Carnegie Mellon Computer Faces Poker Pros in Epic No-Limit Texas Hold’Em Competition

One of the main areas of Artificial Intelligence research has been into game playing. In many games such as chess and draughts, there is perfect information. Each move a player makes is seen by the other player.

Some games have elements of chance, in addition to perfect information. Backgammon is a good example, where each move a player makes is governed by the roll of a dice. Still, there is perfect information available as to the state of the board.


Texas Hold’Em Poker – Todd Klassy

Poker is an interesting game by contrast as there is uncertainty about the state of the game. The only things a play knows for certain are his or her own cards (and in the case of Texas Hold ‘Em, the shared cards). Everything else must be estimated using some element of probability. In the case of poker, it would be what cards the other players have and the probability of the cards to be dealt by the dealer during the betting rounds.

There are various techniques and strategies employed by human players, including reading the body language of the other players. This is probably beyond today’s level of AI, but that hasn’t stopped a team from Carnegie Mellon University from having a go. From April 24th until the 8th May, an AI will be playing a heads-up no-limit Texas Hold ‘Em against professional players. It will be interesting to see if it can follow in the footsteps of Deep Blue, the AI that defeated the then world chess champion, Gary Kasparov, in 1996.

For the latest score in the match, see Brains vs AI at Carnegie Mellon

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