Stochastic optimization theory of backward stochastic differential equations driven by G-Brownian motion (Q2015746)

Summary: We consider the stochastic optimal control problems under G-expectation. Based on the theory of backward stochastic differential equations driven by G-Brownian motion, which was introduced in [\textit{M. Hu} et al., Stochastic Processes Appl. 124, No. 1, 759--784 (2014; Zbl 1300.60074)], we can investigate the more general stochastic optimal control problems under G-expectation than that were constructed in [\textit{D. Zhang}, Optim. Control Appl. Methods 34, No. 1, 96--110 (2013; Zbl 1273.93180)]. Then we obtain a generalized dynamic programming principle, and the value function is proved to be a viscosity solution of a fully nonlinear second-order partial differential equation.