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
1222 2017 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
271 2019 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
79 2019 Solving games with functional regret estimation K Waugh, D Morrill, J Bagnell, M Bowling
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
68 2015 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
54 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
39 2021 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
37 2021 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
26 2020 OpenSpiel: a framework for reinforcement learning in games. CoRR abs/1908.09453 (2019) M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ...
arXiv preprint arXiv:1908.09453, 2019
24 2019 Neural replicator dynamics D Hennes, D Morrill, S Omidshafiei, R Munos, J Perolat, M Lanctot, ...
arXiv preprint arXiv:1906.00190, 2019
23 2019 Using regret estimation to solve games compactly DR Morrill
18 2016 Alternative Function Approximation Parameterizations for Solving Games: An Analysis of R D'Orazio, D Morrill, JR Wright, M Bowling
arXiv preprint arXiv:1912.02967, 2019
11 2019 Neural replicator dynamics S Omidshafiei, D Hennes, D Morrill, R Munos, J Perolat, M Lanctot, ...
arXiv preprint arXiv:1906.00190, 2019
11 2019 Learning to Be Cautious M Mohammedalamen, D Morrill, A Sieusahai, Y Satsangi, M Bowling
arXiv preprint arXiv:2110.15907, 2021
3 2021 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
2 2021 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
1 2022 Hindsight Rational Learning for Sequential Decision-Making: Foundations and Experimental Applications D Morrill
1 2022 Bounds for approximate regret-matching algorithms R D'Orazio, D Morrill, JR Wright
arXiv preprint arXiv:1910.01706, 2019
1 2019 Composing efficient and robust tests to assess artificial agents D Morrill, TJ Walsh, D Hernandez
US Patent App. 18/418,835, 2024
2024 