natetsang/open-rl
Implementations of a large collection of reinforcement learning algorithms.
This repository provides clear, easy-to-understand code for a wide range of reinforcement learning (RL) algorithms. It takes abstract RL concepts and translates them into concrete, runnable code examples that illustrate how these algorithms function. This project is ideal for students, researchers, or practitioners looking to learn, implement, or experiment with various RL techniques without navigating complex, highly optimized production codebases.
No commits in the last 6 months.
Use this if you are learning reinforcement learning and need simple, well-structured code examples to understand different algorithms, from foundational bandits to advanced actor-critic methods.
Not ideal if you need a highly optimized, production-ready library for deploying reinforcement learning agents at scale, as this project prioritizes readability over performance.
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28
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Language
Python
License
MIT
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Last pushed
Nov 30, 2023
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