Tues., Thurs., 10:30-11:50 a.m., Room: B&H 160

- Instructor:
**Paul Dupuis**, 37 Manning Street, Rm 204, Tel: x33238,*dupuis@cfm.brown.edu*, Office hours: 1-2 Thursday and 11-12 Friday.

- Homework: There will be 2-3 homework assignments. These will be a major part of the course, and are mandatory.

- Grading: Grading will be based on the homework and computation projects.

- Textbook:
*Kushner and Dupuis*, Numerical Methods for Stochastic Control Problems in Continuous Time, (2nd ed) Springer, 2001.

- Course outline:

- Introduction: Applications and Elementary Examples
- Theory of Controlled Markov Chains-Dynamic Programming Equations
- Continuous Time Models-Controlled Diffusions
- Standard Formulations of Stochastic Control
- Connections with PDE
- Approximation of Processes-Examples and General Methods
- Dynamic Programming Equations for Markov Chains-Methods of Solution
- Weak Convergence
- Convergence Proofs
- Special Topics (E.g., Reflected or Jump Processes)

- Assignment 1
- Assignment 2
- Assignment 3
- Assignment 4
- Assignment 1 Solutions
- Computational Assignment 1
- Computational Assignment 2
- Computational Assignment 3