论文标题
通过时空分析对个人和团队行为进行建模
Modeling Individual and Team Behavior through Spatio-temporal Analysis
论文作者
论文摘要
在过去的几年中，对玩家在游戏中的行为进行了建模增长。这一研究领域有广泛的应用，包括对学习者进行建模和了解球员策略，以提及一些。在本文中，我们提出了一种称为“交互式行为分析”（IBA）的新方法，该方法由两个可视化系统，一种标记机制和抽象算法组成，这些算法使用动态时间扭曲和聚类算法。该方法在无缝界面中包装，以促进游戏数据中的知识发现。我们证明了这种方法与来自两个基于多人团队的游戏的数据：Boomtown：Boomtown，由Gallup开发的游戏和Dota 2。这项工作的结果表明了这种方法在建模中的有效性，并开发了团队和个人行为的人际交往模型。
Modeling players' behaviors in games has gained increased momentum in the past few years. This area of research has wide applications, including modeling learners and understanding player strategies, to mention a few. In this paper, we present a new methodology, called Interactive Behavior Analytics (IBA), comprised of two visualization systems, a labeling mechanism, and abstraction algorithms that use Dynamic Time Warping and clustering algorithms. The methodology is packaged in a seamless interface to facilitate knowledge discovery from game data. We demonstrate the use of this methodology with data from two multiplayer team-based games: BoomTown, a game developed by Gallup, and DotA 2. The results of this work show the effectiveness of this method in modeling, and developing human-interpretable models of team and individual behavior.
