Beyond Markov: Accounting for Independence Violations in Causal Reasoning


Although many theories of causal cognition are based on causal graphical models, a key property of such models—the inde-pendence relations stipulated by the Markov condition—is routinely violated by human reasoners. Two accounts of why people violate independence are formalized and subjected to experimental test. Subjects’ inferences were more consistent with a dual prototype model in which people favor network states in which variables are all present or all absent than a leaky gate model in which information is transmitted through network nodes when it should normatively be blocked. The article concludes with a call for theories of causal cognition that rest on foundations that are faithful to the kinds of causal inferences people actually draw.

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