ai-snake-lab 0.4.8

Interactive reinforcement learning sandbox for experimenting with AI agents in a classic Snake Game environment.

Introduction

AI Snake Lab is an interactive reinforcement learning sandbox for experimenting with AI agents in a classic Snake Game environment — featuring a live Textual TUI interface, flexible replay memory database, and modular model definitions.

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🚀 Features

• 🐍 Classic Snake environment with customizable grid and rules
• 🧠 AI agent interface supporting multiple architectures (Linear, RNN, CNN)
• 🎮 Textual-based simulator for live visualization and metrics
• 💾 SQLite-backed replay memory for storing frames, episodes, and runs
• 🧩 Experiment metadata tracking — models, hyperparameters, state-map versions
• 📊 Built-in plotting for hashrate, scores, and learning progress

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🧰 Tech Stack

Component	Description
Python 3.11+	Core language
Textual	Terminal UI framework
SQLite3	Lightweight replay memory + experiment store
PyTorch (optional)	Deep learning backend for models
Plotext / Matplotlib	Visualization tools

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Installation

This project is on PyPI. You can install the AI Snake Lab software using pip.

Create a Sandbox

python3 -m venv snake_venv
. snake_venv/bin/activate

Install the AI Snake Lab

After you have activated your venv environment:

pip install ai-snake-lab

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Running the AI Snake Lab

From within your venv environment:

ai-snake-lab

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Links and Acknowledgements

This code is based on a YouTube tutorial, Python + PyTorch + Pygame Reinforcement Learning – Train an AI to Play Snake by Patrick Loeber. You can access his original code here on GitHub. Thank you Patrick!!! You are amazing!!!!

Thanks also go out to Will McGugan and the Textual team. Textual is an amazing framework. Talk about rapid Application Development. Porting this took less than a day.

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