# Rates of convergence for the policy iteration method for Mean Field Games systems

arXiv: https://arxiv.org/abs/2108.00755 · HTML: https://mlsanity.com/paper/2108.00755/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Aug 2021.

## Built on by (most cited first, 2 of 2)

- [Mean Field LQG Social Optimization: A Reinforcement Learning Approach](https://mlsanity.com/paper/2410.15119/) (2024)
- [Rates of Convergence in Certain Native Spaces of Approximations used in Reinforcement Learning](https://mlsanity.com/paper/2309.07383/) (2023)

## Abstract (arXiv)

Convergence of the policy iteration method for discrete and continuous optimal control problems holds under general assumptions. Moreover, in some circumstances, it is also possible to show a quadratic rate of convergence for the algorithm. For Mean Field Games, convergence of the policy iteration method has been recently proved in [9]. Here, we provide an estimate of its rate of convergence.