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A Consensus-Based Algorithm for Non-Convex Multiplayer Games: Nonlinear Oligopoly Games
Manage episode 428397116 series 3474369
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This story was originally published on HackerNoon at: https://hackernoon.com/a-consensus-based-algorithm-for-non-convex-multiplayer-games-nonlinear-oligopoly-games.
A novel algorithm using swarm intelligence to find global Nash equilibria in nonconvex multiplayer games, with convergence guarantees and numerical experiments.
Check more stories related to gaming at: https://hackernoon.com/c/gaming. You can also check exclusive content about #games, #consensus-based-optimization, #numerical-experiments, #zeroth-order-algorithm, #nonconvex-multiplayer-games, #global-nash-equilibria, #metaheuristics, #mean-field-convergence, and more.
This story was written by: @oligopoly. Learn more about this writer by checking @oligopoly's about page, and for more stories, please visit hackernoon.com.
The study was conducted by Enis Chenchene, Hui Huang, Jinniao Qiu and Hui Chen. They studied the dependence of Algorithm 1 with respect to the algorithm’s parameters to solve (3.5) of good produced. They found no significant differences in the convergence behavior of anisotropic or isotropic dynamics.
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