Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites

June 12, 2019 Β· Declared Dead Β· πŸ› 2019 IEEE Conference on Games (CoG)

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Authors Alberto Alvarez, Steve Dahlskog, Jose Font, Julian Togelius arXiv ID 1906.05175 Category cs.AI: Artificial Intelligence Cross-listed cs.NE Citations 83 Venue 2019 IEEE Conference on Games (CoG) Last Checked 3 months ago
Abstract
We propose the use of quality-diversity algorithms for mixed-initiative game content generation. This idea is implemented as a new feature of the Evolutionary Dungeon Designer, a system for mixed-initiative design of the type of levels you typically find in computer role playing games. The feature uses the MAP-Elites algorithm, an illumination algorithm which divides the population into a number of cells depending on their values along several behavioral dimensions. Users can flexibly and dynamically choose relevant dimensions of variation, and incorporate suggestions produced by the algorithm in their map designs. At the same time, any modifications performed by the human feed back into MAP-Elites, and are used to generate further suggestions.
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