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HeuristicsThe Foundations of Adaptive Behavior$
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Gerd Gigerenzer, Ralph Hertwig, and Thorsten Pachur

Print publication date: 2011

Print ISBN-13: 9780199744282

Published to Oxford Scholarship Online: May 2011

DOI: 10.1093/acprof:oso/9780199744282.001.0001

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Categorization with Limited Resources: A Family of Simple Heuristics

Categorization with Limited Resources: A Family of Simple Heuristics

(p.319) Chapter 14 Categorization with Limited Resources: A Family of Simple Heuristics

Laura Martignon

Konstantinos V. Katsikopoulos

Jan K. Woike

Oxford University Press

In categorization tasks where resources such as time, information, and computation are limited, there is pressure to be accurate, and stakes are high, as when deciding if a patient is under high risk of having a disease or if a worker should undergo retraining, and it has been proposed that people use, or should use, simple adaptive heuristics. The chapter introduces a family of deterministic, noncompensatory heuristics, called fast-and-frugal trees, and study them formally. The chapter shows that the heuristics require few resources and are also relatively accurate. First, the chapter characterizes fast-and-frugal trees mathematically as lexicographic heuristics and as noncompensatory linear models, and also shows that they exploit cumulative dominance (the results are interpreted in the language of the paired comparison literature). Second, the chapter shows, by computer simulation, that the predictive accuracy of fast-and-frugal trees compares well with that of logistic regression (proposed as a descriptive model for categorization tasks performed by professionals) and of classification and regression trees (used, outside psychology, as prescriptive models).

Keywords:   categorization, probability, similarity, cue, exemplar, heuristics, lexicographic, trees, classification and regression

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