812 citations · 1.4k across the 24 of their papers we have counts for
7 papers · 1 filter
Hindsight and Sequential Rationality of Correlated Play
Dustin Morrill, Ryan D'Orazio, Reca Sarfati +4
Driven by recent successes in two-player, zero-sum game solving and playing, artificial intelligence work on games has increasingly focused on algorithms that produce equilibrium-b…
Useful Policy Invariant Shaping from Arbitrary Advice
Paniz Behboudian, Yash Satsangi, Matthew E. Taylor +2
Reinforcement learning is a powerful learning paradigm in which agents can learn to maximize sparse and delayed reward signals. Although RL has had many impressive successes in com…
The Advantage Regret-Matching Actor-Critic
Audrūnas Gruslys, Marc Lanctot, Rémi Munos +10
Regret minimization has played a key role in online learning, equilibrium computation in games, and reinforcement learning (RL). In this paper, we describe a general model-free RL…
Marginal Utility for Planning in Continuous or Large Discrete Action Spaces
Zaheen Farraz Ahmad, Levi H. S. Lelis, Michael Bowling
Sample-based planning is a powerful family of algorithms for generating intelligent behavior from a model of the environment. Generating good candidate actions is critical to the s…
Sound Algorithms in Imperfect Information Games
Michal Šustr, Martin Schmid, Matej Moravčík +3
Search has played a fundamental role in computer game research since the very beginning. And while online search has been commonly used in perfect information games such as Chess a…
Sample-Efficient Model-based Actor-Critic for an Interactive Dialogue Task
Katya Kudashkina, Valliappa Chockalingam, Graham W. Taylor +1
Human-computer interactive systems that rely on machine learning are becoming paramount to the lives of millions of people who use digital assistants on a daily basis. Yet, further…