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.
翻译:在本文中,我们建议在“G$-预期”框架下针对随机最佳控制问题制定一组离散时间近似计划,这些拟议计划以零星不变政策为基础,反复制定,我们证明离散计划趋同,并确定汇合率。我们列举了几个数字例子,以说明所获结果的有效性。