The VGLC: The Video Game Level Corpus
Adam James Summerville, Sam Snodgrass, Michael Mateas, Santiago, Onta\~n\'on

TL;DR
This paper introduces the VGLC, a comprehensive corpus of video game levels formatted for machine learning, facilitating research in automatic level generation and game AI.
Contribution
It provides a publicly available, easy-to-parse dataset of video game levels designed to advance machine learning applications in game level generation.
Findings
The VGLC enables new ML research in level generation.
The dataset covers multiple game genres.
It supports various AI research applications.
Abstract
Levels are a key component of many different video games, and a large body of work has been produced on how to procedurally generate game levels. Recently, Machine Learning techniques have been applied to video game level generation towards the purpose of automatically generating levels that have the properties of the training corpus. Towards that end we have made available a corpora of video game levels in an easy to parse format ideal for different machine learning and other game AI research purposes.
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Taxonomy
TopicsArtificial Intelligence in Games · Digital Games and Media · Video Analysis and Summarization
