1 citations · 1 across the 1 of their papers we have counts for
4 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…
Mean-based algorithms: A lower bound and regret
Julius Durmann, Amelie Kleber
Mean-based algorithms are a class of online learning algorithms that assign low probability to actions with low average rewards. Recent work indicates these algorithms converge fav…
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…