gym

What it is

Gym is a toolkit for developing and comparing reinforcement learning algorithms. It provides a standard API to interact with environments, making it easier to test different RL methods across various tasks.

Gym provides a standardized and extensible framework for developing, testing, and comparing reinforcement learning algorithms across various environments.

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 support for non-standard environments

   Custom environment integration requires significant effort and documentation is sparse on this topic

2. 02

   Performance bottlenecks in large-scale deployments

   Gym's architecture can lead to performance issues when scaling up the number of parallel environments

What it does well

• Standardized API for reinforcement learning environments

• Wide range of pre-built environments for testing algorithms

• Easy to extend with custom environments

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.