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A novel decision-making algorithm for beyond visual range air combat based on deep reinforcement learning

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a novel decision-making algorithm based on deep reinforcement learning(DRL) is proposed for the decision-making problem in beyond visual range(BVR) air combat. Firstly, the relative kinematics model of 1 vs 1 air combat is established, and the state space and action space of the fighter are designed. Then, a new reward function is designed according to the situation of the BVR air combat, which is suitable for a wider range of BVR confrontation scenarios, and the construction of a decision-making method based on DRL is completed. Finally, several sets of experimental data are given to verify the effectiveness of the algorithm.

Original languageEnglish
Title of host publicationProceedings - 2022 37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages516-521
Number of pages6
ISBN (Electronic)9781665465366
DOIs
StatePublished - 2022
Event37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022 - Beijing, China
Duration: 19 Nov 202220 Nov 2022

Publication series

NameProceedings - 2022 37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022

Conference

Conference37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022
Country/TerritoryChina
CityBeijing
Period19/11/2220/11/22

Keywords

  • beyond visual range air combat
  • decision-making algorithm
  • deep reinforcement learning

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