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December 25, 2017 12:00 am
Original Link: http://rss.slashdot.org/~r/Slashdot/slashdot/~3/bkbekGiUgFg/cmu-researchers-reveal-how-their-ai-beat-the-worlds-top-poker-players
CMU Researchers Reveal How Their AI Beat The World's Top Poker Players
2017 began with an AI named "Libratus" defeating four of the world's best poker players. Now the AI's creators reveal how exactly they did it. An anonymous reader quotes the Pittsburgh Tribune-Review:First, the AI made the game easier to understand. There are 10**161 potential outcomes in the game of poker -- that's a one followed by 161 zeros, potential outcomes in a game of poker. Libratus grouped similar hands, like a King-high flush and a Queen-high flush, and similar bet sizes to cut down that number. Libratus then created a detailed strategy for how it would play the early rounds of the game and a less-refined strategy for the final rounds. As the game nears the end, Libratus refined the second strategy based on how the game had gone. A third strategy was at work as well. In real-time, Libratus created another model based on how its play stacked up against the play of the humans. If the humans did something unexpected to Libratus, the AI accounted for it and built it into the strategy. Instead of trying to exploit weaknesses in the play of the human, Libratus focused on improving its play. The AI was created by a computer science professor at Carnegie Mellon University and his Ph.D. student, who argue in a new paper that "The techniques that we developed are largely domain independent and can thus be applied to other strategic imperfect-information interactions, including non-recreational applications." "Due to the ubiquity of hidden information in real-world strategic interactions, we believe the paradigm introduced in Libratus will be critical to the future growth and widespread application of AI."Read more of this story at Slashdot.
Original Link: http://rss.slashdot.org/~r/Slashdot/slashdot/~3/bkbekGiUgFg/cmu-researchers-reveal-how-their-ai-beat-the-worlds-top-poker-players
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