A Framework for the Integration of Dynamic Observation, Control and Knowledge in Discrete-Event Systems

离散事件系统中动态观测、控制和知识集成的框架

• 批准号: RGPIN-2015-05699
• 负责人: Rudie, Karen
• 金额: $ 1.6万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=678570
• 关键词: Framework; Integration; Dynamic; Observation; Control

My research focuses on developing mathematical models to represent systems whose behaviour can be thought of as sequences of events or actions in order to automate problem-solving and test potential solutions in such discrete-event systems. The goal of the modeling is to generate controllers to meet given specifications. Controllers, which may be software, hardware or human strategies, must make decisions about which events to disable at various points in time and they must make their decisions based only on partial observations of the system. Prior work in the field uses models where controllability and observability of an event are static properties. In contrast, my proposed research aims to model dynamic control and dynamic observation.****Furthermore, just as humans make decisions based not only on their direct observations of the physical world, but also based on inferences they make about what other people know, so too should automated agents make decisions based on what they know about what other agents know. Consequently, my research will focus on the interaction between observation, control, and "knowledge". I will incorporate formal models of agent knowledge into my framework. ******Fundamental shifts in the way we view observation and control are anticipated in the proposed research program. By incorporating dynamic observation and control, a supervisory control theory model of service composition will be developed for service-oriented computing applications. My research will also have an impact in decentralized distribution systems, for example in electricity markets where the status quo will no longer be viable in the future, when autonomous agents (homes, electric vehicles, private generators) will produce and consume electricity. My research into knowledge-based models for control can be applied to strategies where individual agents are guided by incentives to act in a way that produces some overall desired results. ******Most ambitiously, my research will be applied to solve computer security problems in which adversarial agents have only partial observation of a system and yet try to exert control over the system to glean secret information. With more accurate models of discrete-event systems-based on dynamic observation and dynamic control and using knowledge-based reasoning-we can develop controllers that prevent adversaries from being able to discern information that is intended to be kept private. I will investigate scenarios where the attacker can control and change the system's behaviour. I will consider possible responses a controller can take. I hope to determine whether it is more advantageous to restrict the behaviour of the system or to prevent the attacker from controlling some events. This will have an impact, for example, on Canadian banking and credit card companies, where protecting the privacy of information is of paramount concern.***The research will train 10 HQP.**

我的研究重点是开发数学模型来表示系统，其行为可以被认为是事件或动作的序列，以自动解决问题，并在这种离散事件系统中测试潜在的解决方案。建模的目标是生成满足给定规格的控制器。 控制器，可以是软件、硬件或人工策略，必须决定在不同的时间点禁用哪些事件，并且必须仅基于对系统的部分观察来做出决定。在该领域的先前工作中使用的模型中，事件的可控性和可观测性是静态属性。相比之下，我提出的研究旨在建立动态控制和动态观察的模型。此外，正如人类不仅根据他们对物理世界的直接观察，而且还根据他们对其他人所知的推断做出决策一样，自动代理也应该根据他们对其他代理所知的信息做出决策。因此，我的研究将集中在观察，控制和“知识”之间的相互作用。 我将把代理知识的正式模型纳入我的框架中。** 在我们看待观察和控制的方式上的根本性转变预计将在拟议的研究计划中实现。通过结合动态观测和控制，建立了面向服务计算应用的服务组合监督控制理论模型。我的研究也将对分散的配电系统产生影响，例如在电力市场中，现状在未来将不再可行，届时自主代理人（家庭，电动汽车，私人发电机）将生产和消耗电力。我对基于知识的控制模型的研究可以应用于策略，在这些策略中，个体代理人受到激励的引导，以产生一些总体预期结果的方式行事。 最雄心勃勃的是，我的研究将被应用于解决计算机安全问题，其中敌对代理只有部分观察系统，但试图对系统施加控制以收集秘密信息。 有了更精确的离散事件系统模型基于动态观察和动态控制并使用基于知识的推理我们可以开发控制器，防止对手能够识别旨在保密的信息。我将研究攻击者可以控制和改变系统行为的场景。我会考虑管制员可能采取的应对措施。我希望确定限制系统的行为或阻止攻击者控制某些事件是否更有利。例如，这将对加拿大银行和信用卡公司产生影响，因为保护信息隐私是这些公司最关心的问题。该研究将培训10名HQP。**