It has been known for quite some time that metaphors and analogies can redescribe an object, thereby creating new perspectives on it. However, this phenomenon has not yet been properly addressed in cognitive science and AI research. Previous work has identified and characterized this process of redescription that underlies creative instances of metaphor and analogy. This work will implement a computational model of resdescription in the proportional analogy domain. In this framework, an object is seen as an element of a finitely generated algebra, and a "description of the object is defined to be any possible way in which that object can be generated from other objects by applying appropriate operators. Typically, an object can be generated in many ways and, consequently, has many descriptions. In designing the model, the problem then, is to find efficient algorithms and heuristics which select appropriate descriptions of the objects so that the analogy relation is comprehensible.
