Causal relations from kinematic simulations

Reasoners distinguish between different types of causal relations, such as causes, enabling conditions, and preventions. Psychologists disagree about the representations that give rise to the different relations, but agree that mental simulations play a central role in inferring them. We explore how causal relations are extracted from mental simulations. The theory of mental models posits that people use a kinematic simulation to infer possibilities. It predicts that causes should be easier to infer than enabling conditions, and that the time it takes to infer a causal relation should correlate with the number of moves in a mental simulation. To test these two predictions, we adapted a railway domain designed to elicit mental simulations, and we devised problems in which reasoners had to infer causal relations from simulations of the movements of cars in this domain. Two studies corroborated the model theory's predictions. We discuss the results in light of recent theories of causation and mental simulation.