%0 Journal Article %A DENG Xin %A NA Jun %A ZHANG Handuo %A WANG Yulin %A ZHANG Bin %T Personalized Adjustment Method of Intelligent Lamp Based on Deep Reinforcement Learning %D 2022 %R 10.3778/j.issn.1002-8331.2009-0505 %J Computer Engineering and Applications %P 264-270 %V 58 %N 6 %X This paper proposes a deep reinforcement learning-based method for adjusting personalized smart lamp brightness. It considers the influence of both natural light and the user’s position on his/her actual visual brightness and sets the light intensity dynamically to meet the user’s personalized habits. After each automatic adjustment, according to whether the user takes further changes manually, positive or negative feedback will be collected to train the reinforcement learning model gradually fits the user’s usage habits. The experiment implements three algorithms of DQN, DDQN, and A3C, respectively, and presents the comparative analysis on the data set generated on the DIALux environment. The hardware and software implementation of the prototype system is also introduced. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2009-0505