Decentralized stochastic control: information structures, communication, and learning

拟议的研究方案的目标是开发一种系统的方法来实现分散系统的最优控制，其中所有主体都有一个共同的目标。这种系统出现在几乎所有现代技术中，包括网络控制系统、通信网络、传感器和监视网络、环境遥感、智能电网、交通网络、监测和诊断系统以及机器人技术。在这些不同的应用中出现分散控制问题的原因是，与单个代理共享所有相关信息在技术上或经济上并不总是可行的。虽然这是真的，但在代理的子集之间共享一些相关信息是可行的。在这个研究项目中，我们研究了这种信息共享如何简化分散系统的设计。*这个建议映射了一个五年的研究计划，以解决两个基本问题：(Q1)假设在系统开始运行之前，有资源在代理之间建立固定数量的通信链路。应该建设哪些互联互通？(Q2)假设，一旦系统开始运行，代理可以以一定的成本与其他代理通信信息。代理应在何时、在什么情况下通信以及与谁通信？为了回答这些问题，将寻求三个方向：(1)确定导致易处理设计的新的信息结构类别。(2)确定最优传输策略，以确定代理何时应该与其他代理通信信息。(3)在系统模型未知的情况下，针对上述两个方向制定学习和适应策略。*拟议的研究计划将在系统科学和控制工程的基础领域为4名博士生和3名研究生提供广泛的培训，从而为他们未来的工作提供坚实的基础。在这个项目中获得的成果将在网络控制系统、交通网络、智能电网、传感器和监视网络、医疗保健监测和机器人领域得到应用。

The objective of the proposed research program is to develop a systematic methodology for the optimal control of decentralized systems where all agents have a common objective. Such systems arise in almost all modern technologies, including networked control systems, communication networks, sensor and surveillance networks, environmental remote sensing, smart grids, transportation networks, monitoring and diagnostic systems, and robotics. The reason that decentralized control problems arise in these varied applications is that it is not always technologically or economically feasible to share all pertinent information with a single agent. While this is true, it is feasible to share some pertinent information among a subset of agents. In this research program we investigate how such information sharing simplifies the design of decentralized systems.******This proposal maps a five year research program to address two fundamental questions: (Q1) Suppose, before the system starts running, there are resources to build a fixed number of communication links between agents. Which links should be built? (Q2) Suppose, once the system starts running, agents can communicate information to other agents at a cost. When and what should the agents communicate and to whom? To answer these questions, three directions will be pursued: (1) Identify new classes of information structures that lead to a tractable design. (2) Identify optimal transmission strategies that determine when an agent should communicate information to others. (3) Develop learning and adaptation strategies for the above two directions when the system model is not known. ***The proposed research program will provide broad training to 4 PhD and 3 MEng students in fundamental areas of system science and control engineering, thereby providing them with a solid foundation for their future endeavors. The results obtained in this program will find applications in networked control systems, transportation networks, smart-grids, sensor and surveillance networks, healthcare monitoring, and robotics.********