@inbook{697dcbaa8bf449c3aaf531d925c2935a,
title = "Languages and designs for probability judgment",
abstract = "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.",
author = "Glenn Shafer and Amos Tversky",
note = "Funding Information: l This research has been supported in part by NSF grants MCS-800213 and 8301282 to the first author and by ONR Grant NR197-058 to the second author. The article has benefited from the comments of Jonathan Baron, Morris DeGroot, Persi Diaconis and David Krantz. Correspondence and requests for reprints should be sent to Glenn Shafer at the School of Business, University of Kansas, Lawrence, KS 66045.",
year = "2008",
doi = "10.1007/978-3-540-44792-4_13",
language = "English (US)",
isbn = "9783540253815",
series = "Studies in Fuzziness and Soft Computing",
pages = "345--374",
editor = "Yager, {Roland R.} and Liping Liu",
booktitle = "Classic Works of the Dempster-Shafer Theory of Belief Functions",
}