Yet there is a fundamental difference between games such as chess and go and those like poker in the amount of information available to players. Last year Google DeepMind’s AlphaGo program shocked the world when it beat top human pros in the game of go. Twenty years ago game-playing AI had a breakthrough when IBM’s chess-playing supercomputer Deep Blue defeated World Chess Champion Garry Kasparov. Using this strategy allowed it to defeat its human opponents.įor decades scientists developing artificial intelligence have used games to test the capabilities of their systems and benchmark their progress. During play, DeepStack uses its poker smarts to break down a complicated game into smaller, more manageable pieces that it can then work through on the fly. A study published today in Science describes an AI system called DeepStack that recently defeated professional human players in heads-up, no-limit Texas hold’em poker, an achievement that represents a leap forward in the types of problems AI systems can solve.ĭeepStack, developed by researchers at the University of Alberta, relies on the use of artificial neural networks that researchers trained ahead of time to develop poker intuition. The same elements that make poker so entertaining have also created a complex problem for artificial intelligence (AI). It is no mystery why poker is such a popular pastime: the dynamic card game produces drama in spades as players are locked in a complicated tango of acting and reacting that becomes increasingly tense with each escalating bet.

What beats what in poker texas hold'em