Orchestrating Emergent Storytelling with Embodied Multi-Agent Systems

Abstract

We present a novel approach to emergent storytelling through multi-agent systems powered by large language models (LLMs), advancing beyond current approaches to game AI and interactive storytelling which rely on heavily scripted dialogue systems and moving closer towards genuinely emergent narrative ecosystems. Through two artworks / video games, Conflicts and The Game of Whispers, we demonstrate how LLM-driven agents with persistent memory, behavioral models, and coordination capabilities generate coherent narratives from simulated social dynamics. Our architecture introduces: (1) a hierarchical memory system integrating working memory, episodic buffers, and consolidated narrative storage; (2) a conversation graph that tracks topic centroids, engagement, and unresolved questions; (3) a hybrid orchestrator that directs autonomy by fusing LLM reasoning with the conversation graph; and (4) their integration within embodied agents with a streaming multimodal action-perception loop that enables spatial awareness and environmental responsiveness. Experiments reveal emergent behaviors including strategic deception, coalition formation, the spread of misinformation, and meta-narrative awareness. Our contributions include several architectural patterns for producing stable emergent narrative systems.