The Investigation of Generative AI on Role-Playing Games: Applications, Challenges, and Future Trends

Abstract

In response to problems of homogenized experience caused by the solidification of development logic and interaction methods in desktop RPG games, this paper summarizes the specific application of current generative artificial intelligence in the development process and content of RPG games by reviewing relevant literature; and obtains solutions to optimize the creation paradigms of text and these two types of content in the game industry. In the creation of text content, artificial intelligence generated content (AIGC) technology demonstrates potential auxiliary creation capabilities on two levels: in the narrative dimension, the dynamic task generation system based on GPT solves the problem of mass production of text in open-world games. Compared with traditional manual scripts, the generated content ensures content diversity while reducing expansion costs (low marginal benefit); in the long process of plot interaction, by pre-training dialogue logic to ensure character consistency, task generation that conforms to human player experience habits, has storylines, and is logical is also achieved. Regarding the application of text-to-image generation (TTIG), this paper describes the industrial benefits brought by this technology. The text generation module provides convenience for the iteration of proposals and concept diagrams. TTIG tools  automatically convert neutral sketches to stylized renderings, reducing human input in the prototype design stage by 80% and lowering resource costs, while SketchMetaFace's 2D to 3D deep model generation shortens the modeling cycle of medium-fidelity models. For the above application scenarios of generative AI, this paper also sorts out current obstacles and challenges faced and discusses targeted solutions.