A Qualitative Logical Analysis of Probabilistic Causal Models

Studies in Logic, Vol. 15, No. 6 (2022): 17–27   PII: 1674­3202(2022)­06­0017­11

Kaibo Xie

Abstract.

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 probabilistic 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 co­relation between causality and probability.