Moving target prediction via application of genetic algorithms

被引：0

作者：

Bala, J ^{[1
]}

Baik, S ^{[1
]}

Hadjarian, A ^{[1
]}

Pachowicz, P ^{[1
]}

机构：

[1] George Mason Univ, Sch Informat Technol & Engn, Fairfax, VA 22030 USA

来源：

6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL XVI, PROCEEDINGS: COMPUTER SCIENCE III | 2002年

关键词：

genetic algorithms; GMTI; prediction; 3D visualization and IN3D;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an approach for inferring an opponents' strategic movements and for displaying such predicted movements in an interactive 3D visualization space. The prediction approach generates new movements based on past behaviors and application of an inheritance mechanism. It applies Genetic Algorithms (GAs) learning techniques to evolve new individuals in the population of movements in order to converge the evolution process toward optimal movements. The approach is implemented into the GEM (Genetic Evolution of Movement) system and its performance has been experimentally evaluated.

引用

页码：365 / 369

页数：5