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
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
Week 2: Mixed-Strategy Nash Equilibrium pure and mixed strategy Nash equilibria
Week 3: Alternate Solution Concepts Iterative removal of strictly dominated strategies, minimax strategies and the minimax theorem for zero-sum game, correlated equilibria
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.
Week 5: Repeated Games Repeated prisoners dilemma, finite and infinite repeated games, limited-average versus future-discounted reward, folk theorems, stochastic games and learning.
Week 6: Bayesian Games General definitions, ex ante/interim Bayesian Nash equilibrium.
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.
All three of the professors present the material, but not in a way that is easy to understand. I mention this because there are no prerequisites required for the class.
Once the material is presented in this class, I found that searching via google and youtube found more meaningful examples, and were easier to learn from than the professors.
One complaint I have about the class is Dr. Shoham. I found him to be very dull, lacking energy, and using very complicated formulas and difficult-to-understand ideas in his explanations. It's almost as if he were teaching to everyone that has a PHD in the subject matter.
Overall, this course is okay, but you would be better off searching for the information from other sources.
Suzannevnhdropped this course, spending 5 hours a week on it and found the course difficulty to be very hard.
I was looking forward to this course - a lot. But unfortunately the lectures are very hard to follow for someone with university degrees but no mathematical/game theory background. Random internet sources, including YouTube videos, were making it easier for me to understand some of the topics - but it was basically taking up too much of my time to constantly look for other sources. I wish they would film another (and better) series of lectures for this course.
I really wanted to like this class but found the variation in the lecture styles between the three prof's distracting. One was cool, one was interesting, and one was so bad he sucked every ounce of enthusiasm for the subject right out of me. The leverage in online courses should allow only the best presenters to teach. Dr. Shoham acted like he wanted to be anywhere but sharing his genius with a dullard like me.
I have mixed feelings about this course. The material is inherently interesting to me but the three professors have a way sucking the fun out of it with an excess of mathematical formalism. Their lecturing ability runs the gamut from poor to atrocious. I learned quite a lot despite their best efforts, but I couldn't recommend the course to anyone without a love of math and a passion for the subject.
This is computer science theory course. It focuses on the formal mathematical concepts and shies away from applications. Don't be fooled by the title, it's not fun along with games. The course is highly quantitative and you will need a solid algebra and probability knowledge to feel comfortable. But if you're aiming fro MSCS , take it.
Extremely poor presentation of the material. Look elsewhere. Presenters made many errors and often could not accurately verbalize (hence conceptualize) the material. Professor Jackson was top notch but the other presenters just did not measure up. I have no doubt that each presenter is an expert in his field, but with the exception of Professor Jackson they have a very limited understanding of how to present new material to adult learners.
Interesting material, however, I spent more time googling concepts than listening to lectures though as that was a better way to learn. They tried to teach the online course like a University classroom ignoring the obvious differences. This is basically just a collection of online videos about a subject I wouldn't call it a 'course' at all. There's such better ways to teach online.
Juanracompleted this course, spending 3 hours a week on it and found the course difficulty to be medium.
Very interesting course. The teachers do a good job explaining the different aspects of game theory. Difficulty increasing at he end of the course, you need some time to get it right. I had a good time with this course!!