부산대학교 도서관

We present the infinite dimensional approach to control of a general class of doubly stochastic or otherwise known Q-mark Markov Jump Diffusion (Q-MJD) processes. The governing dynamics for the the probability density function (PDF) of this class of Q-MJD processes is a Partial Integro Differential Equation (PIDE). The infinite dimensional Minimum Principle (MP) is applied to control these PIDE dynamics. We qualitatively compare the infinite dimensional MP and the stochastic Dynamic Programming Principle (DPP) frameworks as applied to control of Q-MJD processes. The developed sampling based algorithms illustrate how the presented framework is a multi trajectory optimization method to solve nonlinear stochastic optimal control problems for Q-MJD processes.