With the operational advantages of unmanned combat platforms in modern war gradually appearing, the research of unmanned combat platforms has become the focus of all circles. In order to realize intelligent and autonomous unmanned operation in a real sense, a combat mission computer based on AI development board was proposed to be built as the control core of unmanned vehicles, simulate the operational mobility situation diagram of unmanned vehicles, and use the deep reinforcement learning network DQN to establish angle and distance decision-making network, so as to realize intelligent mobility decision-making of unmanned vehicles. The experiment verified that the unmanned vehicle can maneuver to the target area autonomously, which proved that the deep reinforcement learning network can realize the feasibility of platform autonomous and intelligent decision-making, and provided a feasible technical approach and theoretical support for the construction of combat mission computer to realize intelligent, autonomous and unmanned combat in a real sense.


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    Titel :

    Research on intelligent combat decision making based on deep reinforcement learning


    Beteiligte:
    Zaidi, Habib (Herausgeber:in) / Shmaliy, Yuriy S. (Herausgeber:in) / Meng, Hongying (Herausgeber:in) / Kolivand, Hoshang (Herausgeber:in) / Sun, Yougang (Herausgeber:in) / Luo, Jianping (Herausgeber:in) / Alazab, Mamoun (Herausgeber:in) / Wang, Yao (Autor:in) / Chen, Qijie (Autor:in) / Ma, Haiqiang (Autor:in)

    Kongress:

    Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023) ; 2023 ; Wuhan, China


    Erschienen in:

    Proc. SPIE ; 12803


    Erscheinungsdatum :

    16.10.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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