Amazon Technologies, Inc.

Marthinus Coenraad De Clercq Wentzel

Leo Parker Dirac

Sunil Mallya Kasaragod

Bharathan Balaji

Eric Li Sun

Sahika Genc

Brian James Townsend

Sahika Gene

Pramod Ravikumar Kumar

A simulation management service receives a request to perform reinforcement learning for a robotic device. The request can include computer-executable code defining a reinforcement function for training a reinforcement learning model for the robotic device. In response to the request, the simulation management service generates a simulation environment and injects the computer-executable code into a simulation application for the robotic device. Using the simulation application and the computer-executable code, the simulation management service performs the reinforcement learning within the simulation environment.

Reinforcement learning model training through simulation

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.

Simulation orchestration for training reinforcement learning models

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Marthinus Coenraad De Clercq Wentzel