What is Gym Retro?

Gym Retro is an open-source library that enables developers to create reinforcement learning algorithms with classic video games. This library makes it easy to access a variety of classic video game environments and provides users with various tools to build their own reinforcement learning algorithms.

With Gym Retro, developers can quickly and easily build, test, and deploy complex AI models with minimal effort. The library's features include access to a comprehensive library of classic game environments, which can be used as the basis for reinforcement learning algorithms.

Additionally, users have access to a wide range of tools for creating custom algorithms, such as custom reward functions, environment wrappers, and an easy-to-use interface. With these features, developers can quickly and efficiently create high-quality reinforcement learning models, allowing for more sophisticated AI applications.

Gym Retro is perfect for developers and AI researchers who want to create reinforcement learning algorithms and build advanced AI models.

Use Cases And Features

1. Use Gym Retro's library of classic game environments to quickly create reinforcement learning algorithms.

2. Access a variety of tools available to create custom algorithms, such as custom reward functions and environment wrappers.

3. Leverage easy-to-use interfaces to quickly and efficiently build high-quality AI models.