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URL: https://www.coursera.org/learn/game-theory-2

⇱ Game Theory II: Advanced Applications | Coursera


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Gain insight into a topic and learn the fundamentals.
4.7

651 reviews

Advanced level
Designed for those already in the industry
Flexible schedule
2 weeks at 10 hours a week
Learn at your own pace
92%
Most learners liked this course

Gain insight into a topic and learn the fundamentals.
4.7

651 reviews

Advanced level
Designed for those already in the industry
Flexible schedule
2 weeks at 10 hours a week
Learn at your own pace
92%
Most learners liked this course

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

20 assignments

Taught in English

There are 5 modules in this course

Popularized by movies such as "A Beautiful Mind", game theory is the mathematical modeling of strategic interaction among rational (and irrational) agents. Over four weeks of lectures, this advanced course considers how to design interactions between agents in order to achieve good social outcomes. Three main topics are covered: social choice theory (i.e., collective decision making and voting systems), mechanism design, and auctions.

In the first week we consider the problem of aggregating different agents' preferences, discussing voting rules and the challenges faced in collective decision making. We present some of the most important theoretical results in the area: notably, Arrow's Theorem, which proves that there is no "perfect" voting system, and also the Gibbard-Satterthwaite and Muller-Satterthwaite Theorems. We move on to consider the problem of making collective decisions when agents are self interested and can strategically misreport their preferences. We explain "mechanism design" -- a broad framework for designing interactions between self-interested agents -- and give some key theoretical results. Our third week focuses on the problem of designing mechanisms to maximize aggregate happiness across agents, and presents the powerful family of Vickrey-Clarke-Groves mechanisms. The course wraps up with a fourth week that considers the problem of allocating scarce resources among self-interested agents, and that provides an introduction to auction theory. You can find a full syllabus and description of the course here: http://web.stanford.edu/~jacksonm/GTOC-II-Syllabus.html There is also a predecessor course to this one, for those who want to learn or remind themselves of the basic concepts of game theory: https://www.coursera.org/learn/game-theory-1 An intro video can be found here: http://web.stanford.edu/~jacksonm/Game-Theory-2-Intro.mp4

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What's included

8 videos1 reading4 assignments

8 videosβ€’Total 89 minutes
  • An Introduction to the Courseβ€’9 minutes
  • 1.1 Social Choice: Taste β€’3 minutes
  • 1.2 Social Choice: Voting Scheme β€’16 minutes
  • 1.3 Paradoxical Outcomes β€’9 minutes
  • 1.4 Impossibility of Non-Paradoxical Social Welfare Functions β€’5 minutes
  • 1.5 Arrow's Theorem β€’32 minutes
  • 1.6 Impossibility of Non-Pardoxical Social Choice Functions β€’7 minutes
  • 1.7 Single-Peaked Preferences β€’7 minutes
1 readingβ€’Total 10 minutes
  • Syllabusβ€’10 minutes
4 assignmentsβ€’Total 120 minutes
  • Unit 1.2 Quizβ€’30 minutes
  • Unit 1.3 Quizβ€’30 minutes
  • Unit 1.5 Quizβ€’30 minutes
  • Problem Set 1β€’30 minutes

The description goes here

What's included

9 videos1 reading6 assignments

9 videosβ€’Total 96 minutes
  • 2.1 Mechanism Design: Taste β€’3 minutes
  • 2.2 Implementation β€’18 minutes
  • 2.3 Mechanism Design: Examplesβ€’12 minutes
  • 2.4 Revelation Principle β€’9 minutes
  • 2.5 Revelation Principle: Examplesβ€’5 minutes
  • 2.6 Impossibility of General Dominant-Strategy Implementation β€’11 minutes
  • 2.7 Transferable Utility β€’9 minutes
  • 2.8 Transferable Utility Exampleβ€’9 minutes
  • 2.9 Mechanism Design as an Optimization Problem β€’19 minutes
1 readingβ€’Total 10 minutes
  • Reading on the theory of Mechanism Designβ€’10 minutes
6 assignmentsβ€’Total 180 minutes
  • Unit 2.2 Quizβ€’30 minutes
  • Unit 2.4 Quizβ€’30 minutes
  • Unit 2.6 Quizβ€’30 minutes
  • Unit 2.8 Quizβ€’30 minutes
  • Unit 2.9 Quizβ€’30 minutes
  • Problem Set 2β€’30 minutes

The description goes here

What's included

6 videos4 assignments

6 videosβ€’Total 83 minutes
  • 3.1 VCG: Taste β€’10 minutes
  • 3.2 VCG: Definitions β€’18 minutes
  • 3.3 VCG: Examples β€’7 minutes
  • 3.4 VCG: Limitations β€’11 minutes
  • 3.5 VCG: Individual Rationality and Budget Balance in VCG β€’16 minutes
  • 3.6 VCG: The Myerson-Satterthwaite Theorem β€’19 minutes
4 assignmentsβ€’Total 120 minutes
  • Unit 3.2 Quizβ€’30 minutes
  • Unit 3.3 Quizβ€’30 minutes
  • Unit 3.6 Quizβ€’30 minutes
  • Problem Set 3β€’30 minutes

The description goes here

What's included

7 videos5 assignments

7 videosβ€’Total 112 minutes
  • 4.1 Auctions: Taste β€’4 minutes
  • 4.2 Auctions: Taxonomy β€’14 minutes
  • 4.3 Bidding in Second-Price Auctions β€’7 minutes
  • 4.4 Bidding in First-Price Auctions β€’13 minutes
  • 4.5 Revenue Equivalence β€’40 minutes
  • 4.6 Optimal Auctions β€’22 minutes
  • 4.7 More Advanced Auctions β€’12 minutes
5 assignmentsβ€’Total 150 minutes
  • Unit 4.2 Quizβ€’30 minutes
  • Unit 4.3 Quizβ€’30 minutes
  • Unit 4.4 Quizβ€’30 minutes
  • Unit 4.6 Quizβ€’30 minutes
  • Problem Set 4β€’30 minutes

The description goes here

What's included

1 assignment

1 assignmentβ€’Total 30 minutes
  • FINAL EXAMβ€’30 minutes

Instructors

Instructor ratings
4.5 (70 ratings)
Stanford University
3 Coursesβ€’643,161 learners
The University of British Columbia
2 Coursesβ€’587,674 learners

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Showing 3 of 651

GL
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Reviewed on Oct 18, 2022

V​ery interesting and challenging... I wish there were more practical/real-world examples to learn the concepts but I was very glad to take this course

HP
Β·

Reviewed on Nov 5, 2020

I learned strategic thinking and how to make applied that in real world with various Game Theory methods. Thanks

AS
Β·

Reviewed on Sep 10, 2016

Outstanding course on Game Theory. Provides excellent mathematical and logical treatment of the concepts and theory. A perfect stepping stone for researchers willing to pursue their research in Gam

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