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cs.GT2025
Meta-Learning in Self-Play Regret Minimization
David Sychrovský, Martin Schmid, Michal Šustr +1
Regret minimization is a general approach to online optimization which plays a crucial role in many algorithms for approximating Nash equilibria in two-player zero-sum games. The l…
cs.GT2023
Learning not to Regret
David Sychrovský, Michal Šustr, Elnaz Davoodi +3
The literature on game-theoretic equilibrium finding predominantly focuses on single games or their repeated play. Nevertheless, numerous real-world scenarios feature playing a gam…