指挥信息系统智能化发展能力演化路线
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摘要
当前指挥信息系统正处于向智能化方向发展的关键时期。系统智能化的核心是自主化,指挥信息系统从自动化转为自主化的重要标志是从基于固定规则转为系统规则可变,逐步具备知识获取、环境理解及方案制定与优选能力。随着人工智能技术的发展,智能化技术分阶段赋能下一代指挥信息系统,以及实现智能化水平的全面提升成为指挥信息系统建设面临的关键问题。将人工智能技术在指挥信息系统中的应用水平划分为5个等级,并分析了下一代指挥信息系统在智能化方向上的能力演进路线及面临的挑战。
The current command information system is in a critical period of intelligent development. The core of intelligent system is autonomy, and the important mark for the command information system to transform from automation to autonomy is to transform from fixed rules to variable system rules, and the capacities of the knowledge acquisition, the environmental understanding, the scheme making and the optimization are acquired gradually. With the development of the artificial intelligence technology, the intelligent technology enables the next generation command information system gradually, and the overall improvement of intelligence level has become a key problem for the command information system construction. The application level of the artificial intelligence technology in the command information system is divided into five grades. The intelligent capacity evolution route and the challenges of the next generation command information system are analyzed.
The current command information system is in a critical period of intelligent development. The core of intelligent system is autonomy, and the important mark for the command information system to transform from automation to autonomy is to transform from fixed rules to variable system rules, and the capacities of the knowledge acquisition, the environmental understanding, the scheme making and the optimization are acquired gradually. With the development of the artificial intelligence technology, the intelligent technology enables the next generation command information system gradually, and the overall improvement of intelligence level has become a key problem for the command information system construction. The application level of the artificial intelligence technology in the command information system is divided into five grades. The intelligent capacity evolution route and the challenges of the next generation command information system are analyzed.
引文
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[3] LIU J Y,LI X L.Artificial intelligence in modeling command and control[C]//2010 2nd International Conference on Computer Modeling and Simulation.Sanya:IEEE,2010:383-386.
[4] SURDU J R,COL J R.Deep green broad agency announcement No.07-56[EB/OL].[2018-07-15].http://www.darpa.mil/ipto/solicitations.
[5] COL J R,SURDU J R.Deep green:commander′s tool for COA′s concept[C]//Computing Communications and Control Technologies (CCCT 2008).Orlando:[s.n.],2008:1-10.
[6] SURDU J R,KITTKA K.The deep green concept[C]//Proceedings of the 2008 Spring Simulation Multiconference.Ottawa:ACM,2008:623-631.
[7] SEFFERS G I.Commanding the future mission[EB/OL].(2016-05-01)[2018-07-15].http://www.afcea.org/content/?q=Article-commanding-future-mission#sthash.O9DjOt3b.dpuf.
[8] 戴浩.人工智能技术及其在指挥与控制领域的应用[EB/OL].[2018-07-15].http://m.sohu.com/a/132-243281_465915.
[9] 金欣.指挥控制智能化问题分析研究[J].指挥与控制学报,2018,4(1):64-68.
[10] 汪霜玲,黄松华,易侃,等.类脑智能及其在下一代指挥信息系统中应用[J].指挥信息系统与技术,2018,9(5):25-30.
[11] Defense Science Board.Summer study on autonomy[R].Washington D.C.:DoD,2016.
[12] 阎岩,唐振民,陆建峰.地面智能机器人自主性评估研究[J].华中科技大学学报(自然科学版),2011,39(S2):68-71.
[13] HUANG H M,JAMES A,ELENA M,et al.Specifying autonomy levels for unmanned systems:intern report[C]//Proceedings of SPIE:the International Society for Optical Engineering.Orlando:SPIE,2004:386-397.
[14] Office of the Secretary of Defense.Unmanned aerial vehicles roadmap 2000-2025[R].Washington D.C.:DoD,2001.
[15] GREENFIELD C.The 5 A′s of artificial intelligence[EB/OL].[2018-06-15].http://www.5AsofAI.com.
[16] 梁健,陈晧晖.基于全分布式处理的统一态势生成技术研究[J].无线电工程,2016,46(1):12-15.
[17] 黄亚锋,李旭东,张航峰.战场态势多尺度表达研究[J].系统仿真学报,2018,30(2):452-464.
[18] 廖鹰,易卓,胡晓峰.基于深度学习的初级战场态势理解研究[J].指挥与控制学报,2017,3(1):67-71.