What you'll learn
Week 1: Introduction and Overview
Week 2: Mixed-Strategy Nash Equilibrium
Week 3: Alternate Solution Concepts
Week 4: Extensive-Form Games
Week 5: Repeated Games
Week 6: Bayesian Games
Week 7: Coalitional Games
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
Access to a computer or mobile device with an internet connection.
Motivation to learn!
There are no special materials or prerequisite knowledge required for this course.
Who this course is for
Students who are new to this field
Students willing to put in a couple hours to learn about Game Theory
Advanced students wanting to add another skill to their portfolio
Matthew O. Jackson – Professor – Economics
Kevin Leyton-Brown – Professor – Computer Science
Yoav Shoham – Professor – Computer Science
This course includes
Option for learning at your own pace
Videos and reading material about the course
Assessed tasks with feedback from other course participants
Evaluated tests with feedback
Evaluated programming tasks