A driving force in the development of technology, and hence society as a whole, is the automation of processes that were previously executed manually. For many tasks, this comes with an intrinsic need for sensing, estimation, and actuation-concepts that are well known in this community. Moreover, an increasing number of such applications involve large networks containing ensembles of agents that interact with other agents and the environment around them. Such physical systems, which communicate through digital communication channels and are autonomously controlled by computer-based algorithms, are called cyberphysical systems[1]. Examples that are currently being developed include self-driving cars [2], smart electric grids [3], and the Internet of Things [4]. However, there are plenty of other multiagent systems of interest, where the agents are not physical systems designed by humans. Examples of such dynamical systems include groups of animals [5], opinion dynamics among humans [6], and economic markets [7].

中文翻译：

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通过结构化最优传输控制和估计集成

技术发展乃至整个社会的驱动力是以前手动执行的流程的自动化。对于许多任务，这伴随着对本社区众所周知的传感、估计和驱动概念的内在需求。此外，越来越多的此类应用程序涉及包含与其他代理及其周围环境交互的代理集合的大型网络。这种通过数字通信渠道进行通信并由基于计算机的算法自主控制的物理系统称为网络物理系统[1]。目前正在开发的示例包括自动驾驶汽车 [2]、智能电网 [3] 和物联网 [4]。然而，还有很多其他有趣的多智能体系统，其中代理不是由人类设计的物理系统。这种动态系统的例子包括动物群体 [5]、人类之间的意见动态 [6] 和经济市场 [7]。