There are 3 repositories under gym-environments topic.
The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)
Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:
PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments
Multi-objective Gymnasium environments for reinforcement learning
Collection of Reinforcement Learning / Meta Reinforcement Learning Environments.
A framework to design Reinforcement Learning environments that model Active Network Management (ANM) tasks in electricity distribution networks.
Gym environments and agents for autonomous driving.
A toolkit for auto-generation of OpenAI Gym environments from RDDL description files.
An open-source framework to benchmark and assess safety specifications of Reinforcement Learning problems.
Pytorch Implementation of Stochastic MuZero for gym environment. This algorithm is capable of supporting a wide range of action and observation spaces, including both discrete and continuous variations.
Set of reinforcement learning environments for optical networks
Cellular Automata Environments for Reinforcement Learning
Framework for integrating ROS and Gazebo with gymnasium, streamlining the development and training of RL algorithms in realistic robot simulations.
Repository of implementation of few algorithms for Underactuated Systems in Robotics and solutions to some interesting problems
A collection of RL gymnasium environments for learning to grasp 3D deformable objects.
Pytorch Implementation of MuZero Unplugged for gym environment. This algorithm is capable of supporting a wide range of action and observation spaces, including both discrete and continuous variations.
Pytorch Implementation of MuZero for gym environment. It support any Discrete , Box and Box2D configuration for the action space and observation space.
A toolkit for working with RDDL domains in Python3.
Gym Interface Wrapper for Simulink Models
A reinforcement learning-oriented Panda Emika Franka gazebo simulation.
Multi agent gym environment based on the classic Snake game with implementations of various reinforcement learning algorithms in pytorch
Beer Game implemented as an OpenAI gym environment.
RL Agent for Atari Game Pong
This package contains several gymnasium environments with positive definite cost functions, designed for compatibility with stable RL agents.
Implementation of Trust Region Policy Optimization and Proximal Policy Optimization algorithms on the objective of Robot Walk.
Clustor deployable custom DDPG algorithm for Multi Agent RL impleted in Tensorflow
A custom implementation of DeepMind's "the commons game"