基于深度学习的军事辅助决策智能化研究

Research on Intelligence of Military Auxiliary Decision-Making System Based on Deep Learning

军事辅助决策的智能化是我军夺取未来战争主动权的关键,是大数据背景下一体化联合作战的重要支撑;结合深度学习目前的技术瓶颈,深入分析了军事辅助决策走向智能化所面临的难题和挑战;针对战场知识提取、态势理解认知、作战意图预测、自我对抗模拟、人机交互等方面,提出了智能化方法运用的思考和对策,并对战场目标识别、作战意图预测和模拟对抗博弈三个主要问题的模型构建进行了初步探索。

The intelligence of military auxiliary decision-making system is the key to seizing the initiative of the future wars.It will play an important supporting role in the integrated joint operations based on big data.Combined with the current technological bottlenecks of deep learning,we have in-depth analysis of the difficulties and challenges it faces.For battle field knowledge extraction,situational understanding and cognition,operational intent prediction,self-confrontation simulation,and human-computer interaction,the thinking and countermeasures for the application of intelligent methods were proposed.The modeling of the three main issues of battlefield target recognition,operational intent prediction,and simulational confrontation was initially explored.