Game Theory

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Game Theory

Coursera (CC)
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Description

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

The course covers the basics: representing games and strategies, the extensive form (which computer scientists call game trees), repeated and stochastic games, coalitional games, and Bayesian games (modeling things like auctions).

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…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

The course covers the basics: representing games and strategies, the extensive form (which computer scientists call game trees), repeated and stochastic games, coalitional games, and Bayesian games (modeling things like auctions).

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 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 real-world applications.

About the Instructor(s)

Matthew O. Jackson is the William D. Eberle Professor of Economics at Stanford University and an external faculty member of the Santa Fe Institute and a fellow of CIFAR. Jackson's research interests include game theory, microeconomic theory, and the study of social and economic networks, on which he has published many articles and the book Social and Economic Networks. Jackson is a Fellow of the Econometric Society and the American Academy of Arts and Sciences, and his honors include the Social Choice and Welfare Prize, a Guggenheim Fellowship, and the B.E.Press Arrow Prize for Senior Economists. He has served as co-editor of Games and Economic Behavior, the Review of Economic Design, and Econometrica. 
 
 
 
 

Kevin Leyton-Brown is an Associate Professor of Computer Science at the University of British Columbia, where he has been since receiving his PhD from Stanford University in 2003. He works at the intersection of computer science and microeconomics, addressing computational problems in economic contexts and incentive issues in multiagent systems. He also studies the application of machine learning to the automated design and analysis of algorithms for solving hard computational problems. With coauthors, he has received numerous paper awards (JAIR, ACM-EC, AAMAS and LION) and medals in international SAT competitions (2003-12). He was program chair for the ACM Conference on Electronic Commerce in 2012, and serves as an associate editor for the Journal of Artificial Intelligence Research, the Artificial Intelligence Journal, and ACM Transactions on Economics and Computation.
 
 
 

Yoav Shoham received his PhD in computer science from Yale University in 1987, and has been a Professor of Computer Science at Stanford University since then. His research interests include logic-based knowledge representation, game theory, and electronic commerce. He has published numerous articles in these areas, and five books. The last one, Essentials of Game Theory (co-written with K. Leyton-Brown), covers the material in this course. Prof. Shoham has also founded several successful internet companies.
 
 
 
 
 
 

Course Syllabus

Week 1. Introduction: Introduction, overview, uses of game theory, some applications and examples, and formal definitions of: the normal form, payoffs, strategies, pure strategy Nash equilibrium, dominated strategies.

Week 2. Mixed-strategy Nash equilibria: Definitions, examples, real-world evidence.

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

Week 7. Bayesian games: General definitions, ex ante/interim Bayesian Nash equilibrium.

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:
  • Essentials of Game Theory, by Kevin Leyton-Brown and Yoav Shoham; Morgan and Claypool Publishers, 2008. This book has the same structure as the course, and covers most of the same material. It is free if you access the link from a school that subscribes to the Morgan & Claypool Synthesis Lectures, and otherwise costs $5 to download. You can also get it as a printed book from (e.g.) amazon.com, or as an ebook for Kindle or Google devices.
  • 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. Lower-resolution 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 non-graded 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.
  • Screen-side Chats. Each week on Thursday (Pacific time; Friday in some parts of the world) we will hold a brief online chat where we answer questions and discuss topics relevant to the course.

FAQ

  • Will I get a statement of accomplishment after completing this class?

    Yes. Students who successfully complete the class will receive a statement of accomplishment signed by the instructors.

Provided by:

University: Stanford University, The University of British Columbia

Instructor(s): Matthew O. Jackson, Professor
Kevin Leyton-Brown, Associate Professor
Yoav Shoham, Professor

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