MW-MADDPG: a meta-learning based decision-making method for collaborative UAV swarm

Unmanned Aerial Vehicles (UAVs) have gained popularity due to their low lifecycle cost and minimal human risk, resulting in their widespread use in recent years. In the UAV swarm cooperative decision domain, multi-agent deep reinforcement learning has significant potential. However, current approach...

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Veröffentlicht in:	Frontiers in neurorobotics Jg. 17; S. 1243174
Hauptverfasser:	Zhao, Minrui, Wang, Gang, Fu, Qiang, Guo, Xiangke, Chen, Yu, Li, Tengda, Liu, XiangYu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Lausanne Frontiers Research Foundation 21.09.2023 Frontiers Media S.A
Schlagworte:	Algorithms Cluster analysis Collaboration Decision making Deep learning Efficiency Evacuations & rescues Learning MADDPG meta learning Model Agnostic Meta Learning (MAML) multi-agent reinforcement learning (MARL) Neuroscience Reinforcement Scheduling UAV Unmanned aerial vehicles
ISSN:	1662-5218, 1662-5218
Online-Zugang:	Volltext
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