New no-regret learning dynamics achieve external and swap regret bounds that adapt to cumulative strategy and utility corruption in games.
Last-iterate convergence with full and noisy feedback in two-player zero-sum games
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Corrupted Learning Dynamics in Games
New no-regret learning dynamics achieve external and swap regret bounds that adapt to cumulative strategy and utility corruption in games.