Level Design

Level design research focuses on automating and assisting the creation of engaging and playable game levels, addressing challenges like generating solvable and stylistically consistent levels. Current approaches leverage machine learning, particularly employing autoencoders, variational autoencoders, and neural networks for tasks such as upscaling, style transfer, and difficulty prediction, often incorporating conditional generation based on pre-defined parameters or user input. These advancements improve efficiency in level creation and offer new creative tools for game developers, while also providing valuable insights into the underlying structure and characteristics of successful level design.