Regret Transfer and Parameter Optimization. - Noam Brown; Tuomas Sandholm (AAAI, 2014)

Tartanian7: A Champion Two-Player No-Limit Texas Hold'em Poker-Playing Program. - Noam Brown; Sam Ganzfried; Tuomas Sandholm (AAAI, 2015)

Hierarchical Abstraction, Distributed Equilibrium Computation, and Post-Processing, with Application to a Champion No-Limit Texas Hold'em Agent. - Noam Brown; Sam Ganzfried; Tuomas Sandholm (AAAI Workshop: Computer Poker and Imperfect Information, 2015)

Simultaneous Abstraction and Equilibrium Finding in Games. - Noam Brown; Tuomas Sandholm (IJCAI, 2015)

Regret-Based Pruning in Extensive-Form Games. - Noam Brown; Tuomas Sandholm (NIPS, 2015)

Strategy-Based Warm Starting for Regret Minimization in Games. - Noam Brown; Tuomas Sandholm (AAAI, 2016)

Baby Tartanian8: Winning Agent from the 2016 Annual Computer Poker Competition. - Noam Brown; Tuomas Sandholm (IJCAI, 2016)

Dynamic Thresholding and Pruning for Regret Minimization. - Noam Brown; Christian Kroer; Tuomas Sandholm (AAAI, 2017)

Reduced Space and Faster Convergence in Imperfect-Information Games via Regret-Based Pruning. - Noam Brown; Tuomas Sandholm (AAAI Workshops, 2017)

Safe and Nested Endgame Solving for Imperfect-Information Games. - Noam Brown; Tuomas Sandholm (AAAI Workshops, 2017)

Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning. - Noam Brown; Tuomas Sandholm (ICML, 2017)

Libratus: The Superhuman AI for No-Limit Poker. - Noam Brown; Tuomas Sandholm (IJCAI, 2017)

Safe and Nested Subgame Solving for Imperfect-Information Games. - Noam Brown; Tuomas Sandholm (NIPS, 2017)

Depth-Limited Solving for Imperfect-Information Games. - Noam Brown; Tuomas Sandholm; Brandon Amos (NeurIPS, 2018)

Reports of the Workshops of the 32nd AAAI Conference on Artificial Intelligence. - Bruno Bouchard 001; Kevin Bouchard; Noam Brown; Niyati Chhaya; Eitan Farchi; Sébastien Gaboury; Christopher W. Geib; Amelie Gyrard; Kokil Jaidka; Sarah Keren; Roni Khardon; Parisa Kordjamshidi; et al. (AI Mag., 2018)

Solving Imperfect-Information Games via Discounted Regret Minimization. - Noam Brown; Tuomas Sandholm (AAAI, 2019)

Deep Counterfactual Regret Minimization. - Noam Brown; Adam Lerer; Sam Gross; Tuomas Sandholm (ICML, 2019)

Stable-Predictive Optimistic Counterfactual Regret Minimization. - Gabriele Farina; Christian Kroer; Noam Brown; Tuomas Sandholm (ICML, 2019)

Improving Policies via Search in Cooperative Partially Observable Games. - Adam Lerer; Hengyuan Hu; Jakob N. Foerster; Noam Brown (AAAI, 2020)

Combining Deep Reinforcement Learning and Search for Imperfect-Information Games. - Noam Brown; Anton Bakhtin; Adam Lerer; Qucheng Gong (NeurIPS, 2020)

DREAM: Deep Regret minimization with Advantage baselines and Model-free learning. - Eric Steinberger; Adam Lerer; Noam Brown (CoRR, 2020)

Unlocking the Potential of Deep Counterfactual Value Networks. - Ryan Zarick; Bryan Pellegrino; Noam Brown; Caleb Banister (CoRR, 2020)

Safe Search for Stackelberg Equilibria in Extensive-Form Games. - Chun Kai Ling; Noam Brown (AAAI, 2021)

Human-Level Performance in No-Press Diplomacy via Equilibrium Search. - Jonathan Gray; Adam Lerer; Anton Bakhtin; Noam Brown (ICLR, 2021)

Off-Belief Learning. - Hengyuan Hu; Adam Lerer; Brandon Cui; Luis Pineda; Noam Brown; Jakob N. Foerster (ICML, 2021)

No-Press Diplomacy from Scratch. - Anton Bakhtin; David J. Wu 002; Adam Lerer; Noam Brown (NeurIPS, 2021)

Scalable Online Planning via Reinforcement Learning Fine-Tuning. - Arnaud Fickinger; Hengyuan Hu; Brandon Amos; Stuart J. Russell; Noam Brown (NeurIPS, 2021)

Off-Belief Learning. - Hengyuan Hu; Adam Lerer; Brandon Cui; Luis Pineda; David J. Wu 002; Noam Brown; Jakob N. Foerster (CoRR, 2021)

Learned Belief Search: Efficiently Improving Policies in Partially Observable Settings. - Hengyuan Hu; Adam Lerer; Noam Brown; Jakob N. Foerster (CoRR, 2021)

Modeling Strong and Human-Like Gameplay with KL-Regularized Search. - Athul Paul Jacob; David J. Wu 002; Gabriele Farina; Adam Lerer; Anton Bakhtin; Jacob Andreas; Noam Brown (CoRR, 2021)

Equilibrium Finding in Normal-Form Games via Greedy Regret Minimization. - Hugh Zhang; Adam Lerer; Noam Brown (AAAI, 2022)

A Fine-Tuning Approach to Belief State Modeling. - Samuel Sokota; Hengyuan Hu; David J. Wu 002; J. Zico Kolter; Jakob Nicolaus Foerster; Noam Brown (ICLR, 2022)

Modeling Strong and Human-Like Gameplay with KL-Regularized Search. - Athul Paul Jacob; David J. Wu 002; Gabriele Farina; Adam Lerer; Hengyuan Hu; Anton Bakhtin; Jacob Andreas; Noam Brown (ICML, 2022)

Human-AI Coordination via Human-Regularized Search and Learning. - Hengyuan Hu; David J. Wu 002; Adam Lerer; Jakob N. Foerster; Noam Brown (CoRR, 2022)

Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning. - Anton Bakhtin; David J. Wu 002; Adam Lerer; Jonathan Gray; Athul Paul Jacob; Gabriele Farina; Alexander H. Miller; Noam Brown (ICLR, 2023)

A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games. - Samuel Sokota; Ryan D'Orazio; J. Zico Kolter; Nicolas Loizou; Marc Lanctot; Ioannis Mitliagkas; Noam Brown; Christian Kroer (ICLR, 2023)

Abstracting Imperfect Information Away from Two-Player Zero-Sum Games. - Samuel Sokota; Ryan D'Orazio; Chun Kai Ling; David J. Wu 002; J. Zico Kolter; Noam Brown (ICML, 2023)

The Update-Equivalence Framework for Decision-Time Planning. - Samuel Sokota; Gabriele Farina; David J. Wu 002; Hengyuan Hu; Kevin A. Wang; J. Zico Kolter; Noam Brown (ICLR, 2024)