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https://github.com/scar17off/ai-2048
A Python implementation of 2048 with a self-learning AI agent powered by TensorFlow. Features reinforcement learning, GPU acceleration, and real-time gameplay visualization.
https://github.com/scar17off/ai-2048
2048 2048-ai 2048-game artificial-intelligence cuda deep-learning game-ai gpu-computing machine-learning neural-networks pygame python reinforcement-learning self-learning tensorflow
Last synced: about 1 month ago
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A Python implementation of 2048 with a self-learning AI agent powered by TensorFlow. Features reinforcement learning, GPU acceleration, and real-time gameplay visualization.
- Host: GitHub
- URL: https://github.com/scar17off/ai-2048
- Owner: scar17off
- License: mit
- Created: 2024-11-07T23:35:53.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-11-07T23:47:50.000Z (3 months ago)
- Last Synced: 2024-11-08T00:28:32.415Z (3 months ago)
- Topics: 2048, 2048-ai, 2048-game, artificial-intelligence, cuda, deep-learning, game-ai, gpu-computing, machine-learning, neural-networks, pygame, python, reinforcement-learning, self-learning, tensorflow
- Language: Python
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
# 2048 Game with AI Self-Learning
A Python implementation of the popular 2048 game featuring an AI agent that learns to play through self-training using TensorFlow.
## Features
- Classic 2048 game implementation
- AI agent powered by TensorFlow
- Self-learning capabilities through reinforcement learning
- GPU acceleration support
- Real-time visualization of game states
- Performance logging and monitoring
- Training progress visualization using Matplotlib
## Requirements
- Python 3.7+
- TensorFlow 2.x
- NumPy
- Pygame
- Matplotlib
## Installation
1. Clone the repository:
```bash
git clone https://github.com/scar17off/ai-2048.git
cd 2048-ai-self-learning
```
2. Install dependencies:
```bash
pip install tensorflow numpy pygame matplotlib
```
## Project Structure
- `self_learn.py`: Main self-learning AI implementation
- `game_logic.py`: 2048 game mechanics
- `train_model.py`: Model training orchestration
- `ai_play.py`: AI gameplay execution
- `colors.py`: Game interface color definitions
## Usage
1. Generate training games:
```bash
python generate_training_games.py
```
Or download pre-generated games (dataset) in releases.
2. Train the AI model:
```bash
python train_model.py
```
Or download pre-trained model in releases.
3. Watch the AI play:
```bash
python ai_play.py
```
## Technical Details
### Running on GPU
The project automatically configures GPU settings for optimal performance. It enables memory growth and selects the primary GPU for processing, as shown in `self_learn.py`.
To run the project on GPU:
1. Install TensorFlow GPU version:
```bash
pip install tensorflow-gpu
```
2. Install CUDA (https://developer.nvidia.com/cuda-downloads) version 12.0 or later.
3. Run the project as usual.
## Contributing
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## License
This project is licensed under the MIT License - see the [LICENSE file](LICENSE.md) for details.
## Acknowledgments
- Original 2048 game by Gabriele Cirulli
- TensorFlow team for the excellent machine learning framework