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

Written by oligopoly | Published 2024/07/28
Tech Story Tags: games | consensus-based-optimization | zeroth-order-algorithm | nonconvex-multiplayer-games | global-nash-equilibria | swarm-intelligence | metaheuristics | numerical-experiments

TLDRThis 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.via the TL;DR App

Table of Links

Abstract and 1 Introduction

2 Global convergence

2.1 Quantitative Laplace principle

2.2 Global convergence in mean-field law

3 Numerical experiments and 3.1 One-dimensional illustrative example

3.2 Nonlinear oligopoly games with several goods

4 Conclusion, Acknowledgments, Appendix, and References

2.1 Quantitative Laplace principle

This paper is available on arxiv under CC BY 4.0 DEED license.

Authors:

(1) Enis Chenchene, Department of Mathematics and Scientific Computing, University of Graz;

(2) Hui Huang, Department of Mathematics and Scientific Computing, University of Graz;

(3) Jinniao Qiu, Department of Mathematics and Statistics, University of Calgary.


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Published by HackerNoon on 2024/07/28