17 citations · 187 across the 55 of their papers we have counts for
13 papers · 1 filter
Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning
Anton Bakhtin, David J Wu, Adam Lerer +5
No-press Diplomacy is a complex strategy game involving both cooperation and competition that has served as a benchmark for multi-agent AI research. While self-play reinforcement l…
Meta-Learning in Games
Keegan Harris, Ioannis Anagnostides, Gabriele Farina +3
In the literature on game-theoretic equilibrium finding, focus has mainly been on solving a single game in isolation. In practice, however, strategic interactions -- ranging from r…
Clairvoyant Regret Minimization: Equivalence with Nemirovski's Conceptual Prox Method and Extension to General Convex Games
Gabriele Farina, Christian Kroer, Chung-Wei Lee +1
A recent paper by Piliouras et al. [2021, 2022] introduces an uncoupled learning algorithm for normal-form games -- called Clairvoyant MWU (CMWU). In this note we show that CMWU is…
Near-Optimal -Regret Learning in Extensive-Form Games
Ioannis Anagnostides, Gabriele Farina, Tuomas Sandholm
In this paper, we establish efficient and uncoupled learning dynamics so that, when employed by all players in multiplayer perfect-recall imperfect-information extensive-form games…
Near-Optimal No-Regret Learning Dynamics for General Convex Games
Gabriele Farina, Ioannis Anagnostides, Haipeng Luo +3
A recent line of work has established uncoupled learning dynamics such that, when employed by all players in a game, each player's \emph{regret} after repetitions grows polylog…
ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret
Stephen McAleer, Gabriele Farina, Marc Lanctot +1
Recent techniques for approximating Nash equilibria in very large games leverage neural networks to learn approximately optimal policies (strategies). One promising line of researc…
Uncoupled Learning Dynamics with Swap Regret in Multiplayer Games
Ioannis Anagnostides, Gabriele Farina, Christian Kroer +3
In this paper we establish efficient and \emph{uncoupled} learning dynamics so that, when employed by all players in a general-sum multiplayer game, the \emph{swap regret} of each…
On Last-Iterate Convergence Beyond Zero-Sum Games
Ioannis Anagnostides, Ioannis Panageas, Gabriele Farina +1
Most existing results about \emph{last-iterate convergence} of learning dynamics are limited to two-player zero-sum games, and only apply under rigid assumptions about what dynamic…
Optimistic Mirror Descent Either Converges to Nash or to Strong Coarse Correlated Equilibria in Bimatrix Games
Ioannis Anagnostides, Gabriele Farina, Ioannis Panageas +1
We show that, for any sufficiently small fixed , when both players in a general-sum two-player (bimatrix) game employ optimistic mirror descent (OMD) with smooth regularizati…
Optimal Correlated Equilibria in General-Sum Extensive-Form Games: Fixed-Parameter Algorithms, Hardness, and Two-Sided Column-Generation
Brian Zhang, Gabriele Farina, Andrea Celli +1
We study the problem of finding optimal correlated equilibria of various sorts in extensive-form games: normal-form coarse correlated equilibrium (NFCCE), extensive-form coarse cor…
Faster No-Regret Learning Dynamics for Extensive-Form Correlated and Coarse Correlated Equilibria
Ioannis Anagnostides, Gabriele Farina, Christian Kroer +2
A recent emerging trend in the literature on learning in games has been concerned with providing faster learning dynamics for correlated and coarse correlated equilibria in normal-…
Team Belief DAG: Generalizing the Sequence Form to Team Games for Fast Computation of Correlated Team Max-Min Equilibria via Regret Minimization
Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm
A classic result in the theory of extensive-form games asserts that the set of strategies available to any perfect-recall player is strategically equivalent to a low-dimensional co…
Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games
Gabriele Farina, Chung-Wei Lee, Haipeng Luo +1
While extensive-form games (EFGs) can be converted into normal-form games (NFGs), doing so comes at the cost of an exponential blowup of the strategy space. So, progress on NFGs an…