I hear more and more about chess players giving up chess and playing professional poker, because there is more money in it. An article in the NYT talks about Ylon Schwartz, a Fide Master (USCF 2304), who is now in the final table of the World Series of Poker Main Event.

I am especially interested in his view of the similarities between chess and poker:

“Chess players are trained to have excellent memories,� he said. “In poker, you need to remember betting patterns.� And strategic skill is essential in poker as well as chess. For instance, keeping the other poker players from folding when you have a good hand depends on how much you bet early on.

He said that both games had geometrical aspects. In chess, it is the shape and size of the board and positions of the pieces. In poker, it is the positions of the players betting on a hand and the number of chips they have.

“All the patience I got in chess really helps me out,�

“Empathy is the most important thing in poker,� he said. “You have to really be aware of what your opponents think. The best thing about poker is that it exposes all your weaknesses.�

“Chess is a purer game,� he said. “It is my passion. I love poker, too, but I don’t know who gets together to play poker for fun. There is always something on the line.�

Jennifer Shahade, who wrote Chess Bitch, has also been playing a lot of poker.

Congratulations to Polaris for winning the Man-Machine Poker Competition in Las Vegas. I knew you could do it. Polaris 2.0 won the event with 3 wins, 2 losses and 1 tie – beating Matt Hawrilenko and other competitors convincingly by winning both sides of a duplicate match.
Computers have long been the best chess players. How long before they are the best day traders? I would say there is a good chance that they already are.

“There are two really big changes in Polaris over last year,” said professor Michael Bowling, who supervised graduate students who programmed Polaris. “First of all, our poker model is much expanded over last year–its much harder for humans to exploit weaknesses. And secondly, we have added an element of learning, where Polaris identifies which common poker stratagy a human is using and switches its own strategy to counter. This complicated the human players ability to compare notes, since Polaris chose a different strategy to use against each of the humans it played,” Bowling said.

“Repeatedly, I heard players exclaim that they had never seen a human do that before,” said Bowling. “Switching strategies really threw the humans for a loop.”

Even though Polaris beat the humans in Las Vegas, the University of Alberta group said it expects to be asked for rematches by the vanquished pros as well as by other poker experts who will claim the win by Polaris was a fluke. “Even after Deep Blue beat Kasparov, there were still some skeptics, and I think the same is true here,” said Bowling. “Over the next year or so there are going to have to be several rematches before everyone is convinced that humans have been surpassed by machines in poker.”

Bill Gates and Warren Buffett are fans of bridge and have invested a million dollars in programs to teach bridge in schools. It is one of only a few strategic games in which humans are still superior to computers.
Here are some things Buffet has to say about the game:

“You know, if I’m playing bridge and a naked woman walks by, I don’t ever see her,” he said, laughing, then added, “don’t test me on that!!”

“You know,” Buffet told Blackstone, “I wouldn’t mind going to jail if I had the right three cell mates, so we could play bridge all the time.”

“There’s a lotta lessons in it,” Buffett assured him, “you have to look at all the facts. You have to draw inferences from what you’ve seen, what you’ve heard. You have to discard improper theories about what the hand had as more evidence comes in sometimes. You have to be open to a possible change of course if you get new information. You have to work with a partner, particularly on defense.”

“I’ve never met anybody that spent time to learn the game that didn’t consider it one of the great things in their life,” he concluded.

After writing about my winnings at the Borgata earlier this year, it is only fair that I write about my losses in Las Vegas over the weekend.
As I said before, even playing craps with the optimal strategy (except for not betting at all) is a negative expectancy game. The house has an edge of less than half of a percent – but it is still an edge and you must expect to lose money over the long run. So I lost some of it back on my trip to Las Vegas this weekend.
Poker is probably a better game to play, since it involves skill. If you study and you are smart, you can play with a positive expectancy.
The one way to really win at craps is to bet enough money, with the optimal strategy, so that the casino comps will offset your small losses over time. This, I think, is the smartest way to gamble at the casino on a game of luck.
But Las Vegas is a pretty crazy place and it was fun. There was a rodeo going on, so there were a bunch of cowboys around town. And then there was a ballroom dancing competition, so there were also ballroom dancers hanging out. The two groups together seemed to give it the strange feel that I expected from the place. I’d never been there before.
On Saturday night for dinner we went to the overpriced and pretentious TAO Asian Bistro and Nightclub. Then we spent the rest of the night at the Hooters casino, which we went to looking for some lower priced tables. A bunch of the cowboys were there and it wasn’t pretentious at all.
On the taxi ride back to the Luxor, a Croatian taxi driver first asked me if I was British and when I said I wasn’t, he proceeded to curse all the British in the world for their low tips. He said the only reason they tip so low is because they are upset that they lose to Croatia at soccer. After I tipped him, he said “you are only a little better than them.”

I found this article in the nytimes (from Jan. 2000) about Parrando’s paradox very interesting. Two losing games can be combined to create a winning strategy.

Economists are studying Parrando’s paradox to help find the best strategies for managing investments. Dr. Sergei Maslov, a physicist at Brookhaven National Laboratory in Upton, N.Y., recently showed that if an investor simultaneously shared capital between two losing stock portfolios, capital would increase rather than decrease. ”It’s mind-boggling,” Dr. Maslov said. ”You can turn two minuses into a plus.” But so far, he said, it is too early to apply his model to the real stock market because of its complexity.

I’m dying to know more about this. Anyone heard of it being used in the market?
I’m also headed to Las Vegas this coming weekend – maybe if I alternate between craps and blackjack I can make millions.
I was disappointed to read this:

Unfortunately, Parrando’s paradox will not work for the kinds of games played in casinos, Dr. Abbott said. Games A and B must be set up to copy a ratchet, which means they must have some direct interaction.

Wikipedia also says that this theory won’t work in the stock market for the same reason.
There must be a way. Maybe I can figure something out on the 5 hour flight to Vegas.

Ian Ayres, economist and lawyer at Yale, wrote a guest entry for the freakonomics blog at the nytimes about the rise of the machines.

It is not an opportune time to start an online gambling site for checkers… What’s true for checkers is also becoming true for poker.

Sound familiar?

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.

…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.

Now imagine the not-so-distant future, where computers are much faster and smarter, using a similar but better strategy to beat day traders? Is it that difficult to imagine? They are and they will. It’s only a matter of time. Seriously.
Human day traders: your days are numbered.

He comes to an interesting conclusion:

Bots won’t kill poker. They’ll just drive it off line. Old fashioned “humans-only� competitions will still thrive.

I guess we could always take the stock market off-line, for fun. And his last sentence is one I agree with 100%:

But this is one Darwinian struggle where the unaided human mind is definitely not the fittest.

Richard says he is not worried about computers that can trade. Others have told me they aren’t worried either – they believe there will always be ways for a human to make money in the markets. They could be right, but I don’t think so. I think it is only a matter of time before even the best human traders (without the help of AI) cannot make consistent profits in the market. Here is a comment I just added to his post:

Basically it comes down to this: computers are getting smarter and smarter. Not just in a brute-force way – they are getting more intuitive and creative. They are really becoming smarter, with pattern-recognition capabilities that are beginning to rival those of humans. Eventually they will be the best traders.
Trading is a lot like poker, and look at the progress of poker-playing AI. I think it is important for traders to watch this progress in poker. When computers dominate poker, as they now do chess, it will be more clear as to how they will also dominate the market.
I don’t think even the best unassisted human brain will be enough to compete with this AI in 10 years. I think it will be like playing Deep Blue. Over time it will just be better and take your money. Why is it so hard for traders to make money in the markets today? Because it is competitive, we all can’t win, and there are really smart, good traders to compete with. Smart AI is currently and will continue to be a growing part of this competition.

Polaris, run on an Apple MacBook Pro, is the computer program that played Phil “the Unabomber” Laak in the recent tournament. Polaris has two parts, “the first being a stored memory bank of optimal strategy for poker situations, the second, a routine to study its opponent, understand their style of play, and adjust its own to take advantage.” The second part is the interesting part – a challenge to the intuition of humanity. This is the part that Deep Blue didn’t have and the part that traders should be worried about.

“I literally felt the same feeling that you would have if you beat 500 people in a tournament and won a million dollars,” Laak said after the game, which ended to the sound of whoops and cheers from the watching crowd of hundreds as the humans vanquished the computer. “We won, not by a significant amount, and the bots are closing in.”

Interestingly, though, I think the second “intuitive” part of the program cost Polaris the match:

After 48 hours of play, Polaris tied the first round, won the second and lost the last two. The two losses came after the program switched modes: it played strictly by the odds of hands in the first two rounds, but the last two were played with alternating “personalities” of passive and daring that were switched out between hands.

The humans beat the computers in the last minutes of the fourth match in the Poker Tournament this week. It was very close, the computer played “brilliantly” – it won’t be long now until computers are the best poker players in the world.

“I really am happy it’s over,” said Eslami, 30, adding that playing against the computer was more exhausting than any previous game in his career.

“I’m surprised we won…. it’s already so good it will be tough to beat in future” as scientists make further improvements on Polaris’ programming.

This is sweet – computers could beat the best human poker players for the first time on Monday. Unlike chess, where all information is available, computers have trouble with poker because of the uncertainty of the opponent’s cards. Poker is more similar to trading, so this should have some interest to traders – especially traders who have automated trading systems.

The game-tree approach doesn’t work in poker because in many situations there is no one best move. There isn’t even a best strategy. A top-notch player adapts his play over time, exploiting his opponent’s behavior. He bluffs against the timid and proceeds cautiously when players who only raise on the strongest hands are betting the limit. He learns how to vary his own strategy so others can’t take advantage of him.

That kind of insight is very hard to program into a computer. You can’t just give the machine some rules to follow, because any reasonably competent human player will quickly intuit what the computer is going to do in various situations.

I like the way they’ve set up the match with the two poker pros to eliminate the luck of the draw:

Laak will play with a partner, fellow pro Ali Eslami. The two will be in separate rooms, and their games will be mirror images of one another, with Eslami getting the cards that the computer received in its hands against Laak, and vice versa.

That way, a lousy hand for one human player will result in a correspondingly strong hand for his partner in the other room. At the end of the tournament the chips of both humans will be added together and compared to the computer’s.

By the way Phil Laak was a day trader before he became a professional poker player.