As the author states, analogical reasoning has had a long history in many disciplines including, but not restricted to, artificial intelligence. The reason for this interest is that analogical reasoning seems to provide one solution to the problem of reducing the explosive search space inherent in most AI problems. Thus, many researchers have examined the question of how to determine when two descriptions or procedures are alike.

One of the major contributions of this work is to provide readers with an organized survey of the different studies on analogical reasoning. The author first defines analogy as the “mapping between elements of a source domain and a target domain” (p. 40). Studies which correspond to this definition are then reviewed in chronological order. Hall concludes his survey by synthesizing all the studies within the context of four major processes of the analogical model: recognition, elaboration, evaluation, and consolidation. He first defines each category and then compares (and contrasts) all the previously described research using these definitions. This section of the paper gives the reader a better understanding of the problems that occur in analogical reasoning as well as the differences between the various systems and their approaches to the problems. Although the author concludes with the comment that analogical reasoning is still in its adolescent stage, this survey paper should enable the researcher to get through puberty.