Reinforcement Learning for Decision-Making and Control in Power Systems-Reference-Cited by-同舟云学术

Reinforcement Learning for Decision-Making and Control in Power Systems

Published:2023 Issue: Volume: Page:265-285
ISSN:2509-6427
Container-title:Women in Power
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Author:

Chen Xin,Qu Guannan,Tang Yujie,Low Steven,Li Na

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-29724-3_10

Reference15 articles.

1. Sutton, R. S., & Barto, A. G. (2018). Reinforcement learning: An introduction. MIT press.

2. Chen, X., Qu, G., Tang, Y., Low, S., & Li, N. (2022). Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges. IEEE Transactions on Smart Grid.

3. Bertsekas, D. (2012). Dynamic programming and optimal control: Volume I (Vol. 1). Athena scientific.

4. Watkins, C. J., & Dayan, P. (1992). Q-learning. Machine learning, 8(3), 279–292.

5. Sutton, R. S., McAllester, D., Singh, S., & Mansour, Y. (1999). Policy gradient methods for reinforcement learning with function approximation. Advances in neural information processing systems, 12.

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