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Showing cs.GTShow all
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cs.GT2024
No-regret learning in harmonic games: Extrapolation in the face of conflicting interests
Davide Legacci, Panayotis Mertikopoulos, Christos H. Papadimitriou +2
The long-run behavior of multi-agent learning - and, in particular, no-regret learning - is relatively well-understood in potential games, where players have aligned interests. By…
cs.GT2023
Local and adaptive mirror descents in extensive-form games
Côme Fiegel, Pierre Ménard, Tadashi Kozuno +3
We study how to learn -optimal strategies in zero-sum imperfect information games (IIG) with trajectory feedback. In this setting, players update their policies sequentially bas…
cs.GT2019★ 3 cited
Low-Variance and Zero-Variance Baselines for Extensive-Form Games
Trevor Davis, Martin Schmid, Michael Bowling
Extensive-form games (EFGs) are a common model of multi-agent interactions with imperfect information. State-of-the-art algorithms for solving these games typically perform full wa…