{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Gaming Tech Brief By HackerNoon","title":"A Consensus-Based Algorithm for Non-Convex Multiplayer Games: Quantitative Laplace principle","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/fa3432c2\"></iframe>","width":"100%","height":180,"duration":70,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/a-consensus-based-algorithm-for-non-convex-multiplayer-games-quantitative-laplace-principle.\n             A novel algorithm using swarm intelligence to find global Nash equilibria in nonconvex multiplayer games, with convergence guarantees and numerical experiments. \n            Check more stories related to gaming at: https://hackernoon.com/c/gaming.\n            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.\n            \n            \n            This story was written by: @oligopoly. Learn more about this writer by checking @oligopoly's about page,\n            and for more stories, please visit hackernoon.com.\n            \n                \n                \n                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.\n        \n        ","thumbnail_url":"https://img.transistorcdn.com/BfMc-ZovSv4rGmZkeFGyHIHwikXuq6NLDmb3tagtH1I/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjcxLzE2ODMz/MTY1MTItYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}