https://github.com/salahbm/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.
https://github.com/salahbm/algorithm-in-python-with-cart-pole-openai-gym--gymnasium-environment
Last synced: about 2 months ago
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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.
- Host: GitHub
- URL: https://github.com/salahbm/algorithm-in-python-with-cart-pole-openai-gym--gymnasium-environment
- Owner: salahbm
- Created: 2024-06-12T02:12:25.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-06-12T05:54:55.000Z (12 months ago)
- Last Synced: 2024-06-12T11:29:51.444Z (12 months ago)
- Language: Python
- Size: 9.77 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
#Algorithm-in-Python-with-Cart-Pole-OpenAI-Gym--Gymnasium-Environment
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.