Learning Causal Structure from Reasoning

Barbey, Aron and Wolff, Phillip (2007) Learning Causal Structure from Reasoning. In [2007] Workshop: Causality, Mechanisms, and Psychology (Pittsburgh, PA; 24 February, 2007).

Abstract

According to the transitive dynamics model, people can
construct causal structures by linking together
configurations of force. The predictions of the model
were tested in two experiments in which participants
generated new causal relationships by chaining together
two (Experiment 1) or three (Experiment 2) causal
relations. The predictions of the transitive dynamics
model were compared against those of Goldvarg and
Johnson-Laird’s model theory (Goldvarg & Johnson-
Laird, 2001). The transitive dynamics model consistently
predicted the overall causal relationship drawn by
participants for both types of causal chains, and, when
compared to the model theory, provided a better fit to the
data. The results suggest that certain kinds of causal
reasoning may depend on force dynamic—rather than on
logical or purely statistical—representations.