Joint Information and Mechanism Design for Queues with Heterogeneous Users

Heydaribeni, Nasimeh; Anastasopoulos, Achilleas

doi:10.1109/cdc45484.2021.9683640

Cited by 7 publications

(5 citation statements)

References 24 publications

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“…Proof: See Appendix. The condition in (11) ensures that X is a Bayesian correlated equilibrium (BCE), see [19] for a definition.…”

Section: Robust Information Design Under Finite Scenariosmentioning

confidence: 99%

“…Thus, we cannot enforce exact BCE explicitly for the worst-case scenario, and annul the other cases using integer variables as is done in ( 12)- (15). Instead, we relax the BCE constraint in (11) as…”

Section: An Sdp Formulation For Social Welfare Maximization Via Infor...mentioning

confidence: 99%

“…For scalar signals ω i ∈ R, if we let b i = 1 and āi = E ζ [ω i ] for i ∈ N , then we have a i = ω i by (41). Moreover, the set of equations in (46) is equivalent to (11).…”

Section: Appendixmentioning

confidence: 99%

“…Various entities such as social media companies [6], advertisements platforms [7] and public health agencies [8] could be considered as information designers. In control systems, information design is employed for routing games [9], Vehicle-to-Vehicle communication [10], and queue management under heterogeneous users [11].…”

Section: Introductionmentioning

confidence: 99%

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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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“…Proof: See Appendix. The condition in (11) ensures that X is a Bayesian correlated equilibrium (BCE), see [19] for a definition.…”

Section: Robust Information Design Under Finite Scenariosmentioning

confidence: 99%

Section: An Sdp Formulation For Social Welfare Maximization Via Infor...mentioning

confidence: 99%

“…For scalar signals ω i ∈ R, if we let b i = 1 and āi = E ζ [ω i ] for i ∈ N , then we have a i = ω i by (41). Moreover, the set of equations in (46) is equivalent to (11).…”

Section: Appendixmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Sezer¹,

Eksin²

2023

Preprint

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“…Inventive mechanisms, where users are assessed monetary penalties or rewards based on their actions, have long been studied as an effective means of coordinating system behavior [17]- [21]. The interplay between incentives and signalling is an emerging area of study, and has up until now been limited to studying mechanisms where users must pay to acquire information [22]- [24]. To the best of our knowledge, no current work has studied how monetary incentives and information signalling can be used Fig.…”

Section: Introductionmentioning

confidence: 99%

Avoiding Unintended Consequences: How Incentives Aid Information Provisioning in Bayesian Congestion Games

Ferguson¹,

Brown²,

Marden³

2022

Preprint

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When users lack specific knowledge of various system parameters, their uncertainty may lead them to make undesirable deviations in their decision making. To alleviate this, an informed system operator may elect to signal information to uninformed users with the hope of persuading them to take more preferable actions. In this work, we study public and truthful signalling mechanisms in the context of Bayesian congestion games on parallel networks. We provide bounds on the possible benefit a signalling policy can provide with and without the concurrent use of monetary incentives. We find that though revealing information can reduce system cost in some settings, it can also be detrimental and cause worse performance than not signalling at all. However, by utilizing both signalling and incentive mechanisms, the system operator can guarantee that revealing information does not worsen performance while offering similar opportunities for improvement. These findings emerge from the closed form bounds we derive on the benefit a signalling policy can provide. We provide a numerical example which illustrates the phenomenon that revealing more information can degrade performance when incentives are not used and improves performance when incentives are used.

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Information Design for a Non-atomic Service Scheduling Game

Heydaribeni

Savla

2021

2021 60th IEEE Conference on Decision and Control (CDC)

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Joint Information and Mechanism Design for Queues with Heterogeneous Users

Cited by 7 publications

References 24 publications

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

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

Avoiding Unintended Consequences: How Incentives Aid Information Provisioning in Bayesian Congestion Games

Information Design for a Non-atomic Service Scheduling Game

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