Items where City Author is "Serramia-Amoros, Marc"
Article
Serramia Amoros, M. 
ORCID: 0000-0003-0993-024X, Rodriguez-Soto, M., Lopez-Sanchez, M. , Rodriguez-Aguilar, J. A., Bistaffa, F., Boddington, P., Wooldridge, M. & Ansotegui, C. (2023).
Encoding ethics to compute value-aligned norms.
Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences,
doi: 10.1007/s11023-023-09649-7
Serramia, M., Lopez-Sanchez, M., Moretti, S. & Rodriguez-Aguilar, J. A. (2023). Building rankings encompassing multiple criteria to support qualitative decision-making. Information Sciences, 631, pp. 288-304. doi: 10.1016/j.ins.2023.02.063
Aydoğan, R., Criado, N., Lang, J. , Sanchez-Anguix, V. & Serramia, M. ORCID: 0000-0003-0993-024X (2022).
Preface.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13753,
v.
doi: 10.1007/978-3-031-21203-1_2
Rodriguez-Soto, M., Serramia, M. ORCID: 0000-0003-0993-024X, Lopez-Sanchez, M. & Antonio Rodriguez-Aguilar, J. (2022).
Instilling moral value alignment by means of multi-objective reinforcement learning.
Ethics and Information Technology, 24(1),
9.
doi: 10.1007/s10676-022-09635-0
Serramia, M. ORCID: 0000-0003-0993-024X, Lopez-Sanchez, M., Moretti, S. & Rodriguez-Aguilar, J. A. (2021).
On the dominant set selection problem and its application to value alignment.
Autonomous Agents and Multi-Agent Systems, 35(2),
42.
doi: 10.1007/s10458-021-09519-5
Conference or Workshop Item
Serramia Amoros, M. ORCID: 0000-0003-0993-024X, Seymour, W., Criado, N. & Luck, M. (2023).
Predicting Privacy Preferences for Smart Devices as Norms.
In:
AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems.
(pp. 2262-2270). New York, USA: ACM.
ISBN 9781450394321
doi: 10.5555/3545946
Lera-Leri, R., Bistaffa, F., Serramia, M. ORCID: 0000-0003-0993-024X , Lopez-Sanchez, M. & Rodriguez-Aguilar, J. A. (2022).
Towards Pluralistic Value Alignment: Aggregating Value Systems through ℓp-Regression.
In:
AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems.
(pp. 780-788). London, UK: ACM.
ISBN 9781713854333