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- W4287827989 abstract "Sequential Model-based Bayesian Optimization has been successful-ly applied to several application domains, characterized by complex search spaces, such as Automated Machine Learning and Neural Architecture Search. This paper focuses on optimal control problems, proposing a Sequential Model-based Bayesian Optimization framework to learn optimal control strategies. A quite general formalization of the problem is provided, along with a specific instance related to optimization of pumping operations in an urban Water Distri-bution Network. Relevant results on a real-life Water Distribution Network are reported, comparing different possible choices for the proposed framework." @default.
- W4287827989 created "2022-07-26" @default.
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- W4287827989 date "2020-03-09" @default.
- W4287827989 modified "2023-09-27" @default.
- W4287827989 title "Learning Optimal Control of Water Distribution Networks through Sequential Model-based Optimization" @default.
- W4287827989 doi "https://doi.org/10.48550/arxiv.2003.04268" @default.
- W4287827989 hasPublicationYear "2020" @default.
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