Microsoft AI first to reach perfect Ms Pac-Man score
The feat is notable because when Ms Pac-Man was developed in the eighties, it was programmed to be less predictable than the original Pac-Man, so that it would be tougher for players to beat it.
As opposed to developing a single intelligent agent to learn the game, the team used a number of simpler intelligent agents to each learn a single aspect of the game.
"By breaking up a problem in this way, it becomes easier to learn, as there are now many agents that learn very simple tasks, instead of just one agent that learns a very complex task," Forbes reported on Wednesday.
Ms Pac-Man has remained elusive for years owing to the game's intentional lack of predictability.
Several people have tried to reach Ms Pac-Man's top score, only coming as close as 266,330 on the "
The researchers believe that breaking up complex problems into simpler, smaller problems can make it much easier for deep learning systems to handle.
That, in turn, could be applied to lots of real-world tasks in the near future.