Noah Golowich
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| title | conference | date |
|---|---|---|
| The Complexity of Markov Equilibrium in Stochastic Games | Multi-Agent Reinforcement Learning and Bandit Learning | 2022-04-29 |
Proves that computing stationary Markov CCE is PPAD-hard even for two-player turn-based stochastic games with a constant discount factor and constant… | ||
| Fast Rates for No-Regret Learning in General Games | Adversarial Approaches in Machine Learning 2022 | 2022-02-17 |
Shows that when all players use Optimistic Hedge in finite general‑sum games each player’s external regret falls to roughly O(log |A| · log^4 T) — i.e., near… | ||
| nothing matches | ||