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Deep Reinforcement Learning Fundamentals, Research and Applications
Penulis: Hao Dong, Zihan Ding, Shanghang Zhang •
Identifier: --haodongzih-472
Deep reinforcement learning (DRL) combines deep learning (DL) with a reinforcement learning (RL) architecture. It has been able to perform a wide range of complex decision-making tasks that were previously intractable for a machine. Moreover, DRL has contributed to the recent great successes in artiï¬Âcial intelligence (AI) like AlphaGo and OpenAI Five. Indeed, DRL has opened up many exciting avenues to explore in a variety of domains such as healthcare, robotics, smart grids, and ï¬Ânance.