Aiming at the problem of low coverage caused by the difficulty of obtaining the optimal deployment position in existing commonly used distributed deployment algorithms, this paper proposes a three-dimensional (3D) deployment algorithm for Unmanned Aerial Vehicles (UAV) based on potential game. Firstly, a local mutually beneficial game model is designed, and proved the existence of exact potential games and Nash equilibrium in this game model, and the Nash equilibrium solution corresponds to the maximum coverage. Secondly, inspired by the idea of exploration, a solution method based on exploration-based automatic learning machine was designed, and the maximum utility function value of multiple step sizes in the exploration direction is used to update the action selection probability, ensuring the optimal deployment position in each decision cycle. Simulation results show that the proposed distributed deployment algorithm has higher coverage than existing commonly used methods.
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