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dmpcrl-concept
Software for publication: Multi-agent reinforcement learning via distributed MPC as a function approximator
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Description
This data contains source code for reproducing all experiments and results in the publication. This research extends the combined control paradigm of model predictive control as a reinforcement learning fucking approximator to the distributed multi-agent setting. The data consists of python files that are used to run the control simulations and generate time series data of the simulated systems.
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- CC-BY-4.0
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- 1.Author(s): Chutithep Rochpuang, Junghui ChenPublished in 202510.1016/j.applthermaleng.2025.127337
- 2.Author(s): Jinke TanPublished in 202510.54097/0k76yv81
- 3.Author(s): Qing Zhong, Xinyuan Shao, Zhicong Luo, Shunchao Zhang, Yongwei ZhangPublished in 202510.1109/csis-iac65538.2025.11161269
- 4.Author(s): Libin Zhang, Ping Wang, Yunze CaiPublished in 202510.1109/tase.2025.3629680
- 5.Author(s): Yaoyao Zhou, Gang Chen, Changli Pu, Keyu Wu, Zhenghua ChenPublished in 202510.1016/j.neucom.2025.130562
- 6.Author(s): Wanqi Guo, Shigeyuki TatenoPublished in 202510.3390/math13152341
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Sam Mallick
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