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Abstract: A reinforcement learning approach to energy transition planning under uncertainty (AGU25)

A reinforcement learning approach to energy transition planning under uncertainty

Mofan Zhang, Stanford University, Stanford, CA, United States, Morgan Edwards, University of Wisconsin Madison, La Follette School of Public Affairs, Madison, United States, Angelo Carlino, Politecnico di Milano, Department of Electronics, Information, and Bioengineering, Milano, Italy, Franklyn Kanyako, University of Wisconsin–Madison, Madison, United States and Sarah Fletcher, Stanford University, Civil and Environmental Engineering, Stanford, CA, United States
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