garage

What it is

Garage is a comprehensive toolkit designed to facilitate reproducible reinforcement learning research. It provides researchers and developers with the tools necessary to conduct experiments in a consistent and reliable manner, ensuring that results are both accurate and repeatable.

Garage stands out by focusing on reproducibility and modularity in reinforcement learning research, making it an ideal choice for researchers who need to ensure the reliability of their experiments.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited integrations with non-Python ecosystems

   Primary support for Python means limited out-of-the-box functionality for other languages

2. 02

   Small community leading to sparse third-party contributions and plugins

   GitHub activity indicates low participation beyond core contributors

What it does well

• Reproducibility in reinforcement learning experiments

• Modular design for easy customization and extension

• Support for a wide range of RL algorithms

• Integration with popular simulation environments

• Documentation and examples to help get started quickly

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.