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In imperfect-information games, the optimal strategy in a subgame may depend on the strategy in other, unreached subgames.
Equilibrium points in n-person games
John Nash · 1950
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The weighted majority algorithm
Nick Littlestone and M. K. Warmuth · 1994
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Deep Blue
Murray Campbell, A Joseph Hoane, and Feng-Hsiung Hsu · 2002
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Approximating game-theoretic optimal strategies for full-scale poker
Darse Billings, Neil Burch, Aaron Davidson, Robert Holte, Jonathan Schaeffer, Terence Schauenberg, and Duane Szafron · 2003
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Excessive gap technique in nonsmooth convex minimization
Yurii Nesterov · 2005
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Better automated abstraction techniques for imperfect information games, with application to Texas Hold’em poker
Andrew Gilpin and Tuomas Sandholm · 2007
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Checkers is solved
Jonathan Schaeffer, Neil Burch, Yngvi Björnsson, Akihiro Kishimoto, Martin Müller, Robert Lake, Paul Lu, and Steve Sutphen · 2007
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Regret minimization in games with incomplete information
Martin Zinkevich, Michael Johanson, Michael H Bowling, and Carmelo Piccione · 2007
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Andrew Gilpin, Tuomas Sandholm, and Troels Bjerre Sørensen · 2008
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Monte Carlo sampling for regret minimization in extensive games
Marc Lanctot, Kevin Waugh, Martin Zinkevich, and Michael Bowling · 2009
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Probabilistic state translation in extensive games with large action sets
David Schnizlein, Michael Bowling, and Duane Szafron · 2009
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Strategy grafting in extensive games
Kevin Waugh, Nolan Bard, and Michael Bowling · 2009
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The state of solving large incomplete-information games, and application to poker
Tuomas Sandholm · 2010
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First-order algorithm with 𝒪 ( ln ( 1 / ϵ ) ) \mathcal{O}(\mathrm{ln}(1/\epsilon)) convergence for ϵ \epsilon -equilibrium in two-person zero-sum games
Andrew Gilpin, Javier Peña, and Tuomas Sandholm · 2012
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Finding optimal abstract strategies in extensive-form games
Michael Johanson, Nolan Bard, Neil Burch, and Michael Bowling · 2012
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Action translation in extensive-form games with large action spaces: axioms, paradoxes, and the pseudo-harmonic mapping
Sam Ganzfried and Tuomas Sandholm · 2013
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Measuring the size of large no-limit poker games
Endgame solving in large imperfect-information games
Sam Ganzfried and Tuomas Sandholm · 2015
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Abstraction for solving large incomplete-information games
Tuomas Sandholm · 2015
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Solving imperfect-information games
Tuomas Sandholm · 2015
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Solving heads-up limit texas hold’em
Oskari Tammelin, Neil Burch, Michael Johanson, and Michael Bowling · 2015
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Baby Tartanian8: Winning agent from the 2016 annual computer poker competition
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Reduced space and faster convergence in imperfect-information games via regret-based pruning
Noam Brown and Tuomas Sandholm · 2016
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Michael Johanson · 2013
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Solving imperfect information games using decomposition
Neil Burch, Michael Johanson, and Michael Bowling · 2014
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Potential-aware imperfect-recall abstraction with earth mover’s distance in imperfect-information games
Sam Ganzfried and Tuomas Sandholm · 2014
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A time and space efficient algorithm for approximately solving large imperfect information games
Eric Jackson · 2014
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Heads-up limit hold’em poker is solved
Michael Bowling, Neil Burch, Michael Johanson, and Oskari Tammelin · 2015
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Regret-based pruning in extensive-form games
Noam Brown and Tuomas Sandholm · 2015
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Simultaneous abstraction and equilibrium finding in games
Noam Brown and Tuomas Sandholm · 2015
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Refining subgames in large imperfect information games
Matej Moravcik, Martin Schmid, Karel Ha, Milan Hladik, and Stephen Gaukrodger · 2016
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Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016
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Dynamic thresholding and pruning for regret minimization
Noam Brown, Christian Kroer, and Tuomas Sandholm · 2017
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Theoretical and practical advances on smoothing for extensive-form games
Christian Kroer, Kevin Waugh, Fatma Kılınç-Karzan, and Tuomas Sandholm · 2017
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Deepstack: Expert-level artificial intelligence in heads-up no-limit poker
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