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An elegant PyTorch deep reinforcement learning library.

Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen2.5, Qwen3, Llama, and more!

An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible.

MuZero

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

Scalable RL solution for advanced reasoning of language models

Implementation of papers in 100 lines of code.

[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning

Latest Advances on System-2 Reasoning

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.

Understanding R1-Zero-Like Training: A Critical Perspective

The open source post-building layer for agents. Our environment data and evals power agent post-training (RL, SFT) and monitoring.

Python library for Reinforcement Learning.

Modular reinforcement learning library (on PyTorch and JAX) with support for NVIDIA Isaac Gym, Omniverse Isaac Gym and Isaac Lab

Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version

[NeurIPS 2025] TTRL: Test-Time Reinforcement Learning