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Artificial Intelligence Goes All-In: Computers Playing Poker
June 15 @ 3:30 pm - 5:00 pm
Michael Bowling, PhD
Professor of Computer Science
Department of Computing Science
University of Alberta
“Artificial Intelligence Goes All-In: Computers Playing Poker”
Abstract: 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, I’ll describe 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 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.
Bio: Professor Bowling leads the Computer Poker Research Group, which has built some of the best poker playing programs on the planet. The programs were the first to beat top professional players in a meaningful competition and more recently have been shown to play a nearly perfect game of limit Texas hold’em poker. He also started the Arcade Learning Environment, a research testbed for investigating artificial intelligence techniques capable of general competency using Atari 2600 games. More recently, Dr. Bowling has begun exploring the application of advanced analytics to the sport of curling.
Michael Bowling completed his Ph.D. at Carnegie Mellon University in 2003, where his dissertation focused on multi-agent learning. His research has been featured on television programs including Scientific American Frontiers, National Geographic Today, and Discovery Channel Canada, as well appearing in the New York Times, Wired, on CBC and BBC radio, and twice in exhibits at the Smithsonian Museums in Washington, DC.
Sponsored jointly by Toyota-AI and MIDAS