Optimal control of stochastic systems with applications in various fields of engineering and applied mathematics. Topics include state-space models, development of control laws by dynamic programming, controlled Markov chain models, control with complete and partial information, linear and non-linear filtering, estimation, Martingales, stochastic stability, convergence of policies, dual effect of control, adaptive control, team decisions, numerical methods, value and policy iteration algorithms. (0/0/0/18/18) PREREQUISITES: MTHE 351 (STAT 351), MTHE 332 (MATH 332), or permission of the instructor
