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Jose R. Vazquez-Canteli et al.
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Jose R. Vazquez-Canteli et al.
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Yuzhen Peng et al.
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William Valladares et al.
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Dayi Lai et al.
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A review of reinforcement learning for autonomous building energy management
Karl Mason et al.
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Wei Li et al.
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June Young Park et al.
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Mengjie Han et al.
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June Young Park et al.
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Seungjae Lee et al.
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Janine Guenther et al.
BUILDING AND ENVIRONMENT (2019)
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Philip Odonkor et al.
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H. Burak Gunay et al.
SCIENCE AND TECHNOLOGY FOR THE BUILT ENVIRONMENT (2018)
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Mehdi Pazhoohesh et al.
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Hussain Kazmi et al.
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Hiroshi Yoshino et al.
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Da Li et al.
BUILDING AND ENVIRONMENT (2017)
The Occupant Mobile Gateway: A participatory sensing and machine-learning approach for occupant-aware energy management
K. Konis et al.
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Satisfaction based Q-learning for integrated lighting and blind control
Zhijin Cheng et al.
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H. Burak Gunay et al.
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A personalized measure of thermal comfort for building controls
David Daum et al.
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Sam Borgeson et al.
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User behavior in whole building simulation
P. Hoes et al.
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On the behaviour and adaptation of office occupants
Frederic Haldi et al.
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