指挥控制与仿真2024，Vol.46Issue(3)：18-24,7.DOI:10.3969/j.issn.1673-3819.2024.03.003
基于深度强化学习的作战概念能力需求分析关键技术
Key technologies of operational concept capability requirement analysis based on deep reinforcement learning
摘要
Abstract
Based on the formal description of the operational concept capability requirement analysis,a method of operational concept capability requirement analysis based on DRL(deep reinforcement learning)is designed.The key tech-nologies of this method,such as simulation experiment,surrogate model,reinforcement learning,are analyzed and studied.Through the implementation of key technologies,small sample data sets with high reliability can be obtained through simula-tion experiments;Based on the experience data,the surrogate model of operation concept is constructed,and the model is optimized and trained by using multi-objective optimization algorithm with the high credibility simulation data set as the in-put;Finally,the surrogate model obtained from the training and the DRL framework are interactively optimized to achieve the reverse exploration of the operational concept capability requirements.关键词
作战概念能力需求分析/深度强化学习/代理模型/仿真推演Key words
operational concept capability requirement analysis/DRL(deep reinforcement learning)/surrogate model/simulation deduction分类
计算机与自动化引用本文复制引用
安靖,刘伟,周杰..基于深度强化学习的作战概念能力需求分析关键技术[J].指挥控制与仿真,2024,46(3):18-24,7.基金项目
全军军事类研究生资助课题(JY2020B031) （JY2020B031）
