Следене
Dustin Morrill
Dustin Morrill
Computing Science PhD Candidate, University of Alberta and the Alberta Machine Intelligence
Потвърден имейл адрес: ualberta.ca - Начална страница
Заглавие
Позовавания
Позовавания
Година
Deepstack: Expert-level artificial intelligence in heads-up no-limit poker
M Moravčík, M Schmid, N Burch, V Lisý, D Morrill, N Bard, T Davis, ...
Science 356 (6337), 508-513, 2017
9092017
OpenSpiel: A framework for reinforcement learning in games
M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ...
arXiv preprint arXiv:1908.09453, 2019
1612019
Computing approximate equilibria in sequential adversarial games by exploitability descent
E Lockhart, M Lanctot, J Pérolat, JB Lespiau, D Morrill, F Timbers, K Tuyls
arXiv preprint arXiv:1903.05614, 2019
592019
Solving games with functional regret estimation
K Waugh, D Morrill, JA Bagnell, M Bowling
Twenty-ninth AAAI conference on artificial intelligence, 2015
592015
Neural replicator dynamics: Multiagent learning via hedging policy gradients
D Hennes, D Morrill, S Omidshafiei, R Munos, J Perolat, M Lanctot, ...
Proceedings of the 19th International Conference on Autonomous Agents and …, 2020
49*2020
Hindsight and sequential rationality of correlated play
D Morrill, R D'Orazio, R Sarfati, M Lanctot, JR Wright, AR Greenwald, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (6), 5584-5594, 2021
202021
Efficient deviation types and learning for hindsight rationality in extensive-form games
D Morrill, R D’Orazio, M Lanctot, JR Wright, M Bowling, AR Greenwald
International Conference on Machine Learning, 7818-7828, 2021
172021
Aivat: A new variance reduction technique for agent evaluation in imperfect information games
N Burch, M Schmid, M Moravcik, D Morill, M Bowling
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
152018
Using regret estimation to solve games compactly
DR Morrill
152016
The advantage regret-matching actor-critic
A Gruslys, M Lanctot, R Munos, F Timbers, M Schmid, J Perolat, D Morrill, ...
arXiv preprint arXiv:2008.12234, 2020
142020
Alternative Function Approximation Parameterizations for Solving Games: An Analysis of -Regression Counterfactual Regret Minimization
R D'Orazio, D Morrill, JR Wright, M Bowling
arXiv preprint arXiv:1912.02967, 2019
82019
Learning to Be Cautious
M Mohammedalamen, D Morrill, A Sieusahai, Y Satsangi, M Bowling
arXiv preprint arXiv:2110.15907, 2021
32021
Deepstack: expert-level artificial intelligence in no-limit poker. CoRR abs/1701.01724 (2017)
M Moravcık, M Schmid, N Burch, V Lisý, D Morrill, N Bard, T Davis, ...
3
The Partially Observable History Process
D Morrill, AR Greenwald, M Bowling
arXiv preprint arXiv:2111.08102, 2021
22021
Bounds for approximate regret-matching algorithms
R D'Orazio, D Morrill, JR Wright
arXiv preprint arXiv:1910.01706, 2019
12019
Interpolating Between Softmax Policy Gradient and Neural Replicator Dynamics with Capped Implicit Exploration
D Morrill, E Saleh, M Bowling, A Greenwald
arXiv preprint arXiv:2206.02036, 2022
2022
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games: Corrections
D Morrill, R D'Orazio, M Lanctot, JR Wright, M Bowling, AR Greenwald
arXiv preprint arXiv:2205.12031, 2022
2022
Hindsight Rational Learning for Sequential Decision-Making: Foundations and Experimental Applications
D Morrill
2022
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games Supplementary
D Morrill, R D’Orazio, M Lanctot, JR Wright, M Bowling, AR Greenwald
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Статии 1–19