摘要
人工智能技术的发展,以及AlphaGo Zero的成功,让人们看到了指挥控制智能化的曙光.然而战场比棋盘复杂太多,照搬其方法有很大难度,基于学习的人工智能方法无法一揽子解决整个指挥控制智能化问题.从对指挥控制智能化问题的复杂度分析入手,提出分而治之的理念,并尝试将其分解为6个子问题.比较了基于知识、基于学习两种主流人工智能方法,分别对6个子问题做了适用性分析.作为一种观点,供业界争论探讨.
The rapid development of artificial intelligence technology has led to the victory of AlphaGo Zero,making people see the hope of intelligent military command and control.However,battlefield is quite more complex than chess-board.Its method is di±cult to copy,as learning based methods may not solve the whole intelligent military command and control problem.Starting from problem complexity analysis,this paper attempts to decompose the problem into 6 sub-problems.Two kinds of mainstream artificial intelligence methods based on knowledge and learning are compared,and six sub-problems are analyzed respectively.The view point is proposed for debate and exploration.
作者
金欣
JIN Xin(The Information System Important Laboratory,Nanjing Jiangsu 210007,China)
出处
《指挥与控制学报》
2018年第1期64-68,共5页
Journal of Command and Control
关键词
指挥控制
人工智能
知识系统
机器学习
command and control
artificial intelligence
knowledge system
machine learning
