Collaborative Research: CCSS: A Distributed Computation Framework for Networked Sensing and Control

目的：本项目的目标是开发一个统一的计算框架，用于具有静态或动态状态的随机多智能体网络中的分布式自适应感知和控制，以及模型的不确定性。在这种完全分布式的信息处理和控制范式中，探索了代理级的协作通信和参与，以构建具有可证明性能保证的实时普适决策的有效可扩展架构。通过适当利用局部感知数据，分布式方法可以适应参数切换和不确定性的实时实现和适应。由此产生的混合时间尺度信息和网络/物理动力学用随机分析中的新技术进行了分析，特别考虑了相关的非马尔可夫性质。智力优势：智力优势在于所提出的分布式自适应框架涉及随机学习、估计和通信之间复杂而微妙的闭环相互作用，其中所提出的方法导致了共识+创新类型的新型混合时间尺度顺序随机方案。这些过程的动力学是非马尔可夫的，为此提出了一种全新的、变革性的系统方法来进行系统性能分析。广泛的影响：广泛的影响是多方面的。结果将使有效的网络物理系统操作成为可能，并将为先进的动态系统分析提供新的方法。拟议的并行教育计划从多个方面解决了本科和研究生教育问题：教学、培训和指导，并与社区和未被充分代表的少数群体进行了接触。

Objective: The objective of this project is to develop a unified computation framework for distributed adaptive sensing and control in stochastic multi-agent networks with either static or dynamic states, coupled with model uncertainties. In such a fully distributed information processing and control paradigm, collaborative communication and participation at the agent level is explored to build efficient scalable architectures for real-time pervasive decision making with provable performance guarantees. The distributed methodologies are amenable to real-time implementation and adaptation over parametric switching and uncertainties, through proper exploitation of locally sensed data. The resulting mixed-time-scale information and cyber/physical dynamics are analyzed with new novel techniques in stochastic analysis, with special considerations over the associated non-Markovian properties.Intellectual merit: The intellectual merit is lying in the fact the proposed distributed adaptive framework involves a complex and subtle closed-loop interplay among stochastic learning, estimation, and communication, where the proposed approach leads to the novel mixed-time-scale sequential stochastic schemes of the consensus + innovation type. The dynamics of these procedures are non-Markovian, for which a completely new and transformative systematic approach is proposed to conduct the system performance analysis. Broader impacts: The broader impacts are multi-fold. The results will enable efficient cyber-physical system operations, and will provide new methodologies for advanced dynamic system analysis. The proposed concurrent education program addresses the undergraduate and graduate education issues in multiple aspects: teaching, training, and mentoring, with outreach to the community and under-represented minority groups.