Multi-unmanned aerial vehicle base station cooperative path planning method based on meta reinforcement learning

The invention discloses a multi-unmanned aerial vehicle base station cooperative path planning method based on meta reinforcement learning. Comprising the following steps: step 1, establishing a multi-unmanned aerial vehicle auxiliary communication system model; 2, modeling an optimization problem as a Markov decision process; step 3, designing a meta-reviewer algorithm based on the behavior-reviewer architecture; and step 4, enabling multiple unmanned aerial vehicles to interact with the environment by using an asynchronous parallel structure, and iteratively updating network parameters. According to the invention, cooperative coverage can be carried out on the ground users under the condition of ensuring the minimum throughput required by the ground users through the unmanned aerial vehicle group, and the planning efficiency and the service quality of the unmanned aerial vehicle base station are improved. 本发明公开了一种基于元强化学习的多无人机基站协同路径规划方法。包括步骤：步骤1、建立多无人机辅助通信系统模型；步骤2、将优化问题建模为马尔可夫决策过程；步骤3、基于行为者-评论家的架构，设计元评论家算法；步