In traditional video games, when a player is offered three choices, the computer doesn’t know what the player will pick. The game computes random choices the player makes and creates a game around it.
Dr. Xingping Sun, math professor at Missouri State University, says this will change.
According to Sun’s research, the computer wouldn’t work to keep up with the player’s choices. Instead, the game could predict what the player would do next. Rather than keep up, it would be leading the way.
He likens it to a passion of his: the ancient board game Go. It is estimated to have more possibilities for moves than atoms in the whole universe.
Working through all of the possible moves, which traditional artificial intelligence does, is a “hopeless way to play the game, even for the fastest computers in the world,” Sun said.
That’s what he thought. But in March 2016, AlphaGo – a program built by Google – beat all the best human Go players for the first time.
Intrigued by the algorithm that let AlphaGo drastically narrow down the possibilities, Sun now employs similar methods to model real-world problems – like weather phenomena and early diagnoses of incurable diseases.
With this same knowledge, video games will continue to evolve.