Multi-objective reinforcement learning-based approach for pressurized water reactor optimization-Reference-Cited by-同舟云学术

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Multi-objective reinforcement learning-based approach for pressurized water reactor optimization

Published:2024-09 Issue: Volume:205 Page:110582
ISSN:0306-4549
Container-title:Annals of Nuclear Energy
language:en
Short-container-title:Annals of Nuclear Energy

Author:

Seurin Paul^ORCID,Shirvan Koroush^ORCID

Funder

Exelon Corporation

Publisher

Elsevier BV

Reference62 articles.

1. Constrained policy optimization;Achiam,2017

2. Machine learning for combinatorial optimization: a methodological tour d’horizon;Bengio,2018

3. Curriculum learning;Bengio,2009

4. Neuro-Dynamic Programming;Bertsekas,1996

5. Evolution strategies - A comprehensive introduction;Beyer;Natl. Comput.,2002

Cited by 1 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. Physics-informed Reinforcement Learning optimization of PWR core loading pattern;Annals of Nuclear Energy;2024-12

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