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Towards a computational model of social norms
We describe a computational model of social norms based on identifying values that a certain culture finds desirable such as dignity, generosity and politeness. The model quantifies these values in the form of Culture-Sanctioned Social Metrics (CSSMs) and treats social norms as the requirement to ma...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5895006/ https://www.ncbi.nlm.nih.gov/pubmed/29641583 http://dx.doi.org/10.1371/journal.pone.0195331 |
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author | Bölöni, Ladislau Singh Bhatia, Taranjeet Khan, Saad Ahmad Streater, Jonathan Fiore, Stephen M. |
author_facet | Bölöni, Ladislau Singh Bhatia, Taranjeet Khan, Saad Ahmad Streater, Jonathan Fiore, Stephen M. |
author_sort | Bölöni, Ladislau |
collection | PubMed |
description | We describe a computational model of social norms based on identifying values that a certain culture finds desirable such as dignity, generosity and politeness. The model quantifies these values in the form of Culture-Sanctioned Social Metrics (CSSMs) and treats social norms as the requirement to maximize these metrics from the perspective of the self, peers and public. This model can be used to create realistic social simulations, to explain or predict human behavior in specific scenarios, or as a component of robots or agents that need to interact with humans in specific social-cultural settings. We validate the model by using it to represent a complex deception scenario and showing that it can yield non-trivial insights such as the explanation of apparently irrational human behavior. |
format | Online Article Text |
id | pubmed-5895006 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58950062018-05-04 Towards a computational model of social norms Bölöni, Ladislau Singh Bhatia, Taranjeet Khan, Saad Ahmad Streater, Jonathan Fiore, Stephen M. PLoS One Research Article We describe a computational model of social norms based on identifying values that a certain culture finds desirable such as dignity, generosity and politeness. The model quantifies these values in the form of Culture-Sanctioned Social Metrics (CSSMs) and treats social norms as the requirement to maximize these metrics from the perspective of the self, peers and public. This model can be used to create realistic social simulations, to explain or predict human behavior in specific scenarios, or as a component of robots or agents that need to interact with humans in specific social-cultural settings. We validate the model by using it to represent a complex deception scenario and showing that it can yield non-trivial insights such as the explanation of apparently irrational human behavior. Public Library of Science 2018-04-11 /pmc/articles/PMC5895006/ /pubmed/29641583 http://dx.doi.org/10.1371/journal.pone.0195331 Text en © 2018 Bölöni et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bölöni, Ladislau Singh Bhatia, Taranjeet Khan, Saad Ahmad Streater, Jonathan Fiore, Stephen M. Towards a computational model of social norms |
title | Towards a computational model of social norms |
title_full | Towards a computational model of social norms |
title_fullStr | Towards a computational model of social norms |
title_full_unstemmed | Towards a computational model of social norms |
title_short | Towards a computational model of social norms |
title_sort | towards a computational model of social norms |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5895006/ https://www.ncbi.nlm.nih.gov/pubmed/29641583 http://dx.doi.org/10.1371/journal.pone.0195331 |
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