Volume 13, Issue 9 pp. 801-820

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

Brian Cloteaux

Brian Cloteaux

Department of Computer Science, University of Texas at El Paso, El Paso, Texas 79968

Currently at Exxon Co., Houston, TX

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Christoph Eick

Christoph Eick

Department of Computer Science, University of Houston, Houston, Texas 77204-3475

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Bernadette Bouchon-Meunier

Bernadette Bouchon-Meunier

LIP6, UPMC, Case 169, 4 place Jussieu, 75252 Paris Cédex 05, France

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Vladik Kreinovich

Corresponding Author

Vladik Kreinovich

Department of Computer Science, University of Texas at El Paso, El Paso, Texas 79968

Department of Computer Science, University of Texas at El Paso, El Paso, Texas 79968Search for more papers by this author

Abstract

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.

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