# Discrete-time approximation for stochastic optimal control problems under the G-expectation framework

arXiv: https://arxiv.org/abs/2104.02268 · HTML: https://mlsanity.com/paper/2104.02268/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Apr 2021.

## Built on by (most cited first, 1 of 1)

- [Neural operators approximate strongly continuous convex monotone semigroups](https://mlsanity.com/paper/2609.02727/) (2026)

## Abstract (arXiv)

In this paper, we propose a class of discrete-time approximation schemes for stochastic optimal control problems under the G-expectation framework. The proposed schemes are constructed recursively based on piecewise constant policy. We prove the convergence of the discrete schemes and determine the convergence rates. Several numerical examples are presented to illustrate the effectiveness of the obtained results.