About this 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 keyword auctions, and peer to peer file-sharing networks, without accounting for the incentives of the people using them? The course will provide the basics: representing games and strategies, the extensive form (which computer scientists call game trees), Bayesian games (modeling things like auctions), repeated and stochastic games, and more. We'll include a variety of examples including classic games and a few applications. You can find a full syllabus and description of the course here: http://web.stanford.edu/~jacksonm/GTOC-Syllabus.html There is also an advanced follow-up course to this one, for people already familiar with game theory: https://www.coursera.org/learn/gametheory2/ You can find an introductory video here: http://web.stanford.edu/~jacksonm/Intro_Networks.mp4
Who is this class for: This course is aimed at students, researchers, and practitioners who wish to understand more about strategic interactions. You must be comfortable with mathematical thinking and rigorous arguments. Relatively little specific math is required; but you should be familiar with basic probability theory (for example, you should know what a conditional probability is), and some very light calculus would be helpful.
Taught by: Matthew O. Jackson, Professor
Economics
Taught by: Kevin Leyton-Brown, Professor
Computer Science
Taught by: Yoav Shoham, Professor
Computer Science
| Level | Beginner |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
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Excellent Cours, deep enough to understand the mathematical concepts.
It is a course for students who are willing to learn something different other than the subjects in your domain of specialization.Excellent faculty,interesting assignments.
Should have more theoretical questions in assignments. Questions which render one to think for hours are required. Essentially, right now assignments are pure pattern matching.
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SG
The course is very well-presented and helpful. The adequate examples and relatively less rigour make this course easy to get along with.