Robustness of Incentive Mechanisms Against System Misspecification in Congestion Games

2025-05-17

AI Summary

This paper investigates the impact of system parameter misspecification on the robustness of tolling mechanisms in atomic congestion games. Addressing the degradation of incentive design efficacy under model mismatch, we propose a unified analytical framework integrating game-theoretic reasoning and robust optimization. We first prove that, under mild parameter misspecification, the originally designed tolls do not induce new Nash equilibria. Second, we derive a tight upper bound on the worst-case degradation of equilibrium social cost. Third, we validate the theoretical bounds via Monte Carlo simulations and explicit worst-case instance construction. Our core contribution is establishing rigorous local robustness guarantees for tolling mechanisms: we quantify how model uncertainty propagates into efficiency loss, and provide verifiable robustness criteria for incentive mechanism deployment in real-world transportation systems.

Technology Category

• Multiagent Systems: Mechanism Design
• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Game Theory and Economic Paradigms: Mechanism Design

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
• Security and Privacy: Large-scale security measurements

Abstract

To steer the behavior of selfish, resource-sharing agents in a socio-technical system towards the direction of higher efficiency, the system designer requires accurate models of both agent behaviors and the underlying system infrastructure. For instance, traffic controllers often use road latency models to design tolls whose deployment can effectively mitigate traffic congestion. However, misspecifications of system parameters may restrict a system designer's ability to influence collective agent behavior toward efficient outcomes. In this work, we study the impact of system misspecifications on toll design for atomic congestion games. We prove that tolls designed under sufficiently minor system misspecifications, when deployed, do not introduce new Nash equilibria in atomic congestion games compared to tolls designed in the noise-free setting, implying a form of local robustness. We then upper bound the degree to which the worst-case equilibrium system performance could decrease when tolls designed under a given level of system misspecification are deployed. We validate our theoretical results via Monte-Carlo simulations as well as realizations of our worst-case guarantees.

Problem

• Impact of system misspecifications on toll design
• Robustness of incentive mechanisms in congestion games
• Worst-case equilibrium performance under parameter misspecification

Innovation

• Tolls designed under minor system misspecifications maintain Nash equilibria
• Upper bounds worst-case equilibrium performance degradation
• Validated via Monte-Carlo simulations and worst-case guarantees