17 citations · 187 across the 55 of their papers we have counts for
8 papers · 1 filter
Fast Payoff Matrix Sparsification Techniques for Structured Extensive-Form Games
Gabriele Farina, Tuomas Sandholm
The practical scalability of many optimization algorithms for large extensive-form games is often limited by the games' huge payoff matrices. To ameliorate the issue, Zhang and San…
Modeling Strong and Human-Like Gameplay with KL-Regularized Search
Athul Paul Jacob, David J. Wu, Gabriele Farina +5
We consider the task of building strong but human-like policies in multi-agent decision-making problems, given examples of human behavior. Imitation learning is effective at predic…
Near-Optimal No-Regret Learning for Correlated Equilibria in Multi-Player General-Sum Games
Ioannis Anagnostides, Constantinos Daskalakis, Gabriele Farina +3
Recently, Daskalakis, Fishelson, and Golowich (DFG) (NeurIPS`21) showed that if all agents in a multi-player general-sum normal-form game employ Optimistic Multiplicative Weights U…
Efficient Decentralized Learning Dynamics for Extensive-Form Coarse Correlated Equilibrium: No Expensive Computation of Stationary Distributions Required
Gabriele Farina, Andrea Celli, Tuomas Sandholm
While in two-player zero-sum games the Nash equilibrium is a well-established prescriptive notion of optimal play, its applicability as a prescriptive tool beyond that setting is l…
Simple Uncoupled No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium
Gabriele Farina, Andrea Celli, Alberto Marchesi +1
The existence of simple uncoupled no-regret learning dynamics that converge to correlated equilibria in normal-form games is a celebrated result in the theory of multi-agent system…
Better Regularization for Sequential Decision Spaces: Fast Convergence Rates for Nash, Correlated, and Team Equilibria
Gabriele Farina, Christian Kroer, Tuomas Sandholm
We study the application of iterative first-order methods to the problem of computing equilibria of large-scale two-player extensive-form games. First-order methods must typically…
Bandit Linear Optimization for Sequential Decision Making and Extensive-Form Games
Gabriele Farina, Robin Schmucker, Tuomas Sandholm
Tree-form sequential decision making (TFSDM) extends classical one-shot decision making by modeling tree-form interactions between an agent and a potentially adversarial environmen…
Model-Free Online Learning in Unknown Sequential Decision Making Problems and Games
Gabriele Farina, Tuomas Sandholm
Regret minimization has proved to be a versatile tool for tree-form sequential decision making and extensive-form games. In large two-player zero-sum imperfect-information games, m…