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Distributed deep reinforcement learning resource allocation scheme for industry 4.0 Device-To-Device scenarios
Burgueño Romero, Jesús; Adeogun, Ramoni; Liborius Bruun, Rasmus; Morejón García, C. Santiago; De la Bandera Cascales, Isabel; Barco-Moreno, Raquel[et al.] (2021)This paper proposes a distributed deep reinforcement learning (DRL) methodology for autonomous mobile robots (AMRs) to manage radio resources in an indoor factory with no network infrastructure. Hence, deep neural networks ...