Gymnasium

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Gymnasium is an AI Agents & Automation tool that provides an API standard for single-agent reinforcement learning environments. It includes popular reference environments and related utilities, formerly known as Gym.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is Gymnasium?

Gymnasium is an open-source Python library designed for developing and comparing reinforcement learning algorithms. It offers a standardized API for communication between learning algorithms and environments, alongside a comprehensive set of API-compliant environments. This library is a fork of OpenAI's Gym, maintained by the original team, ensuring continued development and support. It includes diverse environment families such as Classic Control, Box2D, Toy Text, MuJoCo, and Atari, catering to various complexity levels and problem types. Gymnasium also supports third-party environments and provides strict versioning for reproducibility. It is an essential tool for researchers and developers in the reinforcement learning field.

Best used for

Ideal for developers and data scientists who need to develop and test reinforcement learning algorithms, compare different RL approaches, and simulate various environments. Especially valuable for academic research and practical application of single-agent reinforcement learning.

Common actions

develop reinforcement learning

compare RL algorithms

simulate environments

research AI agents

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Capabilities

Key features

Standardized API for RL
Single-agent environments
Popular reference environments
Python library
Environment versioning

Target Audience

developerdata scientiststudent

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What types of environments does Gymnasium offer?

Gymnasium includes several environment families such as Classic Control, Box2D, Toy Text, MuJoCo, and Atari. These cover a range of complexities and problem types, from simple discrete state spaces to complex physics-based simulations and game emulators.

How does Gymnasium ensure reproducibility of results?

Gymnasium maintains strict versioning for all its environments. When changes are made that might affect learning outcomes, the environment's version number is incremented. This practice helps prevent confusion and ensures consistent results for research and development.

Is Gymnasium compatible with other reinforcement learning libraries?

Yes, Gymnasium's standardized API makes it compatible with various related libraries. Notable examples include CleanRL, which is built on the Gymnasium API for learning, and PettingZoo, a multi-agent version of Gymnasium with its own set of environments.

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