EnvPool

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

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License

Apache License V2.0

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Additional Project Details

Programming Language

C++

Related Categories

C++ Reinforcement Learning Libraries

Registered

2025-03-13

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