OpenAI Gymnasium is an open-source Reinforcement Learning (RL) toolkit designed to help researchers, developers, and students efficiently create, train, and evaluate AI agents in a wide range of simulated environments. With its flexibility and ease of use, Gymnasium provides a robust platform for developing, testing, and benchmarking RL algorithms.

• Extensive environment library including classic control, Atari games, Box2D, MuJoCo, and robotics tasks for diverse RL experiments.
• Supports continuous and discrete action spaces for various algorithmic challenges.
• Standardized API for consistent interaction with environments, simplifying algorithm development and testing.
• Custom environment support, allowing users to create and register their own RL tasks.
• Integration with popular RL libraries and frameworks such as Stable Baselines, RLlib, and PyTorch.
• Headless rendering and GPU support for scalable and efficient experimentation.
• Cross-platform compatibility and Python-based design for easy adoption in research and educational settings.
• Open-source flexibility, allowing full customization to meet specific research or project needs.

To check the version of OpenAigymnasium#source /opt/gymnasium/venv/bin/activate
#pip show gymnasium

Gymnasium is an open-source toolkit distributed under the MIT License. It is not affiliated with, endorsed by, or sponsored by any commercial entity. Gymnasium is provided "as is," without any warranty, express or implied. Users utilize this software at their own risk. The developers and contributors to Gymnasium are not responsible for any damages, losses, or consequences resulting from the use of this software. Users are encouraged to review and comply with licensing terms and any applicable regulations when using Gymnasium.