Communication is the cornerstone of UAV swarms to transmit information and achieve
cooperation. However, artificially designed communication protocols usually rely on prior …

In recent years, deep reinforcement learning (DRL) has proved its great potential in multi-
agent cooperation. However, how to apply DRL to multi-target tracking (MTT) problem for …

Abstract Multi-Target Tracking Guidance (MTTG) in unknown environments has great
potential values in applications for Unmanned Aerial Vehicle (UAV) swarms. Although Multi …

With the advantages of easy deployment and flexible usage, unmanned aerial vehicle (UAV)
has advanced the multitarget tracking (MTT) applications. The UAV-MTT system has great …

In recent years, deep reinforcement learning (DRL) has developed rapidly and has been
applied to multi-UAV target tracking (MTT) research. However, DRL still faces challenges in …

Past few years have witnessed the widespread adoption of unmanned aerial vehicles
(UAVs) in target tracking for regional monitor and strike. Most existing target tracking …

Various interconnected Internet of Things (IoT) devices have emerged, led by the
intelligence of the IoT, to realize exceptional interaction with the physical world. In this …

In this paper, we propose a distributed multi-agent reinforcement learning (MARL) method to
learn cooperative searching and tracking policies for multiple unmanned aerial vehicles …

In recent years, significant progress has been made in the multi-target tracking (MTT) of
unmanned aerial vehicle (UAV) swarms. Most existing MTT approaches rely on the ideal …

In this article, we propose a novel deep reinforcement learning (DRL) approach for
controlling multiple unmanned aerial vehicles (UAVs) with the ultimate purpose of tracking …