Intervention Mechanism Design for Networks With Selfish Users

TL;DR

This paper introduces a novel intervention mechanism framework for networks with selfish users, aiming to optimize network performance by designing intervention games and equilibria, offering advantages over traditional pricing strategies.

Contribution

It develops a general intervention mechanism design framework, introduces intervention games and equilibrium concepts, and analyzes optimal interventions with perfect monitoring, applicable to diverse network scenarios.

Findings

Intervention mechanisms can outperform pricing strategies in requiring less user knowledge.

Analytic results on intervention equilibrium for a benevolent manager with perfect monitoring.

Illustrative example using a random access model demonstrates effectiveness.

Abstract

We consider a multi-user network where a network manager and selfish users interact. The network manager monitors the behavior of users and intervenes in the interaction among users if necessary, while users make decisions independently to optimize their individual objectives. In this paper, we develop a framework of intervention mechanism design, which is aimed to optimize the objective of the manager, or the network performance, taking the incentives of selfish users into account. Our framework is general enough to cover a wide range of application scenarios, and it has advantages over existing approaches such as Stackelberg strategies and pricing. To design an intervention mechanism and to predict the resulting operating point, we formulate a new class of games called intervention games and a new solution concept called intervention equilibrium. We provide analytic results about intervention equilibrium and optimal intervention mechanisms in the case of a benevolent manager with perfect monitoring. We illustrate these results with a random access model. Our illustrative example suggests that intervention requires less knowledge about users than pricing.