# Static Vs. Agentic Game Master AI for Facilitating Solo Role-Playing Experiences

arXiv: https://arxiv.org/abs/2502.19519 · HTML: https://mlsanity.com/paper/2502.19519/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Placed in Reinforcement learning for LLM agents, one of 16 directions in LLM agents and tool use.
- Builds on 10 of its 57 references that are in the map.
- First posted on arXiv 26 Feb 2025.

## Placed in

- LLM agents and tool use / [Reinforcement learning for LLM agents](https://mlsanity.com/agents/reinforcement-learning-for-llm-agents/)

## Builds on (most cited first, 10 of 10)

- [ReAct: Synergizing Reasoning and Acting in Language Models](https://mlsanity.com/paper/2210.03629/) (2022)
- [Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity](https://mlsanity.com/paper/2101.03961/) (2021)
- [The Rise and Potential of Large Language Model Based Agents: A Survey](https://mlsanity.com/paper/2309.07864/) (2023)
- [Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf](https://mlsanity.com/paper/2309.04658/) (2023)
- [Large Language Models and Games: A Survey and Roadmap](https://mlsanity.com/paper/2402.18659/) (2024)
- [Large Language Models and Video Games: A Preliminary Scoping Review](https://mlsanity.com/paper/2403.02613/) (2024)
- [BehAVE: Behaviour Alignment of Video Game Encodings](https://mlsanity.com/paper/2402.01335/) (2024)
- [The AffectToolbox: Affect Analysis for Everyone](https://mlsanity.com/paper/2402.15195/) (2024)
- [How to Compliment a Human -- Designing Affective and Well-being Promoting Conversational Things](https://mlsanity.com/paper/2302.00984/) (2023)
- [Resonating Experiences of Self and Others enabled by a Tangible Somaesthetic Design](https://mlsanity.com/paper/2005.02304/) (2020)

## Built on by (most cited first, 2 of 2)

- [Shall We Play a Game? Language Models for Open-ended Wargames](https://mlsanity.com/paper/2509.17192/) (2025)
- [Orchestrated Reality: From Role-Play to Living, Playable Game Worlds -- LLM-Driven World Simulation as a Parameterized-Action POMDP](https://mlsanity.com/paper/2606.16014/) (2026)

## Abstract (arXiv)

This paper presents a game master AI for single-player role-playing games. The AI is designed to deliver interactive text-based narratives and experiences typically associated with multiplayer tabletop games like Dungeons & Dragons. We report on the design process and the series of experiments to improve the functionality and experience design, resulting in two functional versions of the system. While v1 of our system uses simplified prompt engineering, v2 leverages a multi-agent architecture and the ReAct framework to include reasoning and action. A comparative evaluation demonstrates that v2 as an agentic system maintains play while significantly improving modularity and game experience, including immersion and curiosity. Our findings contribute to the evolution of AI-driven interactive fiction, highlighting new avenues for enhancing solo role-playing experiences.