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Simulation orchestration for training reinforcement learning models

机译:强化学习模型训练的仿真编排

摘要

A simulation workflow manager obtains a set of parameters for simulation of a system and training of a reinforcement learning model for optimizing an application of the system. In response to obtaining the set of parameters, the simulation workflow manager configures a first compute node that includes a training application for training the reinforcement learning model. The simulation workflow manager also configures a second compute note with a simulation application to perform the simulation of the system in a simulation environment. Data is generated through execution of the simulation in the second compute node that is provided to the first compute node to cause the training application to use the data to train the reinforcement learning model.
机译:仿真工作流管理器获取一组参数,用于系统仿真和强化学习模型训练,以优化系统应用。作为对获取参数集的响应,仿真工作流管理器配置第一计算节点,该节点包括用于训练强化学习模型的训练应用程序。simulation workflow manager还使用仿真应用程序配置第二个计算注释,以便在仿真环境中执行系统仿真。通过在提供给第一计算节点的第二计算节点中执行模拟来生成数据,以使训练应用程序使用该数据来训练强化学习模型。

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