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Noam Brown
Noam Brown
Research Scientist, OpenAI
Verified email at cs.cmu.edu - Homepage
Title
Cited by
Cited by
Year
Superhuman AI for multiplayer poker
N Brown, T Sandholm
Science 365 (6456), 885-890, 2019
8232019
Superhuman AI for heads-up no-limit poker: Libratus beats top professionals
N Brown, T Sandholm
Science 359 (6374), 418-424, 2018
8222018
Deep counterfactual regret minimization
N Brown, A Lerer, S Gross, T Sandholm
International Conference on Machine Learning, 2019
2402019
Safe and nested subgame solving for imperfect-information games
N Brown, T Sandholm
Neural Information Processing Systems, 2017
222*2017
Solving imperfect-information games via discounted regret minimization
N Brown, T Sandholm
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1829-1836, 2019
1622019
Human-level play in the game of Diplomacy by combining language models with strategic reasoning
Meta Fundamental AI Research Diplomacy Team (FAIR)†, A Bakhtin, ...
Science 378 (6624), 1067-1074, 2022
1422022
Libratus: The Superhuman AI for No-Limit Poker.
N Brown, T Sandholm
IJCAI, 5226-5228, 2017
1422017
Combining deep reinforcement learning and search for imperfect-information games
N Brown, A Bakhtin, A Lerer, Q Gong
Advances in Neural Information Processing Systems 33, 17057-17069, 2020
1322020
Depth-limited solving for imperfect-information games
N Brown, T Sandholm, B Amos
Advances in neural information processing systems 31, 2018
862018
Hierarchical abstraction, distributed equilibrium computation, and post-processing, with application to a champion no-limit Texas Hold'em agent
N Brown, S Ganzfried, T Sandholm
Workshops at the twenty-ninth AAAI conference on artificial intelligence, 2015
822015
Improving Policies via Search in Cooperative Partially Observable Games
A Lerer, H Hu, J Foerster, N Brown
AAAI Conference on Artificial Intelligence, 2020
702020
Off-belief learning
H Hu, A Lerer, B Cui, L Pineda, N Brown, J Foerster
International Conference on Machine Learning, 4369-4379, 2021
572021
Dream: Deep regret minimization with advantage baselines and model-free learning
E Steinberger, A Lerer, N Brown
arXiv preprint arXiv:2006.10410, 2020
522020
Dynamic thresholding and pruning for regret minimization
N Brown, C Kroer, T Sandholm
Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017
512017
Human-level performance in no-press diplomacy via equilibrium search
J Gray, A Lerer, A Bakhtin, N Brown
arXiv preprint arXiv:2010.02923, 2020
432020
Reduced space and faster convergence in imperfect-information games via pruning
N Brown, T Sandholm
International conference on machine learning, 596-604, 2017
39*2017
Simultaneous abstraction and equilibrium finding in games
N Brown, TW Sandholm
Carnegie Mellon University, 2015
392015
Modeling strong and human-like gameplay with KL-regularized search
AP Jacob, DJ Wu, G Farina, A Lerer, H Hu, A Bakhtin, J Andreas, N Brown
International Conference on Machine Learning, 9695-9728, 2022
382022
Regret-based pruning in extensive-form games
N Brown, T Sandholm
Advances in neural information processing systems 28, 2015
372015
A unified approach to reinforcement learning, quantal response equilibria, and two-player zero-sum games
S Sokota, R D'Orazio, JZ Kolter, N Loizou, M Lanctot, I Mitliagkas, ...
arXiv preprint arXiv:2206.05825, 2022
362022
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