CNN data: Human played the driving simulation Instead of a list of manual rules, we used a convolutional neural network A policy takes in a state and outputs an action In behavioral cloning, the policy tries to mimic what a human would do Slow down + turn until the front is a road Turn in the direction with more road pixels (action)ģ. Count the road pixels on the left and right half of the grid If the front of the car is a road (state): What we see What the computer sees as road Using our road image, separate road pixel colours from all other colours To do (Do we want the car to be in the left lane? Right Rewards - Basically what we want the self driving car State space - All the possible states the self driving carĬan be in - write out 96x96x3 images, put an image onĪction space - All the possible actions the self driving
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