Hierarchical Reinforcement Learning for Air-to-Air Combat-Reference-Cited by-同舟云学术

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Hierarchical Reinforcement Learning for Air-to-Air Combat

Published:2021-06-15 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Unmanned Aircraft Systems (ICUAS)
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Author:

Pope Adrian P.,Ide Jaime S.,Micovic Daria,Diaz Henry,Rosenbluth David,Ritholtz Lee,Twedt Jason C.,Walker Thayne T.,Alcedo Kevin,Javorsek Daniel

Funder

Defense Advanced Research Projects Agency

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9476247/9476672/09476700.pdf?arnumber=9476700

Cited by 81 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. UAV air combat autonomous trajectory planning method based on robust adversarial reinforcement learning;Aerospace Science and Technology;2024-10

2. Learning and Fast Adaptation for Air Combat Decision with Improved Deep Meta-reinforcement Learning;International Journal of Aeronautical and Space Sciences;2024-09-09

3. An evolutionary multi-agent reinforcement learning algorithm for multi-UAV air combat;Knowledge-Based Systems;2024-09

4. Cooperative decision-making algorithm with efficient convergence for UCAV formation in beyond-visual-range air combat based on multi-agent reinforcement learning;Chinese Journal of Aeronautics;2024-08

5. Unit coordination knowledge enhanced autonomous decision-making approach of heterogeneous UAV formation;Chinese Journal of Aeronautics;2024-08

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