# RL environment

URL: https://sellmydatatoai.net/glossary/rl-environment

An RL environment is a software setting in which an AI agent takes actions, receives observations and gets a reward, so it can be trained or tested by trial.

An RL environment is a controlled software setting where an agent observes a state, takes an action and receives a new state and a reward. In reinforcement learning the agent improves by repeating tasks in the environment and learning which actions earn higher rewards.

## What does an RL environment look like for AI agents?

An RL environment for language model agents is usually a sandboxed copy of a real tool or workflow, such as a code repository with tests, a browser, a spreadsheet or a ticketing system. It comes with a set of tasks and an automatic grader that checks whether each task was done, and the grader supplies the reward.

## Who sells RL environments?

RL environments are sold by specialist builders and marketplaces. [DataVendor](https://sellmydatatoai.net/data-buyers/datavendor), run by HUD, lists HUD tasksets and RL environments alongside code repositories. A company's own software and workflows can be the basis of one, provided live data and credentials are replaced.

See [agent trajectory](https://sellmydatatoai.net/glossary/agent-trajectory), [evaluation dataset](https://sellmydatatoai.net/glossary/evaluation-dataset) and [agent trajectories and RL environments explained](https://sellmydatatoai.net/guides/agent-trajectories-and-rl-environments).