to perform complex tasks. In
such clusters, the reliability of the communication network connecting the UAVs is an …
such clusters, the reliability of the communication network connecting the UAVs is an …