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A Behavior Optimization Method for Unmanned Combat Aerial Vehicles Using Matrix Factorization

Title
A Behavior Optimization Method for Unmanned Combat Aerial Vehicles Using Matrix Factorization
Author
신동민
Keywords
Behavior optimization; unmanned vehicle; matrix factorization; reinforcement learning; situation-behavior matrix
Issue Date
2020-06
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE ACCESS, v. 8, page. 100298-100307
Abstract
One of the fundamental technologies for unmanned combat aerial vehicles and combat simulators is behavior optimization, which finds a behavior that maximizes the probability of winning a battle. With the advent of military science, combat logs became available, allowing machine learning algorithms to be used for the behavior optimization. Due to implicit attributes such as the experience of an operator that are not explicitly presented in log data, existing methods for behavior optimization have limitations in performance improvement. Furthermore, specific behaviors occur with low frequency, resulting in a dataset with imbalanced and empty values. Therefore, we apply a matrix factorization (MF) method, which is one of latent factor models and known for sophisticated imputation of empty values, to the behavior optimization problem of unmanned combat aerial vehicles. A situation-behavior matrix, whose elements are ratings indicating the optimality of behaviors in situations, is defined to implement the MF based method. Experiments for performance comparison were conducted on combat logs, in which the proposed method yielded satisfactory results.
URI
https://ieeexplore.ieee.org/document/9103002https://repository.hanyang.ac.kr/handle/20.500.11754/163425
ISSN
2169-3536
DOI
10.1109/ACCESS.2020.2998189
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > INDUSTRIAL AND MANAGEMENT ENGINEERING(산업경영공학과) > Articles
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