Principle Analysis on AlphaGo and Perspective in Milltary Application of Artificial Intelligence
TAO Jiu-Yang1,2 WU Lin1 HU Xiao-Feng1
1. Department of Information Operation & Command Training, National Defense University, Beijing 100091, China
2. College of Command Information Systems, PLA University of Science & Technology, Nanjing Jiangsu 210007, China
Abstract：Compared with chess-playing program ”Deep Blue”, supervised learning of policy networks，rollout policy，reinforcement learning of policy networks and reinforcement learning of policy networks of AlphaGo are studied. A Monte Carlo tree search(MCTS) algorithm guiding by the policy and value networks is analyzed. Based on AlphaGo’s technological breakthroughs, potential applications of artificial intelligence(AI) in physics domain, information domain, cognition domain and social domain of war space are forecasted, and AI programs funded by Defense Advanced Research Projects Agency(DARPA) are analyzed. Finally，the revolutionary impacts of AI on military domain are studied based on the Observation, Orientation, Decision, Action(OODA) loop theory.
陶九阳, 吴琳, 胡晓峰. AlphaGo 技术原理分析及人工智能军事应用展望[J]. 指挥与控制学报, 2016, 2(2): 114-120.
TAO Jiu-Yang, WU Lin, HU Xiao-Feng. Principle Analysis on AlphaGo and Perspective in Milltary Application of Artificial Intelligence. Journal of Command and Control, 2016, 2(2): 114-120.
2016, Vol. 2 
