OK computer, let鈥檚 see you do this (Image: Katarina L枚fgren/Maskot/Plainpicture)
IT鈥橲 humans versus machine at the Rivers casino in Pittsburgh, Pennsylvania. Four professional poker players are squaring up to an artificial intelligence over two weeks, duking it out by playing a total of 80,000 hands of poker for a $100,000 cash prize.
This may turn out to be the latest instalment in a grand tradition of computers beating us at our own games. In 1997, IBM鈥檚 Deep Blue computer famously beat chess great Garry Kasparov. Four years ago, IBM鈥檚 Watson took part in the TV quiz show Jeopardy! and crushed two contestants with a strong track record. AI has even mastered the popular smartphone game 2048.
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, poker is a tough nut to crack. In a game like chess, everyone knows where all the pieces are on the board. By contrast, poker is a game of imperfect information: players don鈥檛 know for sure what cards the others hold or what will come up next in the deck. That makes it a challenge for any player, human or computer, to choose the right play.
Computer scientists have already made some progress, at least with simpler forms of the game. But the version being played at the Pittsburgh tournament, called Heads Up No Limit Texas Hold 鈥檈m, is 鈥渁 completely different beast鈥�, says pro player Vanessa Selbst. 鈥淭here鈥檚 much more human elements and game strategies to employ, so it鈥檚 a much more complex game.鈥� What鈥檚 more, there are no betting limits, so the computer also has to take into account how much players might stake on each game.
Competing in Pittsburgh is Claudico, a program created at the city鈥檚 Carnegie Mellon University. Claudico taught itself poker skills by playing trillions of games in search of some kind of optimal strategy. Whatever it has picked is pretty good: last year, Claudico beat all 13 other computer competitors at no-limit poker in the annual contest run by the Association for the Advancement of Artificial Intelligence.
Computers have a few edges over humans, says graduate student Noam Brown, part of the team behind Claudico. For example, a computer can switch randomly between various betting strategies, which may confuse human opponents.
On the other hand, Claudico is slow to pick up on and adapt to people鈥檚 playing styles 鈥� something that many pro players do with ease. 鈥淥ne of our big concerns is that the human will be able to identify weaknesses that Claudico has and exploit them,鈥� says Brown.
Because Claudico taught itself to play, even the team that built it don鈥檛 quite know how it picks its moves. 鈥淲e鈥檙e putting our faith in Claudico. It knows much better than we do what it鈥檚 doing.鈥�
聯We鈥檙e putting our faith in our program. It knows what it鈥檚 doing much better than we do聰
Algorithms like those used to play poker could be valuable for other kinds of problems characterised by imperfect information. They could suggest optimal locations for military resources in a war, for example. Rival AIs could also be tasked to negotiate with each other over insurance rates or handle legal squabbles. 鈥淚n society, sometimes you see one side getting screwed over because someone has more lawyers or more information or more resources at their disposal,鈥� says Brown. 鈥淪omething like this can really level the playing field.鈥�
The winner of the poker tournament won鈥檛 be crowned until the event ends on 7 May. Eric Jackson, a software engineer who creates poker bots as a hobby, is cautiously optimistic that Claudico can win. As we went to press, the pros and Claudico .
Even if AI triumphs, it won鈥檛 mean programmers have conquered the game. 鈥淏eating humans decisively would be a landmark, but it wouldn鈥檛 mean the end of work on poker,鈥� says Jackson. 鈥淲e still don鈥檛 know what the perfect strategy is.鈥�
This article appeared in print under the headline 鈥淎I wears its best poker face to take on the pros鈥�
