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“In a complete information game you can solve a subtree of the game tree,” says Professor Tuomas Sandholm, who built the Libratus system with PhD student Noam Brown. AI trying to win a game of chess or Go can work through how a sequence of moves will play out. “With incomplete-information games, it’s not like that at all. You can’t know what cards the other player has been dealt,” he explains. “That means you don’t know exactly what subgame you’re in. Also, you don’t know which cards chance will produce next from the deck.”
Incomplete information games have thus far proved much harder to solve. CMU’s AI focuses on information sets, a grouping of possible states that take into account the known and unknown variables. It’s a massive mathematical undertaking. “The game has 10 to the power of 160 information sets, and 10 to the power of 165 nodes in the game tree,” says Sandholm. That means there are more possible permutations in a hand of poker than atoms in our universe. “And even if you had another whole universe for each atom in our universe and counted all the atoms in those universes, it would be more than that.”
Source: This AI will battle poker pros for $200,000 in prizes – The Verge
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