This module develops an understanding of procedural content generation in games, from large-scale worldbuilding systems to smaller asset level automation. Students will explore time intensive development tasks and create bespoke PCG tools or workflows to improve efficiency and delivery of a game development objective.

Fundamental PCG theory, randomness, seeds, and determinism.
Common algorithms and approaches such as noise, cellular automata, L-systems, grammars, and graph-based methods.
Procedural environments, terrain, structures, and object generation.
Procedural animation and physics.
Procedural art and modular asset systems.
Procedural audio and VFX.
Contemporary PCG approaches.
Integration of PCG tools within game engine workflows.
Testing, metrics, data analysis, and evaluation of procedural systems.

Assessment 1 – Large Scale PCG Artefact 70% [Learning Outcomes 1 and 2]

This assessment will require the development of a large-scale PCG artefact. With every entity within the project needing a procedurally generated percentage of 90-100%. The artefact will require pre-approval to assess scope and viability. The project should aim to solve a development problem via the inclusion and development of Procedural Content Generation.

Assessment 2 – Planning Documentation and Critical Review 30% [Learning Outcomes 3 and 4]

This assessment requires the need to produce planning documentation in the form of a Technical Design Document (TDD) that covers:

The technologies, algorithms and techniques used throughout development.
A user manual that provides clear instructions on how the PCG system works.
A completed test plan.

Learning and teaching activities will be delivered through a structured blend of scheduled and independent study designed to support a coherent learning journey. Scheduled sessions will typically include lectures that introduce core concepts and workshops that allow students to apply techniques, engage in facilitated discussions, and undertake activities focused on problem solving and peer learning. Independent study will involve, recommended reading, research tasks, and ongoing development of project work supported by the resources provided.

1. Critically evaluate contemporary procedural generation approaches, demonstrating an understanding, including the ethical or societal implications of automated content creation.

Knowledge & understanding

2. Integrate specialist knowledge to tackle ambiguous or undefined problems through the application of procedural generation.

Application & problem-solving

3. Research and evaluate the capabilities and limitations of procedural content generation methods, determining how these systems can be integrated or extended to solve specific workflow bottlenecks and enhance content scalability.

Research
Reflection

4. Effectively communicate complex design and technical solutions via documentation that is suitable for stakeholders.

Communication

A modern game engine
Appropriate programming IDE
VLE (Such as Blackboard)
Office Applications (Such as Microsoft Office)
University of Staffordshire Library
Internet Access
Digital Academy Forum
Digital Academy Upload
Game Lab

Roberts, P. (2026) Game AI Uncovered series, CRC Press.

Yannakakis, G. (2025) Artificial Intelligence and Games 2nd Edition, Springer.

Eliasz, P.M. (2024) Procedural Content Generation with Unreal Engine 5 : Harness the PCG Framework to Take Your Environment Design and Art Skills to the Next Level. First edition. Birmingham, England: Packt Publishing Ltd.

Kleinberg, J. and Tardos, E. (2014) Algorithm design. International edition. Harlow: Pearson.

Millington, I. (2019) AI for Games. 3rd edn. Boca Raton: Taylor & Francis Group, an Informa business.

Creating a universe with 18 quintillion planets or keeping a game interesting after hundreds of runs isn't magic - it’s mathematics. This module explores Procedural Content Generation (PCG), the technique developers use to automate asset creation and introduce controlled randomness into their designs. We will look under the hood of industry-standard examples.

Whilst the theory and academic research of PCG is important, you will be expected to design and build your own PCG artefact. You’ll have the freedom to choose the problem you want to solve, whether that means generating terrain on a massive scale, creating a system for millions of unique weapons, or experimenting with narrative structures. By the end of the module, you will have a functional tool that demonstrates how these systems work in practice accompanied by quality technical documents, testing strategies, and the ability to academically critically review your work.