Robust persuasion of a privately informed receiver

Hu, Ju; Wang, Xi

doi:10.1007/s00199-020-01299-5

Cited by 18 publications

(9 citation statements)

References 34 publications

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“…Literature on robust persuasion mainly utilises the maximin utility approach. Hu and Weng (2021) consider a setting in which nature chooses the private information of the receiver. Similar to our result, they find that even in the binary setting the optimal mechanism may involve infinitely many messages, with some messages persuading a receiver with certain private beliefs but failing to persuade her if her private beliefs were different.…”

Section: Introductionmentioning

confidence: 99%

“…Similar to our result, they find that even in the binary setting the optimal mechanism may involve infinitely many messages, with some messages persuading a receiver with certain private beliefs but failing to persuade her if her private beliefs were different. In contrast to Hu and Weng (2021), our paper does not rely on the common prior assumption (and a restriction on private beliefs that follows from it) and uses the minimax loss approach, rather than maximin utility.…”

Section: Introductionmentioning

confidence: 99%

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Persuasion without Priors

Parakhonyak

Sobolev

2023

SSRN Journal

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Persuasion without Priors

Parakhonyak

Sobolev

2023

SSRN Journal

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“…In Bayesian persuasion literature, robustness is explored in worst case, online and various other settings [12], [13], [14], [15], [16]. For instance, [17] considers information design where the designer learns unknown utilities via auctions.…”

Section: Introductionmentioning

confidence: 99%

Robust Optimization Approach to Information Design in Linear-Quadratic-Gaussian Games

Sezer¹,

Eksin²

2023

Preprint

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Information design in an incomplete information game includes a designer with the goal of influencing players' actions through signals generated from a designed probability distribution so that its objective function is optimized. We consider a setting in which the designer has partial knowledge on agents' utilities. We address the uncertainty about players' preferences by formulating a robust information design problem against worst case payoffs. If the players have quadratic payoffs that depend on the players' actions and an unknown payoff-relevant state, and signals on the state that follow a Gaussian distribution conditional on the state realization, then the information design problem under quadratic design objectives is a semidefinite program (SDP). Specifically, we consider ellipsoid perturbations over payoff coefficients in linear-quadratic-Gaussian (LQG) games. We show that this leads to a tractable robust SDP formulation. Numerical studies are carried out to identify the relation between the perturbation levels and the optimal information structures.

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“…Consequently, Bayesian persuasion under alternative models of belief formation and processing is a matter of acute interest. The receiver's systematic distortion of beliefs from Bayesian posteriors appears in De Clippel and Zhang (2021); correlation neglect in Levy et al (2018); the multiplicity of the receiver's priors in Kosterina (2020); the multiplicity of the designer's priors in Hu and Weng (2021), and the model misspecification by the designer in Dworczak and Pavan (2020). Yet, not only the development of such alternative models, but also their empirical testing and validation by the field data or in laboratory experiments are crucially important.…”

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confidence: 99%