Hofstadter and his colleagues have criticized current accounts of analogy, claiming that such accounts do not accurately capture interactions between processes of representation construction and processes of mapping. They suggest instead that analogy should be viewed as a form of high level perception that encompasses both representation building and mapping as indivisible operations within a single model. They argue specifically against SME, our model of analogical matching, on the grounds that it is modular, and offer instead programs such as Mitchell and Hofstadter's Copycat as examples of the high level perception approach. In this paper we argue against this positionon two grounds. First, we demonstrate that most of their specific arguments involving SME and Copycat are incorrect. Second, we argue that the claim that analogy is high-level perception, while in some ways an attractive metaphor, is too vague to be useful as a technical proposal. We focus on five issues: (1) how perceptionrelates to analogy,(2) how flexibilityarises in analogicalprocessing, (3) whether analogy is a domain-general process, (4) how micro-worlds should be used in the study of analogy, and (5) how best to assess the psychological plausibility of a model of analogy. We illustrate our discussion with examples taken from computer models embodying both views.

Research was conducted to clarify the role of similarity in transfer of training. Subjects learned a procedure for operating a simulated device and were asked to transfer the knowledge of the procedure to a new device. Two factors were varied: (1) the systematicity of the original device model (i.e. whether the subjects were given a coherent causal model or simply a set of operating procedures); and (2) the transparency of the mapping, or degree of surface similarity between corresponding device components. The dependent measure was the number of trials to a criterion in the original and transfer device. Having a systematic mental model both facilitated learning of the initial device and promoted transfer to the target device. Transparency had strong effects on transfer: subjects learned the new device faster when corresponding pairs of components were similar than when noncorresponding pairs were similar.>