Accelerating Reinforcement Learning controller training for building energy management: A hybrid co-simulation approach

Publication type: Journal Article
Publication date: 2025-01-06
Taylor & Francis
scimago Q2
wos Q3
SJR: 0.451
CiteScore: 3.5
Impact factor: 1.6
ISSN: 23744731, 2374474X
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Zhou Q. et al. Accelerating Reinforcement Learning controller training for building energy management: A hybrid co-simulation approach // Science and Technology for the Built Environment. 2025. pp. 1-18.
GOST all authors (up to 50) Copy
Zhou Q., Liu M., Wang Z., Fu Y., Gao Y. Accelerating Reinforcement Learning controller training for building energy management: A hybrid co-simulation approach // Science and Technology for the Built Environment. 2025. pp. 1-18.
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TY - JOUR
DO - 10.1080/23744731.2024.2444818
UR - https://www.tandfonline.com/doi/full/10.1080/23744731.2024.2444818
TI - Accelerating Reinforcement Learning controller training for building energy management: A hybrid co-simulation approach
T2 - Science and Technology for the Built Environment
AU - Zhou, Qi
AU - Liu, Mingzhe
AU - Wang, Zhe
AU - Fu, Yangyang
AU - Gao, Yuan
PY - 2025
DA - 2025/01/06
PB - Taylor & Francis
SP - 1-18
SN - 2374-4731
SN - 2374-474X
ER -
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@article{2025_Zhou,
author = {Qi Zhou and Mingzhe Liu and Zhe Wang and Yangyang Fu and Yuan Gao},
title = {Accelerating Reinforcement Learning controller training for building energy management: A hybrid co-simulation approach},
journal = {Science and Technology for the Built Environment},
year = {2025},
publisher = {Taylor & Francis},
month = {jan},
url = {https://www.tandfonline.com/doi/full/10.1080/23744731.2024.2444818},
pages = {1--18},
doi = {10.1080/23744731.2024.2444818}
}