By experimenting, computers are figuring out how to do things that no programmer could teach them.

Inside a simple computer

a

simulation, a group of self-driving cars are performing a crazy-looking maneuver on a four-lane virtual highway. Half are trying to move from the right-hand lanes just as the other half try to merge from the left. It seems like just the sort of tricky thing that might flummox a robot vehicle, but they manage it with precision.

I’m watching the driving simulation at the biggest artificial-intelligence conference of the year, held in Barcelona this past December. What’s most amazing is that the software governing the cars’ behavior wasn’t programmed in the conventional sense at all. It learned how to merge, slickly and safely, simply by practicing. During training, the control software performed the maneuver over and over, altering its instructions a little with each attempt. Most of the time the merging happened way too slowly and cars interfered with each other. But whenever the merge went smoothly, the system would learn to favor the behavior that led up to it.

https://www.technologyreview.com/s/603501/10-breakthrough-technologies-2017-reinforcement-learning/