English(EN) Application of machine learning to monster level prediction in tabletop RPG game design

机器学习预测桌面角色扮演游戏中的怪物等级

作者 PulseAugur 编辑部 · [2 个来源] · 2026-07-10 08:39

研究人员开发了一种机器学习模型来预测桌面角色扮演游戏（特别是《开拓者第二版》）中的怪物等级。该方法将任务视为表格序数回归，利用了源自游戏公开可用怪物属性的新数据集。与线性模型和神经网络相比，基于树的集成模型表现出更优越的性能，在预测怪物强度等级方面取得了高准确率，并通过可解释的 AI 分析与人类直觉相符。 AI

影响这项研究展示了机器学习如何应用于游戏设计，有可能简化平衡游戏内容的创建过程。

排序理由该项目是一篇学术论文，详细介绍了机器学习在特定问题领域的新颖应用。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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报道来源 [2]

arXiv cs.LG TIER_1 English(EN) · Jolanta \'Sliwa, Jakub Adamczyk · 2026-07-13 04:00

Application of machine learning to monster level prediction in tabletop RPG game design

arXiv:2607.09196v1 Announce Type: new Abstract: Designing balanced adversaries is a central but labor-intensive task in tabletop role-playing game (TTRPG) development. In systems such as Pathfinder, each monster is described by many numerical attributes that jointly determine its…
arXiv cs.LG TIER_1 English(EN) · Jakub Adamczyk · 2026-07-10 08:39

机器学习在桌面角色扮演游戏设计中怪物等级预测的应用

Designing balanced adversaries is a central but labor-intensive task in tabletop role-playing game (TTRPG) development. In systems such as Pathfinder, each monster is described by many numerical attributes that jointly determine its power, summarized as an ordinal level. We inves…

报道来源 [2]

Application of machine learning to monster level prediction in tabletop RPG game design

机器学习在桌面角色扮演游戏设计中怪物等级预测的应用

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