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Sparse iterative methods, in particular first-order methods, are known to be among the most effective in solving large-scale two-player zero-sum extensive-form games.
Reduction of a game with complete memory to a matrix game
I. Romanovskii · 1962
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Efficient computation of equilibria for extensive two-person games
Daphne Koller, Nimrod Megiddo, and Bernhard von Stengel · 1996
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Efficient computation of behavior strategies
Bernhard von Stengel · 1996
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Fundamentals of convex analysis
Jean-Baptiste Hiriart-Urruty and Claude Lemaréchal · 2001
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Abstraction methods for game theoretic poker
Jiefu Shi and Michael Littman · 2002
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Playing large games using simple strategies
Richard Lipton, Evangelos Markakis, and Aranyak Mehta · 2003
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A polynomial-time Nash equilibrium algorithm for repeated games
Michael Littman and Peter Stone · 2003
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Prox-method with rate of convergence o (1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems
Arkadi Nemirovski · 2004
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Bayes’ bluff: Opponent modelling in poker
Finnegan Southey, Michael Bowling, Bryce Larson, Carmelo Piccione, Neil Burch, Darse Billings, and Chris Rayner · 2005
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Lossless abstraction of imperfect information games
Andrew Gilpin and Tuomas Sandholm · 2007
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Regret minimization in games with incomplete information
Martin Zinkevich, Michael Bowling, Michael Johanson, and Carmelo Piccione · 2007
Earlier work this paper cites.
The complexity of computing a nash equilibrium
Constantinos Daskalakis, Paul W Goldberg, and Christos H Papadimitriou · 2009
Earlier work this paper cites.
Monte Carlo sampling for regret minimization in extensive games
Marc Lanctot, Kevin Waugh, Martin Zinkevich, and Michael Bowling · 2009
Cited alongside, same era.
Smoothing techniques for computing Nash equilibria of sequential games
Samid Hoda, Andrew Gilpin, Javier Peña, and Tuomas Sandholm · 2010
Cited alongside, same era.
The state of solving large incomplete-information games, and application to poker
Tuomas Sandholm · 2010
Cited alongside, same era.
Automated action abstraction of imperfect information extensive-form games
John Hawkin, Robert Holte, and Duane Szafron · 2011
Cited alongside, same era.
Polynomial-time computation of exact correlated equilibrium in compact games
Albert Jiang and Kevin Leyton-Brown · 2011
Cited alongside, same era.
Accelerating best response calculation in large extensive games
Michael Johanson, Kevin Waugh, Michael Bowling, and Martin Zinkevich · 2011
Extensive-form game abstraction with bounds
Christian Kroer and Tuomas Sandholm · 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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Hierarchical abstraction, distributed equilibrium computation, and post-processing, with application to a champion no-limit Texas Hold’em agent
Noam Brown, Sam Ganzfried, and Tuomas Sandholm · 2015
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Near-optimal no-regret algorithms for zero-sum games
Constantinos Daskalakis, Alan Deckelbaum, and Anthony Kim · 2015
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Faster first-order methods for extensive-form game solving
Christian Kroer, Kevin Waugh, Fatma Kılınç-Karzan, and Tuomas Sandholm · 2015
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Abstraction for solving large incomplete-information games
Tuomas Sandholm · 2015
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Cited alongside, same era.
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
Cited alongside, same era.
Using sliding windows to generate action abstractions in extensive-form games
John Hawkin, Robert Holte, and Duane Szafron · 2012
Cited alongside, same era.
No-regret learning in extensive-form games with imperfect recall
Marc Lanctot, Richard Gibson, Neil Burch, Martin Zinkevich, and Michael Bowling · 2012
Cited alongside, same era.
Lossy stochastic game abstraction with bounds
Tuomas Sandholm and Satinder Singh · 2012
Cited alongside, same era.
An exact double-oracle algorithm for zero-sum extensive-form games with imperfect information
Branislav Bosansky, Christopher Kiekintveld, Viliam Lisy, and Michal Pechoucek · 2014
Cited alongside, same era.
Regret transfer and parameter optimization
Noam Brown and Tuomas Sandholm · 2014
Cited alongside, same era.
Later among the works it cites.
Solving heads-up limit Texas hold’em
Oskari Tammelin, Neil Burch, Michael Johanson, and Michael Bowling · 2015
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A unified view of large-scale zero-sum equilibrium computation
Kevin Waugh and Drew Bagnell · 2015
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Strategy-based warm starting for regret minimization in games
Noam Brown and Tuomas Sandholm · 2016
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Imperfect-recall abstractions with bounds in games
Christian Kroer and Tuomas Sandholm · 2016
Later among the works it cites.
Dynamic thresholding and pruning for regret minimization
Noam Brown, Christian Kroer, and Tuomas Sandholm · 2017
Closest in time.
Deepstack: Expert-level artificial intelligence in no-limit poker
Matej Moravčík, Martin Schmid, Neil Burch, Viliam Lisỳ, Dustin Morrill, Nolan Bard, Trevor Davis, Kevin Waugh, Michael Johanson, and Michael Bowling · 2017
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