Describing and Quantifying Contradiction between Pieces of Evidence via Belnap Dunn Logic and Dempster-Shafer Theory

0578922 - FLÚ 2024 RIV ES eng C - Konferenční příspěvek (zahraniční konf.)
Bílková, Marta - Frittella, S. - Kozhemiachenko, D. - Majer, Ondrej - Manoorkar, K.
Describing and Quantifying Contradiction between Pieces of Evidence via Belnap Dunn Logic and Dempster-Shafer Theory.
Proceedings of Machine Learning Research, Volume 215: International Symposium on Imprecise Probability: Theories and Applications,. Almerı́a: PMLR, 2023, s. 37-47. E-ISSN 2640-3498.
[International Symposium on Imprecise Probability: Theories and Applications 2023 /13./. Oviedo (ES), 11.07.2023-14.07.2023]
Grant CEP: GA ČR(CZ) GM21-23610M
Institucionální podpora: RVO:67985955
Klíčová slova: Dempster-Shafer theory * Belnap Dunn logic * contradictory evidence
Obor OECD: Philosophy, History and Philosophy of science and technology
https://proceedings.mlr.press/v215/

Belnap Dunn logic is a four-valued logic introduced to model reasoning with incomplete or contradictory information. In this article, we show how Dempster-Shafer theory can be used over Belnap Dunn logic in order to formalise reasoning with incomplete and/or contradictory pieces of evidence. First, we discuss how to encode different kinds of evidence, and how to interpret the resulting belief and plausibility functions. Then, we discuss the behaviour of Dempster’s rule in this framework and present a variation of the rule. Finally, we show how to construct credal sets of classical probability measures based on this kind of evidence.
Trvalý link: https://hdl.handle.net/11104/0347886