UAV air combat game confrontation requires a high level of intelligence and autonomy, and needs the support of artificial intelligence technology to effectively improve the ability of autonomous air combat. This paper summarizes the reinforcement learning methods for UAV air combat confrontation. Firstly, the problem and application background of UAV air combat confrontation are introduced. Then, the research status of reinforcement learning methods at home and abroad is analyzed, including basic reinforcement learning, reinforcement learning based on Markov chain and deep reinforcement learning algorithm. On this basis, this paper focuses on the reinforcement learning method of UAV air combat confrontation from the two aspects of existing research results and algorithm application advantages. Finally, the simulation is implemented, and results show the effectiveness of reinforcement learning algorithm in air combat confrontation.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Reinforcement learning technology for air combat confrontation of unmanned aerial vehicle


    Beteiligte:
    Zhou, Huan (Autor:in) / Zhang, Xiaoyan (Autor:in) / Zhang, Zhuoran (Autor:in)

    Kongress:

    International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021) ; 2021 ; Harbin,China


    Erschienen in:

    Proc. SPIE ; 12168


    Erscheinungsdatum :

    18.03.2022





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Electronic confrontation investigation unmanned aerial vehicle and confrontation investigation method thereof

    QI ZHIHENG / WANG XIAOXUAN / GAO FEI et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    Target-borne unmanned aerial vehicle for airspace confrontation

    SUN PEILUN / SUN WEI | Europäisches Patentamt | 2022

    Freier Zugriff

    2v2 Air Combat Confrontation Strategy Based on Reinforcement Learning

    Wang, Jinlin / Zhu, Longtao / Yang, Hongyu et al. | Springer Verlag | 2023


    Cooperative Planning for an Unmanned Combat Aerial Vehicle Fleet Using Reinforcement Learning

    Yuksek, Burak / Umut Demirezen, Mustafa / Inalhan, Gokhan et al. | AIAA | 2021

    Freier Zugriff