In this paper, we explore the concept of information design for efficient network flows. We examine how an omniscient planner can observe the state of a network and disclose information to users to minimize system costs. The full-information user equilibrium is a network flow that admits the minimum cost path for each network state. However, revealing full information is suboptimal for the system, as it may incentivize users to deviate from optimal paths. To address this challenge, we propose designing private signal policies to achieve optimality while maintaining user privacy.
Section A: Introduction
In this section, we introduce the context of information design and Bayesian routing games. We discuss how an omniscient planner can observe the state of a network and discloses information to users to minimize system costs. We also define the full-information user equilibrium as a network flow that admits the minimum cost path for each network state.
Section B: Problem Formulation
In this section, we formulate the problem of designing private signal policies to achieve optimality while maintaining user privacy. We discuss how any public signal is inefficient in achieving optimality and why it is important to design private signal policies that balance optimality with user privacy.
Conclusion
In conclusion, this paper explores the concept of information design for efficient network flows. By observing the state of a network and disclosing information to users, an omniscient planner can minimize system costs. However, revealing full information is suboptimal for the system, as it may incentivize users to deviate from optimal paths. To address this challenge, we propose designing private signal policies that achieve optimality while maintaining user privacy.
