PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
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Updated
Jul 27, 2024 - Python
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.
OpenAI Gym environment solutions using Deep Reinforcement Learning.
SocialGym 2: A lightweight benchmark and simulator for multi-robot social navigation using ROS and the OpenAI gym.
🚗 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 designed for training RL agents to control the flight of a two-dimensional drone.
This repository contains an application using ROS2 Humble, Gazebo, OpenAI Gym and Stable Baselines3 to train reinforcement learning agents for a path planning problem.
Implementation of Jump-Start Reinforcement Learning (JSRL) with Stable Baselines3
Reinforcement Learning tool for Network Slice Placement problems
[IROS 22'] Model-free Neural Lyapunov Control
A highly-customizable OpenAI gym environment to train & evaluate RL agents trading stocks and crypto.
Predator-Prey-Grass gridworld environment using PettingZoo, with dynamic deletion and spawning of partially observant agents.
Worst-case MSE Minimization for RIS-assisted mmWave MU-MISO Systems with Hardware Impairments and CSI Imperfection
Study on the application of reinforcement learning to the management of a traffic light intersection.
Code base for SICNav: Safe and Interactive Crowd Navigation using Model Predictive Control and Bilevel Optimization
Python package implementing task generators, traditional and ML-based scheduling algorithms, and assessment tools.
OpenAI Gym environment designed for training RL agents to balance double CartPole.
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