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Prior symmetry, similarity-based reasoning, and endogenous categorization

  • Pe[combining cedilla]ski, Marcin
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    This paper presents a rational theory of categorization and similarity-based reasoning. I study a model of sequential learning in which the decision maker infers unknown properties of an object from information about other objects. The decision maker may use the following heuristics: divide objects into categories with similar properties and predict that a member of a category has a property if some other member of this category has this property. The environment is symmetric: the decision maker has no reason to believe that the objects and properties are a priori different. In symmetric environments, categorization is an optimal solution to an inductive inference problem. Any optimal solution looks as if the decision maker categorizes. Various experimental observations about similarity-based reasoning coincide with the optimal behavior in my model.

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    Article provided by Elsevier in its journal Journal of Economic Theory.

    Volume (Year): 146 (2011)
    Issue (Month): 1 (January)
    Pages: 111-140

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    Handle: RePEc:eee:jetheo:v:146:y:2011:i:1:p:111-140
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