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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. (en)
Title
  • Automated Preference Elicitation for Decision Making
  • Automated Preference Elicitation for Decision Making (en)
skos:prefLabel
  • Automated Preference Elicitation for Decision Making
  • Automated Preference Elicitation for Decision Making (en)
skos:notation
  • RIV/67985556:_____/13:00389631!RIV13-AV0-67985556
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • I, P(GA102/08/0567), Z(AV0Z1075907)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 62578
http://linked.open...ai/riv/idVysledku
  • RIV/67985556:_____/13:00389631
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Bayesian decision making; fully probabilistic design; DM preference elicitation; support of imperfect participants (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [1C29D1B8A81D]
http://linked.open...i/riv/mistoVydani
  • Berlin
http://linked.open...vEdiceCisloSvazku
  • Studies in Computational Intelligence
http://linked.open...i/riv/nazevZdroje
  • Decision Making and Imperfection
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...v/pocetStranKnihy
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kárný, Miroslav
http://linked.open...n/vavai/riv/zamer
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-36406-8_3
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-642-36405-1
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