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Energy and Buildings
This paper is the first part of a two-part investigation of a novel approach to optimally control commercial building passive and active thermal storage inventory. The proposed building control approach is based on simulated reinforcement learning, which is a hybrid control scheme that combines features of model-based optimal control and model-free learning control. An experimental study was carried out to analyze the performance of a hybrid controller installed in a full-scale laboratorydoi:10.1016/j.enbuild.2005.06.002 fatcat:3tov6ao2aff35jdbjur2276c6q