Over the last 20 years, causal-model theory has produced muchknowledge about causal-based categorization. However, per-sistent violations to the normative causal-model theory areprevalent. In particular, violations to the Markov conditionhave been repeatedly found. These violations have receiveddifferent explanations. Here, we develop a model that startsfrom generally accepted cognitive phenomena (e.g., process-ing limitations, the relevance of inference in cognitive process-ing) and assumes that people are not fully causal nor fully asso-ciative when performing causal-based categorization, offeringa new explanation for Markov violations.
