Dynamic Model Selection Under Time Constraints

这是连续三年获奖的第一年。 这 研究解决了在适当的建模问题， 详细程度，以控制物理或 时间或计算资源下的生物系统 约束 该研究旨在开发、实施和测试一种 实时使用的模型的动态选择方法 应用. PI首先开发和组织多个 通过以下方式简化域的详细（基础）模型： 应用特定领域简化假设的组合。 他们创建了这些假设的明确表示， 开发方法来动态地推理假设， 找到最简单的模型和有效的假设。 PI测试 假设最简单的模型与有效的假设是 根据决策理论的定义， 最优性 该系统是在人的领域实现的 心肺生理学，控制任务是发现 呼吸机（机械呼吸装置）的设置。 的 研究将提供应用复杂模型的改进方法 在时间要求严格的应用中， 实时应用中的棘手模型，并合并数值 仿真和控制方法与正式决策理论。 //

This is the first year of a three year continuing award. This research addresses the problems of modeling at the appropriate level of detail for the purpose of controlling physical or biological systems under time or computation resources constraints. The research is to develop, implement and test a method of dynamic selection of models for use in real-time applications. The PI's first develop and organize multiple simplifications of a detailed (base) model of the domain by applying combinations of domain-specific simplifying assumptions. They create an explicit representation of these assumptions and develop methods to reason dynamically with the assumptions to find the simplest model with valid assumptions. The PI's test the hypothesis that the simplest model with valid assumptions is optimal according to a decision-theoretic definition of optimality. The system is implemented in the domain of human cardiopulmonary physiology, with the control task of finding settings for a ventilator (mechanical breathing device). The research will provide improved methods of applying complex models in time-critical applications, enable the use of previously intractable models in real-time applications, and merge numeric simulation and control methodologies with formal decision theory. //