Research Article
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A Mutual-Grand Strategy Modeling of the Russia-Ukraine War 2022: Balancing the Unbalanced

Year 2023, Volume: 5 Issue: 1, 19 - 72, 01.05.2023
https://doi.org/10.53451/ijps.1174300

Abstract

In this research paper, we seek to strategize the Russian-Ukrainian War 2022 based on a game theory and hypergame theory perspective. Setting the most optimal strategies described and prescribed for each conflicting party is the main objective of this Mutual-Grand Strategy Modeling. At the core, theorizing the actual war situation through four waves predicting this war multiple possibilities and explaining the grand strategy made by each side reflects the manner under which the rationality argument and utility assumptions of a (hyper)game theory situation exist. Meaningfully, a rational player picks those moves that (are perceived correctly or incorrectly to) contribute to raising its payoffs in the conflict while reasoning about the opponent’s best strategies and outcomes. By applying our developed balance of deterrence rules and the related equilibria, the war can be terminated by each wave’s end in either a theoretic-strategic diplomatic way, military victory, or both.

Supporting Institution

Sakarya University, Social Sciences Institute, International Relations Department; Turkey

Project Number

Doctorate Project. Ph.D. Student Number: D176007007

Thanks

My acknowledgment and thanks to my Ph.D. dissertation supervisor, Prof. Dr. Ertan Efegil, International Relations Department, Sakarya University.

References

  • Brown, David, Bella Hurrell, Dominic Bailey, Mike Hills, Lucy Rodgers, Paul Sargeant, Mark Bryson, Zoe Bartholomew, Sean Willmott, Sana Dionysiou, Joy Roxas, Gerry Fletcher, Jana Tauschinsk, Debie Loizou, and Prina Shah. “Ukraine War in Maps: Tracking the Russian Invasion.” BBC News. April 4, 2022. https://www.bbc.com/news/world-europe-60506682.

A Mutual-Grand Strategy Modeling of the Russia-Ukraine War 2022: Balancing the Unbalanced

Year 2023, Volume: 5 Issue: 1, 19 - 72, 01.05.2023
https://doi.org/10.53451/ijps.1174300

Abstract

In this research paper, we seek to strategize the Russian-Ukrainian War 2022 based on a game theory and hypergame theory perspective. Setting the most optimal strategies described and prescribed for each conflicting party is the main objective of this Mutual-Grand Strategy Modeling. At the core, theorizing the actual war situation through four waves predicting this war multiple possibilities and explaining the grand strategy made by each side reflects the manner under which the rationality argument and utility assumptions of a (hyper)game theory situation exist. Meaningfully, a rational player picks those moves that (are perceived correctly or incorrectly to) contribute to raising its payoffs in the conflict while reasoning about the opponent’s best strategies and outcomes. By applying our developed balance of deterrence rules and the related equilibria, the war can be terminated by each wave’s end in either a theoretic-strategic diplomatic way, military victory, or both.

Project Number

Doctorate Project. Ph.D. Student Number: D176007007

References

  • Brown, David, Bella Hurrell, Dominic Bailey, Mike Hills, Lucy Rodgers, Paul Sargeant, Mark Bryson, Zoe Bartholomew, Sean Willmott, Sana Dionysiou, Joy Roxas, Gerry Fletcher, Jana Tauschinsk, Debie Loizou, and Prina Shah. “Ukraine War in Maps: Tracking the Russian Invasion.” BBC News. April 4, 2022. https://www.bbc.com/news/world-europe-60506682.
There are 1 citations in total.

Details

Primary Language English
Subjects International Relations
Journal Section Articles
Authors

Mariam Ariba 0000-0001-5052-3924

Project Number Doctorate Project. Ph.D. Student Number: D176007007
Early Pub Date April 14, 2023
Publication Date May 1, 2023
Submission Date September 12, 2022
Acceptance Date February 11, 2023
Published in Issue Year 2023 Volume: 5 Issue: 1

Cite

Chicago Ariba, Mariam. “A Mutual-Grand Strategy Modeling of the Russia-Ukraine War 2022: Balancing the Unbalanced”. International Journal of Politics and Security 5, no. 1 (May 2023): 19-72. https://doi.org/10.53451/ijps.1174300.

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