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Game Theory
I: An Introduction
Game Theory II: Advanced Applications
Game Theory II: Advanced Applications
Matthew O. Jackson
Stanford University
Kevin LeytonBrown
University of British Columbia
Stanford University
News
Game Theory II most recently started
January, 2016 on Coursera.
About the Course
Popularized by movies such as "A Beautiful Mind", game theory is the
mathematical modeling of strategic interaction among rational (and
irrational) agents. Beyond what we call 'games' in common language, such
as chess, poker, soccer, etc., it includes the modeling of conflict
among nations, political campaigns, competition among firms, and trading
behavior in markets such as the NYSE. How could you begin to model eBay,
Google keyword auctions, and peer to peer filesharing networks, without
accounting for the incentives of the people using them?
Our 4week advanced course considers how to design interactions between agents in order to achieve good social outcomes. The course  which is free and open to the public  considers three main topics: social choice theory (i.e., collective decision making), mechanism design, and auctions. More specifically, in the first week we consider the problem of aggregating different agents' preferences, discussing voting rules and the challenges faced in collective decision making. We present some of the most important theoretical results in the area: notably, Arrow's Theorem, which proves that there is no "perfect" voting system, and also the GibbardSatterthwaite and MullerSatterthwaite Theorems. We move on to consider the problem of making collective decisions when agents are self interested and can strategically misreport their preferences. We explain "mechanism design"  a broad framework for designing interactions between selfinterested agents  and give some key theoretical results. Our third week focuses on the problem of designing mechanisms to maximize aggregate happiness across agents, and presents the powerful family of VickreyClarkeGroves mechanisms. The course wraps up with a fourth week that considers the problem of allocating scarce resources among selfinterested agents, and that provides an introduction to auction theory.
This course is a followup to a more basic course in which we provided the foundations to game theory, covering topics such as representing games and strategies, the extensive form, Bayesian games, repeated and stochastic games, and more. Although to a substantial extent our new course stands alone, some of the previous material  e.g., Bayesian games, Nash equilibrium, and dominant strategies  is needed for this more advanced course, whether picked up through our previous course or elsewhere.
Our 4week advanced course considers how to design interactions between agents in order to achieve good social outcomes. The course  which is free and open to the public  considers three main topics: social choice theory (i.e., collective decision making), mechanism design, and auctions. More specifically, in the first week we consider the problem of aggregating different agents' preferences, discussing voting rules and the challenges faced in collective decision making. We present some of the most important theoretical results in the area: notably, Arrow's Theorem, which proves that there is no "perfect" voting system, and also the GibbardSatterthwaite and MullerSatterthwaite Theorems. We move on to consider the problem of making collective decisions when agents are self interested and can strategically misreport their preferences. We explain "mechanism design"  a broad framework for designing interactions between selfinterested agents  and give some key theoretical results. Our third week focuses on the problem of designing mechanisms to maximize aggregate happiness across agents, and presents the powerful family of VickreyClarkeGroves mechanisms. The course wraps up with a fourth week that considers the problem of allocating scarce resources among selfinterested agents, and that provides an introduction to auction theory.
This course is a followup to a more basic course in which we provided the foundations to game theory, covering topics such as representing games and strategies, the extensive form, Bayesian games, repeated and stochastic games, and more. Although to a substantial extent our new course stands alone, some of the previous material  e.g., Bayesian games, Nash equilibrium, and dominant strategies  is needed for this more advanced course, whether picked up through our previous course or elsewhere.
Recommended Background
You must be comfortable with mathematical thinking and rigorous
arguments. Relatively little specific math is required; the course
involves lightweight probability theory (for example, you should know
what a conditional probability is) and very lightweight calculus (for
instance, taking a derivative).
Suggested Readings
The following background readings provide more detailed coverage of the
course material:
 Multiagent Systems: Algorithmic, GameTheoretic, and Logical Foundations, by Yoav Shoham and Kevin LeytonBrown; Cambridge University Press, 2009. This book has the same structure as the course, and covers most of the same material. It is available as a free PDF download from the link above or for sale as a physical book from (e.g.) amazon.com.
 A Brief Introduction to the Basics of Game Theory, by Matthew O. Jackson. These notes offer a quick introduction to the basics of game theory; they are available as a free PDF download.
Course Format
The course consists of the following materials:
 Videos. The lectures are delivered via videos, which are broken into small chunks, usually between five and fifteen minutes each. There will be approximately one and a half hours of video content per week. You may watch the lecture videos at your convenience. Lowerresolution videos are also available for those with slow internet connections.
 Slides. We have made available pdf files of all the lecture slides.
 Quizzes. There will be nongraded short "quiz" questions that will follow some of the videos to help you gauge your understanding.
 Online Lab Exercises After some of the videos, we will ask you to go online to play some games. These are entirely optional, and are designed to illustrate some of the concepts from the course.
 Problem Sets. There will also be graded weekly problem sets that you will also answer online, but may work through offline; those must be completed within two weeks of the time that they are posted in order to be graded for full credit. If you miss a problem set deadline, you may complete it before the end of the course for half credit. You may discuss problems from the problem sets with other students in an online forum, without providing explicit answers.
 Final Exam. There will be an online final exam that you will have to complete within two weeks of its posting. Once you begin the exam, you will have four hours to complete it.
 Screenside Chats. We periodically hold online chats where we answer questions and discuss topics relevant to the course. See an archive here.
Past and Present Course Offerings

Game Theory II, January 2016, Coursera.
Game Theory II, January 11, 2015, Coursera.
Game Theory II, January 13, 2014, Coursera.
Game Theory II, May 27, 2013, Google CourseBuilder