An overview on algorithms and applications of deep reinforcement learning

Abstract

Deep reinforcement learning (DRL) is mainly applied to solve the perception-decision problem, and has become an important research branch in the field of artificial intelligence.Two kinds of DRL algorithms based on value function and policy gradient were summarized, including deep Q network, policy gradient as well as related developed algorithms.In addition, the applications of DRL in video games, navigation, multi-agent cooperation and recommendation field were intensively reviewed.Finally, a prospect for the future research of DRL was made, and some research suggestions were given.

Keywords

• artificial intelligence;deep reinforcement learning;value function;policy gradient;navigation;cooperation;complex environment;generalization;robustness