Interactive Constrained MAP-Elites: Analysis and Evaluation of the Expressiveness of the Feature Dimensions
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Abstract (arXiv)
We propose the Interactive Constrained MAP-Elites, a quality-diversity solution for game content generation, implemented as a new feature of the Evolutionary Dungeon Designer: a mixed-initiative co-creativity tool for designing dungeons. The feature uses the MAP-Elites algorithm, an illumination algorithm that segregates the population among several cells depending on their scores with respect to different behavioral dimensions. Users can flexibly and dynamically alternate between these dimensions anytime, thus guiding the evolutionary process in an intuitive way, and then incorporate suggestions produced by the algorithm in their room designs. At the same time, any modifications performed by the human user will feed back into MAP-Elites, closing a circular workflow of constant mutual inspiration. This paper presents the algorithm followed by an in-depth analysis of its behaviour, with the aims of evaluating the expressive range of all possible dimension combinations in several scenarios, as well as discussing their influence in the fitness landscape and in the overall performance of the mixed-initiative procedural content generation.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Mar 2020.
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Citing papers per year: 2022: 4; 2023: 3; 2024: 1; 2025: 2; 2026: 1.
11 papers.
- 2022TropeTwist: Trope-based Narrative Structure Generationcited by 8
- 2022Relevance-guided Unsupervised Discovery of Abilities with Quality-Diversity Algorithmscited by 8
- 2022Story Designer: Towards a Mixed-Initiative Tool to Create Narrative Structurescited by 6
- 2023Diversity from Human Feedbackcited by 5
- 2024Measuring Diversity of Game Scenarioscited by 5
- 2022EvolvingBehavior: Towards Co-Creative Evolution of Behavior Trees for Game NPCscited by 2
- 2023Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMaxcited by 2
- 2025Level Generation with Constrained Expressive Rangecited by 1
- 2023The Quest for Content: A Survey of Search-Based Procedural Content Generation for Video Gamescited by 0
- 2025Scaling Policy Gradient Quality-Diversity with Massive Parallelization via Behavioral Variationscited by 0
- 2026Quality Diversity for Reliable Data Driven Time-Use Optimizationcited by 0
- 2026Quality Diversity for Reliable Data Driven Time-Use Optimization5 Aug 2026
- 2025Level Generation with Constrained Expressive Range4 Apr 2025
- 2025Scaling Policy Gradient Quality-Diversity with Massive Parallelization via Behavioral Variations30 Jan 2025
- 2024Measuring Diversity of Game Scenarios15 Apr 2024
- 2023The Quest for Content: A Survey of Search-Based Procedural Content Generation for Video Games8 Nov 2023
- 2023Diversity from Human Feedback10 Oct 2023
- 2023Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMax14 Jul 2023
- 2022Story Designer: Towards a Mixed-Initiative Tool to Create Narrative Structures11 Oct 2022
- 2022EvolvingBehavior: Towards Co-Creative Evolution of Behavior Trees for Game NPCs1 Sep 2022
- 2022Relevance-guided Unsupervised Discovery of Abilities with Quality-Diversity Algorithms21 Apr 2022
- 2022TropeTwist: Trope-based Narrative Structure Generation31 Mar 2022