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Samuel Arzt shows off a project where an AI learns to park a car in a parking lot in a 3D physics simulation.

The simulation was implemented using Unity’s ML-Agents framework (https://unity3d.com/machine-learning).

From the video description:

The AI consists of a deep Neural Network with 3 hidden layers of 128 neurons each. It is trained with the Proximal Policy Optimization (PPO) algorithm, which is a Reinforcement Learning approach.