Automated Evaluation of Game Experience based on Game Dynamics and Motives for Play

Thomas Constant, G. Levieux
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Abstract

This paper describes an automated evaluation of the overall game experience using a synthetic agent, that we contextualize for First-Person Shooter games. This evaluation method is based on the characterization of the game experience through dynamics of major FPS games. We define dynamics as sequences of events that are meaningful for the player during the game session. As they trigger players’ emotional responses, and influence their overall enjoyment and motivation, we classify them according to Motives for Play like curiosity, thrill-seeking, problem-solving, victory, and acquisition, in order to facilitate the evaluation process. Based on that, our evaluation method proposes to select synthetic agent routines that target a distinct game experience while playing a game session, using a selection of game dynamics. As the agent navigates through the level and interacts with opponents, dynamics may occur and, if so, are automatically identified, and then classified as Motives for Play. In the end, this classification can be used to evaluate the game experience and the quality of the level itself during playtesting sessions. It may also be utilized to assist the procedural generation of any level that target a specific game experience.
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基于游戏动态和游戏动机的游戏体验自动评估
本文描述了使用合成代理对整体游戏体验的自动评估,我们将其作为第一人称射击游戏的背景。这种评价方法是基于主要FPS游戏的动态特征来描述游戏体验。我们将动态定义为在游戏过程中对玩家有意义的事件序列。因为它们会触发玩家的情绪反应,并影响他们的整体乐趣和动机,所以我们根据游戏动机(游戏邦注:如好奇心、寻求刺激、解决问题、胜利和获取)对它们进行分类,以促进评估过程。在此基础上,我们的评估方法提出选择综合代理例程,使用游戏动态选择,在玩游戏会话时针对不同的游戏体验。当代理在关卡中导航并与对手互动时,可能会出现动态,如果是这样,就会被自动识别,然后归类为游戏动机。最后,这种分类可以用于在测试过程中评估游戏体验和关卡质量。它也可以用于辅助任何针对特定游戏体验的关卡的程序生成。
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