GENERAL PROPERTIES OF BAYESIAN LEARNING AS STATISTICAL INFERENCE DETERMINED BY CONDITIONAL EXPECTATIONS

DOI10.1017/S1755020316000502zbMath1417.03113MaRDI QIDQ4600825

Miklós Rédei, Zalán Gyenis

Publication date: 17 January 2018

Published in: The Review of Symbolic Logic (Search for Journal in Brave)

zbMATH Keywords

Bayesian learningconditionalizationBayes accessibility

Mathematics Subject Classification ID

Bayesian inference (62F15) Axioms; other general questions in probability (60A05) Logic in the philosophy of science (03A10)

Related Items (10)

Jeffrey meets Kolmogorov. A general theory of conditioning ⋮ On the modal logic of Jeffrey conditionalization ⋮ A DUTCH BOOK THEOREM AND CONVERSE DUTCH BOOK THEOREM FOR KOLMOGOROV CONDITIONALIZATION ⋮ KOLMOGOROV CONDITIONALIZERS CAN BE DUTCH BOOKED (IF AND ONLY IF THEY ARE EVIDENTIALLY UNCERTAIN) ⋮ The maxim of probabilism, with special regard to Reichenbach ⋮ Having a look at the Bayes blind spot ⋮ Conditioning using conditional expectations: the Borel-Kolmogorov paradox ⋮ Blocking an argument for emergent chance ⋮ The modal logic of Bayesian belief revision ⋮ A NEW ARGUMENT FOR KOLOMOGOROV CONDITIONALIZATION

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