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Efficient multi-agent deep reinforcement learning algorithm for multi UAV collision avoidance

delete2026-03-30
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OA
AI
M
Mohammad Reza Rezaee
N
Nor Asilah Wati Abdul Hamid *
M
Masnida Hussin
Z
Zuriati Ahmad Zukarnain
DOI:10.1016/j.asoc.2026.115145delete
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Abstract

Abstract

En 中文
• Suggest an efficient multi-agent deep reinforcement learning algorithm for UAV collision avoidance in dynamic environments. • Propose an efficient graph attention network architecture for modeling UAV interactions. • Demonstrate improved scalability with increasing numbers of UAVs based on the suggested architecture and curriculum learning.
Keywords:
Unmanned aerial vehicle
Collision avoidance
Multi-agent learning
Deep reinforcement learning
Graph attention network
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

Organization

U
universiti putra malaysia
Scholars:
3.1K
Papers: 1.2K
Citations: 0