Game Theory with Python

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In this Free Guided Project, you will:

Gain conceptual understanding of Static and Dynamic Games

Understand Pure and Mixed strategies of a game and learn to interpret the results

Learn to implement Nash Games using Python packages Nashpy and Axelrod

Showcase this hands-on experience in an interview

Clock2 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 2-hour long project-based course, you will learn the game theoretic concepts of Two player Static and Dynamic Games, Pure and Mixed strategy Nash Equilibria for static games (illustrations with unique and multiple solutions), Example of Axelrod tournament. You will be building two player Nash games and analyze them using Python packages Nashpy and Axelrod, especially built for game theoretic analyses. Also, you will gain the understanding of computational mechanisms related to the aforementioned concepts. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Requirements

Familiarity with Python programming (specifically Python 3) and concepts of game theory is preferred. Learners must have an existing Google Account .

Skills you will develop

Game TheoryPython ProgrammingSolution Concept

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Two player Static Games

  2. Mixed Strategies and Utilities

  3. Pure Strategy Nash Equilibrium

  4. Multiple Nash Equilibria

  5. Zero Sum Games and Mixed Strategies

  6. Two player Dynamic Games

  7. Analysis of Dynamic Games

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

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Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.