12 citations · 27 across the 15 of their papers we have counts for
8 papers · 1 filter
Scalable Decision Making for Games of Imperfect Information
Samuel Sokota, Eugene Vinitsky, Hengyuan Hu +3
Real-world decision-making generally involves hidden information, that is, information that is unknown to one agent but possessed by another. Unfortunately, the presence of large a…
Reevaluating Policy Gradient Methods for Imperfect-Information Games
Max Rudolph, Nathan Lichtle, Sobhan Mohammadpour +6
In the past decade, motivated by the putative failure of naive self-play deep reinforcement learning (DRL) in adversarial imperfect-information games, researchers have developed nu…
Neural Functional Transformers
Allan Zhou, Kaien Yang, Yiding Jiang +5
The recent success of neural networks as implicit representation of data has driven growing interest in neural functionals: models that can process other neural networks as input b…
Permutation Equivariant Neural Functionals
Allan Zhou, Kaien Yang, Kaylee Burns +5
This work studies the design of neural networks that can process the weights or gradients of other neural networks, which we refer to as neural functional networks (NFNs). Despite…
A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games
Samuel Sokota, Ryan D'Orazio, J. Zico Kolter +5
This work studies an algorithm, which we call magnetic mirror descent, that is inspired by mirror descent and the non-Euclidean proximal gradient algorithm. Our contribution is dem…
Learning Intuitive Policies Using Action Features
Mingwei Ma, Jizhou Liu, Samuel Sokota +2
An unaddressed challenge in multi-agent coordination is to enable AI agents to exploit the semantic relationships between the features of actions and the features of observations.…
Selective Dyna-style Planning Under Limited Model Capacity
Zaheer Abbas, Samuel Sokota, Erin J. Talvitie +1
In model-based reinforcement learning, planning with an imperfect model of the environment has the potential to harm learning progress. But even when a model is imperfect, it may s…
Simultaneous Prediction Intervals for Patient-Specific Survival Curves
Samuel Sokota, Ryan D'Orazio, Khurram Javed +2
Accurate models of patient survival probabilities provide important information to clinicians prescribing care for life-threatening and terminal ailments. A recently developed clas…