AI surpasses humans at six-player poker

Self-learning Pluribus beats five humans in Texas hold'em showdown Superhuman performance by artificial intelligence (AI) has been demonstrated in two-player, deterministic, zero-sum, perfect-information games ( 1 ) such as chess, checkers ( 2 ), Hex, and Go ( 3 ). Research using AI has broadened to include games with challenging attributes such as randomness, multiple players, or imperfect information. Randomness is a feature of dice games, and card games include the additional complexity that each player sees some cards that are hidden from others. These aspects more closely resemble real-world situations, and this research may thus lead to algorithms with wider applicability. On page 885 of this issue, Brown and Sandholm ( 4 ) show that a new computer player called Pluribus exceeds human performance for six-player Texas hold'em poker.