Optimal Utility Design with Arbitrary Information Networks

2025-01-29

AI Summary

This work addresses multi-agent systems over arbitrary-information-topology networks, focusing on designing local agent behavioral rules to robustly improve worst-case global objective performance under distributed decision-making—i.e., maximizing the Price of Anarchy (PoA). We propose the first linear programming framework for characterizing PoA applicable to arbitrary observation topologies, enabling a universal optimal design method for local utility functions—thereby overcoming prior limitations requiring fully connected or symmetric network structures. Theoretical analysis yields an analytically tractable utility design algorithm. Numerical experiments demonstrate that, under perturbations such as stochastic communication link failures, our approach significantly outperforms baseline methods, maintaining high PoA stability across diverse topologies and disturbances.

Technology Category

• Multiagent Systems: Mechanism Design
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs

Abstract

We consider multi-agent systems with general information networks where an agent may only observe a subset of other agents. A system designer assigns local utility functions to the agents guiding their actions towards an outcome which determines the value of a given system objective. The aim is to design these local utility functions such that the Price of Anarchy (PoA), which equals the ratio of system objective at worst possible outcome to that at the optimal, is maximized. Towards this, we first develop a linear program (LP) that characterizes the PoA for any utility design and any information network. This leads to another LP that optimizes the PoA and derives the optimal utility design. Our work substantially generalizes existing approaches to the utility design problem. We also numerically show the robustness of proposed framework against unanticipated communication failures.

Problem

• Information Networks
• Behavioral Rules
• Price of Anarchy Optimization

Innovation

• Optimal Rule Discovery
• Robust Network Communication
• Mathematical Methodology