5 papers
Simultaneous Gradient Learning in First-Price Auctions
Janik Bürgermeister, Julius Durmann, Martin Bichler +3
We study equilibrium learning in discretized Bayesian games, focusing on first-price auctions as a testbed for gradient-based learning dynamics under private information. While the…
Gradient Dynamics in First-Price Auctions: Iterative Strategy Elimination via Cubic Potentials
Mete Şeref Ahunbay, Weiqiang Zheng, Tao Lin
We show that in discretised first-price auctions with complete information, if the buyers learn to bid with online gradient ascent, in time-average the outcome is (almost) the effi…
Avoiding the Worst: The Computational Complexity of Not Worst-Responding
Mete Şeref Ahunbay, Paul W. Goldberg, Edwin Lock +3
Finding, counting, or determining the existence of pure Nash equilibria, where players must play optimally given the others' actions, are known to be computationally intractable pr…
First-order (coarse) correlated equilibria in non-concave games
Mete Şeref Ahunbay
We investigate first-order notions of correlated equilibria in smooth games, in which players do not incur any regret against small modifications of their actions prescribed by som…
On the Uniqueness of Bayesian Coarse Correlated Equilibria in Standard First-Price and All-Pay Auctions
Mete Şeref Ahunbay, Martin Bichler
We study the Bayesian coarse correlated equilibrium (BCCE) of continuous and discretised first-price and all-pay auctions under the standard symmetric independent private-values mo…