摘要
随着大数据、云计算、物联网等一系列新兴技术的大量涌现,人工智能技术不断取得突破性进展.深度强化学习(deep reinforcement learning,DRL)技术作为人工智能的最新成果之一,正被逐渐引入军事领域中,促使军事领域走向信息化和智能化.在未来战争作战模式及军队发展建设中,网络化、信息化、智能化和无人化形成重要特征,已经成为不可逆转的趋势.因此,在回顾了 DRL基本原理和主要算法的基础上,对当前DRL在武器装备、网络安全、无人机(unmanned aerial vehicle,UAV)编队、智能决策与博弈等方面的应用现状进行了系统的梳理与总结.最后,针对实际推进DRL技术在军事领域应用落地所面临的一系列问题和挑战,提供了未来进一步研究的思路.
Abstract
With the emergence of a series of new technologies,such as big data,cloud computing,internet of things,artificial intelligence technology has made breakthrough progress continuously.As one of the latest achievements in artificial intelligence field,deep reinforcement learning(DRL)technology is being gradually introduced into the military field,which promotes the military field's informationization and intelligent.In the future war operation mode and military development and construction,networking,informationization,intelligence,and unmanned development will become an irreversible trend.Therefore,on the basis of reviewing the basic principles and main algorithms of DRL,this paper systematically combs and summarizes the current application status of DRL in weapons and equipment,network security,unmanned aerial vehicle(UAV)formation,intelligent decision-making and game,etc.Finally,in view of a series of problems and challenges facing the actual application of DRL technology in the military field,this paper provides some ideas for further research in the future.
维普
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