Fascinating. Poker is so complex--when considering human unpredictability. Or maybe we're more predictable than we'd like to admit. Initially, the computer bested the world-champion Texas Hold 'Em players:
After their shellacking, Laak and Eslami got their heads together and decided to take an even more focused, deliberate approach to the third set on Tuesday afternoon. The programmers, meanwhile, went to a mixed strategy, selecting three software variants as tag teams for each of the human opponents.So the computer team Polaris will go back at it and they'll try again in a few months. Before you scoff at the silliness, consider the usefulness of smart computers:
In the end, it was the humans who were able to adapt to the bots. The humans won the third faceoff against the tag-team bots, and went on to beat Mr. Pink in the fourth and final round.
"The computer program is tricky," Schaeffer said. "It's hard to model. Its roots are in deep algorithms. Either consciously or subconsciously, [the humans] were able to figure out something and win."
Laak said he and Eslami gave Polaris' programmers some suggestions for making the bots better. "We actually told them the way you can beat us," he said. "If you could take Agent Orange, crank him down 50 percent, then have that guy play us randomly, so that each hand would be the new Agent Orange or Mr. Pink ... that might be the thing we can't beat."Exactly. Some scoff that games like Texas Hold 'Em is gambling and it's wrong. Well, I don't like gambling. I like having complete information, if possible, but it's just not always the case in life. Nor is life 100% chance. We make decisions, we learn by experience, we make different decisions, we learn by experience. Some people learn by other's experience by watching. But there is nothing like playing a lot of hands to learn the game. Just like life.
Eslami said he encouraged the programmers to focus on the adaptive approach used by Agent Orange. "I think that's going to have application in broader society," he said.
The University of Alberta's Schaeffer echoed that view: "The challenge to us is how to get computers to reason and act intelligently in the absence of complete information. Poker is a game of what we call partial information. In this case, you don't know the opponent's cards. That doesn't sound like a big deal, but since you don't know what they have, you have to deal with probabilities."
The same challenges apply to making money in the stock market, where you have only partial information about the prospects for all the companies you could invest in ... or to buying a used car, where you have to sort through incomplete and sometimes misleading information as you negotiate a deal.
"What you're doing is, you're playing a game of poker," Schaeffer said. Next-generation software could help humans play those real-life games better - and, one can hope, more fairly.