A survey of the pursuit–evasion problem in swarm intelligence

Z Mu, J Pan, Z Zhou, J Yu, L Cao - Frontiers of Information Technology & …, 2023 - Springer
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 …

An improved approach towards multi-agent pursuit–evasion game decision-making using deep reinforcement learning

K Wan, D Wu, Y Zhai, B Li, X Gao, Z Hu - Entropy, 2021 - mdpi.com
A pursuit–evasion game is a classical maneuver confrontation problem in the multi-agent
systems (MASs) domain. An online decision technique based on deep reinforcement …

Decentralized optimal large scale multi-player pursuit-evasion strategies: A mean field game approach with reinforcement learning

Z Zhou, H Xu - Neurocomputing, 2022 - Elsevier
In this paper, the intelligent design for the pursuit-evasion game with large scale multi-
pursuer and multi-evader has been investigated. Due to the vast number of agents, the …

A survey of adaptive multi-agent networks and their applications in smart cities

N Nezamoddini, A Gholami - Smart Cities, 2022 - mdpi.com
The world is moving toward a new connected world in which millions of intelligent
processing devices communicate with each other to provide services in transportation …

A novel mean-field-game-type optimal control for very large-scale multiagent systems

Z Zhou, H Xu - IEEE Transactions on Cybernetics, 2020 - ieeexplore.ieee.org
In this article, a decentralized adaptive optimal controller based on the emerging mean-field
game (MFG) and self-organizing neural networks (NNs) has been developed for multiagent …

Decentralized adaptive optimal tracking control for massive autonomous vehicle systems with heterogeneous dynamics: A stackelberg game

Z Zhou, H Xu - IEEE Transactions on Neural Networks and …, 2021 - ieeexplore.ieee.org
In this article, a decentralized optimal tracking control problem has been studied for a large-
scale autonomous vehicle system with heterogeneous system dynamics. Due to the …

Learning cooperative strategies in multi-agent encirclement games with faster prey using prior knowledge

T Li, D Shi, Z Wang, H Yang, Y Chen, YY Shi - Neural Computing and …, 2024 - Springer
Multi-agent encirclement with collision avoidance constitutes a common challenge in the
multi-agent confrontation domain, wherein the focus lies in the development of cooperative …

FINNCH: Cooperative Pursuit Navigation for a Pursuer Team to Capture a Single Evader in Urban Environments

X Lou, M Sun, H Yang, S Yang - ISPRS International Journal of Geo …, 2023 - mdpi.com
The development of a cooperative pursuit strategy for capturing esca** criminals or
dangerous animals in urban public safety emergencies is becoming increasingly in demand …

An Imbalanced Mean-Field Game Theoretical Large-Scale Multiagent Optimization With Constraints

S Dey, H Xu - IEEE Transactions on Systems, Man, and …, 2024 - ieeexplore.ieee.org
A novel optimization algorithm has been developed for distributed large-scale multiagent
systems (LS-MASs), specifically focusing on achieving a terminal density constraint. While …

A Distributed Multi-Robot Collaborative Hunting Method in Dynamic Cluttered Environments

C Wang, J Li, M Zhou, L Zhang - 2024 18th International …, 2024 - ieeexplore.ieee.org
The paper proposes a distributed multi-robot cooperative hunting method in cluttered
environments with guaranteed collision avoidance. First, to achieve collision avoidance, a …