Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games

Autores
Allamigeon, Xavier; Gaubert, Stéphane; Katz, Ricardo David; Skomra, Mateusz
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to a given precision. We show that the number of calls to the oracle needed to determine exact optimal (positional) strategies is, up to a factor polynomial in the dimension, of order R/sep, where the “separation” sep is defined as the minimal difference between distinct values arising from strategies, and R is a metric estimate, involving the norm of approximate sub and super-eigenvectors of the dynamic programming operator. We illustrate this method by two applications. The first one is a new proof, leading to improved complexity estimates, of a theorem of Boros, Elbassioni, Gurvich and Makino, showing that turn-based mean-payoff games with a fixed number of random positions can be solved in pseudo-polynomial time. The second one concerns entropy games, a model introduced by Asarin, Cervelle, Degorre, Dima, Horn and Kozyakin. The rank of an entropy game is defined as the maximal rank among all the ambiguity matrices determined by strategies of the two players. We show that entropy games with a fixed rank, in their original formulation, can be solved in polynomial time, and that an extension of entropy games incorporating weights can be solved in pseudo-polynomial time under the same fixed rank condition.
Fil: Allamigeon, Xavier. Institut National de Recherche en Informatique et en Automatique; Francia
Fil: Gaubert, Stéphane. Institut National de Recherche en Informatique et en Automatique; Francia
Fil: Katz, Ricardo David. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Skomra, Mateusz. Centre National de la Recherche Scientifique; Francia
Materia
MEAN-PAYOFF GAMES
ENTROPY GAMES
VALUE ITERATION
PERRON ROOT
SEPARATION BOUNDS
PARAMATERiZED COMPLEXITY
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/280735

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network_name_str CONICET Digital (CONICET)
spelling Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy gamesAllamigeon, XavierGaubert, StéphaneKatz, Ricardo DavidSkomra, MateuszMEAN-PAYOFF GAMESENTROPY GAMESVALUE ITERATIONPERRON ROOTSEPARATION BOUNDSPARAMATERiZED COMPLEXITYhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to a given precision. We show that the number of calls to the oracle needed to determine exact optimal (positional) strategies is, up to a factor polynomial in the dimension, of order R/sep, where the “separation” sep is defined as the minimal difference between distinct values arising from strategies, and R is a metric estimate, involving the norm of approximate sub and super-eigenvectors of the dynamic programming operator. We illustrate this method by two applications. The first one is a new proof, leading to improved complexity estimates, of a theorem of Boros, Elbassioni, Gurvich and Makino, showing that turn-based mean-payoff games with a fixed number of random positions can be solved in pseudo-polynomial time. The second one concerns entropy games, a model introduced by Asarin, Cervelle, Degorre, Dima, Horn and Kozyakin. The rank of an entropy game is defined as the maximal rank among all the ambiguity matrices determined by strategies of the two players. We show that entropy games with a fixed rank, in their original formulation, can be solved in polynomial time, and that an extension of entropy games incorporating weights can be solved in pseudo-polynomial time under the same fixed rank condition.Fil: Allamigeon, Xavier. Institut National de Recherche en Informatique et en Automatique; FranciaFil: Gaubert, Stéphane. Institut National de Recherche en Informatique et en Automatique; FranciaFil: Katz, Ricardo David. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Skomra, Mateusz. Centre National de la Recherche Scientifique; FranciaAcademic Press Inc Elsevier Science2025-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/280735Allamigeon, Xavier; Gaubert, Stéphane; Katz, Ricardo David; Skomra, Mateusz; Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games; Academic Press Inc Elsevier Science; Information and Computation; 302; 105236; 1-2025; 1-390890-5401CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0890540124001019info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ic.2024.105236info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/2206.09044info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-02-06T12:02:18Zoai:ri.conicet.gov.ar:11336/280735instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-02-06 12:02:19.145CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
title Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
spellingShingle Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
Allamigeon, Xavier
MEAN-PAYOFF GAMES
ENTROPY GAMES
VALUE ITERATION
PERRON ROOT
SEPARATION BOUNDS
PARAMATERiZED COMPLEXITY
title_short Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
title_full Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
title_fullStr Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
title_full_unstemmed Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
title_sort Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
dc.creator.none.fl_str_mv Allamigeon, Xavier
Gaubert, Stéphane
Katz, Ricardo David
Skomra, Mateusz
author Allamigeon, Xavier
author_facet Allamigeon, Xavier
Gaubert, Stéphane
Katz, Ricardo David
Skomra, Mateusz
author_role author
author2 Gaubert, Stéphane
Katz, Ricardo David
Skomra, Mateusz
author2_role author
author
author
dc.subject.none.fl_str_mv MEAN-PAYOFF GAMES
ENTROPY GAMES
VALUE ITERATION
PERRON ROOT
SEPARATION BOUNDS
PARAMATERiZED COMPLEXITY
topic MEAN-PAYOFF GAMES
ENTROPY GAMES
VALUE ITERATION
PERRON ROOT
SEPARATION BOUNDS
PARAMATERiZED COMPLEXITY
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to a given precision. We show that the number of calls to the oracle needed to determine exact optimal (positional) strategies is, up to a factor polynomial in the dimension, of order R/sep, where the “separation” sep is defined as the minimal difference between distinct values arising from strategies, and R is a metric estimate, involving the norm of approximate sub and super-eigenvectors of the dynamic programming operator. We illustrate this method by two applications. The first one is a new proof, leading to improved complexity estimates, of a theorem of Boros, Elbassioni, Gurvich and Makino, showing that turn-based mean-payoff games with a fixed number of random positions can be solved in pseudo-polynomial time. The second one concerns entropy games, a model introduced by Asarin, Cervelle, Degorre, Dima, Horn and Kozyakin. The rank of an entropy game is defined as the maximal rank among all the ambiguity matrices determined by strategies of the two players. We show that entropy games with a fixed rank, in their original formulation, can be solved in polynomial time, and that an extension of entropy games incorporating weights can be solved in pseudo-polynomial time under the same fixed rank condition.
Fil: Allamigeon, Xavier. Institut National de Recherche en Informatique et en Automatique; Francia
Fil: Gaubert, Stéphane. Institut National de Recherche en Informatique et en Automatique; Francia
Fil: Katz, Ricardo David. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Skomra, Mateusz. Centre National de la Recherche Scientifique; Francia
description We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to a given precision. We show that the number of calls to the oracle needed to determine exact optimal (positional) strategies is, up to a factor polynomial in the dimension, of order R/sep, where the “separation” sep is defined as the minimal difference between distinct values arising from strategies, and R is a metric estimate, involving the norm of approximate sub and super-eigenvectors of the dynamic programming operator. We illustrate this method by two applications. The first one is a new proof, leading to improved complexity estimates, of a theorem of Boros, Elbassioni, Gurvich and Makino, showing that turn-based mean-payoff games with a fixed number of random positions can be solved in pseudo-polynomial time. The second one concerns entropy games, a model introduced by Asarin, Cervelle, Degorre, Dima, Horn and Kozyakin. The rank of an entropy game is defined as the maximal rank among all the ambiguity matrices determined by strategies of the two players. We show that entropy games with a fixed rank, in their original formulation, can be solved in polynomial time, and that an extension of entropy games incorporating weights can be solved in pseudo-polynomial time under the same fixed rank condition.
publishDate 2025
dc.date.none.fl_str_mv 2025-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/280735
Allamigeon, Xavier; Gaubert, Stéphane; Katz, Ricardo David; Skomra, Mateusz; Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games; Academic Press Inc Elsevier Science; Information and Computation; 302; 105236; 1-2025; 1-39
0890-5401
CONICET Digital
CONICET
url http://hdl.handle.net/11336/280735
identifier_str_mv Allamigeon, Xavier; Gaubert, Stéphane; Katz, Ricardo David; Skomra, Mateusz; Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games; Academic Press Inc Elsevier Science; Information and Computation; 302; 105236; 1-2025; 1-39
0890-5401
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0890540124001019
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ic.2024.105236
info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/2206.09044
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Academic Press Inc Elsevier Science
publisher.none.fl_str_mv Academic Press Inc Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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