This survey explores procedural content generation via machine learning (PCGML), defined
as the generation of game content using machine learning models trained on existing …

This paper attempts to give a high-level overview of the field of artificial and computational
intelligence (AI/CI) in games, with particular reference to how the different core research …

Progress in machine learning is measured by careful evaluation on problems of outstanding
common interest. However, the proliferation of benchmark suites and environments …

Making a game can be an intensive process, and if not planned accurately can easily run
over budget. The use of procedural generation in game design can help with the intricate …

We have developed a modular virtual reality gaming application that can be used to
synthesize exercise drills for racket sports. By defining cost terms that are related to the …

We show that novel, linear game levels can be created using n-grams that have been
trained on a corpus of existing levels. The method is fast and simple, and produces levels …

Procedural Content Generation (PCG) can be a useful tool for aiding creativity in the process
of designing game levels. Mixed-initiative level generation tools where a designer and an …

The procedural generation of levels and content in video games is a challenging AI problem.
Often such generation relies on an intelligent way of evaluating the content being generated …

This paper presents a genetic algorithm (GA) for the procedural generation of levels in the
Angry Birds game. The GA evaluates the levels based on a simulation which measures the …

A touted use of Procedural Content Generation is generating content tailored to specific
players. Previous work has relied on human identification of player profile features which are …