Implementation of Deep Q-Learning to Learn how to play a simple game written in python.
Here is the demo computer playing the game
This project contains three major files, AI.py file creates the model and train the model to play the game, play_ai.py uses the saved pre-trained model to play the game. If you like play the game by your own you can play using game.py script.
- Pygame
- Keras
- Tensorflow or Theano
- Numpy
git clone https://github.com/mynkpl1998/Save-me-AI.git
cd Save-me-AI
python play_ai.py
git clone https://github.com/mynkpl1998/Save-me-AI.git
cd Save-me-AI
python AI.py
- Convert the screen images to grayscale
- Stack the four frames together
- 3 Convolutional Neural Network without maxpool layers
- 2 Fully Connected Dense layers
- Learning Rate (Default : 1e-06)
- Initial Epsilon (Default : 0.1)
- Final Epsilon (Default : 0.0001)