*Stuart J. Russell*

In the absence of specific relevance information, the traditional assumption in the study of analogy has been that the most similar analogue is most likely to provide the correct solutions; a justification for this assumption has been lacking, as has any relation between the similarity measure used and the probability of correctness of the analogy. We show how a statistical analysis can be performed to give the probability that a given source will provide a successful analogy, using only the assumption that there are some relevant features somewhere in the source and target descriptions. The predicted variation of the probability with source-target similarity corresponds closely to empirical analogy data obtained by Shepard for human and animal subjects for a wide variety of domains. The utility of analogy by similarity seems to rest on some very fundamental assumptions about the nature of our representations.

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