Research on Target Defense Strategy Based on Deep Reinforcement Learning

Research on Target Defense Strategy Based on Deep Reinforcement Learning

Considering the natural advantages of deep reinforcement learning algorithms in dealing with continuous control problems, especially for dynamic interactions, these algorithms can be applied to solve the Attacker-Defender-Target (ADT) game problem. In this paper, the deep deterministic policy gradie...

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Bibliographic Details
Main Authors: Yuelin Luo, Tieqiang Gang, Lijie Chen
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
ADT game
target defense problem
deep reinforcement learning
DDPG
Online Access:https://ieeexplore.ieee.org/document/9785778/

Internet

https://ieeexplore.ieee.org/document/9785778/

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