A Consensus-Based Algorithm for Non-Convex Multiplayer Games: Quantitative Laplace principle - podcast episode cover

A Consensus-Based Algorithm for Non-Convex Multiplayer Games: Quantitative Laplace principle

Jul 29, 20241 min
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Episode description

This story was originally published on HackerNoon at: https://hackernoon.com/a-consensus-based-algorithm-for-non-convex-multiplayer-games-quantitative-laplace-principle.
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, #zeroth-order-algorithm, #nonconvex-multiplayer-games, #global-nash-equilibria, #swarm-intelligence, #metaheuristics, #numerical-experiments, 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.

This paper is available on arxiv.org/abs/2311.08270 under CC BY 4.0 DEED license. Authors: Enis Chenchene, Hui Huang, Jinniao Qiu, and Hui Chen. Table of Links: 1. Introduction, 2. Global convergence, 3. Numerical experiments, 4. Conclusion, Acknowledgments, and References.

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