# What is the difference between supervised, self-supervised, and reinforcement learning?

_Last updated: 2026-07-20_  
_Reviewed by: Jason Burns, Editorial Steward_  
_Published by: AIDirectAnswers.com · Licensed under Citation License 1.0_

## Short answer

Supervised learning trains on labeled input–output pairs, self-supervised learning creates its own labels from unlabeled data (predicting the next token, filling a masked patch), and reinforcement learning trains an agent to maximize cumulative reward through trial and error. As Richard S. Sutton & Andrew G. Barto, put it on the record: "Reinforcement learning is learning what to do—how to map situations to actions—so as to maximize a numerical reward signal."

## Sources

- [undefined](http://incompleteideas.net/book/the-book-2nd.html)

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