Reinforcement learning for multi-agent with asynchronous missing information fusion method
Author:
Funder
Key Technologies Research and Development Program
National Natural Science Foundation of China
Natural Science Foundation of Zhejiang Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13042-024-02170-y.pdf
Reference48 articles.
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3. Nguyen TT, Nguyen ND, Nahavandi S (2020) Deep reinforcement learning for multiagent systems: a review of challenges, solutions, and applications. IEEE Trans Cybern 50(9):3826–3839
4. Luis CE, Schoellig AP (2019) Trajectory generation for multiagent point-to-point transitions via distributed model predictive control. IEEE Robot Autom Lett 4(2):375–382
5. Niroui F, Zhang K, Kashino Z, Nejat G (2019) Deep reinforcement learning robot for search and rescue applications: exploration in unknown cluttered environments. IEEE Robot Autom Lett 4(2):610–617
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