An overview: Attention mechanisms in multi-agent reinforcement learning
K Hu, K Xu, Q Xia, M Li, Z Song, L Song, N Sun - Neurocomputing, 2024 - Elsevier
In recent years, in the field of Multi-Agent Systems (MAS), significant progress has been
made in the research of algorithms that combine Reinforcement Learning (RL) with Attention …
made in the research of algorithms that combine Reinforcement Learning (RL) with Attention …
A graph neural network based deep reinforcement learning algorithm for multi-agent leader-follower flocking
J Xiao, Z Wang, J He, G Yuan - Information Sciences, 2023 - Elsevier
Flocking control is one of the important topics in multi-agent system (MAS), and has great
value in both military and civilian applications. At present, the slow cluster consensus and …
value in both military and civilian applications. At present, the slow cluster consensus and …
Auto-learning communication reinforcement learning for multi-intersection traffic light control
Multi-agent reinforcement learning is a promising solution to achieve intelligent traffic light
control by regarding each intersection as an independent agent. However, agents encounter …
control by regarding each intersection as an independent agent. However, agents encounter …
A multi-agent flocking collaborative control method for stochastic dynamic environment via graph attention autoencoder based reinforcement learning
J Xiao, G Yuan, Z Wang - Neurocomputing, 2023 - Elsevier
The environmental adaptability of the multi-agent flocking collaborative control system is
vital to practical applications. Focusing on the adaptive problem of multi-agent flocking …
vital to practical applications. Focusing on the adaptive problem of multi-agent flocking …
Toward multi-target self-organizing pursuit in a partially observable Markov game
The multiple-target self-organizing pursuit (SOP) problem has wide applications and has
been considered a challenging self-organization game for distributed systems, in which …
been considered a challenging self-organization game for distributed systems, in which …
Joint Optimization of Trajectory Control, Task Offloading, and Resource Allocation in Air–Ground Integrated Networks
In an air–ground integrated network (AGIN), low-altitude unmanned aerial vehicles (UAVs)
and a high-altitude platform (HAP) operate synergistically to support computationally …
and a high-altitude platform (HAP) operate synergistically to support computationally …
Multi-agent Cooperative Area Coverage: A Two-stage Planning Approach Based on Reinforcement Learning
G Yuan, J Xiao, J He, H Jia, Y Wang, Z Wang - Information Sciences, 2024 - Elsevier
Multi-agent area coverage aims to accomplish the complete traversal of the target area
through cooperation between agents. Focusing on the problems of low coverage efficiency …
through cooperation between agents. Focusing on the problems of low coverage efficiency …
Joint Trajectory Control, Frequency Allocation, and Routing for UAV Swarm Networks: A Multi-Agent Deep Reinforcement Learning Approach
Collaborative unmanned aerial vehicle (UAV) swarm networks can effectively execute
various emerging missions such as surveillance and communication coverage. However …
various emerging missions such as surveillance and communication coverage. However …
Emergence of collective adaptive response based on visual variation
J Qi, L Bai, Y Wei, H Zhang, Y Xiao - Information Sciences, 2024 - Elsevier
Abstract Models are constantly being developed to replicate the collective behavior of
biological groups. However, with popular vision-based models, it is difficult to capture the …
biological groups. However, with popular vision-based models, it is difficult to capture the …
Hierarchical RNNs with graph policy and attention for drone swarm
XL Wei, WP Cui, XL Huang, LF Yang… - Journal of …, 2024 - academic.oup.com
In recent years, the drone swarm has experienced remarkable growth, finding applications
across diverse domains such as agricultural surveying, disaster rescue and logistics …
across diverse domains such as agricultural surveying, disaster rescue and logistics …