Game Decision of Multi-UAV Based on Improved Shark Smell Optimization Algorithm

Lei Sun,Yu Kang,Yunbo Zhao,Yuhui Wang,Tongle Zhou

doi:10.1007/978-981-19-6613-2_647

Game Decision of Multi-UAV Based on Improved Shark Smell Optimization Algorithm

Lei Sun, Yu Kang + Show 3 more

https://doi.org/10.1007/978-981-19-6613-2_647

Copy DOI

Publication Date: Jan 1, 2023

Affiliation: University of Science and Technology of China, Nanjing University of Aeronautics and Astronautics

#Shark Smell Optimization Algorithm #Game Decision + Show 8 more

Abstract
Full-Text PDF
Similar Papers

Abstract

AbstractDecision-making is one of the key technologies in the air combat field. In this work, a game decision method based on an improved shark smell optimization (SSO) algorithm is developed for unmanned aerial vehicles (UAVs). The air combat situation assessment result of multi-UAV is described as an uncertain set, and a game model of game decision is established. Then, to upgrade the efficiency of game decision, an improved \(\theta \)-SSO algorithm is proposed. Finally, the simulation results turn out the effectiveness of the algorithm.KeywordsGame decisionmulti-UAV air combatShark smell optimization

Full Text