# RL Environment

> A packaged task world for reinforcement learning - the world, rules, and feedback loop of state, action, and reward a model trains inside.

- Category: Models & Training
- Stage: Rising
- Also called: RL environments, Environments hub
- Canonical: https://www.joelcsaji.com/ai-dictionary/rl-environment

## Plain English

A gym the model practices in; without one, RL is an algorithm with nothing to act on.

## Example

A team wraps their issue tracker's API in an environment with a 'bug fixed, tests pass, no drive-by changes' reward and fine-tunes a coding model that is unusually good at their stack.

## Why it matters

Model improvement is shifting from scraping data to building environments - the Environments Hub made them shareable like datasets, and teams that wrap their product can train and eval against it.

## Related

- [Synthetic Data](https://www.joelcsaji.com/ai-dictionary/synthetic-data)
- [Evals](https://www.joelcsaji.com/ai-dictionary/evals)
- [Fine-Tuning](https://www.joelcsaji.com/ai-dictionary/fine-tuning)

## Sources

- [Prime Intellect: Environments Hub](https://www.primeintellect.ai/blog/environments)