你有十三小时来解开迷宫：利用函数调用增强AI游戏主持人
You Have Thirteen Hours in Which to Solve the Labyrinth: Enhancing AI Game Masters with Function Calling
AI总结：
针对大语言模型局限下文本游戏AI游戏主持人连贯性不足的问题，本文提出在桌面角色扮演游戏中利用函数调用集成游戏专属控制的方法，经人工评估和单元测试验证，可提升叙事质量与状态一致性，优化游戏体验。
摘要：
由于大语言模型（LLM）的局限性以及游戏主持人角色的复杂性，为文本类游戏开发一套连贯可靠的AI游戏主持人是一项具有挑战性的任务。本文提出了一种新颖的方法，在桌面角色扮演游戏《Jim Henson's Labyrinth: The Adventure Game》（吉姆·汉森的迷宫：冒险游戏）的场景下，利用函数调用增强AI游戏主持人的能力。我们的方法通过函数集成了游戏专属的控制机制，研究表明这一机制提升了AI游戏主持人的叙事质量与状态更新的一致性。基于人工评估和单元测试的实验结果证明，我们的方法在提升游戏体验、维持与游戏状态的连贯性方面具有有效性。本工作推动了游戏AI与交互式叙事的发展，为设计更具吸引力、更连贯的AI驱动游戏主持人提供了思路。
英文摘要：
Developing a consistent and reliable AI game master for text-based games is a challenging task due to the limitations of large language models (LLMs) and the complexity of the game master's role. This paper presents a novel approach to enhance AI game masters by leveraging function calling in the context of the table-top role-playing game "Jim Henson's Labyrinth: The Adventure Game." Our methodology involves integrating game-specific controls through functions, which we show improves the narrative quality and state update consistency of the AI game master. The experimental results, based on human evaluations and unit tests, demonstrate the effectiveness of our approach in enhancing gameplay experience and maintaining coherence with the game state. This work contributes to the advancement of game AI and interactive storytelling, offering insights into the design of more engaging and consistent AI-driven game masters.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
