Introduction

Procedural Content Generation (PCG for short) deals with the automated creation of digital content using algorithms and data structures in computer science. PCG has become increasingly important in computer graphics in particular over the last few decades. With increasing consumer demands for visual quality and immersion of interactive media content, the resources required to manually create such content are increasing proportionally. This poses major challenges for both large studios that generate special effects for films or video games and smaller media companies, particularly in terms of competitiveness. In order to minimize the additional work resulting from the increasing requirements, procedural tools are increasingly being used to automate sub-steps in the production of virtual content and thus save resources. The fields of application range from level generators in the games industry or semi-automated tools for generating textures and 3D geometries to generated animations for virtual characters. In particular, the use of machine learning, such as deep reinforcement learning, is constantly exploring new ways to develop the most efficient generators possible.

Recommended reading

Shaker, Noor & Togelius, Julian & Nelson, Mark. (2016). Procedural Content Generation in Games. 10.1007/978-3-319-42716-4.

Lindenmayer, Aristid & Prusinkiewicz, Przemyslaw. (1990), The Algorithmic Beauty of Plants

Jouni Smed and Harri Hakonen. 2017, Algorithms and Networking for Computer Games (2nd. ed.). Wiley Publishing.

Ebert, David & Musgrave, F.K. & Peachey, D. & Perlin, Ken & Worley, Steve & Mark, W.R. & Hart, John. (2002). Texturing and Modeling: A Procedural Approach: Third Edition.

Tanya X. Short and Tarn Adams. 2017. Procedural Generation in Game Design (1st. ed.). A. K. Peters, Ltd, USA.