SoD: A Normative Theory for the Design of Discrete Event Dynamic Systems for Supervisory Control

这个项目解决了一个与离散事件动态系统(DEDS)设计相关的问题领域。该项目的目标是确定控制这些系统的监督政策的易于处理的综合。DED的例子包括：空中交通管制系统；自动化制造系统；计算机网络；综合指挥、控制、通信和信息(C3I)系统；具有事件驱动动态的多组件组织的运营管理，如造船厂、机场、医院等。尽管DED有无数和不同的应用，但DED监督控制的核心方面的进展并没有超出学术界的应用，主要是因为综合程序需要对系统所需行为的完整规范，这是一项困难的任务，如果不是不可能的话。即使有完整的规范可用，适当的监管政策的合成也可能是棘手的。这个项目开发了一个关于DEDS应该如何构建的规范理论，这样，从执行不完全指定的行为的监管政策开始，可以应用渐进的监管纠正，从而最终执行(完整的)所需的规范。该项目倡导的监管政策是基于对观察到的系统的“合意”和“不合意”状态的分析。本项目侧重于DEDS的三个领域：(1)学习阶段：为监管系统开发学习算法，在此阶段，可以使用示例/反例轻松地获得/识别期望的行为；(2)监管政策合成阶段：在学习容易处理的DEDS结构的识别阶段；以及(3)渐进改进阶段：开发改进学习行为的方法，当提供额外信息时，可以用很少的计算工作量逐步改进这些方法。与该项目有关的公开研究课题的成功解决可能意味着上述每个DED例子中的特殊问题(空中交通瓶颈、自动化制造中的死锁/带电锁、网络服务质量差、医院急诊室的分诊服务差等)。可能会被消灭。

This project addresses a problem domain related to the design of Discrete Event Dynamic Systems (DEDS). The goal of the project is to identify tractable synthesis of supervisory policies that control those systems. Examples of DEDS include: air-traffic control systems; automated manufacturing systems; computer networks; integrated command, control, communication and information (C3I ) systems; operations-management of multi-component organizations with event-driven dynamics like shipyards, airports, hospitals, etc. Despite the myriad and diverse applications for DEDS, advances in core aspects of supervisory control of DEDS have not found application beyond academia, primarily due to the fact that synthesis procedures require complete specification of the desired behavior of the system, a difficult, if not impossible task. Even when complete specifications are available, the synthesis of the appropriate supervisory policy can be intractable. This project develops a normative theory of how DEDS should be structured so that, starting from a supervisory policy that enforces an incompletely specified behavior, progressive supervisory corrections can be applied such that the (complete) desired specification is eventually enforced.The supervisory policy advocated by this project is based on analysis of observed "desirable" and "undesirable" states of a system. This project focuses on three areas of DEDS: (1) Learning phase: the development of learning algorithms for supervisory systems where desired behavior can be easily earned/identified using examples/counter-examples, (2) Supervisory policy synthesis phase: the identification of DEDS structures where learning is tractable, and (3) Progressive improvement phase: the development of methods for improving learned behavior that can be progressively improved with little computational effort as additional information is made available. The successful resolution of the open research topics related to this project may mean that idiosyncratic problems in each of the examples of DEDS described above (air-traffic bottlenecks, dead-lock/live-lock in automated manufacturing, poor quality of service in networks, poor triage services in the emergency room of a hospital, etc.) could be eliminated.