Simulation orchestration for training reinforcement learning models

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 includ...

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Main Authors Sun, Eric Li, Wentzel, Marthinus Coenraad De Clercq, Dirac, Leo Parker, Kumar, Pramod Ravikumar, Balaji, Bharathan, Townsend, Brian James, Gene, Sahika, Mallya Kasaragod, Sunil
Format Patent
LanguageEnglish
Published 30.08.2022
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary: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.
Bibliography:Application Number: US201816201872