English

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

Artificial Intelligence 2020-03-06 v1 Neural and Evolutionary Computing

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.

Keywords

Cite

@article{arxiv.1906.05175,
  title  = {Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites},
  author = {Alberto Alvarez and Steve Dahlskog and Jose Font and Julian Togelius},
  journal= {arXiv preprint arXiv:1906.05175},
  year   = {2020}
}

Comments

8 pages, Accepted and to appear in proceedings of 2019 IEEE Conference on Games, COG 2019

R2 v1 2026-06-23T09:51:39.737Z