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A Computational Model of Wason's Selection Task

We apply an algorithmic learning model of inquiry to model reasoning carried by experimental subjects in Wason's _Selection Task_ that represents reasoning in the task as computation of a decision tree that supervenes on (partial) semantic representations. We argue that the resulting model improves on previous probabilistic (Bayesian) and pragmatic (Relevance theory) models of the task. In particu