Great question! Yes, this works much like the doom player. Sensor data (LIDAR, velocity, etc.) becomes the state. You use the score primitive to operate the controls ("What level of braking should be applied" 0: None, 1: just slightly slowing down, 2: there's a suspicious cat on the side of the road you don't trust, ...

Full disclosure, I am not they :=)

This smells like a tool a more broadly capable LLM would take advantage of extremely well.

But the real problem in self driving isn't the decision making but object description. That is, computer vision if with cameras.

Decision making isn't that of a bottleneck I suppose.

99.9% of the time you are right, but in the long tails (construction works, major road damage, temporary road markings that contradict permanent signs) I could see this kind of architecture being useful.