Author

Omar Abbadi

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#machine learning Preprint Sep 2026

Constant regret in general games via higher-order optimism

We introduce an uncoupled learning algorithm which, when employed by all players of an arbitrary $N$-player normal form game with up to $K$ actions per player, guarantees $O(N^3\log^2 K)$ individual regret, uniformly over the horizon of play. The proposed algorithm - which we call higher-order optimism with discounting...

Omar Abbadi, R. Laraki, P. Mertikopoulos · 4 citations · ⚡4

Preprint Aug 2026

What preferences can - and cannot - predict in multi-agent online learning

A three-player game is constructed with a preferentially stable set whose span is dynamically unstable, showing that preferences do not suffice as a criterion of dynamic stability and bridges the gap via the notion of resilience under aggregate deviations.

Omar Abbadi, R. Laraki, P. Mertikopoulos · 2 citations