A representation theorem and applications to measure selection and noninformative priors

DOI10.1016/j.ijar.2004.05.004zbMath1095.68116OpenAlexW2125058212MaRDI QIDQ1763162

Manfred Jaeger

Publication date: 22 February 2005

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2004.05.004

zbMATH Keywords

probabilistic inference

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items (1)

A representation theorem and applications to measure selection and noninformative priors

Cites Work

• A note on the inevitability of maximum entropy
• Common sense and maximum entropy
• A representation theorem and applications to measure selection and noninformative priors
• Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy
• On the Representation of Ignorance
• The Uncertain Reasoner's Companion
• A Bayesian Indifference Procedure
• Invariant Prior Distributions
• Prior Probabilities
• Symbolic and Quantitative Approaches to Reasoning with Uncertainty
• Bertrand's paradox revisited.
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