Robust Information Design with Heterogeneous Beliefs in Bayesian Congestion Games

2026-04-12

AI Summary

This work addresses the fragility of obedience in Bayesian congestion games when users’ beliefs about recommendation signals deviate from the planner’s assumed prior. Focusing on affine-latency congestion games over parallel networks, the paper proposes an information design method robust to perturbations in user beliefs. By characterizing the robustness radius of obedience under heterogeneous beliefs, it establishes necessary and sufficient conditions for the non-emptiness of the robust obedience region and uncovers a trade-off between robustness and system performance. The proposed robust value function demonstrates that the optimal social cost increases monotonically with the robustness requirement, with its local sensitivity governed by the active obedience constraints, thereby confirming both the feasibility and the inherent cost of robust information mechanisms.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Reasoning under Uncertainty: Stochastic Optimization

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

In many engineered systems, agents make decisions under incomplete information, creating opportunities for a planner to influence decentralized behavior through signaling. We study how such signaling can be designed in parallel-network, affine latency congestion games when users may not interpret recommendations using the same beliefs assumed by the planner. To do so, we consider Bayesian congestion games with private recommendations and formulate a robust information design problem in which obedience must hold uniformly over a neighborhood of a nominal prior. This addresses the previously uncharacterized issue of whether obedience itself remains reliable under belief heterogeneity, rather than only under the single prior used at the design stage. We characterize policy-level robustness radii, identify regimes in which the robust obedience region remains nonempty, and analyze the resulting robustness--performance tradeoff through a robust value function whose optimal cost is monotone in the robustness requirement and whose local sensitivity is governed by the active obedience constraints.

Problem

• information design
• belief heterogeneity
• Bayesian congestion games
• robust obedience
• signaling

Innovation

• Robust Information Design
• Bayesian Congestion Games
• Heterogeneous Beliefs
• Obedience Constraints
• Robustness-Performance Tradeoff