David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Theory and Decision 52 (1):29-71 (2002)
This article provides an overview of recent results on lexicographic, linear, and Bayesian models for paired comparison from a cognitive psychology perspective. Within each class, we distinguish subclasses according to the computational complexity required for parameter setting. We identify the optimal model in each class, where optimality is defined with respect to performance when fitting known data. Although not optimal when fitting data, simple models can be astonishingly accurate when generalizing to new data. A simple heuristic belonging to the class of lexicographic models is Take The Best (Gigerenzer & Goldstein (1996) Psychol. Rev. 102: 684). It is more robust than other lexicographic strategies which use complex procedures to establish a cue hierarchy. In fact, it is robust due to its simplicity, not despite it. Similarly, Take The Best looks up only a fraction of the information that linear and Bayesian models require; yet it achieves performance comparable to that of models which integrate information. Due to its simplicity, frugality, and accuracy, Take The Best is a plausible candidate for a psychological model in the tradition of bounded rationality. We review empirical evidence showing the descriptive validity of fast and frugal heuristics
|Keywords||models lexicographic linear Bayesian|
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Citations of this work BETA
Gerd Gigerenzer & Thomas Sturm (2012). How (Far) Can Rationality Be Naturalized? Synthese 187 (1):243-268.
Nathan Berg & Ulrich Hoffrage (2010). Compressed Environments: Unbounded Optimizers Should Sometimes Ignore Information. [REVIEW] Minds and Machines 20 (2):259-275.
Gerd Gigerenzer & Henry Brighton (2009). Homo Heuristicus: Why Biased Minds Make Better Inferences. Topics in Cognitive Science 1 (1):107-143.
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