A literature review of Empirical Evidence on Procedural Content Generation in Game-Related Implementation

Abstract

Procedural Content Generation (PCG) is an emerging field of study in computer science that focuses on automating the process of generating content by using algorithm, making the content generation process with less human effort. However, a more specific empirical evidence on how it is being used in a game-related implementation are still lacking. This paper presents the findings of review performed in the past 5 years looking on how PCG are being applied in game-related content, whether it is from the basic paper characteristic to analyze the trends, the field of PCG itself, and the game domain of game model and game genre. The studies had shown that PCG are being used extensively in game-related content but has seen more uses on specific type of contents rather than being used ubiquitously in all sorts of contents. The result shown that there are not specific best type of PCG method or algorithm being used instead an array of approach can be used based on what content being created. Result also shown that PCG are being used in multiple type of games, but similarly, based on the paper found, only certain types of game benefits PCG extensively such as action and platforming games while other model and genre of games have not seen much PCG application yet. Further studies are also required to analyze how experimentation and evaluation of PCG are being done as well as PCG domain in educational games as well as game-based learning, the quality catachrestic being analyzed on the papers are also worth mentioning to understand the underlying result of PCG usage in game-related contents.