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Adaptive Multi-Agent Control Strategy in Heterogeneous Countermeasure Environments

Adaptive Multi-Agent Control Strategy in Heterogeneous Countermeasure Environments

Wei Wang, Hui Liu, Wangqun Lin
Copyright: © 2021 |Volume: 12 |Issue: 2 |Pages: 26
ISSN: 1947-8534|EISSN: 1947-8542|EISBN13: 9781799860495|DOI: 10.4018/IJMDEM.2021040103
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MLA

Wang, Wei, et al. "Adaptive Multi-Agent Control Strategy in Heterogeneous Countermeasure Environments." IJMDEM vol.12, no.2 2021: pp.31-56. https://doi.org/10.4018/IJMDEM.2021040103

APA

Wang, W., Liu, H., & Lin, W. (2021). Adaptive Multi-Agent Control Strategy in Heterogeneous Countermeasure Environments. International Journal of Multimedia Data Engineering and Management (IJMDEM), 12(2), 31-56. https://doi.org/10.4018/IJMDEM.2021040103

Chicago

Wang, Wei, Hui Liu, and Wangqun Lin. "Adaptive Multi-Agent Control Strategy in Heterogeneous Countermeasure Environments," International Journal of Multimedia Data Engineering and Management (IJMDEM) 12, no.2: 31-56. https://doi.org/10.4018/IJMDEM.2021040103

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Abstract

In the rapidly changing air combat environment, it is quite difficult for pilots to make speedy and reasonable decisions in a very short period due to lack of experience and the uncertainty of perception situation. Hence, the authors propose an intelligent cognitive tactical strategy framework of air combat on multi-source information in uncertain air combat situations for decision support. A fuzzy inferring tree method is proposed to simulate human intellection. Then, to further improve the accuracy of the reasoning results, a genetic algorithm is introduced to optimize the structure and parameters of fuzzy rules. The simulation results show that the proposed model is reasonable, fast, accurate, repeatable, and fatigue-free, which lays a good foundation for future high-end unmanned combat explorations.

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