Bibliographic Details
| Title: |
A Consensus-based Algorithm for Non-convex Multiplayer Games. |
| Authors: |
Chenchene, Enis1 (AUTHOR) enis.chenchene@univie.ac.at, Huang, Hui2 (AUTHOR) hui.huang@uni-graz.at, Qiu, Jinniao3 (AUTHOR) jinniao.qiu@ucalgary.ca |
| Source: |
Journal of Optimization Theory & Applications. Aug2025, Vol. 206 Issue 2, p1-30. 30p. |
| Abstract: |
In this paper, we present a novel consensus-based zeroth-order algorithm tailored for non-convex multiplayer games. The proposed method leverages a metaheuristic approach using concepts from swarm intelligence to reliably identify global Nash equilibria. We utilize a group of interacting particles, each agreeing on a specific consensus point, asymptotically converging to the corresponding optimal strategy. This paradigm permits a passage to the mean-field limit, allowing us to establish convergence guarantees under appropriate assumptions regarding initialization and objective functions. Finally, we conduct a series of numerical experiments to unveil the dependency of the proposed method on its parameters and apply it to solve a nonlinear Cournot oligopoly game involving multiple goods. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
