gymnasium-environment

mikelma/craftium

A framework for creating rich, 3D, Minecraft-like single and multi-agent environments for AI research based on Minetest

HewlettPackard/dc-rl

SustainDC is a set of Python environments for Data Center simulation and control using Heterogeneous Multi Agent Reinforcement Learning. Includes customizable environments for workload scheduling, cooling optimization, and battery management, with integration into Gymnasium.

dfki-ric/deformable_gym

A collection of RL gymnasium environments for learning to grasp 3D deformable objects.

angelomorgado/CARLA-GymDrive

Autonomous driving episode generation for the Carla simulator in a gym environment. This framework makes it easy to create driving scenarios to train/test the agent.

Amirarsalan-sn/Lunar-Lander

Lunar Lander envitoment of gymnasium solved using Double DQN and D3QN

negarhonarvar/DeepReinforcementLearning

A Complete Collection of Deep RL Famous Algorithms implemented in Gymnasium most Popular environments

negarhonarvar/StockTrading_DRL

Automated stock trading strategy using deep reinforcement learning and recurrent neural networks

fauzisho/GymConnectX

Reinforcement Learning Environment Connect X Game + Gymnasium + PyGame GUI

appliedAI-Initiative/armscan_env

A Gymnasium environment and RL algorithms for navigation on human arms using ultrasound/MRI

ProfessorNova/PPO-Car

Gymnasium car environment. Autonomous Racing with Proximal Policy Optimization and custom tracks.

ThalesGroup/open-the-chests

Open-the-chests is a training environment for event-patterns recognition.

wiitt/DQN-Car-Racing

Implementation of DQN and DDQN algorithms for Playing Car Racing Game

Gabo-Tor/gym-sailing

A sailing environment for OpenAI Gym / Gymnasium

humemai/room-env

The Room (Gymnasium) environment

HewlettPackard/green-dcc

Green-DCC is a benchmark environment for evaluating dynamic workload distribution techniques for sustainable Data Center Clusters (DCC) using reinforcement learning and other control algorithms.

hhxc-0/RL_DaVinciCode

A reinforcement learning model for the Da Vinci Code game

PD-Mera/cart-pole-dqn

Try to reproduce basic example of Deep Q Learning (DQN) with Pytorch

AnmolS99/BioGym

Spatio-temporal wildlife management Gymnasium RL Environment created and trained on for my Master's thesis

FuzzyNum/Reinforcement-Learning

Using Q-Learning methods in Gymnasium to solve various games, very basic implementation.

LaurentVeyssier/Deep_Q_Learning

Reinforcement learning with Deep Convolutional Q Learning model

Rajarshi1001/CS780

Repository contains codes for the course CS780: Deep Reinforcement Learning

bcorfman/pettingzoo-classicenvs

PettingZoo ConnectFour and TicTacToe examples, configured with Rye as dependency manager

bragg13/aigs-project-one

Deep Q-network to train an agent to play CartPole and MountainCar environments in gymnasium.

Drakrig/maze-gym

Maze gymnasium-compatible for Reinforcement learning

GameBle/moon_landing

using gymnasium (gymnasium.farma.org) to create a box2d environment of lunar lander and training it using Deep Q-learning for lunar landing

NicolasChagnet/game-ai-421-dice

Simple AI playing the 421 dice game using Reinforcement Learning.

Senich17/Dyna-Q-in-a-deterministic-and-stochastic-env

Experiments with Dyna-Q

yarinbnyamin/DQN

Deep Q-Learning Network using PyTorch

canoksuzoglu1/BipedalWalker-RL

This project implements agent training using the Proximal Policy Optimization (PPO) algorithm in the BipedalWalker-v3 environment at two difficulty levels: normal and hardcore. The model's performance is evaluated based on rewards collected during the training process.

elskow/deep-rl

epap011/NeuroLander

howsmyanimeprofilepicture/mujoco-gym

The Docker image for the isolated Mujoco environment

Mahmood-Anaam/reinforcement-learning-cliff-walking

Implementation of Q-learning and SARSA algorithms in the Cliff Walking environment. Explore and compare reinforcement learning techniques.

phucthaiv02/gymnasium-car2d-rl

Training reinforcement learning agents to control a car in the Car-2D environment using Gymnasium.

StarlitDreams/pacman-convolutional-q-learning

This project implements a Deep Q-Network (DQN) using PyTorch to train an agent to play Atari's Ms. Pac-Man. It utilizes reinforcement learning with a convolutional neural network (CNN) for image processing. Features include experience replay, frame preprocessing, and CUDA support, with trained model saving and video rendering of gameplay.