Creating Hybrid Interactive Narrative Systems with LLM: From Formal Description to Evaluation

The paper presents a new LLM‑based narrative platform that allows interchangeable Experience Managers (EMs) to operate over a shared symbolic world model, enabling explicit preconditions and effects for every operation. By representing each session as a plan in a common state‑transition system, the authors evaluate three different managers—open generation, Monte Carlo repair, and autonomous characters—on four properties: player agency, EM controllability, author intent, and robustness, using an interactive Little Red Riding Hood scenario. The results demonstrate that no single manager excels in all properties, providing authors and designers with concrete criteria to choose a manager that best fits their priorities.

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