Presidential Young Investigator Award (Computer and Information Science)

这项研究为“定性物理学”开发了基于知识的计算机系统，使计算机能够更有效地对物理世界进行推理。定性物理学通过提供(1)在简单情况下的快速答案和(2)更详细分析的框架来补充传统物理学。具体的定性模型正在为流体系统、热系统和运动开发，足以描述复杂的系统，如机械时钟和锅炉。这些模型包括预测、测量、解释以及构建计划和程序的方法。这项研究还包括对人们如何学习物理领域的调查，包括对类比处理的认知模拟。这项研究的重要意义在于，它有可能产生“强大的”计算机推理系统，在没有经典物理模型所需的详细信息和数学方程的情况下，在近似推理周围物理世界将如何运行的能力上，与人类相当。此外，研究人类定性物理专业知识的范围可能为认知的本质提供重要的见解。实用和有效的定性推理系统在开发许多先进的技术系统中也是必不可少的：例子包括用于工厂和发电厂等复杂系统的智能监视器，以及用于机械和工程设计的智能计算机助手。

This research develops knowledge based computer systems for "qualitative physics," allowing computers to reason more effectively about the physical world. Qualitative physics complements traditional physics by providing (1) fast answers in simple situations and (2) a framework for more detailed analysis. Specific qualitative models are being developed for fluid systems, thermal systems, and motion, adequate to describe complex systems such as as mechanical clocks and boilers. The models include methods for prediction, measurement, interpretation, and for constructing plans and procedures. The research also includes an investigation of how people learn physical domains, including cognitive simulations of analogical processing. The significance of this research is its potential to produce "robust" computer reasoning systems, comparable to humans in their ability to reason approximately about how the physical world around them will behave, without the detailed information and mathematical equations required for classical models of physics. In addition, studying the range of qualitative physics expertise in humans may provide important insight into the nature of cognition. Practical and effective qualitative reasoning systems will also be essential in developing many advanced technological systems: Examples include intelligent monitors for complex systems such as factories and power plants, and intelligent computer assistants for mechanical and engineering design.