Learning Deviation Payoffs in Simulation-Based Games. - Samuel Sokota; Caleb Ho; Bryce Wiedenbeck (AAAI, 2019)

Simultaneous Prediction Intervals for Patient-Specific Survival Curves. - Samuel Sokota; Ryan D'Orazio; Khurram Javed; Humza Haider; Russell Greiner (IJCAI, 2019)

Selective Dyna-Style Planning Under Limited Model Capacity. - Zaheer Abbas; Samuel Sokota; Erin Talvitie; Martha White (ICML, 2020)

Solving Common-Payoff Games with Approximate Policy Iteration. - Samuel Sokota; Edward Lockhart; Finbarr Timbers; Elnaz Davoodi; Ryan D'Orazio; Neil Burch; Martin Schmid; Michael Bowling; Marc Lanctot (AAAI, 2021)

Monte Carlo Tree Search With Iteratively Refining State Abstractions. - Samuel Sokota; Caleb Ho; Zaheen Farraz Ahmad; J. Zico Kolter (NeurIPS, 2021)

Implicit Communication as Minimum Entropy Coupling. - Samuel Sokota; Christian Schröder de Witt; Maximilian Igl; Luisa M. Zintgraf; Philip H. S. Torr; Shimon Whiteson; Jakob N. Foerster (CoRR, 2021)

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)

Communicating via Markov Decision Processes. - Samuel Sokota; Christian A. Schröder de Witt; Maximilian Igl; Luisa M. Zintgraf; Philip H. S. Torr; Martin Strohmeier; J. Zico Kolter; Shimon Whiteson; Jakob N. Foerster (ICML, 2022)

Off-Team Learning. - Brandon Cui; Hengyuan Hu; Andrei Lupu; Samuel Sokota; Jakob N. Foerster (NeurIPS, 2022)

Self-Explaining Deviations for Coordination. - Hengyuan Hu; Samuel Sokota; David J. Wu 002; Anton Bakhtin; Andrei Lupu; Brandon Cui; Jakob N. Foerster (NeurIPS, 2022)

Learning to Coordinate with Humans using Action Features. - Mingwei Ma; Jizhou Liu; Samuel Sokota; Max Kleiman-Weiner; Jakob N. Foerster (CoRR, 2022)

Adversarial Diversity in Hanabi. - Brandon Cui; Andrei Lupu; Samuel Sokota; Hengyuan Hu; David J. Wu 002; Jakob Nicolaus Foerster (ICLR, 2023)

Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. - Yat Long Lo; Christian Schröder de Witt; Samuel Sokota; Jakob Nicolaus Foerster; Shimon Whiteson (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)

Perfectly Secure Steganography Using Minimum Entropy Coupling. - Christian Schröder de Witt; Samuel Sokota; J. Zico Kolter; Jakob Nicolaus Foerster; Martin Strohmeier (ICLR, 2023)

Learning Intuitive Policies Using Action Features. - Mingwei Ma; Jizhou Liu; Samuel Sokota; Max Kleiman-Weiner; Jakob Nicolaus Foerster (ICML, 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)

Permutation Equivariant Neural Functionals. - Allan Zhou; Kaien Yang; Kaylee Burns; Adriano Cardace; Yiding Jiang; Samuel Sokota; J. Zico Kolter; Chelsea Finn (NeurIPS, 2023)

Neural Functional Transformers. - Allan Zhou; Kaien Yang; Yiding Jiang; Kaylee Burns; Winnie Xu; Samuel Sokota; J. Zico Kolter; Chelsea Finn (NeurIPS, 2023)

Permutation Equivariant Neural Functionals. - Allan Zhou; Kaien Yang; Kaylee Burns; Yiding Jiang; Samuel Sokota; J. Zico Kolter; Chelsea Finn (CoRR, 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)

Computing Low-Entropy Couplings for Large-Support Distributions. - Samuel Sokota; Dylan Sam; Christian Schröder de Witt; Spencer Compton; Jakob N. Foerster; J. Zico Kolter (UAI, 2024)

Reevaluating Policy Gradient Methods for Imperfect-Information Games. - Max Rudolph; Nathan Lichtle; Sobhan Mohammadpour; Alexandre M. Bayen; J. Zico Kolter; Amy Zhang 001; Gabriele Farina; Eugene Vinitsky; Samuel Sokota (CoRR, 2025)