There have been a few “firsts” in AI-versus-human gaming lately, and the computers are now beating us at trivia, chess and Go. But in some sense, none of these are really interesting; they’re all games of fact. Poker is different. Aside from computing the odds of holding the winning hand, where a computer would obviously have an advantage, the key to winning in poker is bluffing, and figuring out when your opponent is bluffing. Until recently, this has helped man beat the machine. Those days are over.
Chess and Go are what a game theorist would call games of perfect information: everyone knows everything about the state of the game just from looking at the board, and this means that there is, in principle, a best strategy (series of moves) for every possible position. Granted, it’s hard to figure these out because it’s a big brute-force problem, but it’s still a brute-force problem where computers have an innate advantage. Chess and Go are games where the machines should be winning.
In poker, you don’t know the state of the game because you can’t see your opponent’s cards. And when your opponent signals that it has good cards by betting big, your job is to interpret that signal and raise or fold. A good human poker player can get by on defensive play like this, but the really great poker players also know when to bluff. (As well as when to walk away, and when to run.) This element of strategic deception has been enough in the past to give humans the advantage over the computer’s rock-solid statistics. We’ve out-bluffed the machines.
The Carnegie Mellon team, in addition to throwing tons of computing power at the problem, focused on improving defense. Every night, the computer asked itself what its three biggest mistakes were, and modified its strategies to avoid them the next day. By improving its defense against bluffs in the early phase of the hands, it survived to the later phases, where it had the advantage that it could accurately compute the odds. This may have forced the human players to be riskier than they should before the flop.
We’re dying to see more information and analysis, but we’ll have to wait a couple of months for the paper to be published. Now though, you should put this day on your calendar — the day that the computers called our bluffs.