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Updated: Aug 13, 2026

An Unbiased Approach of Sampling TEM Sections in Neuroscience
Published on: April 13, 2019
Decision by sampling
Neil Stewart1, Nick Chater, Gordon D A Brown
1Department of Psychology, University of Warwick, Coventry CV4 7AL, UK. neil.stewart@warwick.ac.uk
Abstract:
We present a theory of decision by sampling (DbS) in which, in contrast with traditional models, there are no underlying psychoeconomic scales. Instead, we assume that an attribute's subjective value is constructed from a series of binary, ordinal comparisons to a sample of attribute values drawn from memory and is its rank within the sample. We assume that the sample reflects both the immediate distribution of attribute values from the current decision's context and also the background, real-world distribution of attribute values. DbS accounts for concave utility functions; losses looming larger than gains; hyperbolic temporal discounting; and the overestimation of small probabilities and the underestimation of large probabilities.
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