PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

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

PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control

Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code

Deep Reinforcement Learning for Robotic Grasping from Octrees

A collection of pre-trained RL agents using Stable Baselines3

🚗 This repository offers a ready-to-use training and evaluation environment for conducting various experiments using Deep Reinforcement Learning (DRL) in the CARLA simulator with the help of Stable Baselines 3 library.

Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierarchical reinforcement learning. It includes the code for the proposed method and experimental results on real-world stock data to demonstrate its effectiveness.

Train quadruped locomotion using reinforcement learning in Mujoco

Train a reinforcement learning agent (PPO) to play a retro helicopter arcade game using Stable-Baselines3 and a custom Gymnasium environment.

Tutorial: Tools for Robotic Reinforcement Learning, Hands-on RL for Robotics with EAGER and Stable-Baselines3

Deep Reinforcement Learning based autonomous navigation for quadcopters using PPO algorithm.

Additional code for Stable-baselines3 to load and upload models from the Hub.

Code base for SICNav T-RO paper and SICNav-Diffusion RA-L paper

This repository contains an application using ROS2 Humble, Gazebo, OpenAI Gym and Stable Baselines3 to train reinforcement learning agents for a path planning problem.

Modular DRL framework for autonomous robot navigation in ROS2. Plug-and-play RL backends (Stable-Baselines3, DreamerV3), composable reward functions, observation spaces & neural architectures - built for research and deployment.

OpenAI Gym environment solutions using Deep Reinforcement Learning.

A custom PyBullet environment for UR5 pick-and-place task. Trained using the SAC algorithm from Stable-Baselines3 for continuous control and robotic manipulation.

SocialGym 2: A lightweight benchmark and simulator for multi-robot social navigation using ROS and the OpenAI gym.

Stable-Baselines3 (SB3) reinforcement learning tutorial for the Reinforcement Learning Virtual School 2021.

Pytorch Implementation of Policy Distillation for control, which has well-trained teachers via stable_baselines3.

OpenAI Gym environment designed for training RL agents to control the flight of a two-dimensional drone.

My implementation of a reinforcement learning model using Stable-Baselines3 to play the NES Super Mario Bros.

GBRL-based Actor-Critic algorithms implemented in stable-baselines3

Implementation of Jump-Start Reinforcement Learning (JSRL) with Stable Baselines3

Deep Reinforcement Learning (DRL) stock trading system with LSTM-PPO, integrating technical indicators and FinBERT-based news sentiment analysis.

How to create a custom Gymnasium-compatible (formerly, OpenAI Gym) Reinforcement Learning environment. Then test it using Q-Learning and the Stable Baselines3 library. Companion YouTube tutorial playlist:

Vehicle dynamics simulator

A PyTorch implementation of the IEEE WCNC 2025 paper "Worst-Case MSE Minimization for RIS-Assisted mmWave MU-MISO Systems With Hardware Impairments and Imperfect CSI"

Simple converter for deploying Stable-Baselines3 model to TFLite and/or Coral