1 citations · 1 across the 1 of their papers we have counts for
6 papers
Online Optimization Algorithms in Repeated Price Competition: Equilibrium Learning and Algorithmic Collusion
Martin Bichler, Julius Durmann, Matthias Oberlechner
This paper investigates whether online learning algorithms in pricing produce competitive outcomes or tacit collusion. This issue has drawn considerable attention from competition…
Agentic Markets: Game Dynamics and Equilibrium in Markets with Learning Agents
Martin Bichler, Julius Durmann, Matthias Oberlechner
Autonomous and learning agents increasingly participate in markets - setting prices, placing bids, ordering inventory. Such agents are not just aiming to optimize in an uncertain e…
Algorithmic Pricing and Algorithmic Collusion
Martin Bichler, Julius Durmann, Matthias Oberlechner
The rise of algorithmic pricing in online retail platforms has attracted significant interest in how autonomous software agents interact under competition. This article explores th…
Characterizing the Convergence of Game Dynamics via Potentialness
Martin Bichler, Davide Legacci, Panayotis Mertikopoulos +2
Understanding the convergence landscape of multi-agent learning is a fundamental problem of great practical relevance in many applications of artificial intelligence and machine le…
On the Convergence of Learning Algorithms in Bayesian Auction Games
Martin Bichler, Stephan B. Lunowa, Matthias Oberlechner +2
Equilibrium problems in Bayesian auction games can be described as systems of differential equations. Depending on the model assumptions, these equations might be such that we do n…
Revenue in First- and Second-Price Display Advertising Auctions: Understanding Markets with Learning Agents
Martin Bichler, Alok Gupta, Matthias Oberlechner
The transition of display ad exchanges from second-price auctions (SPA) to first-price auctions (FPA) has raised questions about its impact on revenue. Auction theory predicts the…