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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F13%3A00396808%21RIV14-GA0-67985556
rdf:type
skos:Concept n11:Vysledek
dcterms:description
An efficient support of a single decision maker is vital in constructing scalable systems addressing complex decision-making (DM) tasks. Fully probabilistic design (FPD) of DM strategies, an extension of dynamic Bayesian DM, provides a firm basis for such a support. The limited cognitive and evaluation resources of the supported decision maker cause that theoretically optimal solutions are realised only approximately. Thus, the truly efficient support has to include reliable means for constructing approximate solutions of DM subtasks. The current paper deals with the design of the approximately optimal DM strategy for a known environment model and adequately described DM preferences. The design relies on: a) the explicit minimiser found within FPD; b) randomised nature of the strategy provided by FPD. An efficient support of a single decision maker is vital in constructing scalable systems addressing complex decision-making (DM) tasks. Fully probabilistic design (FPD) of DM strategies, an extension of dynamic Bayesian DM, provides a firm basis for such a support. The limited cognitive and evaluation resources of the supported decision maker cause that theoretically optimal solutions are realised only approximately. Thus, the truly efficient support has to include reliable means for constructing approximate solutions of DM subtasks. The current paper deals with the design of the approximately optimal DM strategy for a known environment model and adequately described DM preferences. The design relies on: a) the explicit minimiser found within FPD; b) randomised nature of the strategy provided by FPD.
dcterms:title
On Approximate Fully Probabilistic Design of Decision-Making Units On Approximate Fully Probabilistic Design of Decision-Making Units
skos:prefLabel
On Approximate Fully Probabilistic Design of Decision-Making Units On Approximate Fully Probabilistic Design of Decision-Making Units
skos:notation
RIV/67985556:_____/13:00396808!RIV14-GA0-67985556
n11:predkladatel
n20:ico%3A67985556
n3:aktivita
n4:I n4:P
n3:aktivity
I, P(GA13-13502S)
n3:dodaniDat
n14:2014
n3:domaciTvurceVysledku
n21:6585256
n3:druhVysledku
n13:D
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n7:predkladatel
n3:idSjednocenehoVysledku
93652
n3:idVysledku
RIV/67985556:_____/13:00396808
n3:jazykVysledku
n15:eng
n3:klicovaSlova
decision making; Bayesian learning; minimum cross-entropy principle; fully probabilistic design of DM strategies; linear-quadratic DM
n3:klicoveSlovo
n10:Bayesian%20learning n10:minimum%20cross-entropy%20principle n10:decision%20making n10:linear-quadratic%20DM n10:fully%20probabilistic%20design%20of%20DM%20strategies
n3:kontrolniKodProRIV
[2952930CA1AD]
n3:mistoKonaniAkce
Prague
n3:mistoVydani
Prague
n3:nazevZdroje
Preprints of the 3rd International Workshop on Scalable Decision Making held in conjunction with ECML/PKDD 2013
n3:obor
n17:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:projekt
n12:GA13-13502S
n3:rokUplatneniVysledku
n14:2013
n3:tvurceVysledku
Kárný, Miroslav
n3:typAkce
n8:WRD
n3:zahajeniAkce
2013-09-23+02:00
s:numberOfPages
12
n18:hasPublisher
Ústav teorie informace a automatizace AV ČR
n5:isbn
978-80-903834-8-7