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Amazon Reinforcement Learning Simplifies Training and Deploying Robots

Amazon launches reinforcement learning tools to manage robots' workflows



Introducing Amazon SageMaker Reinforcement Learning Components for open-source Kubeflow pipelines


SageMaker Reinforcement Learning (RL) trains an RL agent by collecting experience from Gazebo (an open-source software to simulate populations of robots in complex indoor and outdoor environments) in AWS RoboMaker using ROS (a library for building robot applications).


When training is done, the RL agent model is stored in an Amazon S3 bucket, and an Amazon SageMaker inference node can be created for deployment in production. The model is then downloaded to the robot to perform the required tasks.


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