Analysis of Dynamic Game Narrative and Player Behavior Adaptation System Based on Generative Artificial Intelligence

Abstract

Traditional pre-designed narratives struggle to meet players’ personalized needs, and generative AI offers possibilities to break through this limitation. This review focuses on generative AI-based dynamic game narrative and player behavior adaptive systems, exploring the shortcomings of traditional pre-designed narratives in satisfying players personalized and immersive needs, as well as the breakthroughs brought by generative AI. The article analyzes the applications of generative AI in scenarios such as NPC behavior generation in simulation strategy games and procedural content generation (PCG) in open worlds, noting issues like insufficient narrative coherence; expounds on the technical foundations including dynamic narrative generation frameworks and player behavior modeling, identifies challenges such as contradictions and inadequate capture of implicit features, and points out development directions including multimodal fusion and model lightweighting. Currently, generative AI has been applied in various types of games, yet it faces numerous technical issues. The review also covers the analysis of dynamic narrative mechanisms and player behavior modeling, providing a perspective for interdisciplinary integration and helping to alleviate industry contradictions.