Abstract
Two experiments investigated whether there is evidence for acquisition of rules in implicit artificial grammar learning (AGL). Two different methods were used in meeting this goal, multiple regression analysis and analysis of receiver-operating characteristics (ROCs). By means of multiple regression analysis, several types of knowledge were identified that were used in judgments of grammaticality, for example, about single letters and about larger stimulus fragments. There was no evidence for the contribution of rule knowledge. The ROCs were in accord with a similarity-based account of AGL and thus did not support the notion that rule knowledge is acquired in AGL either. Simulations with a connectionist model corroborated the conclusion that the results were in accord with a similarity-based, associative account.
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