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
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/280735
Ver los metadatos del registro completo
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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. |
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2025 |
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2025-01 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
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publishedVersion |
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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 |
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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 |
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eng |
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eng |
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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 |
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openAccess |
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https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
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application/pdf application/pdf application/pdf |
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Academic Press Inc Elsevier Science |
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Academic Press Inc Elsevier Science |
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reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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