There are 0 repository under gymnasium-environment topic.
Simple Gridworld Gymnasium Environment
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.
A collection of RL gymnasium environments for learning to grasp 3D deformable objects.
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.
Lunar Lander envitoment of gymnasium solved using Double DQN and D3QN
Reinforcement Learning Environment Connect X Game + Gymnasium + PyGame GUI
A Gymnasium environment and RL algorithms for navigation on human arms using ultrasound/MRI
A sailing environment for OpenAI Gym / Gymnasium
Gymnasium car environment. Autonomous Racing with Proximal Policy Optimization and custom tracks.
Open-the-chests is a training environment for event-patterns recognition.
A reinforcement learning model for the Da Vinci code game
Try to reproduce basic example of Deep Q Learning (DQN) with Pytorch
Using Q-Learning methods in Gymnasium to solve various games, very basic implementation.
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.
Implementation of DQN and DDQN algorithms for Playing Car Racing Game
PettingZoo ConnectFour and TicTacToe examples, configured with Rye as dependency manager
Nokia's classic 'snake' game, written in NumPy and converted into a Gymnasium Environment() for use with gradient-based reinforcement learning algorithms
using gymnasium (gymnasium.farma.org) to create a box2d environment of lunar lander and training it using Deep Q-learning for lunar landing
Experiments with Dyna-Q
Deep Q-Learning Network using PyTorch
The Docker image for the isolated Mujoco environment
Reinforcement learning with Deep Convolutional Q Learning model
Implementation of Q-learning and SARSA algorithms in the Cliff Walking environment. Explore and compare reinforcement learning techniques.
Simple AI playing the 421 dice game using Reinforcement Learning.
Gymnasium environment based on real room and robot
Repository contains codes for the course CS780: Deep Reinforcement Learning
GPT 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.