Mean-field multiagent reinforcement learning : a decentralized network approach
Year of publication: |
2025
|
---|---|
Authors: | Gu, Haotian ; Guo, Xin ; Wei, Xiaoli ; Xu, Renyuan |
Published in: |
Mathematics of operations research. - Hanover, Md. : INFORMS, ISSN 1526-5471, ZDB-ID 2004273-5. - Vol. 50.2025, 1, p. 506-536
|
Subject: | mean-field | multiagent reinforcement learning | neural network approximation | Neuronale Netze | Neural networks | Theorie | Theory | Lernprozess | Learning process | Agentenbasierte Modellierung | Agent-based modeling | Lernen | Learning |
-
Artificial intelligence : can seemingly collusive outcomes be avoided?
Abada, Ibrahim, (2023)
-
Lindkvist, Emilie, (2014)
-
Two-sided deep reinforcement learning for dynamic mobility-on-demand management with mixed autonomy
Xie, Jiaohong, (2023)
- More ...
-
Dynamic programming principles for mean-field controls with learning
Gu, Haotian, (2023)
-
Mean-Field Multi-Agent Reinforcement Learning : A Decentralized Network Approach
Gu, Haotian, (2021)
-
Entropy Regularization for Mean Field Games with Learning
Guo, Xin, (2021)
- More ...