This content originally appeared on HackerNoon and was authored by Oligopoly
:::info Authors:
(1) Enis Chenchene, Department of Mathematics and Scientific Computing, University of Graz;
(2) Hui Huang, Department of Mathematics and Scientific Computing, University of Graz;
(3) Jinniao Qiu, Department of Mathematics and Statistics, University of Calgary.
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Table of Links
2.1 Quantitative Laplace principle
2.2 Global convergence in mean-field law
3 Numerical experiments and 3.1 One-dimensional illustrative example
3.2 Nonlinear oligopoly games with several goods
4 Conclusion, Acknowledgments, Appendix, and References
3 Numerical experiments
In this section, we present our numerical experiments, which are performed in Python on a 12thGen. Intel(R) Core(TM) i7–1255U, 1.70–4.70 GHz laptop with 16 Gb of RAM and are available for reproducibility at https://github.com/echnen/CBO-multiplayer. As usual in CBO schemes, we discretize the interacting particle system in (1.2) with a Euler– Maruyama time discretization scheme [34], resulting in the method depicted in Algorithm 1.
3.1 One-dimensional illustrative example
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\ 3.1.1 Experimental setup
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\ 3.1.2 Results and discussion
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:::info This paper is available on arxiv under CC BY 4.0 DEED license.
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This content originally appeared on HackerNoon and was authored by Oligopoly
Oligopoly | Sciencx (2024-07-10T19:00:14+00:00) A Consensus-Based Algorithm for Non-Convex Multiplayer Games: Numerical Experiments. Retrieved from https://www.scien.cx/2024/07/10/a-consensus-based-algorithm-for-non-convex-multiplayer-games-numerical-experiments/
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