Communication publiée dans un ouvrage (Colloques, congrès, conférences scientifiques et actes)
A Probabilistic Deontic Logic
DE WIT, Vincent; DODER, Dragan; Meyer, John Jules
2021 • In Vejnarová, Jirina (Ed.) Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 16th European Conference, ECSQARU 2021, Proceedings
[en] In this article, we introduce a logic for reasoning about probability of normative statements. We present its syntax and semantics, describe the corresponding class of models, provide an axiomatization for this logic and prove that the axiomatization is sound and complete. We also prove that our logic is decidable.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
DE WIT, Vincent ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) ; UU - University of Utrecht [NL] > Department of Information and Computing Sciences
DODER, Dragan ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Computer Science ; Department of Information and Computing Sciences, Utrecht University, Utrecht, Netherlands
Meyer, John Jules; Department of Information and Computing Sciences, Utrecht University, Utrecht, Netherlands
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
A Probabilistic Deontic Logic
Titre original :
[en] A Probabilistic Deontic Logic
Date de publication/diffusion :
2021
Nom de la manifestation :
European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU)
Lieu de la manifestation :
Prague, Cze
Date de la manifestation :
21-09-2021 => 24-09-2021
Titre de l'ouvrage principal :
Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 16th European Conference, ECSQARU 2021, Proceedings
Editeur scientifique :
Vejnarová, Jirina
Maison d'édition :
Springer Science and Business Media Deutschland GmbH
Boella, G., van der Torre, L.W.N., Verhagen, H.: Introduction to normative multiagent systems. Comput. Math. Organ. Theor. 12(2–3), 71–79 (2006). https://doi. org/10.1007/s10588-006-9537-7
Chellas, B.F.: Modal Logic: An Introduction. Cambridge University Press (1980). https://doi.org/10.1017/CBO9780511621192
Fagin, R., Halpern, J.Y.: Reasoning about knowledge and probability. J. ACM 41(2), 340–367 (1994)
Fagin, R., Halpern, J.Y., Megiddo, N.: A logic for reasoning about probabilities. Inf. Computat. 87(1), 78–128 (1990)
Frisch, A., Haddawy, P.: Anytime deduction for probabilistic logic. Artif. Intell. 69, 93–122 (1994)
van der Hoek, W.: Some considerations on the logic pfd. J. Appl. Non Class. Logics 7(3), 287–307 (1997)
Horty, J.F.: Agency and Deontic Logic. Oxford University Press (2001)
Hughes, G.E., Cresswell, M.J.: A Companion to Modal Logic. Methuen London, New York (1984)
Parent, X., Van Der Torre, L.: Introduction to Deontic Logic and Normative Systems. Texts in Logic and Reasoning. College Publications (2018). https://books. google.nl/books?id=IyUYwQEACAAJ
Riveret, R., Oren, N., Sartor, G.: A probabilistic deontic argumentation framework. Int. J. Approximate Reason. 126, 249–271 (2020)
Sarathy, V., Scheutz, M., Malle, B.F.: Learning behavioral norms in uncertain and changing contexts. In: 2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), pp. 000301–000306 (2017). https://doi.org/10.1109/CogInfoCom.2017.8268261
Savic, N., Doder, D., Ognjanovic, Z.: Logics with lower and upper probability operators. Int. J. Approx. Reason. 88, 148–168 (2017)
Tomic, S., Pecora, F., Saffiotti, A.: Learning normative behaviors through abstraction. In: Giacomo, G.D. (eds.) 24th European Conference on Artificial Intelligence, ECAI 2020, 29 August–8 September 2020, Santiago de Compostela, Spain, Including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020). Frontiers in Artificial Intelligence and Applications, vol. 325, pp. 1547–1554. IOS Press (2020). https://doi.org/10.3233/FAIA200263
von Wrigth, G.H.: I. Deontic logic. Mind LX(237), 1–15 (1951). https://doi.org/10.1093/mind/LX.237.1
