The developers told Science journal they had "solved" the two-player game Fixed-limit Heads-up Texas Hold ’em. And the algorithm had a strategy so close to optimal "it can’t be beaten with statistical significance within a lifetime of human poker playing". The poker-ace algorithm is also now available online for people to test, query and even play against.
Since scientists first started to develop game-playing artificial intelligence, there have been a series of famous cases where computer algorithms developed strategies better than the very best human players. In 1997, for example, IBM supercomputer Deep Blue defeated world chess champion Garry Kasparov.
But these machine victories have been in what are termed "perfect-information games" – where all players are informed about everything that has occurred in the game before making a decision. This is not the case in poker, where players do not know which cards have been dealt to other players.
This new poker-playing program has taught itself to overcome this. It has played trillions of hands of poker and been designed to learn by "regretting" and remembering every decision that does not lead to the optimum outcome.