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AI Tested on 'Super Mario Brothers' Game

Eric Bland, Discovery News

There are two broad approaches that Togelius expects programmers will use to keep Mario safe.

The first is artificial evolution. Computer programmers create many different controllers, let them loose on the game, evaluate their effectiveness, eliminate the worst controllers and reproduce the best controllers. Artificial evolution is effective, but time-consuming.

Another technique is called temporal difference learning. Say Mario is next to a short pipe with a mushroom shaped Goomba approaching from behind. Mario can can squish the Goomba or jump over the wall. With temporal difference learning, the AI plays out both scenarios, finds the best one and then applies that to the next scenario. The computer learns from each situation as the game progresses.

Robert Baumgarten is a Ph.D. student at Imperial College London developing his own Mario AI with another approach.

"I gave it all the basic instructions, but I don't really know what the AI would do," said Baumgarten. This technique is called pathfinding, since the computer finds its own way once these instructions are programmed.

At first Baumgarten's AI liked to run fast and constantly jump over enemies, and occasionally into pits. A few tweaks to his program corrected the program, and the computer stopped jumping into holes.

Baumgarten's AI also had some pleasant surprises. Without programming, the AI learned to grab the shells from defeated enemies and use them to destroy other enemies.

"This nice behavior sometimes just appears," said Baumgarten. "We try to optimize the behaviors that will lead to success."

The competition will be decided by the AI that can complete the most levels. The winner will be revealed at two upcoming conferences: the Games Innovation Conference at the end of August and the IEEE Symposium on computational Intelligence and Games in early September.

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