shehio/rl
Implementing RL agents, one algorithm at a time
This project helps AI developers and researchers quickly set up and experiment with various reinforcement learning (RL) algorithms and classical game AI techniques. It takes game environments like Atari games or chess and outputs trained AI agents capable of playing these games. It's designed for individuals looking to explore and understand how different AI algorithms perform in game settings.
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Use this if you are an AI researcher or developer wanting to implement, test, and compare different reinforcement learning or classical game AI algorithms on various game environments.
Not ideal if you are looking for a plug-and-play solution to deploy the best-performing game AI agent without needing to understand or modify the underlying algorithms.
Stars
9
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2
Language
Python
License
MIT
Category
Last pushed
Aug 25, 2025
Commits (30d)
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