This HTML5 document contains 42 embedded RDF statements represented using HTML+Microdata notation.

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

Namespace Prefixes

PrefixIRI
n15http://linked.opendata.cz/ontology/domain/vavai/riv/typAkce/
dctermshttp://purl.org/dc/terms/
n17http://purl.org/net/nknouf/ns/bibtex#
n7http://linked.opendata.cz/resource/domain/vavai/projekt/
n4http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n21http://linked.opendata.cz/ontology/domain/vavai/
n8https://schema.org/
n13http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F67985556%3A_____%2F10%3A00353209%21RIV11-GA0-67985556/
n5http://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/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n12http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n18http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n14http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n9http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n20http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n6http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n16http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F10%3A00353209%21RIV11-GA0-67985556
rdf:type
skos:Concept n21:Vysledek
dcterms:description
Any systematic decision-making design selects a decision strategy that makes the resulting closed-loop behaviour close to the desired one. Fully Probabilistic Design (FPD) describes modelled and desired closed-loop behaviours via their distributions. The designed strategy is a minimiser of Kullback-Leibler divergence of these distributions. FPD: i) unifies modelling and aim-expressing languages; ii) directly describes multiple aims and constraints; iii) simplifies an (inevitable) approximate design as it has an explicit minimiser. The paper enriches the theory of FPD, in particular, it: i) improves its axiomatic basis; ii) quantitatively relates FPD to standard Bayesian decision making showing that the set of FPD tasks is a dense extension of Bayesian problem formulations; iii) opens a way to a systematic data-based preference elicitation, i.e., quantitative expression of decision-making aims. Any systematic decision-making design selects a decision strategy that makes the resulting closed-loop behaviour close to the desired one. Fully Probabilistic Design (FPD) describes modelled and desired closed-loop behaviours via their distributions. The designed strategy is a minimiser of Kullback-Leibler divergence of these distributions. FPD: i) unifies modelling and aim-expressing languages; ii) directly describes multiple aims and constraints; iii) simplifies an (inevitable) approximate design as it has an explicit minimiser. The paper enriches the theory of FPD, in particular, it: i) improves its axiomatic basis; ii) quantitatively relates FPD to standard Bayesian decision making showing that the set of FPD tasks is a dense extension of Bayesian problem formulations; iii) opens a way to a systematic data-based preference elicitation, i.e., quantitative expression of decision-making aims.
dcterms:title
Preference Elicitation in Fully Probabilistic Design of Decision Strategies Preference Elicitation in Fully Probabilistic Design of Decision Strategies
skos:prefLabel
Preference Elicitation in Fully Probabilistic Design of Decision Strategies Preference Elicitation in Fully Probabilistic Design of Decision Strategies
skos:notation
RIV/67985556:_____/10:00353209!RIV11-GA0-67985556
n3:aktivita
n14:P n14:Z
n3:aktivity
P(GA102/08/0567), Z(AV0Z10750506)
n3:dodaniDat
n16:2011
n3:domaciTvurceVysledku
n4:4780280 n4:6585256
n3:druhVysledku
n6:D
n3:duvernostUdaju
n18:S
n3:entitaPredkladatele
n13:predkladatel
n3:idSjednocenehoVysledku
281208
n3:idVysledku
RIV/67985556:_____/10:00353209
n3:jazykVysledku
n9:eng
n3:klicovaSlova
knowledge elicitation; Bayesian decision making; fullz probabilistic design
n3:klicoveSlovo
n12:fullz%20probabilistic%20design n12:Bayesian%20decision%20making n12:knowledge%20elicitation
n3:kontrolniKodProRIV
[72A9ABA7F4B5]
n3:mistoKonaniAkce
Atlanta
n3:mistoVydani
Atlanta
n3:nazevZdroje
Proceedings of the 49th IEEE Conference on Decision and Control
n3:obor
n20:BB
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n7:GA102%2F08%2F0567
n3:rokUplatneniVysledku
n16:2010
n3:tvurceVysledku
Guy, Tatiana Valentine Kárný, Miroslav
n3:typAkce
n15:WRD
n3:zahajeniAkce
2010-12-14+01:00
n3:zamer
n5:AV0Z10750506
s:numberOfPages
6
n17:hasPublisher
IEEE
n8:isbn
978-1-4244-7745-6