We analyse the asymptotic properties of a continuous-time, two-timescale stochastic approximation algorithm designed for stochastic bilevel optimisation problems in continuous-time models. We obtain the weak convergence rate of this algorithm in the form of a central limit theorem. We also demonstrate how this algorithm can be applied to several continuous-time bilevel optimisation problems.

翻译：我们分析一个连续时间、两次规模的随机近似算法的无症状特性,该算法是为连续时间模型中随机性双级优化问题设计的。我们以中心限制理论的形式获得了这一算法的微弱趋同率。我们还演示了该算法如何适用于几个连续时间、双级优化问题。