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

Deep Reinforcement Learning for Robotic Grasping from Octrees

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.

🚗 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.

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

OpenAI Gym environment solutions using Deep Reinforcement Learning.

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

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

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

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

Build better navigation agents, faster. RosNav-RL is a modular DRL framework for ROS 2 with a pluggable architecture, allowing you to switch between RL backends like Stable-Baselines3 and DreamerV3 to accelerate research and deployment.

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

Reinforcement Learning tool for Network Slice Placement problems

stable-baselines3 reinforcement learning on SUMO traffic light system

[IROS 22'] Model-free Neural Lyapunov Control

Intelligent Artificial Life. Researching behavior by nature and nurture simulation, deploying multi-agent reinforcement learning and evolving generational inheritance.

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

Using deep reinforcement learning to train drones to fly autonomously.

A highly-customizable OpenAI gym environment to train & evaluate RL agents trading stocks and crypto.

[ 👾 ] ➡️ 💾 ➡️ { 🎮🕹️ } Extra Stable-Baselines3 buffer classes. Reducing RL memory usage drastically with minimal overhead.