Procedural Generation of First Person Shooter Maps using Map-Elites

Researchers apply MAP-Elites, a quality diversity algorithm, to procedurally generate First-Person Shooter game maps using novel representation methods. The study introduces Point-Line and Spatial-Layout representations that outperform existing approaches in generating diverse, high-quality FPS maps by analyzing both topological and emergent gameplay properties.

This research demonstrates significant advancement in procedural content generation (PCG) for video games by leveraging quality diversity algorithms originally developed for optimization problems. The application of MAP-Elites to FPS map design represents a meaningful intersection of computational creativity and game development, addressing a longstanding challenge in the industry: automatically generating compelling playable environments that maintain both structural coherence and engaging gameplay mechanics.

The introduction of Point-Line and Spatial-Layout representations marks a departure from previous binary and grid-based approaches, enabling richer characterization of map features. By distinguishing between topological properties (layout-dependent metrics) and emergent properties (gameplay-dependent characteristics), the research acknowledges that successful game levels require evaluation beyond pure geometric optimization. This distinction proves crucial because FPS maps must balance aesthetic design with practical gameplay considerations like player sightlines, engagement pacing, and competitive balance.

For the game development industry, this work has substantial implications. Procedural generation powered by quality diversity algorithms could accelerate level design workflows, reduce production costs, and enable developers to explore vastly larger design spaces than traditional manual authoring allows. The methodology becomes particularly valuable for indie developers and smaller studios lacking large design teams.

Looking forward, the research suggests several development vectors: integration with machine learning models trained on professional map designs, real-time adjustment based on player telemetry, and extension to other game genres. The framework's validation across multiple representation methods indicates scalability potential, making it relevant for broader PCG applications beyond FPS titles.

• →MAP-Elites algorithm successfully generates diverse FPS maps with improved quality compared to previous procedural methods.
• →Novel Point-Line and Spatial-Layout representations better capture both structural and emergent gameplay properties than binary or grid approaches.
• →Procedural generation could significantly reduce level design costs and timelines for game developers.
• →The distinction between topological and emergent properties proves essential for generating playable game content.
• →Research demonstrates scalability toward other game genres and broader procedural content generation applications.