Journal of System Simulation
Abstract
Abstract: With the rapid development of Machine Learning, especially deep learning, it has become an important way of modeling Computer Generated Force (CGF) behavior by ML methods, which can overcome the challenges of traditional methods. The existing research and application of three typical learning methods in CGF behavior modeling are discussed, and the effects of introducing learning into different stages of the typical CGF applications are analyzed, and the function and performance requirements of CGF behavior modeling using machine learning are proposed. Four potential research directions in the field for future are proposed.
Recommended Citation
Qi, Zhang; Zeng, Junjie; Kai, Xu; Long, Qin; and Yin, Quanjun
(2021)
"Behavior Modeling for Computer Generated Forces Based on Machine Learning,"
Journal of System Simulation: Vol. 33:
Iss.
2, Article 5.
DOI: 10.16182/j.issn1004731x.joss.20-0931
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol33/iss2/5
First Page
280
Revised Date
2020-12-24
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.20-0931
Last Page
287
CLC
TP391.9
Recommended Citation
Zhang Qi, Zeng Junjie, Xu Kai, Qin Long, Yin Quanjun. Behavior Modeling for Computer Generated Forces Based on Machine Learning[J]. Journal of System Simulation, 2021, 33(2): 280-287.
DOI
10.16182/j.issn1004731x.joss.20-0931
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons