![]() ![]() Libratus: Masters Two-Player Texas Hold ’Em After playing 44,852 games, DeepStack’s results were ten times what a professional poker player considers a sizable margin. DeepStack played two-player Texas Hold 'em against professional poker players from the International Federation of Poker. ![]() The AI relies on its neural networks to determine the best moves. DeepStack’s neural networks were trained by solving more than 10 million poker game situations. The DeepStack team, from the University of Alberta in Edmonton, Canada, combined deep machine learning and algorithms to create AI capable of winning at two-player, “no-limit” Texas Hold ’em, a game more complex for AI to master than others because of its random nature, hidden cards and players’ bluffs. ![]()
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