@inbook{9fca5268b2794fc4a0a7367072cb2e6a,
title = "Agent EXPRI: Licence to Explain",
abstract = "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.",
keywords = "Explainable AI, Multi-user privacy, Practical reasoning",
author = "Francesca Mosca and {\c S}tefan Sarkadi and Such, {Jose M.} and Peter McBurney",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 2nd International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, EXTRAAMAS 2020 ; Conference date: 09-05-2020 Through 13-05-2020",
year = "2020",
doi = "10.1007/978-3-030-51924-7_2",
language = "English",
isbn = "9783030519230",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "SPRINGER",
pages = "21--38",
editor = "Davide Calvaresi and Amro Najjar and Michael Winikoff and Kary Fr{\"a}mling",
booktitle = "Explainable, Transparent Autonomous Agents and Multi-Agent Systems - 2nd International Workshop, EXTRAAMAS 2020, Revised Selected Papers",
}