Constant Individual Regret in General Games
Abstract
Uncoupled no-regret dynamics provide a decentralized route to equilibrium, but prior guarantees for individual regret retain a polylogarithmic dependence on the horizon. We remove this dependence for every finite $N$-player normal-form game under full-information feedback. We introduce \emph{ECHO-OFTRL}: optimistic follow-the-regularized-leader (OFTRL) equipped with an EMA cascade for high-order optimism (ECHO), where EMA denotes exponential moving average. The algorithm is deterministic and ful...
Description / Details
Uncoupled no-regret dynamics provide a decentralized route to equilibrium, but prior guarantees for individual regret retain a polylogarithmic dependence on the horizon. We remove this dependence for every finite -player normal-form game under full-information feedback. We introduce \emph{ECHO-OFTRL}: optimistic follow-the-regularized-leader (OFTRL) equipped with an EMA cascade for high-order optimism (ECHO), where EMA denotes exponential moving average. The algorithm is deterministic and fully uncoupled. If denotes the largest action-set size, then, simultaneously for every horizon , it guarantees that each of the players in the game incurs regret upper bounded by . Our algorithm leverages a new form of optimism inspired by modern filter design.
Source: arXiv:2608.31166v1 - http://arxiv.org/abs/2608.31166v1 PDF: https://arxiv.org/pdf/2608.31166v1 Original Link: http://arxiv.org/abs/2608.31166v1
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Sep 1, 2026
Data Science
Machine Learning
0