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A Consensus-Based Algorithm for Non-Convex Multiplayer Games: Abstract and Introduction
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This story was originally published on HackerNoon at: https://hackernoon.com/a-consensus-based-algorithm-for-non-convex-multiplayer-games-abstract-and-introduction.
A novel algorithm using swarm intelligence to find global Nash equilibria in nonconvex multiplayer games, with convergence guarantees and numerical experiments.
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In this paper, we present a novel consensus-based zeroth-order algorithm tailored for nonconvex multiplayer games. The proposed method leverages a metaheuristic approach using concepts from swarm intelligence to reliably identify global Nash equilibria. We utilize a group of interacting particles, each agreeing on a specific consensus point, asymptotically converging to the corresponding optimal strategy.
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