How do people acquire and use causal knowledge? This chapter argues that causal learning and reasoning are intertwined, and recruit similar representations and inferential procedures. In contrast to covariation‐based approaches to learning, this chapter maintains that people use multiple sources of evidence to discover causal relations, and that the causal representation itself is separate from these informational sources. The key roles of prior knowledge and interventions in learning are also discussed. Finally, this chapter speculates about the role of mental simulation in causal inference. Drawing on parallels with work in the psychology of mechanical reasoning, the notion of a causal mental model is proposed as a viable alternative to reasoning systems based in logic or probability theory alone. The central idea is that when people reason about causal systems they utilize mental models that represent objects, events or states of affairs, and reasoning and inference is carried out by mental simulation of these models.
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