Procedural content generation in video games has a long history. Existing procedural
content generation methods, such as search-based, solver-based, rule-based and grammar …

Despite the recency of their conception, Generative Adversarial Networks (GANs) constitute
an extensively-researched machine learning sub-field for the creation of synthetic data …

Generative systems for graphical assets have the potential to provide users with high quality
assets at the push of a button. However, there are many forms of assets, and many …

The generative adversarial network (GAN), which has received considerable notice for its
outstanding data generating abilities, is one of the most intriguing fields of artificial …

The main objective of this study is to identify features of mini-map design as a navigational
aid in the virtual geographical space in 100 popular video games for a computer platform …

Game development is simultaneously a technical and an artistic challenge. The past two
decades have brought many improvements to general-purpose game engines, reducing the …

The accuracy and performance of deep neural network models become important issues as
the applications of deep learning increase. For example, the navigation system of …

In recent years, the field of artificial intelligence (AI) has witnessed remarkable progress and
its applications have extended to the realm of video games. The incorporation of AI in video …

Abstract Generative Adversarial Networks (GANs) have been proposed as a method to
generate multiple replicas from an original version combining a Discriminator and a …

Procedural content generation (PCG) can be applied to a wide variety of tasks in games,
from narratives, levels and sounds, to trees and weapons. A large amount of game content is …