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

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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Bibliographic Details
Main Authors: Yufan Ji, Jiang Wang, Weilu Wu, Lunwen Wang, Chuang Peng, Hao Shao
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Communication emitter
motion behavior cognition
deep reinforcement learning
DDPG
attention mechanism
Online Access:https://ieeexplore.ieee.org/document/9309304/

Internet

https://ieeexplore.ieee.org/document/9309304/

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