{"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: Nonlinear Oligopoly Games","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/a9616efe\"></iframe>","width":"100%","height":180,"duration":137,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/a-consensus-based-algorithm-for-non-convex-multiplayer-games-nonlinear-oligopoly-games.\nA novel algorithm using swarm intelligence to find global Nash equilibria in nonconvex multiplayer games, with convergence guarantees and numerical experiments.\nCheck more stories related to gaming at: https://hackernoon.com/c/gaming.\n            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.\nThis 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.\nThe 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.","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}