This Paper explores a new non-linear programming approach for determining mixed strategies in non-zero-sum games. Our approach leverages the power of non-linear optimization algorithms to solve the mixed strategy determination problem efficiently. We formulate the problem as a non-linear programming model, considering the individual player’s utility functions and the strategic interdependencies among them. The proposed approach offers accurately represents strategic interactions by incorporating non-linear objective functions and constraints. The proposed non-linear programming technique offers several advantages for solving game theory problems. Firstly, it enables the consideration of complex and nonlinear relationships among players' strategies, allowing for more realistic and nuanced modeling. Secondly, the technique offers flexibility in incorporating various types of constraints, including capacity limitations, budget constraints, or regulatory requirements, enhancing the applicability to real-world scenarios. Lastly, NLP algorithms provide efficient and robust optimization procedures, ensuring reliable solutions within reasonable time frames. We use MATLAB to solve the Non-Linear programming problem which gives us more accurate results. To demonstrate the effectiveness of the proposed technique, it can be applied to diverse game theory problems, such as auctions, bargaining, pricing decisions, and resource allocation. The results obtained through this approach offer insights into optimal strategies, equilibrium outcomes, and potential trade-offs, facilitating informed decision-making in strategic environments.
| Published in | International Journal of Systems Science and Applied Mathematics (Volume 8, Issue 2) |
| DOI | 10.11648/j.ijssam.20230802.11 |
| Page(s) | 17-22 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Equilibrium Concepts, Strategic Interactions, Nash Equilibrium, Pareto Optimal, Dominant Strategy, Mixed Strategy, Payoff Matrix, Saddle Point
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APA Style
Md. Golam Robbani, Md. Asadujjaman, Md. Mehedi Hassan. (2023). A Proposed New Non-Linear Programming Technique for Solving a Mixed Strategy Problem in Game Theory. International Journal of Systems Science and Applied Mathematics, 8(2), 17-22. https://doi.org/10.11648/j.ijssam.20230802.11
ACS Style
Md. Golam Robbani; Md. Asadujjaman; Md. Mehedi Hassan. A Proposed New Non-Linear Programming Technique for Solving a Mixed Strategy Problem in Game Theory. Int. J. Syst. Sci. Appl. Math. 2023, 8(2), 17-22. doi: 10.11648/j.ijssam.20230802.11
AMA Style
Md. Golam Robbani, Md. Asadujjaman, Md. Mehedi Hassan. A Proposed New Non-Linear Programming Technique for Solving a Mixed Strategy Problem in Game Theory. Int J Syst Sci Appl Math. 2023;8(2):17-22. doi: 10.11648/j.ijssam.20230802.11
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Download@article{10.11648/j.ijssam.20230802.11,
author = {Md. Golam Robbani and Md. Asadujjaman and Md. Mehedi Hassan},
title = {A Proposed New Non-Linear Programming Technique for Solving a Mixed Strategy Problem in Game Theory},
journal = {International Journal of Systems Science and Applied Mathematics},
volume = {8},
number = {2},
pages = {17-22},
doi = {10.11648/j.ijssam.20230802.11},
url = {https://doi.org/10.11648/j.ijssam.20230802.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssam.20230802.11},
abstract = {This Paper explores a new non-linear programming approach for determining mixed strategies in non-zero-sum games. Our approach leverages the power of non-linear optimization algorithms to solve the mixed strategy determination problem efficiently. We formulate the problem as a non-linear programming model, considering the individual player’s utility functions and the strategic interdependencies among them. The proposed approach offers accurately represents strategic interactions by incorporating non-linear objective functions and constraints. The proposed non-linear programming technique offers several advantages for solving game theory problems. Firstly, it enables the consideration of complex and nonlinear relationships among players' strategies, allowing for more realistic and nuanced modeling. Secondly, the technique offers flexibility in incorporating various types of constraints, including capacity limitations, budget constraints, or regulatory requirements, enhancing the applicability to real-world scenarios. Lastly, NLP algorithms provide efficient and robust optimization procedures, ensuring reliable solutions within reasonable time frames. We use MATLAB to solve the Non-Linear programming problem which gives us more accurate results. To demonstrate the effectiveness of the proposed technique, it can be applied to diverse game theory problems, such as auctions, bargaining, pricing decisions, and resource allocation. The results obtained through this approach offer insights into optimal strategies, equilibrium outcomes, and potential trade-offs, facilitating informed decision-making in strategic environments.},
year = {2023}
}
TY - JOUR T1 - A Proposed New Non-Linear Programming Technique for Solving a Mixed Strategy Problem in Game Theory AU - Md. Golam Robbani AU - Md. Asadujjaman AU - Md. Mehedi Hassan Y1 - 2023/07/31 PY - 2023 N1 - https://doi.org/10.11648/j.ijssam.20230802.11 DO - 10.11648/j.ijssam.20230802.11 T2 - International Journal of Systems Science and Applied Mathematics JF - International Journal of Systems Science and Applied Mathematics JO - International Journal of Systems Science and Applied Mathematics SP - 17 EP - 22 PB - Science Publishing Group SN - 2575-5803 UR - https://doi.org/10.11648/j.ijssam.20230802.11 AB - This Paper explores a new non-linear programming approach for determining mixed strategies in non-zero-sum games. Our approach leverages the power of non-linear optimization algorithms to solve the mixed strategy determination problem efficiently. We formulate the problem as a non-linear programming model, considering the individual player’s utility functions and the strategic interdependencies among them. The proposed approach offers accurately represents strategic interactions by incorporating non-linear objective functions and constraints. The proposed non-linear programming technique offers several advantages for solving game theory problems. Firstly, it enables the consideration of complex and nonlinear relationships among players' strategies, allowing for more realistic and nuanced modeling. Secondly, the technique offers flexibility in incorporating various types of constraints, including capacity limitations, budget constraints, or regulatory requirements, enhancing the applicability to real-world scenarios. Lastly, NLP algorithms provide efficient and robust optimization procedures, ensuring reliable solutions within reasonable time frames. We use MATLAB to solve the Non-Linear programming problem which gives us more accurate results. To demonstrate the effectiveness of the proposed technique, it can be applied to diverse game theory problems, such as auctions, bargaining, pricing decisions, and resource allocation. The results obtained through this approach offer insights into optimal strategies, equilibrium outcomes, and potential trade-offs, facilitating informed decision-making in strategic environments. VL - 8 IS - 2 ER -
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