This HTML5 document contains 48 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/
n8http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F00216224%3A14330%2F14%3A00074494%21RIV15-GA0-14330___/
n4http://localhost/temp/predkladatel/
n19http://linked.opendata.cz/resource/domain/vavai/projekt/
n11http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n16http://linked.opendata.cz/ontology/domain/vavai/
shttp://schema.org/
rdfshttp://www.w3.org/2000/01/rdf-schema#
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n15http://bibframe.org/vocab/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n9http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n14http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n20http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n17http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n18http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n13http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n12http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F14%3A00074494%21RIV15-GA0-14330___
rdf:type
skos:Concept n16:Vysledek
rdfs:seeAlso
http://www.lmcs-online.org/ojs/viewarticle.php?id=1109&layout=abstract
dcterms:description
We study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives. Given an MDP with k limit-average functions, in the expectation objective the goal is to maximize the expected limit-average value, and in the satisfaction objective the goal is to maximize the probability of runs such that the limit-average value stays above a given vector. We show that under the expectation objective, in contrast to the case of one limit-average function, both randomization and memory are necessary for strategies even for epsilon-approximation, and that finite-memory randomized strategies are sufficient for achieving Pareto optimal values. Under the satisfaction objective, in contrast to the case of one limit-average function, infinite memory is necessary for strategies achieving a specific value (i.e. We study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives. Given an MDP with k limit-average functions, in the expectation objective the goal is to maximize the expected limit-average value, and in the satisfaction objective the goal is to maximize the probability of runs such that the limit-average value stays above a given vector. We show that under the expectation objective, in contrast to the case of one limit-average function, both randomization and memory are necessary for strategies even for epsilon-approximation, and that finite-memory randomized strategies are sufficient for achieving Pareto optimal values. Under the satisfaction objective, in contrast to the case of one limit-average function, infinite memory is necessary for strategies achieving a specific value (i.e.
dcterms:title
Markov Decision Processes with Multiple Long-Run Average Objectives Markov Decision Processes with Multiple Long-Run Average Objectives
skos:prefLabel
Markov Decision Processes with Multiple Long-Run Average Objectives Markov Decision Processes with Multiple Long-Run Average Objectives
skos:notation
RIV/00216224:14330/14:00074494!RIV15-GA0-14330___
n3:aktivita
n17:P
n3:aktivity
P(GPP202/12/P612)
n3:cisloPeriodika
1
n3:dodaniDat
n12:2015
n3:domaciTvurceVysledku
n11:1762834 n11:9872655 n11:5532787 n11:2477912
n3:druhVysledku
n18:J
n3:duvernostUdaju
n14:S
n3:entitaPredkladatele
n8:predkladatel
n3:idSjednocenehoVysledku
27459
n3:idVysledku
RIV/00216224:14330/14:00074494
n3:jazykVysledku
n20:eng
n3:klicovaSlova
Markov decision processes; mean-payoff reward; multi-objective optimisation; formal verification
n3:klicoveSlovo
n9:multi-objective%20optimisation n9:Markov%20decision%20processes n9:formal%20verification n9:mean-payoff%20reward
n3:kodStatuVydavatele
DE - Spolková republika Německo
n3:kontrolniKodProRIV
[805E257BDA96]
n3:nazevZdroje
Logical Methods in Computer Science
n3:obor
n13:IN
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
5
n3:projekt
n19:GPP202%2F12%2FP612
n3:rokUplatneniVysledku
n12:2014
n3:svazekPeriodika
10
n3:tvurceVysledku
Kučera, Antonín Brožek, Václav Brázdil, Tomáš Forejt, Vojtěch Chatterjee, Krishnendu
n3:wos
000333744700001
s:issn
1860-5974
s:numberOfPages
29
n15:doi
10.2168/LMCS-10(1:13)2014
n4:organizacniJednotka
14330