A framework for decentralized, dynamic discrete-event systems

我的研究重点是那些行为可以被认为是一系列事件或行动的系统，这些事件或行动在时间限制下以各种概率发生。我开发了数学模型来表示这种离散事件系统，其中控制涉及多个代理，以便自动解决问题和测试解决方案。我将使用我的模型来开发公共应急响应程序，并改进分布式系统的软件开发。在紧急响应协议中，例如流行病所需的应急响应协议，我们需要对具有许多主体（例如，患者、护理人员、卫生单位）的系统进行建模，其中事件的发生具有概率（例如，如果暴露于某种疾病，患者可能有40%的机会感染该疾病），有时需要在特定时间采取行动（例如，医院的患者必须在特定时间进食）。药物组随着时间的推移而变化（如病人康复或死亡，新病人生病）。我的研究将有助于确定突发公共事件的协议、程序和政策。通过优化资源分配和尽量减少疾病爆发、水污染和大规模停电等危机对人民造成的伤害，改进应急响应协议将使加拿大受益。

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.