Decision making in large scale systems

Lectures: 2 sessions / week, 1.5 hours / session

Topic coverage will be adapted according to students' interests. Some or all of the following will be covered:

Markov Decision Processes and Dynamic Programming (2-3 weeks)

Simulation-Based Methods (2 weeks)

Value Function Approximation (4 weeks)

Policy Search Methods (2-3 weeks)

Online Learning and Games (2 weeks)

We will see applications throughout the course, including dynamic resource allocation, finance and queuing networks, among others.

Bertsekas, Dimitri P. Dynamic Programming and Optimal Control. 2 vols. Belmont, MA: Athena Scientific, 2007. ISBN: 9781886529083.

Bertsekas, Dimitri P., and John N. Tsitsiklis. Neuro-Dynamic Programming. Belmont, MA: Athena Scientific, 1996. ISBN: 9781886529106.

Individual Papers are also used for many class sessions, as listed in the readings section.

Students will be offered the option of working on theory, algorithms and/or applications. Project proposals will be submitted midway through the term, with the final project due at the end of the term.

A 10-15 page project report and 15-20 minute presentation are required.

Don't show me this again

This is one of over 2,200 courses on OCW. Find materials for this course in the pages linked along the left.

MIT OpenCourseWare is a free & open publication of material from thousands of MIT courses, covering the entire MIT curriculum.

No enrollment or registration. Freely browse and use OCW materials at your own pace. There's no signup, and no start or end dates.

Knowledge is your reward. Use OCW to guide your own life-long learning, or to teach others. We don't offer credit or certification for using OCW.

Made for sharing. Download files for later. Send to friends and colleagues. Modify, remix, and reuse (just remember to cite OCW as the source.)

Learn more at Get Started with MIT OpenCourseWare