Improving Collaborative Storytelling with a Multi-Agent Framework Based on Large Language Models

2026-05-28

AI Summary

This study addresses a critical gap in collaborative storytelling research, which has predominantly focused on adult–AI interactions in digital environments, overlooking child-centered approaches that integrate physical play. To bridge this gap, the work proposes the first multi-agent large language model (LLM) framework tailored for children’s physical tabletop gameplay, introducing an iterative Writer–Editor mechanism that enables children to co-create stories through tangible interactions with AI. Experimental results demonstrate that even with minimal rounds of editorial feedback, the system significantly enhances narrative quality, consistently generating age-appropriate, coherent, and creative stories for young users. By extending multi-agent LLM–based co-creation into the domain of children’s embodied play, this research establishes a novel paradigm for child–AI collaborative storytelling.

Abstract

The topic of Co-creation, i.e., AI agents interacting with humans to generate outputs (e.g., art), has gained significant attention recently. However, most studies focus on adult-human interactions in a digital setting. This paper explores a novel ludic co-creation scenario involving children and Large Language Models (LLMs) interacting through a physical board game to create written stories. Our goal is to develop a multi-agent framework capable of producing high-quality narratives suitable for young players. At the core of our approach is an iterative Writer-Editor process in which one LLM generates stories while another evaluates them and provides feedback for refinement. Through a simulation study involving multiple LLMs, we show that this iterative interaction consistently improves the perceived quality of generated stories across successive loops. The results indicate that a small number of refinement steps may be sufficient to achieve high-quality outputs in interactive storytelling systems.

Problem

• Collaborative Storytelling
• Large Language Models
• Co-creation
• Children
• Interactive Storytelling

Innovation

• multi-agent framework
• large language models
• iterative refinement
• collaborative storytelling
• child-AI co-creation