概率因果模型的质化逻辑分析

A Qualitative Logical Analysis of Probabilistic Causal Models

因果推理往往需要处理不确定性。尽管传统的结构等式模型擅于处理确定因果结构中的推理,却不能直接用来刻画涉及概率的因果推理。当前一些学者试图将量化的概率表达式引入到关于因果性的形式语言中,从而描述概率因果推理。有别于这种量化研究路径,本文提出一种关于概率因果推理的质化模型,通过认知关系来表达变元的不确定性。此外,基于该模型的形式语言能够在质化的意义上表达变元间的独立关系,有助于进一步研究因果与概率之间的联系。

Uncertainty occurs frequently in the process of causal reasoning. Although the traditional structural equation model is very successful in the reasoning of deterministic causal structure, yet it is not designed to characterize probabilistic reasoning. Recently there have been proposals aiming to account for probabilistic causal reasoning by adding quantitative probabilis-tic expressions in the causal language. Contrast with the quantitative approach, this paper will present a qualitative model of probabilistic causal reasoning, which represents uncertainty of variables in terms of doxastic relations. The formal language based on this framework is able to express a qualitative notion of independence among causal variables, which can be used to analyse the co-relation between causality and probability.