A framework for decentralized, dynamic discrete-event systems

我的研究重点是其行为可以被认为是事件或动作序列的系统，这些事件或动作在时间约束下以不同的概率发生。我开发了数学模型来表示这样的离散事件系统，其中的控制涉及多个代理，以便自动化问题解决和解决方案的测试。我将使用我的模型来开发公共紧急响应程序，并改进分布式系统的软件开发。在紧急响应协议中，例如流行所需的那些，我们需要使用许多代理(例如，患者、护理人员、医疗单位)来对系统进行建模，其中事件以概率发生(例如，如果暴露在疾病中，患者可能有40%的机会感染疾病)，有时需要在特定的时间发生操作(例如，医院的患者必须在特定的时间进食)，并且代理的组随着时间的推移而变化(随着患者的康复或死亡以及新患者的患病)。我的研究将有助于确定应对公共突发事件的协议、程序和政策。改进的应急响应协议将使加拿大受益，因为它可以优化资源分配，并将疾病爆发、水污染和大规模电力中断等危机对人们造成的伤害降至最低。

My research focuses on systems whose behaviour can be thought of as sequences of events or actions, which occur with various probabilities under timing constraints. I develop mathematical models to represent such discrete-event systems in which control involves multiple agents in order to automate problem-solving and testing of solutions. I will use my models to develop public emergency response procedures and to improve software development for distributed systems. In emergency response protocols, such as those needed for an epidemic, we need to model systems with many agents (e.g., patients, care workers, health units), where events occur with probabilities (e.g., if exposed to a disease, a patient may have a 40% chance of contracting the disease), where actions sometimes need to occur at specific times (e.g., patients in a hospital must eat at specific hours), and the group of agents changes over time (as patients recover or die and new patients become ill). My research will aid in determining protocols, procedures and policies for public emergencies. Improved emergency response protocols will benefit Canada by optimizing resource allocation and minimizing the harm done to people by crises such as disease outbreaks, water contamination, and massive electrical outages.