This empirical study examines the impact of environmental regulations on carbon productivity under varying conditions using panel data from Chinese provinces from 2011 to 2019. Prior research has reported inconsistent results regarding the relationships between these variables. We developed a spatial Durbin model (SDM) and tested the non-linear effects of environmental regulation on carbon productivity from a spatial linkage perspective.
View Article and Find Full Text PDFThe combination of reinforcement learning with deep learning is a promising approach to tackle important sequential decision-making problems that are currently intractable. One obstacle to overcome is the amount of data needed by learning systems of this type. In this article, we propose to address this issue through a divide-and-conquer approach.
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