Design Techniques for LLM-Powered Interactive Storytelling: A Case Study of the Dramamancer System

2026-01-26

AI Summary

This work addresses the fundamental tension in interactive storytelling between authorial intent and player agency. It proposes Dramamancer, a novel design paradigm for large language model (LLM)-driven interactive narratives that reconciles these competing demands by parsing author-defined story schemata and integrating dynamic response mechanisms to player actions. Leveraging the generative capabilities of LLMs, the system produces narrative content in real time that adheres to underlying story logic while supporting high degrees of interactivity. Empirical evaluation demonstrates that this approach effectively balances narrative coherence with creative control and player autonomy. The study thus offers a reproducible design framework and evaluation pathway for LLM-powered interactive storytelling systems.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Machine Learning: Large Multimodal Models (LMMs)
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

The rise of Large Language Models (LLMs) has enabled a new paradigm for bridging authorial intent and player agency in interactive narrative. We consider this paradigm through the example of Dramamancer, a system that uses an LLM to transform author-created story schemas into player-driven playthroughs. This extended abstract outlines some design techniques and evaluation considerations associated with this system.

Problem

• interactive storytelling
• authorial intent
• player agency
• Large Language Models
• narrative design

Innovation

• Large Language Models
• Interactive Storytelling
• Authorial Intent
• Player Agency
• Story Schemas