Player Experience Modelling (PEM) is the study of AI techniques applied to modelling a player's experience within a video game. PEM development can be labour-intensive, requiring expert hand-authoring or specialized data collection. In this work, we propose a novel PEM development approach, approximating player experience from gameplay video. We evaluate this approach predicting affect in the game Angry Birds via a human subject study. We validate that our PEM can strongly correlate with self-reported and sensor measures of affect, demonstrating the potential of this approach.

翻译：玩家体验建模（PEM）是研究将人工智能技术应用于建模玩家在视频游戏中的体验。PEM的开发通常是劳动密集型的，需要专家手动设计或专门的数据收集。在本研究中，我们提出了一种新颖的PEM开发方法，通过游戏视频来近似估算玩家体验。我们通过一项人类受试者研究，评估了该方法在预测游戏《愤怒的小鸟》中情感状态的效果。我们验证了我们的PEM模型能够与自我报告和传感器测量的情感数据高度相关，证明了该方法的潜力。