Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted Case

Autores
Vecchia, Eugenio Della; Di Marco, Silvia; Jean-Marie, Alain
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
We study the behavior of the rolling horizon procedure for semi-Markov decision processes, with infinite-horizon discounted reward, when the state space is a Borel set and the action spaces are considered compact. We prove the convergence of the rewards produced by the rolling horizon policies to the optimal reward function, when the horizon length tends to infinity, under different assumptions on the instantaneous reward function. The approach is based on extensions of the results obtained in [7] for the discrete-time Markov decision process case and in [3] for the case of discrete-time Markov games. Finally, we also analyse the performance of an approximate rolling horizon procedure.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Semi-Markov decision processes
Rolling horizon
Discounted criterion
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/139314
Acceder
id SEDICI_0107b587db019838740404f39796e722
oai_identifier_str oai:sedici.unlp.edu.ar:10915/139314
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted CaseVecchia, Eugenio DellaDi Marco, SilviaJean-Marie, AlainCiencias InformáticasSemi-Markov decision processesRolling horizonDiscounted criterionWe study the behavior of the rolling horizon procedure for semi-Markov decision processes, with infinite-horizon discounted reward, when the state space is a Borel set and the action spaces are considered compact. We prove the convergence of the rewards produced by the rolling horizon policies to the optimal reward function, when the horizon length tends to infinity, under different assumptions on the instantaneous reward function. The approach is based on extensions of the results obtained in [7] for the discrete-time Markov decision process case and in [3] for the case of discrete-time Markov games. Finally, we also analyse the performance of an approximate rolling horizon procedure.Sociedad Argentina de Informática e Investigación Operativa2011-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf25-37http://sedici.unlp.edu.ar/handle/10915/139314enginfo:eu-repo/semantics/altIdentifier/url/https://40jaiio.sadio.org.ar/sites/default/files/T2011/SIO/701.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2865info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:27:12Zoai:sedici.unlp.edu.ar:10915/139314Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:27:12.759SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted Case
title Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted Case
spellingShingle Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted Case
Vecchia, Eugenio Della
Ciencias Informáticas
Semi-Markov decision processes
Rolling horizon
Discounted criterion
title_short Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted Case
title_full Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted Case
title_fullStr Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted Case
title_full_unstemmed Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted Case
title_sort Rolling Horizon Procedure on Controlled Semi-Markov Models. The Discounted Case
dc.creator.none.fl_str_mv Vecchia, Eugenio Della
Di Marco, Silvia
Jean-Marie, Alain
author Vecchia, Eugenio Della
author_facet Vecchia, Eugenio Della
Di Marco, Silvia
Jean-Marie, Alain
author_role author
author2 Di Marco, Silvia
Jean-Marie, Alain
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Semi-Markov decision processes
Rolling horizon
Discounted criterion
topic Ciencias Informáticas
Semi-Markov decision processes
Rolling horizon
Discounted criterion
dc.description.none.fl_txt_mv We study the behavior of the rolling horizon procedure for semi-Markov decision processes, with infinite-horizon discounted reward, when the state space is a Borel set and the action spaces are considered compact. We prove the convergence of the rewards produced by the rolling horizon policies to the optimal reward function, when the horizon length tends to infinity, under different assumptions on the instantaneous reward function. The approach is based on extensions of the results obtained in [7] for the discrete-time Markov decision process case and in [3] for the case of discrete-time Markov games. Finally, we also analyse the performance of an approximate rolling horizon procedure.
Sociedad Argentina de Informática e Investigación Operativa
description We study the behavior of the rolling horizon procedure for semi-Markov decision processes, with infinite-horizon discounted reward, when the state space is a Borel set and the action spaces are considered compact. We prove the convergence of the rewards produced by the rolling horizon policies to the optimal reward function, when the horizon length tends to infinity, under different assumptions on the instantaneous reward function. The approach is based on extensions of the results obtained in [7] for the discrete-time Markov decision process case and in [3] for the case of discrete-time Markov games. Finally, we also analyse the performance of an approximate rolling horizon procedure.
publishDate 2011
dc.date.none.fl_str_mv 2011-08
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/139314
url http://sedici.unlp.edu.ar/handle/10915/139314
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://40jaiio.sadio.org.ar/sites/default/files/T2011/SIO/701.pdf
info:eu-repo/semantics/altIdentifier/issn/1850-2865
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
25-37
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1846064319412830208
score 13.22299

Publicaciones similares