Abstract

Recent advances in normative frameworks for causal reasoning have inspired psychologists to model human causal inference using these normative frameworks. These models are, however, vulnerable to the same criticisms as connectionist and other probabilistic models. A proposed response to these criticisms is the notion of first-order causal rules, which are a simple generalization of dependencies in causal Bayes nets, adding universally quantified logical variables.

Citations