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.

Created by: Stanford University, The University of British Columbia

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	4.5 stars Average User Rating 4.5See what learners said

Syllabus

WEEK 1

Week 1: Introduction and Overview

Introduction, overview, uses of game theory, some applications and examples, and formal definitions of: the normal form, payoffs, strategies, pure strategy Nash equilibrium, dominant strategies

11 videos, 2 readings, 1 reading

Graded: Problem Set 1

WEEK 2

Week 2: Mixed-Strategy Nash Equilibrium

pure and mixed strategy Nash equilibria

7 videos, 1 reading

Graded: Problem Set 2

WEEK 3

Week 3: Alternate Solution Concepts

Iterative removal of strictly dominated strategies, minimax strategies and the minimax theorem for zero-sum game, correlated equilibria

6 videos, 1 reading

Graded: Problem Set 3

WEEK 4

Week 4: Extensive-Form Games

Perfect information games: trees, players assigned to nodes, payoffs, backward Induction, subgame perfect equilibrium, introduction to imperfect-information games, mixed versus behavioral strategies.

10 videos, 1 reading

Graded: Problem Set 4

WEEK 5

Week 5: Repeated Games

Repeated prisoners dilemma, finite and infinite repeated games, limited-average versus future-discounted reward, folk theorems, stochastic games and learning.

7 videos, 1 reading

Graded: Problem Set 5

WEEK 6

Week 6: Bayesian Games

General definitions, ex ante/interim Bayesian Nash equilibrium.

6 videos, 1 reading

Graded: Problem Set 6

WEEK 7

Week 7: Coalitional Games

Transferable utility cooperative games, Shapley value, Core, applications.

5 videos, 1 reading

Graded: Problem Set 7

WEEK 8

Week 8: Final Exam

The description goes here

Graded: Final Exam

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Stanford University

The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.

The University of British Columbia

The University of British Columbia is a global centre for research and teaching.

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Game Theory