2025/03/21 by Jiwen Yu, Yiran Qin, Yu, Jiwen +13 · 2 voices · 7 citations
Computer Science · Engineering · #Artificial Intelligence in Games #Computer Vision and Pattern Recognition (cs.CV) #Core (optical fiber) #FOS: Computer and information sciences #Game Developer #Game design #Game development tool #Game testing #Generative grammar #Human Motion and Animation #Music Technology and Sound Studies #Position paper #Video game #Video game development #cs.CV
paper · pdf · doi:10.48550/arxiv.2503.17359
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2025/03/21 · arxiv published 2025/03/21 · arxiv updated 2025/05/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Modern game development faces significant challenges in creativity and cost due to predetermined content in traditional game engines. Recent breakthroughs in video generation models, capable of synthesizing realistic and interactive virtual environments, present an opportunity to revolutionize game creation. In this position paper, we propose Interactive Generative Video (IGV) as the foundation for Generative Game Engines (GGE), enabling unlimited novel content generation in next-generation gaming. GGE leverages IGV's unique strengths in unlimited high-quality content synthesis, physics-aware world modeling, user-controlled interactivity, long-term memory capabilities, and causal reasoning. We present a comprehensive framework detailing GGE's core modules and a hierarchical maturity roadmap (L0-L4) to guide its evolution. Our work charts a new course for game development in the AI era, envisioning a future where AI-powered generative systems fundamentally reshape how games are created and experienced.