Decision by sampling implements efficient coding of psychoeconomic functions
The theory of decision by sampling (DbS) proposes that an attribute's subjective value is its rank within a sample of attribute values retrieved from memory. This can account for instances of context dependence beyond the reach of classic theories that assume stable preferences. In this paper,...
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| Veröffentlicht in: | Psychological review Jg. 125; H. 6; S. 985 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
01.11.2018
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| Schlagworte: | |
| ISSN: | 1939-1471, 1939-1471 |
| Online-Zugang: | Weitere Angaben |
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| Zusammenfassung: | The theory of decision by sampling (DbS) proposes that an attribute's subjective value is its rank within a sample of attribute values retrieved from memory. This can account for instances of context dependence beyond the reach of classic theories that assume stable preferences. In this paper, we provide a normative justification for DbS that is based on the principle of efficient coding. The efficient representation of information in a noiseless communication channel is characterized by a uniform response distribution, which the rank transformation implements. However, cognitive limitations imply that decision samples are finite, introducing noise. Efficient coding in a noisy channel requires smoothing of the signal, a principle that leads to a new generalization of DbS. This generalization is closely connected to range-frequency theory, and helps descriptively account for a wider set of behavioral observations, such as how context sensitivity varies with the number of available response categories. (PsycINFO Database Record (c) 2018 APA, all rights reserved). |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1939-1471 1939-1471 |
| DOI: | 10.1037/rev0000123 |