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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F13%3A00389631%21RIV13-AV0-67985556
rdf:type
n8:Vysledek skos:Concept
dcterms:description
In the contemporary complex world decisions are made by an imperfect participant devoting limited deliberation resources to any decision-making task. A normative decision-making (DM) theory should provide support systems allowing such a participant to make rational decisions in spite of the limited resources. Efficiency of the support systems depends on the interfaces enabling a participant to benefit from the support while exploiting the gradually accumulating knowledge about DM environment and respecting incomplete, possibly changing, participant’s DM preferences. The insufficiently elaborated preference elicitation makes even the best DM supports of a limited use. This chapter proposes a methodology of automatic eliciting of a quantitative DM preference description, discusses the options made and sketches open research problems. The proposed elicitation serves to fully probabilistic design, which includes a standard Bayesian decision making. In the contemporary complex world decisions are made by an imperfect participant devoting limited deliberation resources to any decision-making task. A normative decision-making (DM) theory should provide support systems allowing such a participant to make rational decisions in spite of the limited resources. Efficiency of the support systems depends on the interfaces enabling a participant to benefit from the support while exploiting the gradually accumulating knowledge about DM environment and respecting incomplete, possibly changing, participant’s DM preferences. The insufficiently elaborated preference elicitation makes even the best DM supports of a limited use. This chapter proposes a methodology of automatic eliciting of a quantitative DM preference description, discusses the options made and sketches open research problems. The proposed elicitation serves to fully probabilistic design, which includes a standard Bayesian decision making.
dcterms:title
Automated Preference Elicitation for Decision Making Automated Preference Elicitation for Decision Making
skos:prefLabel
Automated Preference Elicitation for Decision Making Automated Preference Elicitation for Decision Making
skos:notation
RIV/67985556:_____/13:00389631!RIV13-AV0-67985556
n8:predkladatel
n12:ico%3A67985556
n3:aktivita
n9:Z n9:P n9:I
n3:aktivity
I, P(GA102/08/0567), Z(AV0Z1075907)
n3:dodaniDat
n5:2013
n3:domaciTvurceVysledku
n17:6585256
n3:druhVysledku
n15:C
n3:duvernostUdaju
n4:S
n3:entitaPredkladatele
n19:predkladatel
n3:idSjednocenehoVysledku
62578
n3:idVysledku
RIV/67985556:_____/13:00389631
n3:jazykVysledku
n10:eng
n3:klicovaSlova
Bayesian decision making; fully probabilistic design; DM preference elicitation; support of imperfect participants
n3:klicoveSlovo
n16:DM%20preference%20elicitation n16:Bayesian%20decision%20making n16:fully%20probabilistic%20design n16:support%20of%20imperfect%20participants
n3:kontrolniKodProRIV
[1C29D1B8A81D]
n3:mistoVydani
Berlin
n3:nazevEdiceCisloSvazku
Studies in Computational Intelligence
n3:nazevZdroje
Decision Making and Imperfection
n3:obor
n7:BC
n3:pocetDomacichTvurcuVysledku
1
n3:pocetStranKnihy
187
n3:pocetTvurcuVysledku
1
n3:projekt
n22:GA102%2F08%2F0567
n3:rokUplatneniVysledku
n5:2013
n3:tvurceVysledku
Kárný, Miroslav
n3:zamer
n21:AV0Z1075907
s:numberOfPages
35
n11:doi
10.1007/978-3-642-36406-8_3
n13:hasPublisher
Springer-Verlag
n18:isbn
978-3-642-36405-1