Anti-missile Firepower Allocation Based on Multi-agent Reinforcement Learning

Author:

Wang Yuanhao,Du Guo,Liu Yi,Wu Xiang

Publisher

Springer Nature Singapore

Reference19 articles.

1. Yu, J., Xiao, B., Liang, H.: Decomposition modeling of uncertain combat missions for air defense and anti-missile based on IDEF. In: 2022 6th International Conference on Automation, Control and Robots, pp. 176–179. IEEE (2022)

2. Hu, Y., Wang, W., Liu, H., et al.: Reinforcement learning tracking control for robotic manipulator with Kernel-based dynamic model. IEEE Trans. Neural Netw. Learn. Syst. 31(9), 3570–3578 (2019)

3. Lowe, R., Wu, Y.I., Tamar, A., et al.: Multi-agent actor-critic for mixed cooperative-competitive environments. Adv. Neural Inf. Process. Syst. 6832–6393 (2017)

4. Zhao, W.F., Liu, X.L., Ma, C., et al.: Multi-objective fuzzy planning-based dynamic firepower allocation for maritime air defense. Syst. Eng. Electron. 45(3), 347–359 (2023)

5. Zhao, W.F., Chen, J., Wang, Q., et al.: Dynamic firepower assignment for maritime air defense based on reinforcement learning. Acta Armamentarii 32(8), 216–228 (2023)

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