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 …

In this article, we perform an exhaustive analysis of the use of Artificial Neural Networks and
Deep Learning in the Visual Arts. We begin by introducing changes in Artificial Intelligence …

In this paper, we review recent deep learning advances in the context of how they have
been applied to play different types of video games such as first-person shooters, arcade …

We investigate how reinforcement learning can be used to train level-designing agents. This
represents a new approach to procedural content generation in games, where level design …

Deep reinforcement learning (RL) has shown impressive results in a variety of domains,
learning directly from high-dimensional sensory streams. However, when neural networks …

Quality diversity (QD) is a growing branch of stochastic optimization research that studies the
problem of generating an archive of solutions that maximize a given objective function but …

Procedural content generation (PCG) refers to the practice of generating game content, such
as levels, quests or characters, algorithmically. Motivated by the need to make games …

Machine learning advances have afforded an increase in algorithms capable of creating art,
music, stories, games, and more. However, it is not yet well-understood how machine …

In many reinforcement learning tasks, the goal is to learn a policy to manipulate an agent,
whose design is fixed, to maximize some notion of cumulative reward. The design of the …

Large language models (LLMs) have taken the scientific world by storm, changing the
landscape of natural language processing and human-computer interaction. These powerful …