AtDelfi: Automatically Designing Legible, Full Instructions For Games
Michael Cerny Green, Ahmed Khalifa, Gabriella A.B. Barros, Tiago, Machado, Andy Nealen, Julian Togelius

TL;DR
This paper presents AtDelfi, an automated system for generating comprehensive and understandable video game tutorials using graph-based representations of game mechanics, tested on various games within the GVG-AI framework.
Contribution
The paper introduces a novel graph-based approach for automatic tutorial generation, enabling scalable and adaptable instruction creation for diverse video games.
Findings
Graph representation works well for simple arcade games.
Tutorials for complex games may need higher-level understanding.
Automated tutorials can effectively teach basic game mechanics.
Abstract
This paper introduces a fully automatic method for generating video game tutorials. The AtDELFI system (AuTomatically DEsigning Legible, Full Instructions for games) was created to investigate procedural generation of instructions that teach players how to play video games. We present a representation of game rules and mechanics using a graph system as well as a tutorial generation method that uses said graph representation. We demonstrate the concept by testing it on games within the General Video Game Artificial Intelligence (GVG-AI) framework; the paper discusses tutorials generated for eight different games. Our findings suggest that a graph representation scheme works well for simple arcade style games such as Space Invaders and Pacman, but it appears that tutorials for more complex games might require higher-level understanding of the game than just single mechanics.
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