摘要
feature representations from a large amount of data,and use reinforcement learning to learn the best strategy to complete the task.Through the combination of deep learning and reinforcement learning,end-to-end input and output can be achieved,and substantial breakthroughs have been made in many planning and decision-making systems with infinite states,such as games,in particular,AlphaGo,robotics,natural language processing,dialogue systems,machine translation,and computer vision.In this paper we have summarized the main techniques of deep reinforcement learning and its applications in image processing.
基金
This work was supported in part by the Open Research Project of State Key Laboratory of Novel Software Technology under Grant KFKT2018B23
the Priority Academic Program Development of Jiangsu Higher Education Institutions,the 2018 Tiancheng Huizhi Innovation Promotion Education and Scientific Research Innovation Fund of the Ministry of Education under Grant 2018A03038 and the Open Project Program of the State Key Lab of CAD&CG(Grant No.A1916),Zhejiang University.
