Deep reinforcement learning model unmanned aerial vehicle deployment test method and system

The embodiment of the invention provides a deep reinforcement learning algorithm model unmanned aerial vehicle deployment test method and system. The method comprises the steps of receiving state information sent by an unmanned aerial vehicle; and processing the state information of the unmanned aerial vehicle according to a preset test algorithm model to obtain decision action information, and sending the decision action information to the unmanned aerial vehicle. A preset deep reinforcement learning algorithm model is deployed on an algorithm model calculation platform located on the ground,decision action information is sent back to an unmanned aerial vehicle task board to control an unmanned aerial vehicle, and deployment of a general deep reinforcement learning algorithm model calculation operation framework in an unmanned aerial vehicle test system is achieved. 本发明实施例提供一种深度强化学习算法模型无人机部署试验方法和系统，所述方法包括：接收无人机发送的状态信息；将所述无人机的状态信息按照预设的试验算法模型进行处理，获取决策行动信息，发送所述决策行动信息给所述无人机。通过将预设的深度强化学习算法模型部署于位于地面的算法模型计算平台，及发送决策