Paper recorded by Signals 4 on 2026-09-03 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-03 on arXiv · recorded by Signals 4 on 2026-09-04
Category: cs.LG · 机器学习 · first seen 2026-09-04
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 (HOOD) is a variant of optimistic follow-the-regularized-leader (OptFTRL) that