Ian Ayres is an economist and lawyer at Yale and the author of Super Crunchers, which we excerpted here. He has agreed to write occasional guest posts on our blog, which delights us, since he has a lot of compelling interests and insights.
Ian is not the only notable guest blogger who will turn up on this site in the future — although, in keeping with the casual and random nature of this blog, I don’t want to make any promises since we tend to play things by ear. Suffice it to say that we will continue to strive to bring you the best in arcane, trivial, and time-wasting blogification by the likes of ourselves, Ian Ayres, and sundry others. — SJD
It is not an opportune time to start an online gambling site for checkers.
In July, researchers at University of Alberta “solved the game” using brute computer force. As such, their computer knew the best strategy to play in any of the possible 50 billion checker positions. Humans should now be very scared to bet money against any virtual opponent, for fear that they are really facing the Alberta computer or its clone. (You also wouldn’t want to play a money game against a computer in Connect Four or Othello, or even backgammon.)
What’s true for checkers is also becoming true for poker. The same group at Alberta has just shown that their Polaris program is on the verge of taking down poker professionals. In the recent “Man vs. Machine” Poker Championship, Phil “The Unabomber” Laak and Ali Eslami barely beat Polaris two sessions to one (with one a virtual draw). After the tournament, Laak candidly acknowledged that “the bots are closing in.”
People have expressed worry that computerized competition and game-theoretic solutions could psychologically depress player enthusiasm. What’s the point of playing checkers now that we know it should always end in a draw? What’s the thrill of playing chess, when we humans know that we can never be the best?
But the rise of gambling bots may soon depress online poker participation for a very different reason. In the very near future, online poker may become a suckers’ game that humans won’t have a chance to win. Bots are quite scale-able and it will be virtually impossible to prohibit computer or computer-assisted online playing.
Poker sites are trying to assure customers that they will kick bots off their site and seize their assets. But unlike the statistical trail left by crude poker cheats at Absolute Poker, it is possible for bots to randomize their strategies and even hire individual humans to run them.
Ultimately the Albertus Polaris program and its offspring could be more effective than any Justice Department indictment in crippling the growth of online gambling. Indeed, our government might even think about subsidizing the development and use of these bots. Imagine a DARPA-like competition for creating a bot that can beat the average law breaker. Constructing a bot that can consistently win (and then publicizing this fact) is a sure step toward virtual temperance. (By the way, I’m agnostic about whether online poker should be illegal.)
Poker enthusiasts have argued for online legalization, saying that poker is a game of skill. And of course, it is (just like chess and checkers). But ironically, it’s because poker is a game of skill that humans’ chance of winning are undermined. Unlike checkers, the key to poker is to predict whether other players are bluffing. On the Internet (without the possibility of visual cues), computers are probably better at predicting a rival’s hand from his or her past play. But computers are much better at confounding the expectations of their human opponents. Computers can play randomized strategies much better than we can. Our brains are so hardwired to see patterns, it’s devilishly hard for most of us to generate random behavior.
Indeed, take a minute and try to write down a random sequence of 200 heads or tails. If you actually flip a coin that many times, there’s a very large chance (98%) that there will be a run of at least 6 heads or 6 tails in a row. But very few people can bring themselves to produce such runs in trying to be random. Your iPod’s shuffle function isn’t broken when it plays songs from the same artist two or three times in a row. By chance, runs do happen.
When I play poker, I use my watch as a crude random number generator. Before my first bet, I look down and bluff if the second hand on my watch is between :00 and :06. Unlike machines, people have a hard time ignoring the past. Our biggest tells aren’t facial tics but that we just can’t stop ourselves from playing non-randomly. With training, we can get better, but we should fool ourselves. The handwriting is on the wall. High quality bots are an online gambler’s worst nightmare.
Bots won’t kill poker. They’ll just drive it off line. Old fashioned “humans-only” competitions will still thrive. But this is one Darwinian struggle where the unaided human mind is definitely not the fittest.
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The Polaris match and others like it are a little misleading. The poker bots that can compete well with humans generally only play heads-up, limit Hold Em. That kind of game, which only has two players and very limitted betting options, is much easier for a computer to “brute force” than a full table game of No Limit Hold Em.
Doing well at a full table, No Limit game takes a lot different kind of thinking than what computers are good at. The most important part in those situations is being able to mentally model the actions of your oponents, which computers are very bad at right now. I think computers will need to progress to the point that they can understand the meaning of what humans are saying in a conversation before they will be able to understand what’s going on in the average No Limit Hold Em game.
The Polaris match and others like it are a little misleading. The poker bots that can compete well with humans generally only play heads-up, limit Hold Em. That kind of game, which only has two players and very limitted betting options, is much easier for a computer to “brute force” than a full table game of No Limit Hold Em.
Doing well at a full table, No Limit game takes a lot different kind of thinking than what computers are good at. The most important part in those situations is being able to mentally model the actions of your oponents, which computers are very bad at right now. I think computers will need to progress to the point that they can understand the meaning of what humans are saying in a conversation before they will be able to understand what’s going on in the average No Limit Hold Em game.
Welcome, Ian!
This does seem likely, but some poker-watchers think that a combination of sophisticated virtual reality and reputational mechanisms may maintain trust in some form of the online game. We’ll see.
Fans of this post may also be interested in a feature article I wrote about a year ago, covering “Poker Machine” Chris Ferguson, the pokerbots – including those from Alberta – and the economics behind it all. I come to a similar conclusion to Ian Ayres.
The article is available at:
http://timharford.com/2006/05/the-poker-machine/
Welcome, Ian!
This does seem likely, but some poker-watchers think that a combination of sophisticated virtual reality and reputational mechanisms may maintain trust in some form of the online game. We’ll see.
Fans of this post may also be interested in a feature article I wrote about a year ago, covering “Poker Machine” Chris Ferguson, the pokerbots – including those from Alberta – and the economics behind it all. I come to a similar conclusion to Ian Ayres.
The article is available at:
http://timharford.com/2006/05/the-poker-machine/
CT, Look at the people who play 20 tables at the same time of No Limit Hold’em. They are basically bots who just occasionally have to “think/deviate from their standard strategy”. Everything else is memorized. The “thinking” part will be here before we know it (it already is to some extent). And like Ian said, machines are much better randomizers than us.
CT, Look at the people who play 20 tables at the same time of No Limit Hold’em. They are basically bots who just occasionally have to “think/deviate from their standard strategy”. Everything else is memorized. The “thinking” part will be here before we know it (it already is to some extent). And like Ian said, machines are much better randomizers than us.
CT (#5):
Bots aren’t “good” or “bad” at any particular kind of strategical thinking – they’re only more or less sophisticated; i.e. they can only account for certain factors. That’s not an inherent limitation, but a technological one that can be overpassed simply by intelligently adding complexity to existing methods.
In short, there are different tells and strategies at play in your no limit, full-table scenario, which the Polaris doesn’t yet incorporate in its methodology.
But that doesn’t mean it can’t.
CT (#5):
Bots aren’t “good” or “bad” at any particular kind of strategical thinking – they’re only more or less sophisticated; i.e. they can only account for certain factors. That’s not an inherent limitation, but a technological one that can be overpassed simply by intelligently adding complexity to existing methods.
In short, there are different tells and strategies at play in your no limit, full-table scenario, which the Polaris doesn’t yet incorporate in its methodology.
But that doesn’t mean it can’t.