Policy Gradient Methods Find the Nash Equilibrium in N-player General-sum Linear-quadratic Games
Optimization and Control
2022-08-16 v2 Computer Science and Game Theory
Machine Learning
Machine Learning
Abstract
We consider a general-sum N-player linear-quadratic game with stochastic dynamics over a finite horizon and prove the global convergence of the natural policy gradient method to the Nash equilibrium. In order to prove the convergence of the method, we require a certain amount of noise in the system. We give a condition, essentially a lower bound on the covariance of the noise in terms of the model parameters, in order to guarantee convergence. We illustrate our results with numerical experiments to show that even in situations where the policy gradient method may not converge in the deterministic setting, the addition of noise leads to convergence.
Keywords
Cite
@article{arxiv.2107.13090,
title = {Policy Gradient Methods Find the Nash Equilibrium in N-player General-sum Linear-quadratic Games},
author = {Ben Hambly and Renyuan Xu and Huining Yang},
journal= {arXiv preprint arXiv:2107.13090},
year = {2022}
}