用神经符号方法生成连贯且可玩的互动小说世界。
IVIE: A Neuro-symbolic Approach to Incremental and Validated Generation of Interactive Fiction Worlds

- 分四阶段逐步生成,大模型负责创意,符号系统保证逻辑一致
- 生成的世界包含关联场景、道具、角色与连贯谜题,围绕核心目标构建
- 适合想兼顾创意与结构的互动叙事研究者或游戏开发者
互动小说中的计算创造力面临根本矛盾:大语言模型(LLM)虽能生成创意叙事,却难以保持世界一致性;符号系统虽能确保一致,却缺乏创造性灵活性。我们提出IVIE(增量式且经验证的互动体验),一种从零开始生成完整可玩互动小说世界的神经符号方法。基于PAYADOR的神经符号框架,IVIE采用四阶段增量生成流程,将设定、角色、谜题设计等创造性决策交由LLM处理,同时通过符号验证约束世界状态。系统生成的世界包含相互关联的场景、功能性物品、非玩家角色及逻辑自洽的谜题,均围绕核心目标架构。人类评估显示,该方法生成的世界具有沉浸感与主题一致性,玩家参与度高。结果表明,神经符号方法有效平衡了灵活性与叙事连贯性:符号验证虽约束了LLM生成,但未剥夺其创造自由。然而仍存在挑战:部分情况下LLM会绕过谜题限制,且客观验证存在缺口,导致少数结构上不可能的目标出现。本文总结了未来神经符号互动叙事系统的关键设计考量,尤其关注LLM的能力边界及其局限。
原文摘要 · Abstract (English)
Computational creativity in Interactive Fiction faces a fundamental tension: Large Language Models (LLM) may produce creative narratives but struggle with world coherence, while symbolic systems ensure consistency but lack creative flexibility. We present IVIE (Incremental & Validated Interactive Experiences), a neuro-symbolic approach to generating complete and playable interactive fiction worlds from scratch. Building upon PAYADOR's neuro-symbolic framework, IVIE implements a four-stage incremental generation pipeline that delegates creative decisions--setting and character creation, puzzle design--to LLMs while grounding the world state through symbolic validation. The system generates worlds with interconnected locations, functional items, non-player characters, and coherent puzzles, all structured around a central goal-oriented architecture. Human evaluation shows the approach generates immersive, thematically coherent worlds with high player engagement. Results seem to indicate that the neuro-symbolic approach successfully balances flexibility with narrative coherence: symbolic validation grounds LLM generation without eliminating generative freedom. However, challenges remain: LLM inconsistencies occasionally bypass puzzle constraints, and objective validation gaps allow some structurally impossible goals. We identify key design considerations for future neurosymbolic interactive storytelling systems, particularly regarding LLM capabilities and their limitations.
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