Languages and Designs for Probability Judgment,10.1007/978-3-540-44792-4_13,Glenn Shafer,Amos Tversky

Languages and Designs for Probability Judgment


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Theories of subjective probability are viewed as formal languages for analyzing evidence and expressing degrees of belief. This article focuses on two probability language, the Bayesian language and the language of belief functions [199]. We describe and compare the semantics (i.e., the meaning of the scale) and the syntax (i.e., the formal calculus) of these languages. We also investigate some of the designs for probability judgment afforded by the two languages.

Published in 2008.

DOI: 10.1007/978-3-540-44792-4_13

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Languages and Designs for Probability Judgment,10.1007/978-3-540-44792-4_13,Glenn Shafer,Amos Tversky

References (15)

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Probabilistic Information Processing Systems: Design and Evaluation (Citations: 17)

Fault trees: Sensitivity of estimated failure probabilities to problem representation (Citations: 202)

The Logic of Decision (Citations: 439)

Variants of uncertainty (Citations: 172)


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