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M. Bichler

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Preprint Oct 2026

Simultaneous Gradient Learning in First-Price Auctions

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 symmetric independent private values model admits a unique Bayesian correlated equilibrium (BCE) in the continuous limit, standard converge...

Janik Bürgermeister, Julius Durmann, M. Bichler et al. · 0 citations
#machine learning Preprint Oct 2026

How language model agents reshape price competition

Repeated Bertrand competition is a stringent benchmark for algorithmic pricing: in homogeneous-goods markets, standard learning procedures typically select the stage-game Nash outcome with prices near marginal cost. We show that LLM pricing agents can escape this benchmark, depending on deployment decisions. LLMs outpe...

M. Bichler, Philip Hierhager, Kassian Köck et al. · 0 citations

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