(CS/SS 241a) Introduction to SISL:
Topics in Algorithmic game theory

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Time/Location

Tuesday/Thursday, 2:30-3:55pm, Baxter 127

Instructors

Adam Wierman, 258 Jorg, OFFICE HOURS: on request
John Ledyard, 102 Baxter, OFFICE HOURS: on request
Jason Marden, 335 Moore

Course Description

Over the last few years there has been enormous activity at the interface of computer science, game theory, economics, and control. In this course, our goal is to survey some important of the important new areas that are emerging in this field. Some of the topics we will study include:

• Routing, scheduling, and load balancing games
• facility location and network formation games
• Price of anarchy
• Learning in games
• Mechanism design
• Sponsored search
• Prediction markets

This course is intended for graduate students and will be organized as a topics course. Post-docs are also encouraged to attend lectures on topics of interest to them, and need not be registered to do so. Registered students will be expected to present multiple lectures in addition to completing homework assignments. It is expected that students are comfortable with the basics of game theory, graph theory, and probability theory.

Required Text

Algorithmic Game Theory, Edited by Nisan, Roughgarden, Tardos, Vazirani

Grading

• Homeworks -- 50%
• Presentations -- 40%
• Class Participation -- 10%

Collaboration vs. cheating

You will receive one homework every few weeks. These are meant to reinforce the material that we are learning during that time, so please start immediately. Please do not search the web for help on the homework problems. It is difficult to develop good homework problems, and thus you may come across similar problems if you search the web for help.

You are strongly encouraged to collaborate with your classmates on these problems, but each person must write up the final solutions individually. You should note on your homework specifically which problems were a collaborative effort and with whom.

Presentation policies

The ideal presentation will cover a few results from either a book chapter or paper and then highlight interesting extensions and open problems that remain. Presentations should be 60-80min in length and may be done individually or in groups of two. Presentations may use any combination projector/whiteboard desired. In order to prepare for the presentation, students are required to discuss the topic and book chapter/paper that will be presented with one of the professors outside of class.

The grade of the presentation will (in large part) be determined by the audience of the presentation. Every member of the audience will complete this form. The grade will be a weighted average of the audience and professor scores, where the professor scores count as 3 student scores.

(TENTATIVE) Course outline

Other relevant books

• Selfish Routing and the Price of Anarchy, Tim Roughgarden
• Strategic Learning and its Limits, H. Peyton Young
• The Theory of Learning in Games, Fudenberg and Levine
• Individual Strategy and Social Structure: An Evolutionary Theory of Institutions, H. Peyton Young

Other relevant courses

• Berkeley, Algorithmic aspects of game theory, Christos Papadimitriou
• Cornell, Algorithmic game theory, Eva Tardos
• Stanford, Introduction to algorithmic game theory, Tim Roughgarden
• UMASS Amherst, Game theory: Applications to computer networks, Don Towsley
• Stanford Foundations of sponsored search, Tim Roughgarden