In this article, a GRU-Multi-agent Proximal Policy Optimization (GRU-MAPPO) algorithm was proposed to address unmanned aerial vehicle (UAV) cooperative air combat decision-making problem. This algorithm adds a layer of GRU to the Actor-Critic network framework, uses update gate to extract the historical temporal information and enhance situational awareness. Finally, experiments in our constructed UAV cooperative air combat environment demonstrate that UAVs using the algorithm proposed in this article can learn effective strategies in air combat environments and achieve high win rates.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    UAV Cooperative Air Combat Maneuvering Decision-Making Using GRU-MAPPO


    Contributors:
    Chen, Caiyi (author) / Guo, Zhengyu (author) / Luo, Delin (author) / Xu, Yang (author) / Duan, Haibin (author)


    Publication date :

    2024-06-18


    Size :

    845517 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    UAV Swarm Cooperative Dynamic Target Search: A MAPPO-Based Discrete Optimal Control Method

    Dexing Wei / Lun Zhang / Quan Liu et al. | DOAJ | 2024

    Free access

    Maneuvering-decision analysis for air-to-air combat

    Wang, H. / Tong, M. | British Library Online Contents | 1997


    Resource Baseline MAPPO for Multi-UAV Dog Fighting

    Zhao, Zhe / Rao, Ying / Long, Han et al. | Springer Verlag | 2022


    Cooperative Combat Decision-making Research for Multi UAVs

    Shao, Jiang / Xu, Yang / Luo, Delin | British Library Online Contents | 2018


    Intelligent Air Combat Maneuvering Decision Based on TD3 Algorithm

    Xiaoyu, Zhou / Jiangtao, Huang / Zhe, Zhu et al. | Springer Verlag | 2023