Decision-Making for Satellite Anti-Interception Missions Leveraging Multi-Agent Reinforcement Learning

Many-to-many spacecraft autonomous evasion missions necessitate highly coordinated decision-making among several spacecraft to successfully avoid interceptions. Conventional control methods often struggle to manage the inherent complexity and uncertainty of these missions. In response to this challe...

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Vydané v:	2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS) s. 1 - 7
Hlavní autori:	Chen, Zixuan, Wang, Jianqi, Wang, Dan, Yu, Sheng, Huo, Jing, Gao, Yang
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 22.09.2023
Predmet:	Heuristic algorithms Machine learning algorithms multi-agent reinforcement learning Reinforcement learning Satellites Space vehicles spacecraft evasion missions spacecraft systems Training Uncertainty
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