Conference
META-LEARNING IN GAMES
META-LEARNING IN GAMES
Near-Optimal No-Regret Learning for Correlated Equilibria in Multi-Player General-Sum Games
On the Complexity of Computing Sparse Equilibria and Lower Bounds for No-Regret Learning in Games
Optimal Anytime Coalition Structure Generation Utilizing Compact Solution Space Representation
Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning
Faster No-Regret Learning Dynamics for Extensive-Form Correlated and Coarse Correlated Equilibria