Microsoft researchers built AI that used a divide and conquer approach to beat 'Ms. Pac-Man'

The team from Maluuba, a Canadian AI startup that Microsoft acquired early this year have built an AI that got the highest possible score on the Atari 2600 version of Ms. Pac-Man. Building the capabilities of AI agents to tackle video games is a test of the AI systems, but Ms. Pac-Man has proven a tough nut to crack among AI researchers. The Maluuba team, however, managed to get 999,990 points by using an approach they call the Hybrid Reward Architecture.A number of discrete agents were used for the task. Each agent was made to focus on a very narrow goal and was rewarded for meeting very specific objectives, such as avoiding a ghost or gobbling up a particular pellet on the screen. The 150 agents were controlled by a top agent, which processed all the inputs from the agent into the final command. While the number of votes for a particular action was counted, there was also a weight given to the intensity with which an agent wanted to make a move. For example, avoiding a ghost was more important than grabbing a pellet.The researchers managed to crack the game by dividing it into a series of very small problems. The overall architecture of the AI is similar to how the brain is believed to function. Rahul Mehrotra, a program manager at Maluuba said, "A lot of companies working on AI use games to build intelligent algorithms because there’s a lot of human-like intelligence capabilities that you need to beat the games." The research has been published at Arxiv and is available to the public.