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The Partially Observable History Process

Nov 15, 2021
Dustin Morrill, Amy R. Greenwald, Michael Bowling

* 8 pages, 2 figures 

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Learning to Be Cautious

Oct 29, 2021
Montaser Mohammedalamen, Dustin Morrill, Alexander Sieusahai, Yash Satsangi, Michael Bowling

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Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games

Feb 13, 2021
Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy Greenwald

* 32 pages, 6 figures 

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Hindsight and Sequential Rationality of Correlated Play

Dec 17, 2020
Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy Greenwald, Michael Bowling

* Technical report for a paper to appear at AAAI 2021. 26 pages, 15 figures 

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The Advantage Regret-Matching Actor-Critic

Aug 27, 2020
Audrūnas Gruslys, Marc Lanctot, Rémi Munos, Finbarr Timbers, Martin Schmid, Julien Perolat, Dustin Morrill, Vinicius Zambaldi, Jean-Baptiste Lespiau, John Schultz, Mohammad Gheshlaghi Azar, Michael Bowling, Karl Tuyls

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Alternative Function Approximation Parameterizations for Solving Games: An Analysis of $f$-Regression Counterfactual Regret Minimization

Dec 06, 2019
Ryan D'Orazio, Dustin Morrill, James R. Wright, Michael Bowling

* 11 pages, includes appendix. arXiv admin note: text overlap with arXiv:1910.01706 

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OpenSpiel: A Framework for Reinforcement Learning in Games

Oct 10, 2019
Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinicius Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds, Ryan Faulkner, János Kramár, Bart De Vylder, Brennan Saeta, James Bradbury, David Ding, Sebastian Borgeaud, Matthew Lai, Julian Schrittwieser, Thomas Anthony, Edward Hughes, Ivo Danihelka, Jonah Ryan-Davis

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Bounds for Approximate Regret-Matching Algorithms

Oct 03, 2019
Ryan D'Orazio, Dustin Morrill, James R. Wright

* Smooth Games Optimization and Machine Learning Workshop: Bridging Game Theory and Deep Learning (SGO&ML), at the Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Dec 14th, 2019, Vancouver, Canada 
* 4 pages + acknowledgements, references, and appendices (9 pages total) 

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Neural Replicator Dynamics

Jun 01, 2019
Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Remi Munos, Julien Perolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls

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Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent

Mar 21, 2019
Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls

* 11 pages, 1 figure 

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DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker

Mar 03, 2017
Matej Moravčík, Martin Schmid, Neil Burch, Viliam Lisý, Dustin Morrill, Nolan Bard, Trevor Davis, Kevin Waugh, Michael Johanson, Michael Bowling

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Solving Games with Functional Regret Estimation

Dec 31, 2014
Kevin Waugh, Dustin Morrill, J. Andrew Bagnell, Michael Bowling

* AAAI Conference on Artificial Intelligence 2015 

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