Communication Emitter Motion Behavior's Cognition Based on Deep Reinforcement Learning

Considering the successful application of deep reinforcement learning (DRL) on tasks of moving objects, this paper innovatively applies deep deterministic policy gradient algorithm (DDPG) to complete the cognition task on multi-dimension and continuous communication emitter motion behavior. First, w...

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Veröffentlicht in:	IEEE access 2021, Vol.9, p.3033-3045
Hauptverfasser:	Ji, Yufan, Wang, Jiang, Wu, Weilu, Wang, Lunwen, Peng, Chuang, Shao, Hao
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms attention mechanism Cognition Cognition & reasoning Communication Communication emitter Computational modeling Data models DDPG Deep learning deep reinforcement learning Emitters motion behavior cognition Robot sensing systems Task analysis Training
Online-Zugang:	Volltext
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