Qualitative Decision Theory with Sugeno Integrals
This paper presents an axiomatic framework for qualitative decision under uncertainty in a finite setting. The corresponding utility is expressed by a sup-min expression, called Sugeno (or fuzzy) integral. Technically speaking, Sugeno integral is a median, which is indeed a qualitative counterpart t...
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| creator | Dubois, Didier Prade, Henri Sabbadin, Regis |
| description | This paper presents an axiomatic framework for qualitative decision under
uncertainty in a finite setting. The corresponding utility is expressed by a
sup-min expression, called Sugeno (or fuzzy) integral. Technically speaking,
Sugeno integral is a median, which is indeed a qualitative counterpart to the
averaging operation underlying expected utility. The axiomatic justification of
Sugeno integral-based utility is expressed in terms of preference between acts
as in Savage decision theory. Pessimistic and optimistic qualitative utilities,
based on necessity and possibility measures, previously introduced by two of
the authors, can be retrieved in this setting by adding appropriate axioms. |
| doi_str_mv | 10.48550/arxiv.1301.7372 |
| format | Conference Proceeding |
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uncertainty in a finite setting. The corresponding utility is expressed by a
sup-min expression, called Sugeno (or fuzzy) integral. Technically speaking,
Sugeno integral is a median, which is indeed a qualitative counterpart to the
averaging operation underlying expected utility. The axiomatic justification of
Sugeno integral-based utility is expressed in terms of preference between acts
as in Savage decision theory. Pessimistic and optimistic qualitative utilities,
based on necessity and possibility measures, previously introduced by two of
the authors, can be retrieved in this setting by adding appropriate axioms.</description><identifier>ISBN: 155860555X</identifier><identifier>ISBN: 9781558605558</identifier><identifier>DOI: 10.48550/arxiv.1301.7372</identifier><language>eng</language><publisher>Morgan Kaufmann</publisher><subject>Artificial Intelligence ; Computer Science ; Computer Science - Artificial Intelligence</subject><ispartof>Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI 1998), 2013, p.121-128</ispartof><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-6286-1821 ; 0000-0002-6505-2536 ; 0000-0003-4586-8527</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,309,310,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1301.7372$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1301.7372$$DView paper in arXiv$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-04026168$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Dubois, Didier</creatorcontrib><creatorcontrib>Prade, Henri</creatorcontrib><creatorcontrib>Sabbadin, Regis</creatorcontrib><title>Qualitative Decision Theory with Sugeno Integrals</title><title>Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI 1998)</title><description>This paper presents an axiomatic framework for qualitative decision under
uncertainty in a finite setting. The corresponding utility is expressed by a
sup-min expression, called Sugeno (or fuzzy) integral. Technically speaking,
Sugeno integral is a median, which is indeed a qualitative counterpart to the
averaging operation underlying expected utility. The axiomatic justification of
Sugeno integral-based utility is expressed in terms of preference between acts
as in Savage decision theory. Pessimistic and optimistic qualitative utilities,
based on necessity and possibility measures, previously introduced by two of
the authors, can be retrieved in this setting by adding appropriate axioms.</description><subject>Artificial Intelligence</subject><subject>Computer Science</subject><subject>Computer Science - Artificial Intelligence</subject><isbn>155860555X</isbn><isbn>9781558605558</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>GOX</sourceid><recordid>eNo9j0tLw0AUhQfEhVb3riRbF4lzZzKvZamPFgIi7cLdcJPeNAMxkTSN9t-btOLqwOHjcD7G7oAnqVWKP2L3E4YEJIfESCMu2DUoZTVXSn1cMXg_YB167MNA0RMVYR_aJtpU1HbH6Dv0VbQ-7Khpo1XT067Den_DLssx6PYvZ2z98rxZLOPs7XW1mGcxOifiggqnpdZY5mVBkCrtiFypbEoWwBmx5Q7Q5FqJXCqJRhjMx4_5VgAVVs7Yw3m1wtp_deETu6NvMfjlPPNTx1MuNGg7wMjen9mT6j89KftJWf4CQrNNmQ</recordid><startdate>20130130</startdate><enddate>20130130</enddate><creator>Dubois, Didier</creator><creator>Prade, Henri</creator><creator>Sabbadin, Regis</creator><general>Morgan Kaufmann</general><scope>AKY</scope><scope>GOX</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-6286-1821</orcidid><orcidid>https://orcid.org/0000-0002-6505-2536</orcidid><orcidid>https://orcid.org/0000-0003-4586-8527</orcidid></search><sort><creationdate>20130130</creationdate><title>Qualitative Decision Theory with Sugeno Integrals</title><author>Dubois, Didier ; Prade, Henri ; Sabbadin, Regis</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a992-cec96366afbfce14569ee9f584e811972d091a7b652b353a727ab301bd21ec83</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Artificial Intelligence</topic><topic>Computer Science</topic><topic>Computer Science - Artificial Intelligence</topic><toplevel>online_resources</toplevel><creatorcontrib>Dubois, Didier</creatorcontrib><creatorcontrib>Prade, Henri</creatorcontrib><creatorcontrib>Sabbadin, Regis</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dubois, Didier</au><au>Prade, Henri</au><au>Sabbadin, Regis</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Qualitative Decision Theory with Sugeno Integrals</atitle><btitle>Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI 1998)</btitle><date>2013-01-30</date><risdate>2013</risdate><spage>121</spage><epage>128</epage><pages>121-128</pages><isbn>155860555X</isbn><isbn>9781558605558</isbn><abstract>This paper presents an axiomatic framework for qualitative decision under
uncertainty in a finite setting. The corresponding utility is expressed by a
sup-min expression, called Sugeno (or fuzzy) integral. Technically speaking,
Sugeno integral is a median, which is indeed a qualitative counterpart to the
averaging operation underlying expected utility. The axiomatic justification of
Sugeno integral-based utility is expressed in terms of preference between acts
as in Savage decision theory. Pessimistic and optimistic qualitative utilities,
based on necessity and possibility measures, previously introduced by two of
the authors, can be retrieved in this setting by adding appropriate axioms.</abstract><pub>Morgan Kaufmann</pub><doi>10.48550/arxiv.1301.7372</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-6286-1821</orcidid><orcidid>https://orcid.org/0000-0002-6505-2536</orcidid><orcidid>https://orcid.org/0000-0003-4586-8527</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI 1998), 2013, p.121-128 |
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| subjects | Artificial Intelligence Computer Science Computer Science - Artificial Intelligence |
| title | Qualitative Decision Theory with Sugeno Integrals |
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