In the past two decades, we've seen chess grandmasters and the best Jeopardy players in the world alike fall to in competition to computers. Heads-up No-limit Texas Hold 'em poker may be next. But the future of artificial intelligence (AI) is about way more than games.
Last April and May, Carnegie Mellon University's AI, Claudico (developed by Professor Tuomas Sandholm and his team), played an 80,000-hand tournament against four poker pros. When the game ended, three of the four players had bigger hands than Claudico.
"We think we're at the point where poker will fall," says Andrew Moore, professor and dean of CMU's School of Computer Science. "We think it will happen at the next competition in two years."
Know when to hold 'em ...
"In computer science terms, the algorithm it needs [to play poker] is exponentially harder than chess, and it's all because it's a game of hidden information," he says. "A game like chess or backgammon, both sides can see the board at all times and know what the future scenarios might be. When you're playing in a hidden game, it turns out you have to think about every possible card your opponent might have and what every possible game-play strategy might be. The computation is much, much harder. You can have a world championship-level chess player running on one moderate laptop now — something only a few humans have a chance of beating. But you still need a massive super computer to play No-Limit Texas Hold 'em."
Moore, whose own background is in statistical machine learning, AI, robotics and statistical computation for large volumes of data, heads up a department of 30 faculty at CMU focused on AI research. CMU faculty have been working on things like AIs playing poker because teaching AIs to process scenarios with hidden information will unlock whole new vistas of applicability for the technology.
For instance, Moore says two CMU faculty are working on projects that will help Apple's Siri or Microsoft's Cortana become better personal assistants. You might spot a set of red sneakers that catch your fancy and ask your AI to buy them for you — if it can get a good deal. Or maybe you want it to get you a deal on baseball tickets.
"To do that, your own personal computer assistant can't just advertise what you're willing to pay," Moore says. "It needs to withhold information."
The technology could also lead to blind negotiations with no opportunity for gaming the system. One example, Moore says, would be organ exchanges. Consider kidneys. Some people are willing to donate a kidney to help a relative whose kidney is failing. But, of course, not all relatives are donor matches. Still, another person may be in a similar situation. One possible solution is a large system for completely fair negotiation in which willing donors swap with other people that are matches.
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