Name: Game Theory II: Advanced Applications
Brand: Stanford University
Availability: OnlineOnly
Rating: 4.7 (129 reviews)

Back to Game Theory II: Advanced Applications

Learner Reviews & Feedback for Game Theory II: Advanced Applications by Stanford University

4.7

stars

639 ratings

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. 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://porcelainpromo.shop/learn/game-theory-1 An intro video can be found here: http://web.stanford.edu/~jacksonm/Game-Theory-2-Intro.mp4...

Top reviews

Jul 16, 2020

This was a wonderful and very mathematically intensive course, but completing all the quizzes gave a great sense of accomplishment and developed my understanding of game theory and its various facets.

May 1, 2017

Very interesting! One missing thing: please write explanations for correct/incorrect questions in quizzes. In the basic course, I found them very helpful in understanding why my reasoning was wrong.

Filter by:

76 - 100 of 129 Reviews for Game Theory II: Advanced Applications

By Runyang W

•

Jan 8, 2019

话题主要为高级微观中的机制设计，非常适合我这种转专业的同学

By Rithish S P

•

Oct 20, 2024

Great start to game theory

By Dina I

•

Jan 16, 2018

Very interesting material.

By Pruthviraj k

•

Oct 14, 2024

habhabhha good excelent

By 任翔宇

•

Jun 12, 2020

difficult but intersting

By StevenX

•

Apr 6, 2018

A very well-taught class

By Sebastian P

•

Feb 7, 2021

Warmly recommended!

By Scott M

•

Mar 22, 2017

Outstanding course.

By Keyu Z

•

Jul 11, 2017

Really impressive!

By Qian L

•

Sep 17, 2022

Very good course!

By J H P

•

Apr 28, 2021

Very interesting

By Yin Z

•

Sep 21, 2017

very challenging

By shihyang y

•

Feb 23, 2024

it is very good

By 彭兴宇

•

Sep 11, 2021

Amazing math!

By Michael F

•

Mar 22, 2020

Great course!

By Rinkesh V

•

Sep 15, 2016

finest course

By Deleted A

•

Mar 4, 2025

Outstanding.

By Blake C

•

Dec 30, 2017

Great course

By 韩天煦

•

Jan 7, 2018

excellent

By Venkatraman R

•

Jun 16, 2017

very good

By Shiheng W

•

Oct 25, 2016

Great

By Noé d C A

•

Aug 19, 2020

lit

By Jin-wook L

•

Jan 1, 2017

By ZHU S

•

Jan 10, 2019

The lecture are useful and the lecturer clear in their content and delivery. However, it would be better if more practices with answers can be given, and the tutorial should include questions of greater difficulty, such as those with real game settings and rules to solve for optimum strategy.