Drawing on an example from artificial grammar learning, I present the case that similarity processes can be computationally identical to rules processes, but that participants in an artificial grammar learning experiment may use different processing modes to classify stimuli. The number of properties and other representational differences between rule and similarity processes are an accidental consequence of strategies used.
