EE266: Stochastic Control

Sanjay Lall, Stanford University, Spring Quarter 2016.

Course description

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.

Prerequisites: Linear algebra (as in EE263) and probability (as in EE178 or MS&E220).


The materials for this course were written by Professors Stephen Boyd, Sanjay Lall, and Benjamin Van Roy at Stanford.

This year the course is taught by Professor Sanjay Lall


  • Lectures Tuesdays and Thursdays, 9:00 - 10:20am in 200-034

  • Review Sessions Fridays, 3:00 - 4:00pm in Hewlett 102


  • EE266 is the same as MS&E251, Stochastic Decision Models.

  • EE266 was numbered EE365 in previous years. We'll use most of last year's notes, but add some new sections too.

Final Exam

  • The final exam will be a 24hr take-home. It will be available for pickup at:

    • Friday Jun 3, 5pm

    • Monday Jun 6, 10am or 5pm

    • Tuesday Jun 7, 10am or 5pm

    • Wednesday Jun 8, 10am