Eavesdropping Game Based on Multi-Agent Deep Reinforcement Learning

被引：0

作者：

Guo, Delin ^{[1
]}

Tang, Lan ^{[1
]}

Yang, Lvxi ^{[2
,3
]}

Liang, Ying-Chang ^{[2
,3
]}

机构：

[1] Nanjing University, Nanjing, China

[2] Southeast University, Nanjing, China

[3] University of Electronic Science and Technology of China, Chengdu, China

来源：

IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC | 2022年 / 2022-July卷

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Computation theory - Deep learning - Game theory - Jamming - Learning algorithms - Learning systems - Multi agent systems - Network layers - Security systems - Stochastic models - Stochastic systems - Transmitters

引用

共 50 条

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[9] Selective Information Communication Considering the Influence of Each Other’s Messages in Multi-Agent Reinforcement Learning
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[10] On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)
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