I'm trying to make an AI car controlled by a neural net.
I saw this two videos: Neural Network Demo and Q Learning and neural network in 2D car driving and I want to replicate that.
I already have the neural net code made, with a back propagation algorithm.
The thing is, I don't know how to reinforce the learning of the net. What kind of value should I use to calculate the error?
My car currently have 5 inputs (similar to the first video), and outputs 2 numbers, 1 which is plugged in the rotation torque of the car, if it's positive it will rotate clock-wise, if it's negative counter-clock-wise, and how much it will turn is based on it's magnitude, it ranges from -1~1, and I mapped it to a desired min-max rotation. The second output number is acceleration, it's from 0~1, but mapped to -10~100 (so it can reverse).