Reinforcement Learning from Algorithm Model to Industry Innovation: A Foundation Stone of Future Artificial Intelligence
DONG Shaokang, CHEN Jiarui, LIU Yong, BAO Tianyi, and GAO Yang
(State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210008, China)
Reinforcement learning (RL) algorithm has been introduced for several decades, which becomes a paradigm in sequential decision-making and control. The development of reinforcement learning, especially in recent years, has enabled this algorithm to be applied in many industry fields, such as robotics, medical intelligence, and games. This paper first introduces the history and background of reinforcement learning, and then illustrates the industrial application and open source platforms. After that, the successful applications from AlphaGo to AlphaZero and future reinforcement learning technique are focused on. Finally, the artificial intelligence for complex interaction (e.g., stochastic environment, multiple players, selfish behavior, and distributes optimization) is considered and this paper concludes with the highlight and outlook of future general artificial intelligence.
artificial intelligence; decision-making and control problems; reinforcement learning