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

Abstract

Achieving consensus among self-interested 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 a regulated decentralized negotiation framework that augments a decentralized negotiation mechanism with limited regulatory oversight. The framework builds upon the trading auction for consensus, enabling self-interested agents with conflicting preferences to negotiate through asset trading while avoiding direct disclosure of private asset valuations. 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 regulatory 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 self-interested airspace sector managers, and reveals how the level of regulatory intervention regulates the relationship between system efficiency and convergence speed. Taken together, the theoretical and experimental results indicate that the proposed framework provides a mechanism for regulated decentralized coordination that preserves noncooperative final selection while safeguarding system-level objectives.