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Poker Program Battles Humans In Vegas
Bridger writes "Poker software called Polaris will play a rematch against human players during the 2008 World Series of Poker in Las Vegas.
Developed by an artificial intelligence group at the University of Alberta in Canada, Polaris will be pitted against several professionals at the Rio Hotel between July 3rd and 6th. 'It's possible, given enough computing power, for computers to play "perfectly," where over a long enough match, the program cannot lose money,"' said associate professor Michael Bowling.'"
One intelligent comment on this thread. We can model that with a Poisson distribution.
What was your tell? Translating "mathematically optimum poker" to "immediate pot odds". Optimum? Which optimum? You mean there's more than one? I fold.
OK, what you say is right, but it applies to two-person, zero-sum games. In multi-player games, no strategy is immune to collusion.
Let's refer to optimum play from the conventional game-theoretic context as the unbeatable strategy. Such a two person, zero-sum game such a strategy exists.
It's not necessarily an easy computation. It's a randomized strategy which can be computed before-hand. The U of A people are better are performing this computation.
Even so, they had to simplify the betting structure to make the problem tractable. This is the reason they chose Limit Hold'em. Fewer betting states, smaller game tree, exponentially faster solution time.
There is no particular challenge to No Limit, if the number of allowable betting states were similarly constricted. I think it would be hard to sufficiently constrict this, because strategy would vary as a function of chip stack for both competitors. Maybe it could be roughly interpolated.
As far as randomized play is concerned, the unbeatable strategy tends to be far more randomized than most humans. One expert who played against the U of A system a while back said that his first session was a nightmare until he learned that he couldn't bluff the computer out. The computer had a tendency to call aggressive betting. It expected highly randomized bids based on its own bidding structure, so didn't make a strong inference of strength when confronted by the behaviour.
What few seem to understand is that the unbeatable solution is entirely unlike poker. The unbeatable solution rarely wins. The unbeatable solution will often draw against strategies with glaring weaknesses. It won't ever be beaten, but it also won't maximize advantage of opponent's weaknesses.
Why not? Because it's impossible to take advantage of the weakness in an opponent without exposing yourself to a counter-measure where you would lose (you must stray from the unbeatable path). When you take advantage of a weak opponent, you do it on faith that the opponent is too dumb to spring the optimal counter-measure to your strategic adaptation.
The theory that U of A employs has far less to say about exploiting the weaknesses of your adversary. To do so requires exposing a weakness in your own strategy. How does the algorithm judge whether the exposed weakness is acceptable? Even poor human players can spot certain kinds of weaknesses quickly. There are other weaknesses an expert might not immediately spot. How does the program know which weaknesses are a risk against which players? It doesn't fall out of game theory, it's a matter of human cognition and psychology, and our model for this is far from complete.
One thing we need to include in this model is the incredible difficulty in explaining to most humans that winning in poker and not losing in poker are entirely different enterprises, with entirely different theoretical foundations. Commander Data has trouble assimilating that fact. 100 trillion brain cells and most of us can't reliably multiply a pair of two digit numbers. If computers had invented humans as part of a BI program (biological intelligence), humans would have been tossed aside as barely having achieved perfect game play at Tic-Tac-Toe. What use is 100 trillion brain cells that can't reliably compute a 15% tip after a heavy lunch? Many computers would like to know.
As computers became better at chess, chess as a human enterprise was somewhat devalued. Few of us wish to put the work into it that the modern theory requires.
I fear the same will soon happen with poker. As the elements of the unbeatable strategy become better known, the relatively inexperienced players can hunker down and not lose much money. They won't be able to win, either, because t