Analogical Retrieval Within a Hybrid Spreading-Activation Network

The mechanisms by which people are initially reminded of analogies remain poorly understood. Psychological evidence suggests that memories retrieved tend to be semantically similar and structurally consistent with the new situation. This paper describes a hybrid symbolic/connectionist model of analogical retrieval that is influenced by the language understanding process. In this model, activation is spread through a semantic network that disambiguates and makes inferences about the input cue. A network of units is then dynamically created to represent competing mappings between the cue's winning interpretation and the activated subset of potential targets. Connections created from the semantic network to these new mapping units imposes priming by semantic similarity, with links between mapping units enforcing structural consistency with the cue. The mapping network then settles by constraint satisfaction into the most coherent analogical match to the cue, after which the winning mapping units feed activation back into the semantic network, where the most highly-activated target is retrieved as the analog.