Description: Stochastic control theory and applications in a variety of areas including dynamic resource allocation, finance, inventory, queueing and stochastic networks, and epidemiology. Topics include foundations of stochastic control for Markov processes and diffusions, maximum principle, dynamic programming and Hamilton-Jacobi-Bellman (HJB) equations, finite-horizon and infinite-horizon discounted and average problems, optimal stopping problem, impulse control, risk sensitive control, differential games, viscosity solutions, iteration and policy iteration and other numerical solution algorithms. Cross-list: CMOR 555. Recommended Prerequisite(s): Equivalent of advanced course work in calculus (e.g., MATH 212, 221, or 232), statistics and probability theory (e.g., STAT 310 or STAT 311, STAT 315), linear algebra (e.g., CMOR 302, 303, MATH 354, or MATH 355) and analysis (e.g., MATH 302, 321 or 331), and differential equations (e.g., MATH 211 or CMOR 304).