CAREER: Reasoning with Cause and Effect: Model Testing, Axiomatization, and Identification

该项目解决了因果推理中的基本问题，其长期目标是发展理论基础，以促进构建能够在动态和不确定环境中自主运行的智能系统。该项目使用因果贝叶斯网络来表示和推理因果关系，并解决几个相关的主题，包括公理化因果推理，模型测试，识别因果效应和结构方程模型中的因果推理。此外，该项目将制作一个因果推理软件工具，可以回答因果查询。因果推理本质上是一个多学科的主题，这个项目的结果，特别是由此产生的软件工具，将是有用的，在其他领域，如统计，经济，医疗保健和社会科学。该项目的教育部分包括课程开发，学生辅导活动，并努力让本科生参与研究。

This project addresses fundamental issues in causal reasoning with the long range goal of developing theoretical foundations that will facilitate building intelligent systems capable of operating autonomously in dynamic and uncertain environments. This project uses causal Bayesian networks to represent and reason about causal relationships and to address several related topics, including axiomatizing causal reasoning, model testing, identifying causal effects, and causal reasoning in structural equation models. In addition, the project will produce a causal reasoning software tool that can answer causal queries. Causal reasoning is intrinsically a multidisciplinary topic and the results of this project, particularly the resulting software tools, would be useful in other fields such as statistics, economics, health care, and social sciences. The educational component of this project includes curriculum development, student mentoring activities, and efforts to involve undergraduate students in research.