AWS DeepRacer
Developer Guide

How AWS DeepRacer Works

AWS DeepRacer uses reinforcement learning to enable the AWS DeepRacer 1/18th scale vehicle to drive autonomously. To achieve this, you train and evaluate a reinforcement learning model in a virtual environment with a simulated track. After the training, you upload the trained model artifacts to your AWS DeepRacer vehicle. You can then set the vehicle for autonomous driving in a physical environment with a real track.

Training a reinforcement learning model can be challenging, especially if you're new to the field. AWS DeepRacer simplifies the process by integrating required components together and providing easy-to-follow wizard-like task templates. However, it's helpful to have a good understanding of the basics of reinforcement learning training implemented in AWS DeepRacer.