In networks of autonomous agents (e.g., fleets of vehicles, scattered sensors), the problem of minimizing the sum of the agents' local functions has received a lot of interest. We tackle here this distributed optimization problem in the case of open networks when agents can join and leave the network at any time. Leveraging recent online optimization techniques, we propose and analyze the convergence of a decentralized asynchronous optimization method for open networks.

翻译：在自主代理商的网络中(例如车队、分散的传感器),最大限度地减少代理商当地功能的总和的问题引起了很大的兴趣。我们在这里处理在开放网络中分散的优化问题,代理商可随时加入和离开网络。我们利用最近的在线优化技术,提出和分析开放网络的分散式非同步优化方法的趋同。