玩家用自然语言造法术，AI实时生成并平衡属性。
SpellForger: Prompting Custom Spell Properties In-Game using BERT supervised-trained model
- 用BERT模型将文本描述转为法术模板并自动调参。
- 实测可即时生成多样法术，保持游戏平衡性。
- 适合想玩创意自定义玩法的玩家和开发者。
人工智能在游戏中的应用已显著发展，支持动态内容生成。然而，其作为核心玩法共创工具的潜力仍待挖掘。本文提出SpellForger，一款让玩家通过自然语言提示自定义法术的游戏，旨在提供个性化与创造力并重的独特体验。系统采用监督训练的BERT模型解析玩家输入，将文本描述映射到多个法术预制件，并调节其伤害、成本、效果等参数以确保平衡性。游戏基于Unity开发，AI后端使用Python实现。预期成果为交付一个功能原型，展示实时法术生成能力，嵌入富有吸引力的游戏循环中，验证AI作为直接游戏机制的有效性。
原文摘要 · Abstract (English)
Introduction: The application of Artificial Intelligence in games has evolved significantly, allowing for dynamic content generation. However, its use as a core gameplay co-creation tool remains underexplored. Objective: This paper proposes SpellForger, a game where players create custom spells by writing natural language prompts, aiming to provide a unique experience of personalization and creativity. Methodology: The system uses a supervisedtrained BERT model to interpret player prompts. This model maps textual descriptions to one of many spell prefabs and balances their parameters (damage, cost, effects) to ensure competitive integrity. The game is developed in the Unity Game Engine, and the AI backend is in Python. Expected Results: We expect to deliver a functional prototype that demonstrates the generation of spells in real time, applied to an engaging gameplay loop, where player creativity is central to the experience, validating the use of AI as a direct gameplay mechanic.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。