Equilibrium Learning in Combinatorial Auctions: Computing Approximate Bayesian Nash Equilibria via Pseudogradient Dynamics. - Stefan Heidekrüger; Paul Sutterer; Nils Kohring; Maximilian Fichtl; Martin Bichler (CoRR, 2021)

Learning equilibria in symmetric auction games using artificial neural networks. - Martin Bichler; Maximilian Fichtl; Stefan Heidekrüger; Nils Kohring; Paul Sutterer (Nat. Mach. Intell., 2021)

Enabling First-Order Gradient-Based Learning for Equilibrium Computation in Markets. - Nils Kohring; Fabian Raoul Pieroth; Martin Bichler (ICML, 2023)

Equilibrium Computation in Multi-Stage Auctions and Contests. - Fabian R. Pieroth; Nils Kohring; Martin Bichler (CoRR, 2023)

Learning Equilibria in Asymmetric Auction Games. - Martin Bichler; Nils Kohring; Stefan Heidekrüger (INFORMS J. Comput., 2023)

Learning equilibrium in bilateral bargaining games. - Martin Bichler; Nils Kohring; Matthias Oberlechner; Fabian R. Pieroth (Eur. J. Oper. Res., 2023)

Multi-Agent Reinforcement Learning for the Computation of Market Equilibria. - Nils Kohring (2024)