论文标题
分布式二阶多代理在不平衡网络上优化而没有梯度的界限
Distributed Second-order Multi-Agent Optimization over unbalanced network without boundedness of gradients
论文作者
论文摘要
本文主要致力于通过不平衡和有向网络的分布式二阶多代理优化问题。为了解决这个问题，根据本地邻居信息和私人目标功能提出了一种新的分布式算法。通过协调转换，闭环系统被分为两个一阶子系统，这很容易处理。在网络的牢固连接性的假设下，证明所有代理都可以合作地收敛到团队目标函数的某些最佳解决方案，在这种函数的情况下，私人目标函数的梯度不被认为是有限的。
This paper is mainly devoted to the distributed second-order multi-agent optimization problem with unbalanced and directed networks. To deal with this problem, a new distributed algorithm is proposed based on the local neighbor information and the private objective functions. By a coordination transformation, the closed-loop system is divided into two first-order subsystems, which is easier to be dealt with. Under the assumption of the strong connectivity of networks, it is proved that all agent can collaboratively converge to some optimal solution of the team objective function, where the gradient of the private objective functions is not assumed to be bounded.
