A Consensus-Based Algorithm for Non-Convex Multiplayer Games: Nonlinear Oligopoly Games

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.

What is Gaming Tech Brief By HackerNoon?

Learn the latest gaming updates in the tech world.