EE365: Stochastic Control
Spring Quarter 2014
Introduction to stochastic control, with applications taken from a variety of areas including supply-chain optimization, advertising, finance, dynamic resource allocation, caching, and traditional automatic control. Markov decision processes, optimal policy with full state information for finite-horizon case, infinite-horizon discounted, and average stage cost problems. Bellman value function, value iteration, and policy iteration. Approximate dynamic programming. Linear quadratic stochastic control.
Professor Sanjay Lall and teaching assistants Samuel Bakouch, Alex Lemon and Paris Syminelakis.