Skip to main content

A simple NashQ-learning implementation in Python

Project description

LearningNashQLearning

This is an educational project to see the inner workings of the Nash-Q Learning algorithm. The Nash-Q Learning algorithm is a multi-agent reinforcement learning algorithm that is designed to learn Nash equilibria in general-sum stochastic games. This project is designed to be educational and is not intended to be used in production environments.

What's in here?

You can find the following subpackages in this project:

  • Model: Contains the implementation of the Nash-Q Learning algorithm as well as a wide range of classes to define Stochastic Games.
  • View: Contains the implementation of a wide variety of widgets to visualize the Nash-Q Learning algorithm. They are designed to be used in python Notebooks via the ipythonwidgets library.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

LearningNashQLearning-0.12.tar.gz (19.8 kB view hashes)

Uploaded Source

Built Distribution

LearningNashQLearning-0.12-py3-none-any.whl (26.5 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page