This HTML5 document contains 44 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
dctermshttp://purl.org/dc/terms/
n20http://purl.org/net/nknouf/ns/bibtex#
n13http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n5http://linked.opendata.cz/resource/domain/vavai/projekt/
n19http://linked.opendata.cz/resource/domain/vavai/subjekt/
n18http://linked.opendata.cz/ontology/domain/vavai/
n12http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F67985556%3A_____%2F12%3A00364850%21RIV12-AV0-67985556/
n17https://schema.org/
n11http://linked.opendata.cz/resource/domain/vavai/zamer/
shttp://schema.org/
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n14http://bibframe.org/vocab/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n7http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n10http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n21http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n9http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n22http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n6http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n16http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F12%3A00364850%21RIV12-AV0-67985556
rdf:type
skos:Concept n18:Vysledek
dcterms:description
Bayesian decision theory provides a strong theoretical basis for a singleparticipant decision making under uncertainty, that can be extended to multipleparticipant decision making. However, this theory (similarly as others) assumes unlimited abilities of a participant to probabilistically model the participant’s environment and to optimise its decision-making strategy. The proposed methodology solves knowledge and preference elicitation, as well as sharing of individual, possibly fragmental, knowledge and preferences among imperfect participants. The approach helps to overcome the non-realistic assumption on participants’ unlimited abilities. Bayesian decision theory provides a strong theoretical basis for a singleparticipant decision making under uncertainty, that can be extended to multipleparticipant decision making. However, this theory (similarly as others) assumes unlimited abilities of a participant to probabilistically model the participant’s environment and to optimise its decision-making strategy. The proposed methodology solves knowledge and preference elicitation, as well as sharing of individual, possibly fragmental, knowledge and preferences among imperfect participants. The approach helps to overcome the non-realistic assumption on participants’ unlimited abilities.
dcterms:title
On Support of Imperfect Bayesian Participants On Support of Imperfect Bayesian Participants
skos:prefLabel
On Support of Imperfect Bayesian Participants On Support of Imperfect Bayesian Participants
skos:notation
RIV/67985556:_____/12:00364850!RIV12-AV0-67985556
n18:predkladatel
n19:ico%3A67985556
n3:aktivita
n9:Z n9:P
n3:aktivity
P(1M0572), P(GA102/08/0567), Z(AV0Z10750506)
n3:dodaniDat
n16:2012
n3:domaciTvurceVysledku
n13:4780280 n13:6585256
n3:druhVysledku
n22:C
n3:duvernostUdaju
n10:S
n3:entitaPredkladatele
n12:predkladatel
n3:idSjednocenehoVysledku
156343
n3:idVysledku
RIV/67985556:_____/12:00364850
n3:jazykVysledku
n21:eng
n3:klicovaSlova
Decision Making; Imperfect Decision Makers; Intelligent Systems
n3:klicoveSlovo
n7:Decision%20Making n7:Intelligent%20Systems n7:Imperfect%20Decision%20Makers
n3:kontrolniKodProRIV
[A62FC422BA62]
n3:mistoVydani
Berlin Heidelberg
n3:nazevEdiceCisloSvazku
Vol. 28
n3:nazevZdroje
Decision Making with Imperfect Decision Makers
n3:obor
n6:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetStranKnihy
210
n3:pocetTvurcuVysledku
2
n3:projekt
n5:1M0572 n5:GA102%2F08%2F0567
n3:rokUplatneniVysledku
n16:2012
n3:tvurceVysledku
Kárný, Miroslav Guy, Tatiana Valentine
n3:zamer
n11:AV0Z10750506
s:numberOfPages
27
n14:doi
10.1007/978-3-642-24647-0
n20:hasPublisher
Springer-Verlag
n17:isbn
978-3-642-24646-3