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Preprint Sep 2026

Risk-Averse Bayesian Games with an Unknown Type Distribution: Bayesian Learning, Equilibrium Analysis, and Finite-Sample Guarantees

Classical Bayesian games assume that the joint distribution of players'types is common knowledge, an assumption that rarely holds in practical applications. We address this issue by studying a group of myopic players who repeatedly interact under the Bayesian Nash conjecture and learn a parametric joint type distributi...

Yuan Tao, Hui-Fu Xu · 1 citation
#machine learning Preprint Sep 2026

Error Bounds for Statistical Estimators in BTL Model with Parametric Multivariate Utility Functions

We study preference elicitation under the Bradley-Terry-Luce (BTL) model where the true partworth vector is unknown and has to be estimated as a parameter with elicited preference information. The set of selected pairwise queries is non-uniform, deterministic, and arbitrary over a collection of alternatives, provided t...

Yi-Chen Li, Hui-Fu Xu · 1 citation
Sep 2026

Continuous and Monotone Bayesian Nash Equilibrium with Incomplete Information about Player’s Risk Preferences

Abstract. In this paper, we consider a noncollaborative game where each player faces two types of uncertainty: aleatoric uncertainty arising from inherent randomness of underlying data in its own decision-making problem and epistemic uncertainty arising from lack of knowledge and statistical information on the rivals’...

Zi-Heng Su, Hui-Fu Xu · 4 citations

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