Details

Autor(en) / Beteiligte

• Klein, Dominik
• Majer, Ondrej
• Rafiee Rad, Soroush

Titel

Non-Classical Probabilities for Decision Making in Situations of Uncertainty

Ist Teil von

• Roczniki filozoficzne, 2020-01, Vol.68 (4), p.315-343

Ort / Verlag

Towarzystwo Naukowe KUL & Katolicki Uniwersytet Lubelski Jana Pawła II

Erscheinungsjahr

2020

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Analyzing situations where information is partial, incomplete or contradictory has created a demand for quantitative belief measures that are weaker than classic probability theory. In this paper, we compare two frameworks that have been proposed for this task, Dempster-Shafer theory and non-standard probability theory based on Belnap-Dunn logic. We show the two frameworks to assume orthogonal perspectives on informational shortcomings, but also provide a partial correspondence result. Lastly, we also compare various dynamical rules of the two frameworks, all seen as generalizations of classic Bayes’ conditiong.