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Finding the Strong Nash Equilibrium: Computation, Existence and Characterization for Markov Games

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  • Julio B. Clempner

    (National Polytechnic Institute)

  • Alexander S. Poznyak

    (Center for Research and Advanced Studies)

Abstract

This paper suggests a procedure to construct the Pareto frontier and efficiently computes the strong Nash equilibrium for a class of time-discrete ergodic controllable Markov chain games. The procedure finds the strong Nash equilibrium, using the Newton optimization method presenting a potential advantage for ill-conditioned problems. We formulate the solution of the problem based on the Lagrange principle, adding a Tikhonov’s regularization parameter for ensuring both the strict convexity of the Pareto frontier and the existence of a unique strong Nash equilibrium. Then, any welfare optimum arises as a strong Nash equilibrium of the game. We prove the existence and characterization of the strong Nash equilibrium, which is one of the main results of this paper. The method is validated theoretically and illustrated with an application example.

Suggested Citation

  • Julio B. Clempner & Alexander S. Poznyak, 2020. "Finding the Strong Nash Equilibrium: Computation, Existence and Characterization for Markov Games," Journal of Optimization Theory and Applications, Springer, vol. 186(3), pages 1029-1052, September.
    • Handle: RePEc:spr:joptap:v:186:y:2020:i:3:d:10.1007_s10957-020-01729-3
    DOI: 10.1007/s10957-020-01729-3
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    References listed on IDEAS

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    3. Clempner, Julio B. & Poznyak, Alexander S., 2016. "Solving the Pareto front for multiobjective Markov chains using the minimum Euclidean distance gradient-based optimization method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 142-160.
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    7. Clempner, Julio B. & Poznyak, Alexander S., 2015. "Computing the strong Nash equilibrium for Markov chains games," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 911-927.
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    Cited by:

    1. Julio B. Clempner, 2021. "A Proximal/Gradient Approach for Computing the Nash Equilibrium in Controllable Markov Games," Journal of Optimization Theory and Applications, Springer, vol. 188(3), pages 847-862, March.
    2. Julio B. Clempner, 2023. "A Dynamic Mechanism Design for Controllable and Ergodic Markov Games," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1151-1171, March.
    3. Julio B. Clempner & Alexander S. Poznyak, 2021. "Analytical Method for Mechanism Design in Partially Observable Markov Games," Mathematics, MDPI, vol. 9(4), pages 1-15, February.

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