title: DeepStack: Expert-level artificial intelligence in heads-up no-limit poker.
abstract: Artificial intelligence has seen several breakthroughs in recent years, with games often serving as milestones. A common feature of these games is that players have perfect information. Poker, the quintessential game of imperfect information, is a long-standing challenge problem in artificial intelligence. We introduce DeepStack, an algorithm for imperfect-information settings. It combines recursive reasoning to handle information asymmetry, decomposition to focus computation on the relevant decision, and a form of intuition that is automatically learned from self-play using deep learning. In a study involving 44,000 hands of poker, DeepStack defeated, with statistical significance, professional poker players in heads-up no-limit Texas hold'em. The approach is theoretically sound and is shown to produce strategies that are more difficult to exploit than prior approaches.
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.|Department of Applied Mathematics, Charles University, Prague, Czech Republic.
authors.forename: Matej
authors.identifier: 0000-0001-5205-5378
authors.initials: M
authors.lastname: Moravčík
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.|Department of Applied Mathematics, Charles University, Prague, Czech Republic.
authors.forename: Martin
authors.identifier: 0000-0001-5341-9209
authors.initials: M
authors.lastname: Schmid
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.
authors.forename: Neil
authors.initials: N
authors.lastname: Burch
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.|Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University, Prague, Czech Republic.
authors.forename: Viliam
authors.identifier: 0000-0002-1647-1507
authors.initials: V
authors.lastname: Lisý
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.
authors.forename: Dustin
authors.identifier: 0000-0002-6454-1848
authors.initials: D
authors.lastname: Morrill
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.
authors.forename: Nolan
authors.initials: N
authors.lastname: Bard
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.
authors.forename: Trevor
authors.initials: T
authors.lastname: Davis
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.
authors.forename: Kevin
authors.initials: K
authors.lastname: Waugh
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.
authors.forename: Michael
authors.initials: M
authors.lastname: Johanson
authors.affiliation: Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada. bowling@cs.ualberta.ca.
authors.forename: Michael
authors.identifier: 0000-0003-2960-8418
authors.initials: M
authors.lastname: Bowling