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Agent EXPRI: Licence to Explain

Online social networks are known to lack adequate multi-user privacy support. In this paper we present EXPRI, an agent architecture that aims to assist users in managing multi-user privacy conflicts. By considering the personal utility of sharing content and the individually preferred moral values o...

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Detalles Bibliográficos
Autores principales: Mosca, Francesca, Sarkadi, Ştefan, Such, Jose M., McBurney, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338150/
http://dx.doi.org/10.1007/978-3-030-51924-7_2
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author Mosca, Francesca
Sarkadi, Ştefan
Such, Jose M.
McBurney, Peter
author_facet Mosca, Francesca
Sarkadi, Ştefan
Such, Jose M.
McBurney, Peter
author_sort Mosca, Francesca
collection PubMed
description Online social networks are known to lack adequate multi-user privacy support. In this paper we present EXPRI, an agent architecture that aims to assist users in managing multi-user privacy conflicts. By considering the personal utility of sharing content and the individually preferred moral values of each user involved in the conflict, EXPRI identifies the best collaborative solution by applying practical reasoning techniques. Such techniques provide the agent with the cognitive process that is necessary for explainability. Furthermore, the knowledge gathered during the practical reasoning process allows EXPRI to engage in contrastive explanations.
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spelling pubmed-73381502020-07-07 Agent EXPRI: Licence to Explain Mosca, Francesca Sarkadi, Ştefan Such, Jose M. McBurney, Peter Explainable, Transparent Autonomous Agents and Multi-Agent Systems Article Online social networks are known to lack adequate multi-user privacy support. In this paper we present EXPRI, an agent architecture that aims to assist users in managing multi-user privacy conflicts. By considering the personal utility of sharing content and the individually preferred moral values of each user involved in the conflict, EXPRI identifies the best collaborative solution by applying practical reasoning techniques. Such techniques provide the agent with the cognitive process that is necessary for explainability. Furthermore, the knowledge gathered during the practical reasoning process allows EXPRI to engage in contrastive explanations. 2020-06-04 /pmc/articles/PMC7338150/ http://dx.doi.org/10.1007/978-3-030-51924-7_2 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Mosca, Francesca
Sarkadi, Ştefan
Such, Jose M.
McBurney, Peter
Agent EXPRI: Licence to Explain
title Agent EXPRI: Licence to Explain
title_full Agent EXPRI: Licence to Explain
title_fullStr Agent EXPRI: Licence to Explain
title_full_unstemmed Agent EXPRI: Licence to Explain
title_short Agent EXPRI: Licence to Explain
title_sort agent expri: licence to explain
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338150/
http://dx.doi.org/10.1007/978-3-030-51924-7_2
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