Download
EnvPool is a fast, asynchronous, and parallel RL environment library designed for scaling reinforcement learning experiments. Developed by SAIL at Singapore, it leverages C++ backend and Python frontend for extremely high-speed environment interaction, supporting thousands of environments running in parallel on a single machine. It's compatible with Gymnasium API and RLlib, making it suitable for scalable training pipelines.
Features
- Supports highly parallelized RL environment execution
- Uses C++ backend for ultra-fast simulation
- Compatible with Gym/Gymnasium and RLlib APIs
- Asynchronous stepping and reset for better throughput
- Supports a variety of classic control, Atari, and custom environments
- Easy integration with existing RL libraries for training
Project Samples
Categories
Reinforcement Learning LibrariesLicense
Apache License V2.0Follow EnvPool
Other Useful Business Software
Paessler - Monitor Your Whole Network in Minutes
Waiting weeks for a monitoring rollout isn't an option when infrastructure doesn't stop running. PRTG's auto-discovery scans your network and suggests from over 200 pre-configured sensor types, so you're watching servers, applications and devices within minutes, not after a multi-week deployment. Enterprise-strength monitoring, without the enterprise complexity. Start your free trial today.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of EnvPool!
