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Learning What to Want: Context-Sensitive Preference Learning
We have developed a method for learning relative preferences from histories of choices made, without requiring an intermediate utility computation. Our method infers preferences that are rational in a psychological sense, where agent choices result from Bayesian inference of what to do from observab...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4619741/ https://www.ncbi.nlm.nih.gov/pubmed/26496645 http://dx.doi.org/10.1371/journal.pone.0141129 |
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author | Srivastava, Nisheeth Schrater, Paul |
author_facet | Srivastava, Nisheeth Schrater, Paul |
author_sort | Srivastava, Nisheeth |
collection | PubMed |
description | We have developed a method for learning relative preferences from histories of choices made, without requiring an intermediate utility computation. Our method infers preferences that are rational in a psychological sense, where agent choices result from Bayesian inference of what to do from observable inputs. We further characterize conditions on choice histories wherein it is appropriate for modelers to describe relative preferences using ordinal utilities, and illustrate the importance of the influence of choice history by explaining all major categories of context effects using them. Our proposal clarifies the relationship between economic and psychological definitions of rationality and rationalizes several behaviors heretofore judged irrational by behavioral economists. |
format | Online Article Text |
id | pubmed-4619741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-46197412015-10-29 Learning What to Want: Context-Sensitive Preference Learning Srivastava, Nisheeth Schrater, Paul PLoS One Research Article We have developed a method for learning relative preferences from histories of choices made, without requiring an intermediate utility computation. Our method infers preferences that are rational in a psychological sense, where agent choices result from Bayesian inference of what to do from observable inputs. We further characterize conditions on choice histories wherein it is appropriate for modelers to describe relative preferences using ordinal utilities, and illustrate the importance of the influence of choice history by explaining all major categories of context effects using them. Our proposal clarifies the relationship between economic and psychological definitions of rationality and rationalizes several behaviors heretofore judged irrational by behavioral economists. Public Library of Science 2015-10-23 /pmc/articles/PMC4619741/ /pubmed/26496645 http://dx.doi.org/10.1371/journal.pone.0141129 Text en © 2015 Srivastava, Schrater http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Srivastava, Nisheeth Schrater, Paul Learning What to Want: Context-Sensitive Preference Learning |
title | Learning What to Want: Context-Sensitive Preference Learning |
title_full | Learning What to Want: Context-Sensitive Preference Learning |
title_fullStr | Learning What to Want: Context-Sensitive Preference Learning |
title_full_unstemmed | Learning What to Want: Context-Sensitive Preference Learning |
title_short | Learning What to Want: Context-Sensitive Preference Learning |
title_sort | learning what to want: context-sensitive preference learning |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4619741/ https://www.ncbi.nlm.nih.gov/pubmed/26496645 http://dx.doi.org/10.1371/journal.pone.0141129 |
work_keys_str_mv | AT srivastavanisheeth learningwhattowantcontextsensitivepreferencelearning AT schraterpaul learningwhattowantcontextsensitivepreferencelearning |