Induction: processes of inference, learning, and discovery
Induction: processes of inference, learning, and discovery
The structure-mapping engine: algorithm and examples
Artificial Intelligence
Analog retrieval by constraint satisfaction
Artificial Intelligence
Similarity and analogical reasoning
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Motivation - The purpose of this article is to reinvigorate debate concerning the nature of analogy and broaden the scope of current conceptions of analogy. Research approach - An analysis of the history of the concept of analogy, case studies on the use of analogy in problem-solving, cognitive research on analogy comprehension, and a naturalistic inquiry into the various functions of analogy. Findings and Implications - Psychological theories and computational models have generally relied on: (a) A single set of ontological concepts (a property called "similarity" and a structuralist categorization of types of semantic relations) (b) A single form category (i.e., the classic four-term analogy), and (c) A single set of morphological distinctions (e.g., verbal versus pictorial analogies). The taxonomy presented here distinguishes functional kinds of analogy, each of which presents an opportunity for research on aspects of reasoning that have been largely unrecognized. Originality/Value - The various functional kinds of analogy will each require their own treatment in macrocognitive theories and computational models. Take away message - The naturalistic investigation of the functions of analogy suggests that analogy is a macrocognitive phenomenon derivative of number of supporting processes, including the apperception of resemblances and distinctions, metaphor, and the balancing of semantic flexibility and inference constraint.