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 …

The focus of this survey is on research in applying evolutionary and other metaheuristic
search algorithms to automatically generating content for games, both digital and nondigital …

Georgios N. Yannakakis Julian Togelius Page 1 Artificial Intelligence and Games Georgios N.
Yannakakis Julian Togelius Page 2 Artificial Intelligence and Games Page 3 Georgios N …

Generative Adversarial Networks (GANs) are a machine learning approach capable of
generating novel example outputs across a space of provided training examples. Procedural …

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 …

The procedural generation of video game levels has existed for at least 30 years, but only
recently have machine learning approaches been used to generate levels without specifying …

This paper describes the Mario AI benchmark, a game-based benchmark for reinforcement
learning algorithms and game AI techniques developed by the authors. The benchmark is …

This chapter discusses the challenges and opportunities of procedural content generation
(PCG) in games. It starts with defining three grand goals of PCG, namely multi-level …

We introduce a procedural content generation (PCG) framework at the intersections of
experience-driven PCG and PCG via reinforcement learning, named ED (PCG) RL, EDRL in …

This paper presents a framework and an initial study in general video game level
generation, the problem of generating levels for not only a single game but for any game …