Iterative Negotiation and Oversight: A Case Study in Decentralized Air Traffic Management

TL;DR

This paper introduces an iterative negotiation framework with oversight for decentralized multi-agent systems, ensuring system efficiency and fairness with formal guarantees, demonstrated through air traffic management case studies.

Contribution

It presents a novel oversight mechanism that guides decentralized negotiations towards efficient and equitable outcomes with proven finite-time convergence guarantees.

Findings

Framework achieves reliable consensus among noncooperative agents.

Oversight mechanism balances system efficiency and convergence speed.

Case study confirms practical applicability in air traffic management.

Abstract

Achieving consensus among noncooperative agents remains challenging in decentralized multi-agent systems, where agents often have conflicting preferences. Existing coordination methods enable agents to reach consensus without a centralized coordinator, but do not provide formal guarantees on system-level objectives such as efficiency or fairness. To address this limitation, we propose an iterative negotiation and oversight framework that augments a decentralized negotiation mechanism with taxation-like oversight. The framework builds upon the trading auction for consensus, enabling noncooperative agents with conflicting preferences to negotiate through asset trading while preserving valuation privacy. We introduce an oversight mechanism, which implements a taxation-like intervention that guides decentralized negotiation toward system-efficient and equitable outcomes while also regulating how fast the framework converges. We establish theoretical guarantees of finite-time termination and derive bounds linking system efficiency and convergence rate to the level of central intervention. A case study based on the collaborative trajectory options program, a rerouting initiative in U.S. air traffic management, demonstrates that the framework can reliably achieve consensus among noncooperative airspace sector managers, and reveals how the level of intervention regulates the relationship between system efficiency and convergence speed. Taken together, the theoretical and experimental results indicate that the proposed framework provides a general mechanism for decentralized coordination in noncooperative multi-agent systems while safeguarding system-level objectives.