Article by Hollie Wilcox

Already supercomputers have establishes their superiority over humans at chess, and are just beginning to demonstrate their prowess at the ancient game of go, a game so complex that it has more positions than the total number of sub-atomic particles in the total universe. Now the supercomputer is learning to play poker, and is proving to be a mean player.

Big Blue, the IBM computer that beat the world chess champion Garry Kasparov, started it off, (though Kasparov did subsequently accuse the computer boffins of cheating.) Next came the game of draughts; a computer programme was developed that was shown to be invincible against any human player. More recently a computer has beaten a high ranking Dan Go player, which is a feat that nobody thought possible. These computers combined huge number crunching capabilities with massive databases of historical games in order to compute their winning strategies.

Can these approaches win at poker? Can a supercomputer beat an expert human poker player? This question was asked at a poker room in a casino at Las Vegas and … the computer won, taking a line up of top world-class poker players to the cleaners.

The game they were playing was heads up, limit Texas Hold’em with two players, and it is in this version of the game where the computer excels. The computer is not so good at multi-player games, at least not yet. The people who are developing the software believe that they are getting there. They believe that by the end of the decade they will be able to take on top class players at no-limit Hold’em.

The challenge is getting the computer to come up with optimal decisions in a game where some of the information is concealed, that is different players have access to different information. This means that the number of nodes on the decision tree is huge. The number of possible game permutations even in limit Hold’em is over one billion billion, consequently some approximations are required. As with chess computers, the software interrogates a massive database of over 800 million simulated hands in order to learn the optimum strategy.

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