# "Press Space to Fire": Automatic Video Game Tutorial Generation

arXiv: https://arxiv.org/abs/1805.11768 · HTML: https://mlsanity.com/paper/1805.11768/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 May 2018.

## Built on by (most cited first, 3 of 3)

- [Gen'eLive! Generating Rhythm Actions in Love Live!](https://mlsanity.com/paper/2202.12823/) (2022)
- [Predicting Personas Using Mechanic Frequencies and Game State Traces](https://mlsanity.com/paper/2203.13351/) (2022)
- [Game Mechanic Alignment Theory and Discovery](https://mlsanity.com/paper/2102.10247/) (2021)

## Abstract (arXiv)

We propose the problem of tutorial generation for games, i.e. to generate tutorials which can teach players to play games, as an AI problem. This problem can be approached in several ways, including generating natural language descriptions of game rules, generating instructive game levels, and generating demonstrations of how to play a game using agents that play in a human-like manner. We further argue that the General Video Game AI framework provides a useful testbed for addressing this problem.