The presentation of the application of game theory to historical events
DOI:
https://doi.org/10.31181/jdaic10011122024iKeywords:
Game theory, Conflict situations, Nash equilibrium, Pareto optimalityAbstract
The modern world is characterized by a multitude of problems that contain conflicts of different interests. The importance and frequency of the problem caused the need to develop techniques for managing conflict situations. Accordingly, game theory has developed as a special direction and methodology used in the study, analysis and resolution of conflict situations. This theoretical direction deals with the phenomenon of making rational decisions in conflict situations and is considered a specific type of mathematical analysis of conflicts. It is a mathematical discipline that deals with the formalization of the decision-making process in situations where multiple decision-making subjects participate, who have conflicting interests. Each of the opposing sides has several strategies at their disposal. The goal is to determine the strategy that is best for each side in a conflict situation. The use of game theory provides a clearer representation of possible alternative solutions to a conflict situation. The paper shows the application of game theory to certain historical events. Through the petition payment matrix, solutions to the Battle of the Bismarck Sea, the Cuban Missile Crisis and the arms race are possible. It should be noted that for the analysis of a mathematical model, game theory requires quantifying and measuring something that is immeasurable, such as motives, outcomes, preferences, etc., when it comes to different (some) conflict situations. During the selection of the strategy, only the most important decision-making factors are included in the consideration, and the others are neglected, which can lead to the absence of a wider picture that could influence the final choice of strategy. Game theory is widely applicable, but the high degree of abstraction greatly limits its practical value.
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References
Abid, M., & Saqlain, M. (2024). Optimizing Diabetes Data Insights Through Kmapper-Based Topological Networks: A Decision Analytics Approach for Predictive and Prescriptive Modeling. Management Science Advances, 1(1), 1-19.
Biswas, A., Gazi, K. H., & Mondal, S. P. (2024). Finding Effective Factor for Circular Economy Using Uncertain MCDM Approach. Management Science Advances, 1(1), 31-52.
Božanić, D., Pamučar, D., & Komazec, N. (2023). Applying D numbers in risk assessment process: General approach. Journal of Decision Analytics and Intelligent Computing, 3(1), 286–295.
Coser, L. (1956). The Functions of Social Conflict. New York – London: The Free Press - Cothier-Macmillan Limited.
Čupić, M., & Tummala, R. (1991). Modern decision-making – Methods and Application (Only on Serbian: Savremeno odlučivanje – metode i primena). Belgrade: Naučna knjiga.
Djebara, S., Achemine, F., & Larbani, M. (2024). Solving Constrained Matrix Games With Fuzzy Random Linear Constraints. Yugoslav Journal of Operations Research, Online first. https://doi.org/10.2298/YJOR231122013D.
Doğan, E., Esmerok, İ.B. (2024). An egalitarian solution to minimum cost spanning tree problems. International journal of Game Theory, 53(1), 127–141.
Ivetic, Z., & Tosic, J. (2024). Application of game theory in resolving conflict situations. In Proceedings of the 10th International Scientific-Professional Conference - Security and Crisis Management - Theory and Practice (SeCMan), International Forum “Safety for the Future” 2024 (pp. 82-88). Belgrade: Regional Association for Security and Crisis Management & S4 GLOSEC Global Security.
Jangid, V., & Kumar, D. (2022). A Novel Technique for Solving Two-Person Zero-Sum Matrix Games in a Rough Fuzzy Environment. Yugoslav Journal of Operations Research, 32(2), 251-278.
Kapor, P. (2017). Game theory: The system approach and development. Megatrend Review, 14(1), 253-282.
Nash, J. (1951). Non-Cooperative Games. Annals of Mathematics, 54(2), 286–295.
Neumann, J., & Morgenstern, O. (1953). Theory of games and economic behavior. Princeton: Princeton University Press.
Nikolić, M. (2012). Decision-making methods (Only in Serbian: Metode odlučivanja). Zrenjanin: Technical Faculty "Mihajlo Pupin", University of Novi Sad.
Pavličić, D. (2010). Decision theory (Only in Serbian: Teorija odlučivanja). Belgrade: Faculty of Economics and Business.
Pavlović, D. (2015). Game theory: Basic games and application (Only in Serbian: Teorija odlučivanja: Osnovne igre I primena). Belgrade: Faculty of political scientist.
Sahoo, S. K., Choudhury, B. B., & Dhal, P. R. (2024). A Bibliometric Analysis of Material Selection Using MCDM Methods: Trends and Insights. Spectrum of Mechanical Engineering and Operational Research, 1(1), 189-205.
Shimoji, M. (2022). Bayesian persuasion in unlinked games. International journal of Game Theory, 51(3-4), 451–481.
Stojanović, B. (2005). Game theory: Elements and Application (Only on Serbian: Teorija igara: elementi i primena). Belgrade: Institute of European Studies.
Sweeney, P. (2020). The Battle of the Bismarck Sea. United Service, 71(4), 8-11.
Tadić, D., Suknović, M., Radojević, G., & Jovanović, V. (2005). Operational research (Only on Serbian: Operaciona istraživanja). Kruševac: School of Engineering Management.
Vignjević M. (2024). Game model in the geostrategic rivalry of Greece and Turkey. Politička revija. 80(2), 35-62.
Zhijan, W., Shujie, Z., Qinmei, Y., Yijia, W., & Gang, P. (2022). Dynamic Structure in a Four-strategy Game: Theory and Experiment. Contribution to game theory and management, 15, 365-385.
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