Pre-requisites: EE 325 or EE 601 or an equivalent basic course on probability and random processes; Review of probability theory, Controlled Markov chains: dynamic programming and computational schemes, Linear stochastic control: LQG problem, Kalman filter and separation principle, Introduction to stochastic differential equations and continuous-time stochastic, control: Hamilton-Jacobi-Bellman equation, nonlinear filtering.