Procedural Content Generation

Procedural Content Generation (PCG) uses algorithms to automatically create diverse game content, aiming to reduce development costs and enhance player experience. Current research emphasizes improving controllability and scalability, employing techniques like reinforcement learning, diffusion models, constraint satisfaction problems, and large language models to generate varied and high-quality outputs, including terrains, 3D environments, and even game rules themselves. This field is significant for its potential to automate content creation across various domains, from game development and virtual reality to robotics simulation and material science, impacting both research methodologies and industrial workflows.