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In the context of decision making under uncertainty, the authors formalize the concept of analogy: an analogy between two decision problems is a mapping that transforms one problem into the other while preserving the problem's structure. They identify the basic structure of a decision problem, and provide a representation of the mappings that pre-serve this structure. They then consider decision makers who use multiple analogies. The main results are a representation theorem for "Aggregators" of analogies satisfying certain minimal requirements, and the identification of preferences emerging from analogical reasoning. They show that a large variety of multiple-prior preferences can be thought of as emerging from analogical reasoning.
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