Agent-Constrained Truthful Facility Location Games

2024-05-08

Algorithmic Game Theory

AI Summary

This paper studies truthful facility location games under agent-specific operational constraints—such as mobility limitations or privacy-preserving requirements—in multi-agent settings where each agent privately holds their true location. The objective is to design strategyproof mechanisms minimizing either the total cost (sum of distances from agents to assigned facilities) or the maximum cost (largest distance), while approximating optimal social welfare. It is the first work to incorporate explicit action constraints into truthful mechanism design, departing from the standard unconstrained assumption. The authors propose a constraint-aware threshold mechanism and a unified approximation analysis framework that integrates mechanism design, game theory, and approximation algorithms. Theoretically, the mechanism satisfies dominant-strategy truthfulness under diverse constraint classes and achieves O(1)-approximation guarantees for both total and maximum cost objectives. This significantly extends the applicability and theoretical foundations of truthful facility location.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Constraint Satisfaction and Optimization: Constraint Learning and Acquisition

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Problem

• truthful facility location
• private agent locations
• strategyproof mechanisms bounds

Innovation

• Truthful facility location
• Strategyproof mechanisms
• Social cost approximation