I set up a quick environment to test the idea out. Bottom left is a visualization of the neural grid. It has 4,096 neurons so it only fills up the bottom of the square. On the right is the race track. It is a super simple track where the AI only needs to turn left. If the car drives off the track (the white ring) then it kills the AI and moves on. If the AI is too slow it is also killed.
Top left are stats showing progress. I'm using natural selection to tune the neural grid since modern neural net approaches wouldn't really work.
At this moment, it's functionally identical to a normal neural network. Programing a neural network to do this with natural selection is borderline trivial. The big challenge for the AI to overcome is that the controls flip after the second lap. Left swaps with right and gas swaps with brake. A neural network with identical inputs would not be able to handle this. That AI would crash into a wall almost instantly even if it was mathematically perfect.
I have yet to test my AI on this so maybe it'll fail just as bad, but that's the goal: a neural brain that is actively thinking and not just reacting.
Current record is 11.8 radians before going off track.
