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...
Gespeichert in:
Veröffentlicht in: | International journal of intelligent systems 1998-09, Vol.13 (9), p.801-820 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 820 |
---|---|
container_issue | 9 |
container_start_page | 801 |
container_title | International journal of intelligent systems |
container_volume | 13 |
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 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_27523512</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>27523512</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4052-1bf1cf1f4edb0fde93a9362942cceb9a28f57ef2a24226fd4d7c327ac63d21863</originalsourceid><addsrcrecordid>eNqFkV1v0zAUhiMEEmXwH3yBUHuR4o8kjss0aQS2VtpWTRSNuyPHsZlZEhc7Uem_J6GjXIDElXV8znle6TxRdErwnGBM304_rYrVjGCRx4SQL1MiRI7FjLCFOM0xWSzOVx_i1c2GnrE5nhfrdzS-fhJNjgtPownO8yTOCWfPoxchfMOYEJ6kk6i_8K5Bzlfa6wqVurbaBNQ51PZNqX1YoKXbjfXQUbb7_Y12trt3fYdkeLDtV2ScR929btC0crKsNSqHnnLNtu9kZ10r63qPKmuMVX3dzV5Gz4ysg371-J5Eny8-boplfLW-XBXnV7FKcEpjUhqiDDGJrkpsKi2YFCyjIqFK6VJImpuUa0MlTSjNTJVUXDHKpcpYRUmesZPozYG79e57r0MHjQ1K17VstesDUJ5SlhI6DG4Og8q7ELw2sPW2kX4PBMPoAGB0AONJYTwpHBwAYSBgcAAwOIDRATDAUKyBwvWAff2YL4OStfGyVTYc2ZRxnifZn_SdrfX-r-j_JP8j-Fc9YOMD1oZO_zhipX-AjDOewt3NJWRkyW_f33K4Yz8BrQW3lw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>27523512</pqid></control><display><type>article</type><title>From ordered beliefs to numbers: How to elicit numbers without asking for them (doable but computationally difficult)</title><source>Wiley Online Library Journals Frontfile Complete</source><creator>Cloteaux, Brian ; Eick, Christoph ; Bouchon-Meunier, Bernadette ; Kreinovich, Vladik</creator><creatorcontrib>Cloteaux, Brian ; Eick, Christoph ; Bouchon-Meunier, Bernadette ; Kreinovich, Vladik</creatorcontrib><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.</description><identifier>ISSN: 0884-8173</identifier><identifier>EISSN: 1098-111X</identifier><identifier>DOI: 10.1002/(SICI)1098-111X(199809)13:9<801::AID-INT2>3.0.CO;2-M</identifier><identifier>CODEN: IJISED</identifier><language>eng</language><publisher>New York: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Exact sciences and technology ; Learning and adaptive systems</subject><ispartof>International journal of intelligent systems, 1998-09, Vol.13 (9), p.801-820</ispartof><rights>Copyright © 1998 John Wiley & Sons, Inc.</rights><rights>1998 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2F%28SICI%291098-111X%28199809%2913%3A9%3C801%3A%3AAID-INT2%3E3.0.CO%3B2-M$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2F%28SICI%291098-111X%28199809%2913%3A9%3C801%3A%3AAID-INT2%3E3.0.CO%3B2-M$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=2377846$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Cloteaux, Brian</creatorcontrib><creatorcontrib>Eick, Christoph</creatorcontrib><creatorcontrib>Bouchon-Meunier, Bernadette</creatorcontrib><creatorcontrib>Kreinovich, Vladik</creatorcontrib><title>From ordered beliefs to numbers: How to elicit numbers without asking for them (doable but computationally difficult)</title><title>International journal of intelligent systems</title><addtitle>Int. J. Intell. Syst</addtitle><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.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Learning and adaptive systems</subject><issn>0884-8173</issn><issn>1098-111X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><recordid>eNqFkV1v0zAUhiMEEmXwH3yBUHuR4o8kjss0aQS2VtpWTRSNuyPHsZlZEhc7Uem_J6GjXIDElXV8znle6TxRdErwnGBM304_rYrVjGCRx4SQL1MiRI7FjLCFOM0xWSzOVx_i1c2GnrE5nhfrdzS-fhJNjgtPownO8yTOCWfPoxchfMOYEJ6kk6i_8K5Bzlfa6wqVurbaBNQ51PZNqX1YoKXbjfXQUbb7_Y12trt3fYdkeLDtV2ScR929btC0crKsNSqHnnLNtu9kZ10r63qPKmuMVX3dzV5Gz4ysg371-J5Eny8-boplfLW-XBXnV7FKcEpjUhqiDDGJrkpsKi2YFCyjIqFK6VJImpuUa0MlTSjNTJVUXDHKpcpYRUmesZPozYG79e57r0MHjQ1K17VstesDUJ5SlhI6DG4Og8q7ELw2sPW2kX4PBMPoAGB0AONJYTwpHBwAYSBgcAAwOIDRATDAUKyBwvWAff2YL4OStfGyVTYc2ZRxnifZn_SdrfX-r-j_JP8j-Fc9YOMD1oZO_zhipX-AjDOewt3NJWRkyW_f33K4Yz8BrQW3lw</recordid><startdate>199809</startdate><enddate>199809</enddate><creator>Cloteaux, Brian</creator><creator>Eick, Christoph</creator><creator>Bouchon-Meunier, Bernadette</creator><creator>Kreinovich, Vladik</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><general>Wiley</general><scope>BSCLL</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>199809</creationdate><title>From ordered beliefs to numbers: How to elicit numbers without asking for them (doable but computationally difficult)</title><author>Cloteaux, Brian ; Eick, Christoph ; Bouchon-Meunier, Bernadette ; Kreinovich, Vladik</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4052-1bf1cf1f4edb0fde93a9362942cceb9a28f57ef2a24226fd4d7c327ac63d21863</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Learning and adaptive systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cloteaux, Brian</creatorcontrib><creatorcontrib>Eick, Christoph</creatorcontrib><creatorcontrib>Bouchon-Meunier, Bernadette</creatorcontrib><creatorcontrib>Kreinovich, Vladik</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal of intelligent systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cloteaux, Brian</au><au>Eick, Christoph</au><au>Bouchon-Meunier, Bernadette</au><au>Kreinovich, Vladik</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>From ordered beliefs to numbers: How to elicit numbers without asking for them (doable but computationally difficult)</atitle><jtitle>International journal of intelligent systems</jtitle><addtitle>Int. J. Intell. Syst</addtitle><date>1998-09</date><risdate>1998</risdate><volume>13</volume><issue>9</issue><spage>801</spage><epage>820</epage><pages>801-820</pages><issn>0884-8173</issn><eissn>1098-111X</eissn><coden>IJISED</coden><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.</abstract><cop>New York</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><doi>10.1002/(SICI)1098-111X(199809)13:9<801::AID-INT2>3.0.CO;2-M</doi><tpages>20</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0884-8173 |
ispartof | International journal of intelligent systems, 1998-09, Vol.13 (9), p.801-820 |
issn | 0884-8173 1098-111X |
language | eng |
recordid | cdi_proquest_miscellaneous_27523512 |
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) |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T03%3A47%3A20IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=From%20ordered%20beliefs%20to%20numbers:%20How%20to%20elicit%20numbers%20without%20asking%20for%20them%20(doable%20but%20computationally%20difficult)&rft.jtitle=International%20journal%20of%20intelligent%20systems&rft.au=Cloteaux,%20Brian&rft.date=1998-09&rft.volume=13&rft.issue=9&rft.spage=801&rft.epage=820&rft.pages=801-820&rft.issn=0884-8173&rft.eissn=1098-111X&rft.coden=IJISED&rft_id=info:doi/10.1002/(SICI)1098-111X(199809)13:9%3C801::AID-INT2%3E3.0.CO;2-M&rft_dat=%3Cproquest_cross%3E27523512%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=27523512&rft_id=info:pmid/&rfr_iscdi=true |