matin-ghorbani/Snake-AI-Deep-QLearning
Implement a snake AI with deep Q learning using PyTorch
This project helps you explore and understand how a computer can learn to play the classic Snake game really well. It takes the game's state (snake position, food location, obstacles) as input and outputs the optimal next move for the snake. This is useful for anyone curious about basic artificial intelligence, particularly those interested in how machines can learn through trial and error.
No commits in the last 6 months.
Use this if you want to see a practical example of deep reinforcement learning applied to a simple game environment.
Not ideal if you're looking for an advanced AI for complex real-world control problems or a production-ready game AI.
Stars
9
Forks
—
Language
Python
License
MIT
Category
Last pushed
Jun 04, 2024
Commits (30d)
0
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