Towards a Computational Model of Evaluating and Using Analogical Inferences

Reasoning by analogy is a central phenomena in cognition. Existing computational models of analogy provide accounts of how analogical inferences are generated, but do not specify how they might be evaluated or integrated with other methods of reasoning. This paper extends the model of analogical inference in structure-mapping theory in two ways. First, we propose techniques for the structural evaluation of analogical inferences, to model one of the factors people appear to use in evaluating the plausibility of arguments based on comparisons. Second, we propose an information-level model of analogical inferences that supports reasoning about correspondences and mappings. We describe how this model fits with existing psychological evidence and illustrate its operation on several examples, using a computer simulation. These examples include evaluating the validity of a qualitative mental model and a prototype case-based coach that is being added to an alreadyfielded intelligent learning environment.