CleanRL
High-quality single file implementations of Deep Reinforcement Learning algorithms.
Pricing
See website
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
—Overview
What is CleanRL?
CleanRL offers high-quality, single-file implementations of popular Deep Reinforcement Learning algorithms like PPO, DQN, C51, DDPG, TD3, SAC, and PPG. It is designed to be research-friendly with a focus on clarity and ease of use.
Key differentiator
“CleanRL stands out by providing high-quality, single-file implementations of popular Deep Reinforcement Learning algorithms with a focus on clarity and ease of use, making it ideal for research and educational purposes.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Researchers who need high-quality and easy-to-understand implementations for testing new ideas in reinforcement learning.
Educators looking to provide students with clear examples of popular RL algorithms.
Developers working on projects that require a deep understanding of the underlying mechanics of reinforcement learning.
✕ Not a fit for
Projects requiring real-time performance or low-latency execution, as CleanRL focuses more on clarity and research than optimization for speed.
Teams looking for a fully managed service or platform to deploy RL models in production environments.
Cost structure
Pricing
Free Tier
None
Starts at
See website
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Next step
Get Started with CleanRL
Step-by-step setup guide with code examples and common gotchas.