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Systematic Review on Deep Reinforcement Learning-Based Energy Management for Different Building Types. (2022). Shaqour, Ayas ; Hagishima, Aya.
In: Energies.
RePEc:gam:jeners:v:15:y:2022:i:22:p:8663-:d:976978.

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  1. Reinforcement learning for data center energy efficiency optimization: A systematic literature review and research roadmap. (2025). Elmusrati, Mohammed ; Vlisuo, Petri ; Sharma, Shiva ; Kahil, Hussain.
    In: Applied Energy.
    RePEc:eee:appene:v:389:y:2025:i:c:s0306261925004647.

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  2. Review and Evaluation of Reinforcement Learning Frameworks on Smart Grid Applications. (2023). Michailidis, Panagiotis ; Kosmatopoulos, Elias ; Vamvakas, Dimitrios ; Korkas, Christos.
    In: Energies.
    RePEc:gam:jeners:v:16:y:2023:i:14:p:5326-:d:1192246.

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  33. Energy saving and indoor temperature control for an office building using tube-based robust model predictive control. (2023). Gao, Yuan ; Akashi, Yasunori ; Miyata, Shohei.
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  34. The Impact of Thermo-Modernization and Forecast Regulation on the Reduction of Thermal Energy Consumption and Reduction of Pollutant Emissions into the Atmosphere on the Example of Prefabricated Buildings. (2022). Cieliski, Krzysztof ; Bielskus, Jonas ; Piotrowska-Woroniak, Joanna.
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  35. Systematic Review on Deep Reinforcement Learning-Based Energy Management for Different Building Types. (2022). Shaqour, Ayas ; Hagishima, Aya.
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  36. Multi-agent reinforcement learning dealing with hybrid action spaces: A case study for off-grid oriented renewable building energy system. (2022). Matsunami, Yuki ; Gao, Yuan ; Akashi, Yasunori ; Miyata, Shohei.
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  37. A practical deep reinforcement learning framework for multivariate occupant-centric control in buildings. (2022). Peng, Yuzhen ; Lei, Yue ; Hasama, Takamasa ; Zhan, Sicheng ; Ono, Eikichi ; Chong, Adrian ; Zhang, Zhiang.
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