论文标题
随机燃烧方程，随时间变化的lévy噪声和最大原理
Stochastic Volterra equations with time-changed Lévy noise and maximum principles
论文作者
论文摘要
由于自然资源的最佳收获问题，我们研究了由随时间变化的莱维噪声驱动的伏特拉型动力学的控制问题，这通常不是马尔可夫人。为了利用噪声的性质，我们在最大的原理方法中利用不同种类的信息流。为此，我们与时间更换的后退随机微分方程（BSDE）合作，并利用[15]中引入的非期望随机衍生物。我们证明了足够和必要的随机最大原理。
Motivated by a problem of optimal harvesting of natural resources, we study a control problem for Volterra type dynamics driven by time-changed Lévy noises, which are in general not Markovian. To exploit the nature of the noise, we make use of different kind of information flows within a maximum principle approach. For this we work with backward stochastic differential equations (BSDE) with time-change and exploit the non-anticipating stochastic derivative introduced in [15]. We prove both a sufficient and necessary stochastic maximum principle.
