AleksandarHaber / Q-Learning-Algorithm-in-Python-with-Cart-Pole-OpenAI-Gym--Gymnasium-Environment

In this repository, we post the implementation of the Q-Learning (Reinforcement) learning algorithm in Python. The codes are tested in the Cart Pole OpenAI Gym (Gymnasium) environment.

Q-Learning-Algorithm-in-Python-with-Cart-Pole-OpenAI-Gym--Gymnasium-Environment

This GitHub repository contains the implementation of the Q-Learning (Reinforcement) learning algorithm in Python. The codes are tested in the Cart Pole OpenAI Gym (Gymnasium) environment. The tutorial webpage explaining the posted codes is given here:

https://aleksandarhaber.com/q-learning-in-python-with-tests-in-cart-pole-openai-gym-environment-reinforcement-learning-tutorial/

The posted files are:

• "driverCode.py" - you should start from here. This is a driver code file that explains how to use the Q-learning algorithm. This code file imports a class called "Q_Learning" that is developed in "functions.py"

• "functions.py" - this file contains the implementation of the Q-Learning algorithm. The class "Q_Learning" defined in this file implements the algorithm.