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cs.LG2023
Achieving Better Regret against Strategic Adversaries
Le Cong Dinh, Tri-Dung Nguyen, Alain Zemkoho +1
We study online learning problems in which the learner has extra knowledge about the adversary's behaviour, i.e., in game-theoretic settings where opponents typically follow some n…
cs.LG2021★ 1 cited
Online Markov Decision Processes with Non-oblivious Strategic Adversary
Le Cong Dinh, David Henry Mguni, Long Tran-Thanh +2
We study a novel setting in Online Markov Decision Processes (OMDPs) where the loss function is chosen by a non-oblivious strategic adversary who follows a no-external regret algor…