Analogical Retrieval

We observe that thus far all computational models of analogy have modelled memory as a set of disjoint, encapsulated, domains. As there does not appear to be any psychological evidence for modelling memory in this way, we suggest that a more realistic model of analogy could be constructed if memory was modelled as one large data structure. We argue that the retrieval sub-process of analogy may not be independent of the mapping sub-process, and that both processes may well be governed by structural similarity. We describe a computational model of analogy which incorporates these three ideas; it models mapping and retrieval together, uses structural similarity to govern matching, and models memory as one large data structure. Retrieval in this system corresponds to the searching of the data structure for analogical matches to a supplied probe. We suggest a practical and efficient algorithm for such retrieval.