In human-computer gaming scenarios, the autonomous decision-making problem of an unmanned combat air vehicle (UCAV) is a complex sequential decision-making problem involving multiple decision-makers. In this paper, an autonomous maneuver decision-making method for UCAV that considers the partially observable states of Human (the adversary) is proposed, building on a game-theoretic approach. The maneuver decision-making process within the current time horizon is modeled as a game of Human and UCAV, which significantly reduces the computational complexity of the entire decision-making process. In each established game decision-making model, an improved maneuver library that contains all possible maneuvers (called the continuous maneuver library) is designed, and each of these maneuvers corresponds to a mixed strategy of the established game. In addition, the unobservable states of Human are predicted via the Nash equilibrium strategy of the previous decision-making stage. Finally, the effectiveness of the proposed method is verified by some adversarial experiments.


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    Titel :

    Autonomous Maneuver Decision-Making of UCAV with Incomplete Information in Human-Computer Gaming


    Beteiligte:
    Shouyi Li (Autor:in) / Qingxian Wu (Autor:in) / Bin Du (Autor:in) / Yuhui Wang (Autor:in) / Mou Chen (Autor:in)


    Erscheinungsdatum :

    2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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