The invention discloses a
satellite group
orbit pursuit decision-making method based on multi-near-end
reinforcement learning. The method comprises the following steps: S1, updating a
satellite state by adopting an eight-order Runge-Kutta method; s2, all satellites in the
satellite group collect state information of each other, a
state vector is constructed, and a strategy and
value network is formed according to the
state vector; selecting and executing an action through a policy network, and updating a
state vector after receiving an environment reward; calculating a
time sequence difference error and a dominant function, and updating the network by using a near-end strategy optimization
algorithm; meanwhile, fusing the strategy networks of the satellites by adopting a federal near-end
algorithm; and S3, carrying out comprehensive performance evaluation on the satellite group, dynamically adjusting an updating strategy of each satellite strategy
network parameter, and continuously optimizing the
overall efficiency of the satellite group. According to the method, efficient cooperation of the satellite groups in a complex environment is ensured, the overall response speed and decision accuracy are improved through continuous learning and adjustment, and efficient and stable task execution is ensured.