Multi-agent deep reinforcement learning for trajectory planning in UAVs-assisted mobile edge computing with heterogeneous requirements

In heterogeneous wireless networks, massive user equipments (UEs) generate computing tasks with time-varying heterogeneous requirements. To improve the service quality, this paper formulates a unmanned aerial vehicles (UAVs)-assisted mobile edge computing (MEC) framework for time-varying heterogeneo...

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Vydané v:	Computer networks (Amsterdam, Netherlands : 1999) Ročník 248; s. 110469
Hlavní autori:	Fan, Chenchen, Xu, Hongyu, Wang, Qingling
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.06.2024
Predmet:	Counterfactual inference Deep reinforcement learning Mobile edge computing Unmanned aerial vehicle Whale optimization algorithm Deep reinforcement learning Whale optimization algorithm Unmanned aerial vehicle Counterfactual inference Mobile edge computing
ISSN:	1389-1286, 1872-7069
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