Presidential Young Investigator Award

这位总统青年研究员的研究是在学习和自动推理的人工智能领域。由于计算机需要显式的系统模型来执行推理，而推理的性质关键取决于模型的性质，因此可以通过使程序能够动态地重新表述其模型来获得巨大的影响力。这位调查者在他的关于聚合和比较分析技术的工作中进行了重新表述，这些技术包括差异化、定性分析和夸大。他现在将结合机器学习的想法来帮助重新制定任务。一个具体的项目是推广现有的模型重构方案。每个模型的适用范围将根据模型隐含假设的简化用一种语言显式表示。第二个项目是理论形成的一种受限形式：自动构建世界模型。这里的方法是通过使用上面描述的建模语言来表征程序的视图，从而概括以前关于测量、解释和视图应用的工作。

The research of this Presidential Young Investigator is in the artificial intelligence fields of learning and automated reasoning. Because computers require an explicit model of a system to perform reasoning and the character of the reasoning depends critically on the nature of the model, great leverage can be obtained by enabling programs to reformulate their models dynamically. The investigator has pursued reformulation in his work on aggregation and the comparative analysis techniques of differential qualitative analysis and exaggeration. He will now incorporate ideas from machine learning to aid in the reformulation task. One specific project is to generalize current schemes for model reformulation. The limits of applicability for each model will be represented explicitly in a language based on the simplifications implicitly assumed by the model. A second project is a restricted form of theory formation: the automatic construction of world models. Here the approach is to generalize previous work on measurement interpretation and view application by characterizing the program's views with the modeling language described above.