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Game Theory II: Advanced Applications

Approx. 17 hours to complete

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Course Summary

This course offers an introduction to game theory and its applications in various fields such as economics, political science, and computer science. You will learn about strategic interaction, Nash equilibrium, and game theory's role in decision making.

Key Learning Points

Understand the fundamental concepts of game theory and apply them in real-world scenarios
Learn how to analyze and solve games using different techniques
Explore the applications of game theory in various fields, including economics, political science, and computer science

Job Positions & Salaries of people who have taken this course might have

- USA: $72,000
- India: ₹5,00,000
- Spain: €36,000
- USA: $72,000
- India: ₹5,00,000
- Spain: €36,000
- USA: $61,000
- India: ₹4,50,000
- Spain: €30,000
- USA: $72,000
- India: ₹5,00,000
- Spain: €36,000
- USA: $61,000
- India: ₹4,50,000
- Spain: €30,000
- USA: $75,000
- India: ₹6,00,000
- Spain: €39,000

Learning Outcomes

Apply game theory concepts to analyze strategic interaction in different scenarios
Solve games using various techniques, including dominance, backward induction, and mixed strategies
Identify and analyze game theory applications in various fields

Prerequisites or good to have knowledge before taking this course

Basic knowledge of algebra and probability
Familiarity with economic concepts (optional)

Course Difficulty Level

Intermediate

Course Format

Self-paced
Video lectures
Quizzes and assignments

Similar Courses

Microeconomics
Behavioral Economics in Action
Econometrics

Related Education Paths

Notable People in This Field

John Nash
Thomas Schelling

Related Books

Description

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

Outline

Social Choice
An Introduction to the Course
1.1 Social Choice: Taste
1.2 Social Choice: Voting Scheme
1.3 Paradoxical Outcomes
1.4 Impossibility of Non-Paradoxical Social Welfare Functions
1.5 Arrow's Theorem
1.6 Impossibility of Non-Pardoxical Social Choice Functions
1.7 Single-Peaked Preferences
Syllabus
Problem Set 1
Unit 1.2 Quiz
Unit 1.3 Quiz
Unit 1.5 Quiz

Mechanism Design
2.1 Mechanism Design: Taste
2.2 Implementation
2.3 Mechanism Design: Examples
2.4 Revelation Principle
2.5 Revelation Principle: Examples
2.6 Impossibility of General Dominant-Strategy Implementation
2.7 Transferable Utility
2.8 Transferable Utility Example
2.9 Mechanism Design as an Optimization Problem
Reading on the theory of Mechanism Design
Problem Set 2
Unit 2.2 Quiz
Unit 2.4 Quiz
Unit 2.6 Quiz
Unit 2.8 Quiz
Unit 2.9 Quiz

Efficient Mechanisms
3.1 VCG: Taste
3.2 VCG: Definitions
3.3 VCG: Examples
3.4 VCG: Limitations
3.5 VCG: Individual Rationality and Budget Balance in VCG
3.6 VCG: The Myerson-Satterthwaite Theorem
Problem Set 3
Unit 3.2 Quiz
Unit 3.3 Quiz
Unit 3.6 Quiz

Auctions
4.1 Auctions: Taste
4.2 Auctions: Taxonomy
4.3 Bidding in Second-Price Auctions
4.4 Bidding in First-Price Auctions
4.5 Revenue Equivalence
4.6 Optimal Auctions
4.7 More Advanced Auctions
Problem Set 4
Unit 4.2 Quiz
Unit 4.3 Quiz
Unit 4.4 Quiz
Unit 4.6 Quiz

Final Exam
FINAL EXAM

Summary of User Reviews

Discover the world of Game Theory with Coursera's online course. User reviews showcase a great learning experience with engaging content and knowledgeable instructors. Many users appreciated the practical applications of Game Theory in real-life scenarios.

Key Aspect Users Liked About This Course

Practical applications of Game Theory in real-life scenarios were appreciated by most users.

Pros from User Reviews

Engaging and interactive content.
Knowledgeable instructors.
Real-world examples and applications.
Flexible learning schedule.
Great value for the price.

Cons from User Reviews

Some sections were too complex for beginners.
Limited interaction with instructors.
Not enough opportunities for hands-on practice.
Some users found the course to be too theoretical.
Not enough focus on advanced topics.

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