Game Theory with Python
This 2-hour project-based course will teach you the game theoretic principles of two-player static and dynamic games; pure and mixed strategy Nash Equilibria for static games (illustrations with unique and numerous solutions); and an example of an Axelrod tournament. You will create two-player Nash games and analyze them using the Python packages Nashpy and Axelrod, which are specifically designed for game theoretic studies. You will also get a knowledge of the computational methods associated with the aforementioned notions.
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.
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
- Two-player Static Games
- Mixed Strategies and Utilities
- Pure Strategy, Nash Equilibrium
- Multiple Nash Equilibria
- Zero Sum Games and Mixed Strategies
- Two-player Dynamic Games
- An Analysis of Dynamic Games
Barsha Saha is a PhD Scholar working in the area of IO (Industrial Organization) and Game Theory. She is an Electronics and Instrumentation Engineer with a professional experience as an SAP Consultant. Her courses/guided projects are designed as a blend of theoretical concepts and hands-on application of various Statistical analyses.
This course offers
- two hours
- Intermediate
- No download needed.
- Split-screen video
- English
- Desktop only
Coursera rating: 4.3/5
Enroll here: https://www.coursera.org/projects/game-theory-with-python
