Optimal Bayesian Persuasion for Containing SIS Epidemics

Fuente: arXiv
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Main Authors: Maitra, Urmee, Hota, Ashish R., Paré, Philip E.
Format: Preprint
Published: 2024
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author Maitra, Urmee
Hota, Ashish R.
Paré, Philip E.
author_facet Maitra, Urmee
Hota, Ashish R.
Paré, Philip E.
contents We consider a susceptible-infected-susceptible (SIS) epidemic model in which a large group of individuals decide whether to adopt partially effective protection without being aware of their individual infection status. Each individual receives a signal which conveys noisy information about its infection state, and then decides its action to maximize its expected utility computed using its posterior probability of being infected conditioned on the received signal. We first derive the static signal which minimizes the infection level at the stationary Nash equilibrium under suitable assumptions. We then formulate an optimal control problem to determine the optimal dynamic signal that minimizes the aggregate infection level along the solution trajectory. We compare the performance of the dynamic signaling scheme with the optimal static signaling scheme, and illustrate the advantage of the former through numerical simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2410_20303
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimal Bayesian Persuasion for Containing SIS Epidemics
Maitra, Urmee
Hota, Ashish R.
Paré, Philip E.
Systems and Control
We consider a susceptible-infected-susceptible (SIS) epidemic model in which a large group of individuals decide whether to adopt partially effective protection without being aware of their individual infection status. Each individual receives a signal which conveys noisy information about its infection state, and then decides its action to maximize its expected utility computed using its posterior probability of being infected conditioned on the received signal. We first derive the static signal which minimizes the infection level at the stationary Nash equilibrium under suitable assumptions. We then formulate an optimal control problem to determine the optimal dynamic signal that minimizes the aggregate infection level along the solution trajectory. We compare the performance of the dynamic signaling scheme with the optimal static signaling scheme, and illustrate the advantage of the former through numerical simulations.
title Optimal Bayesian Persuasion for Containing SIS Epidemics
topic Systems and Control
url https://arxiv.org/abs/2410.20303