Procedural generation algorithms for modern games are created by interdisciplinary teams that blend game design, software engineering, and academic research. At the studio level, game designers define the play goals and constraints, technical artists translate aesthetic rules into shaders and models, and engine programmers implement performant systems inside game engines. The visible world is often the product of invisible collaboration: a designer’s intent encoded by an engineer and tuned by an artist.
Academic and research contributors
Researchers in universities and labs develop core techniques and frameworks that studios adopt. Ken Perlin New York University introduced Perlin noise, a mathematical method widely used for naturalistic terrain and texture generation. Julian Togelius New York University has published foundational work on procedural content generation, coauthoring the book Procedural Content Generation in Games with Noor Shaker and Mark Nelson, which synthesizes algorithms, evaluation methods, and design trade-offs. These academics and their students create algorithms, produce evaluation metrics, and investigate ethical and aesthetic implications; their work supplies both theoretical grounding and practical prototypes that practitioners adapt.
Industry practitioners and toolmakers
Within companies, roles often overlap. A systems designer might prototype level-generation rules, while a tools engineer builds editors so designers can manipulate those rules without coding. Small teams or indie developers sometimes have a single person performing all roles, as in Hello Games where Sean Murray Hello Games led the conception and tuning of No Man's Sky’s vast, algorithmically generated universe. Engine vendors and middleware teams, including those at Epic Games and Unity Technologies, provide procedural toolkits and runtime support that shape how algorithms are implemented across projects.
Designers and researchers must also consider cultural and environmental contexts. Procedural systems can help represent diverse landscapes economically, but if seeded with narrow assumptions, they risk flattening cultural specificities into generic artifacts. For territories with strong local heritage, designers increasingly consult cultural experts or employ data-driven methods that respect local patterns. Environmentally, procedural generation can reduce the need to manually author thousands of assets, lowering production time and material resources, yet it concentrates computational cost during development and testing.
Consequences of who builds these systems show up in game experience and industry practice. When AI researchers and designers work closely, algorithms tend to produce content that is not only varied but also meaningful to player goals. When technical constraints dominate, procedural output can feel repetitive or disjointed. The discipline has shifted from purely algorithmic novelty toward human-centered design of generation rules and evaluation metrics. As studios scale, procedural generation specialists — hybrid practitioners with backgrounds in algorithms and play design — are becoming central hires, ensuring systems align with aesthetic, cultural, and performance requirements while drawing on proven academic methods.