https://github.com/vietnh1009/chrome-dino-deep-q-learning-pytorch
Deep Q-learning for playing chrome dino game
https://github.com/vietnh1009/chrome-dino-deep-q-learning-pytorch
Last synced: 2 months ago
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Deep Q-learning for playing chrome dino game
- Host: GitHub
- URL: https://github.com/vietnh1009/chrome-dino-deep-q-learning-pytorch
- Owner: vietnh1009
- Created: 2021-04-11T12:00:34.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2021-05-01T15:06:14.000Z (over 4 years ago)
- Last Synced: 2025-05-04T17:46:36.082Z (5 months ago)
- Language: Python
- Size: 37.9 MB
- Stars: 71
- Watchers: 5
- Forks: 11
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# [PYTORCH] Deep Q-learning for playing Chrome Dino
## Introduction
Here is my python source code for training an agent to play flappy bird. It could be seen as a very basic example of Reinforcement Learning's application.
Result
The corresponding output video will also be generated and stored by default at **output/chrome_dino.mp4**
Output video
## How to use my code
With my code, you can:
* **Train your model from scratch** by running **python train.py**
* **Test your trained model** by running **python test.py**
## Trained models
You could find my trained model at **trained_models/chrome_dino.pth**
## Requirements
* **python 3.6**
* **pygame**
* **cv2**
* **pytorch**
* **numpy**
## Reference
* https://github.com/shivamshekhar/Chrome-T-Rex-Rush: My environment is based on this great repository.