Follow
Dustin Morrill
Dustin Morrill
Computing Science PhD Candidate, University of Alberta and the Alberta Machine Intelligence
Verified email at ualberta.ca - Homepage
Title
Cited by
Cited by
Year
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
7852017
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
124*2019
Solving games with functional regret estimation
K Waugh, D Morrill, JA Bagnell, M Bowling
Twenty-ninth AAAI conference on artificial intelligence, 2015
542015
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
442019
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
37*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
142021
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
142018
Using regret estimation to solve games compactly
DR Morrill
132016
Deepstack: expert-level artificial intelligence in no-limit poker. CoRR abs/1701.01724 (2017)
M Moravcík, M Schmid, N Burch, V Lisý, D Morrill, N Bard, T Davis, ...
arXiv preprint arXiv:1701.01724, 2017
122017
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
112021
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
92020
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
52019
The Partially Observable History Process
D Morrill, AR Greenwald, M Bowling
arXiv preprint arXiv:2111.08102, 2021
12021
Learning to Be Cautious
M Mohammedalamen, D Morrill, A Sieusahai, Y Satsangi, M Bowling
arXiv preprint arXiv:2110.15907, 2021
12021
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
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
The system can't perform the operation now. Try again later.
Articles 1–18