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A Mean Field Game of Sequential Testing

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arxiv 2403.18297 v1 pith:6IERKMHG submitted 2024-03-27 math.OC math.PR

Steven Campbell , Yuchong Zhang This is my paper · ORCID
classification math.OCmath.PR
keywords fieldgamemeanfilteringsequentialtestingassumptionsbest
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We introduce a mean field game for a family of filtering problems related to the classic sequential testing of the drift of a Brownian motion. To the best of our knowledge this work presents the first treatment of mean field filtering games with stopping and an unobserved common noise in the literature. We show that the game is well-posed, characterize the solution, and establish the existence of an equilibrium under certain assumptions. We also perform numerical studies for several examples of interest.

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Cited by 1 Pith paper

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  1. A Bayesian sequential soft classification problem for a Brownian motion's drift

    math.PR 2025-01 conditional novelty 6.0 of 10

    The optimal stopping rule for soft classification of a Brownian drift is characterized by two free boundaries, with explicit asymptotic behavior in the signal-to-noise ratio.

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