Languages and designs for probability judgment

作者: Glenn Shafer , Amos Tversky

DOI: 10.1207/S15516709COG0903_2

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

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