One of the proving grounds for artificial intelligence is games. Classic games have a fixed set of rules, and these make it easier for researchers to develop new techniques and algorithms that enable computers to play (and hopefully win) various games. Tic-tac-toe, checkers, and chess are all games where researchers have developed software that is capable of winning or drawing when paired off against the best human players in the world. Last weekend, researchers at the University of Alberta added another classic game to this list: poker. In a series of matches that took place over the Fourth of July weekend in Las Vegas, the researchers’ Polaris poker program won against a group of top-ranked online poker players.
The first three games mentioned above are known as perfect information games. In games of this type, each player has all the available knowledge about the current state of the game. With that information, the player can, in theory, work out every possible outcome from that point. Given a computer’s ability to evaluate hundreds of thousands (or more) of scenarios each second, they are an ideal tool for calculating probabilities in such games. Theoretically, with enough computing power, every possible outcome at each point in the game could be calculated, and a computer could never lose. (link)

