Data di Pubblicazione:
2021
Citazione:
Scoring Rules for Belief Functions and Imprecise Probabilities: A Comparison / E.A. Corsi, T. Flaminio, H. Hosni (LECTURE NOTES IN ARTIFICIAL INTELLIGENCE). - In: Symbolic and Quantitative Approaches to Reasoning with Uncertainty / [a cura di] J. Vejnarová, N. Wilson. - [s.l] : Springer, 2021. - ISBN 978-3-030-86771-3. - pp. 301-313 (( Intervento presentato al 16. convegno ECSQARU tenutosi a Prague nel 2021 [10.1007/978-3-030-86772-0_22].
Abstract:
This paper investigates de Finetti’s coherence as an opera- tional foundation for a wide range of non-additive uncertainty measures and focuses, in particular, on Belief functions and Lower probabilities. In a companion paper we identify a number of non-limiting circumstances under which Dutch Book criteria for Belief functions and Lower proba- bility are undistinguishable, which is surprising given that Lower prob- abilities are known to exist which do no satisfy the axioms of Belief functions. The main contribution of this paper consists in putting for- ward a comparison between a criterion based on the Brier scoring rule for Belief Functions and the scoring rule introduced in 2012 by Seidenfeld, Schervish and Kadane for Imprecise probabilities. Through this compar- ison we show that scoring rules allow us to distinguish coherence-wise between Belief functions and Imprecise probabilities.
Tipologia IRIS:
03 - Contributo in volume
Keywords:
Scoring rules; Belief functions; Lower probabilities; Imprecise probabilities; Coherence
Elenco autori:
E.A. Corsi, T. Flaminio, H. Hosni
Link alla scheda completa:
Titolo del libro:
Symbolic and Quantitative Approaches to Reasoning with Uncertainty