First, they come up with counterfactual values representing different game outcomes. Typical CFR algorithms try to solve games such as poker through several steps at each decision point. To deal with such a game, many AI rely on a technique called counterfactual regret minimization (CFR). Such complexity exists because this two-player version of poker allows for unrestricted bet sizes. But heads-up, no-limit Texas Hold’em represents an especially complex challenge with 10 160 possible plays at different stages of the game (possibly more than the number of atoms in the universe).

Game-playing AI has found solutions to some versions of poker. “It’s quite possible that humans will win this event, but it’s also possible that we’ll pull an upset.” “I still think it will happen within the next five years, but it could be within the next month,” says Tuomas Sandholm, a computer scientist at Carnegie Mellon University. One of the researchers who helped build both Claudico and Libratus believes that AI will beat the best human players sometime within the next several years-if not sooner. Artificial Intelligence: Upping the Ante” event being held at the Rivers Casino in Pittsburgh starting on 11 January. This year’s rematch features four human poker pros playing for a prize pot of $200,000 against an AI called Libratus in the “ Brains Vs. The human margin of victory from the past event was not large enough to statistically prove whether humans or the Claudico AI were really the better poker players.

Beginning tomorrow, a rematch of humans versus AI will test whether humanity can hold its own against an even more capable challenger.

In 2015, several of the world’s top poker players faced down a supercomputer-powered artificial intelligence named Claudico during a grueling 80,000 hands of no-limit Texas Hold’em.

Machine learning online poker