Multiple unmanned aerial vehicles (UAVs) are able to efficiently accomplish a variety of
tasks in complex scenarios. However, developing a collision-avoiding flocking policy for …

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 …

For complex functions to emerge in artificial systems, it is important to understand the
intrinsic mechanisms of biological swarm behaviors in nature. In this paper, we present a …

Aiming at the confrontation game problems between pursuit-evasion unmanned surface
vehicles under complex multi-obstacle environment, a pursuit-evasion game strategy is …

In the contemporary landscape, the escalating deployment of drones across diverse
industries has ushered in a consequential concern, including ensuring the security of drone …

It is of great challenge, though promising, to coordinate collective robots for hunting an
evader in a decentralized manner purely in light of local observations. In this paper, this …

Compared with a single robot, Multi-robot Systems (MRSs) can undertake more challenging
tasks in complex scenarios benefiting from the increased transportation capacity and fault …

Abstract Unmanned Surface Vehicles (USVs) have been widely applied in ocean
engineering. However, there are few studies for Pursuit–Evasion Game based on USVs …

Multi-agent pursuit-evasion tasks involving intelligent targets are notoriously challenging
coordination problems. In this paper, we investigate new ways to learn such coordinated …

To solve the problem of multi-target hunting by an unmanned surface vehicle (USV) fleet, a
hunting algorithm based on multi-agent reinforcement learning is proposed. Firstly, the …