Over the last decade, a normative framework for making causal inferences, Bayesian
Probabilistic Causal Networks, has come to dominate psychological studies of inference …

There are two accounts describing causal conditional reasoning: the probabilistic and the
mental models account. According to the probabilistic account, the tendency to accept a …

Two experiments examined the contribution of working memory (WM) to the retrieval and
inhibition of background knowledge about counterexamples (alternatives and disablers …

Causal graphical models (CGMs) are a popular formalism used to model human causal
reasoning and learning. The key property of CGMs is the causal Markov condition, which …

Abstract Reasoning with conditionals involving causal content is known to be affected by
retrieval of counterexamples from semantic memory. In this study we examined the …

Conditional reasoning is reasoning that involves statements of the sort If A (Antecedent) then
C (Consequent). This type of reasoning is ubiquitous; everyone engages in it. Indeed, the …

Causal reasoning belongs to our most central cognitive competencies. Causal knowledge is
used as the basis of predictions and diagnoses, categorization, action planning, decision …

This study tested and refined a framework that proposes a mechanism for retrieving
alternative causes and disabling conditions (Cummins, 1995) during reasoning. Experiment …

In this paper, two experiments are reported investigating the nature of the cognitive
representations underlying causal conditional reasoning performance. The predictions of …

Two experiments examined developmental patterns in children's conditional reasoning with
everyday causal conditionals. In Experiment 1, a group of pre-, early, young, and late …