Researchers at the University of Alberta's Computer Poker Research Group in Canada pioneered game theory mathematics that has transformed how professional poker players approach the game.
Poker's mathematical complexity rivals or surpasses that of chess, while adding randomness and hidden data, bringing it closer to the "real world" that artificial intelligence scientists want to control.
Many poker-playing algorithms incorporate the minimization of regret, a mathematical concept for decision-making in uncertain environments.
Game-theory optimal poker players hire programmers to analyze their game data, finding "leaks" or errors in strategy, and to conduct game-theoretical analyses, calculating optimal plays in any of the innumerable situations that can confront a player.
From The Wall Street Journal
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