: This review presents empirical researchers with recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving from traditional stati...
Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children rec...
David M. Sobel, Joshua B. Tenenbaum, Alison Gopnik
Abstract. Bayesian nets (BNs) appeared in the 1980s as a solution to computational and representational problems encountered in knowledge representation of uncertain information. S...
Causality is a central issue in many AI applications. Social causality, in contrast to physical causality, seeks to attribute cause and responsibility to social events, and account...
In this paper we introduce a new method of combined synthesis and inference of biological signal transduction networks. A main idea of our method lies in representing observed cau...