Matrix norm based hybrid Shapley and iterative methods for the solution of stochastic matrix games

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dc.authoridÖzkaya, Murat / 0000-0001-7241-4710
dc.contributor.authorİzgi, Burhaneddin
dc.contributor.authorÖzkaya, Murat
dc.contributor.authorÜre, Nazım Kemal
dc.contributor.authorPerc, Matjaz
dc.date.accessioned2025-01-27T21:13:02Z
dc.date.available2025-01-27T21:13:02Z
dc.date.issued2024
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractIn this paper, we present four alternative solution methods to Shapley iteration for the solution of stochastic matrix games. We first combine the extended matrix norm method for stochastic matrix games with Shapley iteration and then state and prove the weak and strong hybrid versions of Shapley iterations. Then, we present the semi-extended matrix norm and iterative semi-extended matrix norm methods, which are analytic-solution-free methods, for finding the approximate solution of stochastic matrix games without determining the strategy sets. We illustrate comparisons between the Shapley iteration, weak and strong hybrid Shapley iterations, semi-extended matrix norm method, and iterative semi-extended matrix norm method with several examples. The results reveal that the strong and weak hybrid Shapley iterations improve the Shapley iteration and decrease the number of iterations, and the strong hybrid Shapley iteration outperforms all the other proposed methods. Finally, we compare these methods and present their performance analyses for large-scale stochastic matrix games as well.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (in Turkish: TUBITAK) [121E394]; Slovenian Research Agency [P1-0403, J1-2457]
dc.description.sponsorshipThis work is supported by the Scientific and Technological Research Council of Turkey (in Turkish: TUBITAK) under grant agreement 121E394. M.P. is supported by the Slovenian Research Agency (Grant Nos. P1-0403 and J1-2457) . The authors would like to thank the anonymous referees and the editor for their valuable suggestions and comments that helped to improve the content of the article.
dc.identifier.doi10.1016/j.amc.2024.128638
dc.identifier.issn0096-3003
dc.identifier.issn1873-5649
dc.identifier.scopus2-s2.0-85188051691
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.amc.2024.128638
dc.identifier.urihttps://hdl.handle.net/20.500.12428/28255
dc.identifier.volume473
dc.identifier.wosWOS:001216832100001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Science Inc
dc.relation.ispartofApplied Mathematics and Computation
dc.relation.publicationcategoryinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20250125
dc.subjectGame theory
dc.subjectStochastic games
dc.subjectMatrix games
dc.subjectShapley iteration
dc.subjectEMN method
dc.titleMatrix norm based hybrid Shapley and iterative methods for the solution of stochastic matrix games
dc.typeArticle

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