Autonomous Demand-Side Management system based on Monte Carlo Tree Search
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Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/6844296/6850389/06850585.pdf?arnumber=6850585
Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Demand response for residential building heating: Effective Monte Carlo Tree Search control based on physics-informed neural networks;Energy and Buildings;2024-05
2. Towards Understanding the Effects of Evolving the MCTS UCT Selection Policy;2022 IEEE Symposium Series on Computational Intelligence (SSCI);2022-12-04
3. Evolving the MCTS Upper Confidence Bounds for Trees Using a Semantic-inspired Evolutionary Algorithm in the Game of Carcassonne;IEEE Transactions on Games;2022
4. Real-Time Shipboard Power Management Based on Monte-Carlo Tree Search;IEEE Transactions on Power Systems;2022
5. On the Evolution of the MCTS Upper Confidence Bounds for Trees by Means of Evolutionary Algorithms in the Game of Carcassonne;2021 IEEE Symposium Series on Computational Intelligence (SSCI);2021-12-05
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