基于多智能体深度强化学习的无人机集群自主决策

Utonomous decision making of UAV cluster with multi-agent deep reinforcement learning

由于传统的无人机由人工进行操控,无人机群在强电磁干扰和复杂多变的战场环境中表现较为呆板。在这项研究中,开发了一种灵活智能的无人机控制器。通过使用一个经过多智能体深度强化学习技术训练的神经网络,无人机可以在飞行中控制自己的行为,从战场环境中获取状态信息,自主决策,并且和其他无人机形成有效战斗队形,灵活协调和配合,并产生了最优的动作。

Because the traditional UAV is controlled manually,UAV cluster is more rigid in the strong electromagnetic interference and complex and changeable battlefield environment.In the study,a flexible and intelligent UAV controller is developed.With a neural network trained by multi-agent deep reinforcement learning technology,UAV can control his be-havior in flight.At the same time,UAV obtains state information from the battlefield environment,makes independent de-cisions,forms an effective combat formation with other UAVs,flexibly coordinates and cooperates with each other,and produces the optimal action.