Artificial intelligence has seen several breakthroughs in recent years, with games such as checkers, chess, and go often serving as milestones of progress. Poker is another game entirely, with players having their own asymmetric information about what's happening in the game. In this talk, University of Alberta researcher Michael Bowling (also a principal investigator at the Alberta Machine Intelligence Institute) describes a decade long research program to build AI that can cope with the hallmarks of poker — deception, bluffing, and manipulating what other players know. This research has culminated in two landmark results: Cepheus playing a perfect game of limit poker, and most recently, DeepStack (in a collaboration with Czech researchers) beating poker pros at the game of no-limit poker. These two computer programs take very different approaches, and shed light on what is required to play a game at an expert-level and what is required to play it perfectly.
Michael Bowling
https://www.youtube.com/watch?v=qndXrHcV1sM