Congratulations to the #NeurIPS2020 award winners

AIHub 

The winners of the NeurIPS 2020 awards have been announced. This year, three papers have received Best Paper Awards. There was also one Test of Time Award; this recognises a paper that has had significant and lasting impact on the community. No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium Andrea Celli, Alberto Marchesi, Gabriele Farina, Nicola Gatti Abstract: The existence of simple, uncoupled no-regret dynamics that converge to correlated equilibria in normal-form games is a celebrated result in the theory of multi-agent systems. Specifically, it has been known for more than 20 years that when all players seek to minimize their internal regret in a repeated normal-form game, the empirical frequency of play converges to a normal-form correlated equilibrium.

Duplicate Docs Excel Report

Title
None found

Similar Docs  Excel Report  more

TitleSimilaritySource
None found