The platformer experience dataset

K. Karpouzis, Georgios N. Yannakakis, Noor Shaker, S. Asteriadis
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引用次数: 35

Abstract

Player modeling and estimation of player experience have become very active research fields within affective computing, human computer interaction, and game artificial intelligence in recent years. For advancing our knowledge and understanding on player experience this paper introduces the Platformer Experience Dataset (PED) - the first open-access game experience corpus - that contains multiple modalities of user data of Super Mario Bros players. The open-access database aims to be used for player experience capture through context-based (i.e. game content), behavioral and visual recordings of platform game players. In addition, the database contains demographical data of the players and self-reported annotations of experience in two forms: ratings and ranks. PED opens up the way to desktop and console games that use video from webcameras and visual sensors and offer possibilities for holistic player experience modeling approaches that can, in turn, yield richer game personalization.
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平台游戏体验数据集
近年来,玩家建模和玩家体验评估已成为情感计算、人机交互和游戏人工智能领域非常活跃的研究领域。为了提高我们对玩家体验的认识和理解,本文介绍了平台体验数据集(PED)——第一个开放访问的游戏体验语料库——它包含了《超级马里奥兄弟》玩家的多种用户数据。开放访问数据库旨在通过基于上下文(即游戏内容)、平台游戏玩家的行为和视觉记录来捕获玩家体验。此外,该数据库还包含玩家的人口统计数据和两种形式的自我报告经验注释:评级和排名。PED为使用网络摄像头和视觉传感器视频的桌面和主机游戏开辟了道路,并为整体玩家体验建模方法提供了可能性,从而产生更丰富的游戏个性化。
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