3 papers
cs.LG2025
On Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games
Yang Cai, Gabriele Farina, Julien Grand-Clément +4
Non-ergodic convergence of learning dynamics in games is widely studied recently because of its importance in both theory and practice. Recent work (Cai et al., 2024) showed that a…
cs.GT2025
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
Yang Cai, Gabriele Farina, Julien Grand-Clément +4
We study last-iterate convergence properties of algorithms for solving two-player zero-sum games based on Regret Matching (RM). Despite their widespread use for solving rea…
cs.GT2025
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
Yang Cai, Gabriele Farina, Julien Grand-Clément +4
Self-play via online learning is one of the premier ways to solve large-scale two-player zero-sum games, both in theory and practice. Particularly popular algorithms include optimi…