Generalized from the concept of consensus, this paper considers a group of edge agreements, i.e. constraints defined for neighboring agents, in which each pair of neighboring agents is required to satisfy one edge agreement constraint. Edge agreements are defined locally to allow more flexibility than a global consensus. This work formulates a multi-agent optimization problem under edge agreements and proposes a continuous-time distributed augmented Lagrangian algorithm. Both analytical proof and numerical examples are provided to validate the effectiveness of the proposed distributed algorithm.

翻译：本文从一致性概念推广出发，考虑一组边缘一致性约束（即为相邻智能体定义的约束条件），要求每对相邻智能体满足一项边缘一致性约束。与全局一致性相比，边缘一致性约束采用局部定义方式，从而具备更高的灵活性。本研究建立了一个在边缘一致性约束下的多智能体优化问题，并提出了一种连续时间分布式增广拉格朗日算法。通过解析证明与数值算例，验证了所提分布式算法的有效性。