Autonomous maneuver decision-making for a UCAV in short-range aerial combat based on an MS-DDQN algorithm

To solve the problem of realizing autonomous aerial combat decision-making for unmanned combat aerial vehicles (UCAVs) rapidly and accurately in an uncertain environment, this paper proposes a decision-making method based on an improved deep reinforcement learning (DRL) algorithm: the multi-step double deep Q-network (MS-DDQN) algorithm. First, a six-degree-of-freedom UCAV model based on an aircraft control system is established on a simulation platform, and the situation assessment functions of the UCAV and its target are established by considering their angles, altitudes, environments, missile attack performances, and UCAV performance. By controlling the flight path angle, roll angle, and flight velocity, 27 common basic actions are designed. On this basis, aiming to overcome the defects of traditional DRL in terms of training speed and convergence speed, the improved MS-DDQN method is introduced to incorporate the final return value into the previous steps. Finally, the pre-training learning model is used as the starting point for the second learning model to simulate the UCAV aerial combat decision-making process based on the basic training method, which helps to shorten the training time and improve the learning efficiency. The improved DRL algorithm significantly accelerates the training speed and estimates the target value more accurately during training, and it can be applied to aerial combat decision-making.     

浅析军校图书馆军事类图书的馆藏建设——基于三方统计数据分析

以某军校图书馆军事类图书的馆藏流通数据为例,分析军事类图书的馆藏利用现状。通过对CNKI学术关注度、超星读秀学术搜索以及《世界军事年鉴》专题资讯近年数量变化情况的三方的统计数据进行分析,提出了军校图书馆军事类图书馆藏建设方面的若干建议。     

强化信息意识 提升武警院校图书馆信息服务功能

分析了目前武警院校图书馆在信息服务中存在的问题,提出了加强图书馆信息服务工作的对策：要强化信息意识,抓好信息服务的基础工作;提高人员素质,加强参考咨询,开展定题服务工作。