From ordered beliefs to numbers: How to elicit numbers without asking for them (doable but computationally difficult)

One of the most important parts of designing an expert system is elicitation of the expert's knowledge. This knowledge usually consists of facts and rules. Eliciting these rules and facts is relatively easy: the more complicated task is assigning weights (numerical or interval‐valued degrees of...

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Veröffentlicht in:International journal of intelligent systems 1998-09, Vol.13 (9), p.801-820
Hauptverfasser: Cloteaux, Brian, Eick, Christoph, Bouchon-Meunier, Bernadette, Kreinovich, Vladik
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container_end_page 820
container_issue 9
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container_title International journal of intelligent systems
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creator Cloteaux, Brian
Eick, Christoph
Bouchon-Meunier, Bernadette
Kreinovich, Vladik
description One of the most important parts of designing an expert system is elicitation of the expert's knowledge. This knowledge usually consists of facts and rules. Eliciting these rules and facts is relatively easy: the more complicated task is assigning weights (numerical or interval‐valued degrees of belief) to different statements from the knowledge base. Experts often cannot quantify their degrees of belief, but they can order them (by suggesting which statements are more reliable). It is, therefore, reasonable to try to reconstruct the degrees of belief from such an ordering.In this paper, we analyze when such a reconstruction is possible, whether it lead to unique values of degrees of belief, and how computationally complicated the corresponding reconstruction problem can be. © 1998 John Wiley & Sons, Inc.
doi_str_mv 10.1002/(SICI)1098-111X(199809)13:9<801::AID-INT2>3.0.CO;2-M
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source Wiley Online Library Journals Frontfile Complete
subjects Applied sciences
Artificial intelligence
Computer science
control theory
systems
Exact sciences and technology
Learning and adaptive systems
title From ordered beliefs to numbers: How to elicit numbers without asking for them (doable but computationally difficult)
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