Improving multi-UAV cooperative path-finding through multiagent experience learning
Author:
Funder
the Science and Technology Innovation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05771-w.pdf
Reference41 articles.
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2. Yu YP, Duan HB Yuan WM (2022) Pursuit-evasion control for uav swarm imitating the intelligent behavior in hawks-starlings. J Command Control 8(422-433)
3. Feng L, Ruixuan W, Kai Z, Chao D (2022) Research on multi-uav roundup strategy based on the unity of group will. J Beijing University Aeronaut Astronaut 48(2241-2249). https://doi.org/10.13700/j.bh.1001-5965.2021.0109
4. Canese L, Cardarilli GC, Di Nunzio L, Fazzolari R, Giardino D, Re M, Spanò S (2021) Multi-agent reinforcement learning: A review of challenges and applications. Appl Sci 11(11):4948. https://doi.org/10.3390/app11114948
5. Du W, Ding S (2021) A survey on multi-agent deep reinforcement learning: from the perspective of challenges and applications. Artif Intell Rev 54(5):3215–3238. https://doi.org/10.1007/s10462-020-09938-y
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