Automated battlefield simulation command and control using artificial neural networks

I. Jaszlics, S. L. Jaszlics, S. Jones
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引用次数: 2

Abstract

Contemporary distributed interactive battle simulations are becoming increasingly large and complex and therefore difficult to manage. The success of future projects will depend in part on the ability to manage aspects of the command and control surfaces in an automated and highly predictable manner. Artificial intelligence in general and artificial neural networks (ANNs) in particular offer attractive mechanisms to automate command and control. This paper describes the linear interactive activation and competition model ANN, a highspeed, object-oriented model, for use in several battle simulations and has demonstrated that this is a feasible application of the technology.<>
基于人工神经网络的自动化战场模拟指挥与控制
当代分布式交互式战斗模拟正变得越来越庞大和复杂,因此难以管理。未来项目的成功将部分取决于以自动化和高度可预测的方式管理命令和控制面方面的能力。一般来说,人工智能和人工神经网络(ANNs)为自动化指挥和控制提供了有吸引力的机制。本文描述了一种高速的、面向对象的线性交互激活和竞争模型——神经网络(ANN),用于几种战斗模拟,并证明了这是该技术的一种可行应用。
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